openapi.yaml

openapi: 3.0.0
info:
  title: Portkey API
  description: The Portkey REST API. Please see https://portkey.ai/docs/api-reference for more details.
  version: "2.0.0"
  termsOfService: https://portkey.ai/terms
  contact:
    name: Portkey Developer Forum
    url: https://portkey.wiki/community
  license:
    name: MIT
    url: https://github.com/Portkey-AI/portkey-openapi/blob/master/LICENSE
servers:
  - url: https://api.portkey.ai/v1
tags:
  - name: Assistants
    description: Build Assistants that can call models and use tools.
  - name: Audio
    description: Turn audio into text or text into audio.
  - name: Chat
    description: Given a list of messages comprising a conversation, the model will return a response.
  - name: Prompts
    description: Given a prompt template ID and variables, will run the saved prompt template and return a response.
  - name: Completions
    description: Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.
  - name: Embeddings
    description: Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.
  - name: Fine-tuning
    description: Manage fine-tuning jobs to tailor a model to your specific training data.
  - name: Batch
    description: Create large batches of API requests to run asynchronously.
  - name: Files
    description: Files are used to upload documents that can be used with features like Assistants and Fine-tuning.
  - name: Images
    description: Given a prompt and/or an input image, the model will generate a new image.
  - name: Models
    description: List and describe the various models available in the API.
  - name: Moderations
    description: Given a input text, outputs if the model classifies it as potentially harmful.
  - name: Configs
    description: Create, List, Retrieve, and Update your Portkey Configs.
  - name: Feedback
    description: Send and Update any feedback.
  - name: Logs
    description: Custom Logger to add external logs to Portkey.
  - name: Virtual-keys
    description: Create, List, Retrieve, Update, and Delete your Portkey Virtual keys.
  - name: Users
    description: Create and manage users.
  - name: User-invites
    description: Create and manage user invites.
  - name: Workspaces
    description: Create and manage workspaces.
  - name: Workspaces > Members
    description: Create and manage workspace members.
  - name: Api-Keys
    description: Create, List, Retrieve, Update, and Delete your Portkey Api keys.
  - name: Logs Export
    description: Exports logs service .
  - name: Analytics
    description: Get analytics over different data points like requests, costs, tokens, etc.
  - name: Analytics > Graphs
    description: Get data points for graphical representation.
  - name: Analytics > Summary
    description: Get overall summary for the selected time bucket.
  - name: Analytics > Groups
    description: Get grouped metrics for the selected time bucket.

paths:
  # Note: When adding an endpoint, make sure you also add it in the `groups` section, in the end of this file,
  # under the appropriate group
  /chat/completions:
    post:
      operationId: createChatCompletion
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Chat
      summary: Chat
      parameters:
        - $ref: "#/components/parameters/PortkeyTraceId"
        - $ref: "#/components/parameters/PortkeySpanId"
        - $ref: "#/components/parameters/PortkeyParentSpanId"
        - $ref: "#/components/parameters/PortkeySpanName"
        - $ref: "#/components/parameters/PortkeyMetadata"
        - $ref: "#/components/parameters/PortkeyCacheNamespace"
        - $ref: "#/components/parameters/PortkeyCacheForceRefresh"
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateChatCompletionRequest"

      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateChatCompletionResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: cURL
          label: Default
          source: |
            curl https://api.portkey.ai/v1/chat/completions \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "gpt-4o",
                "messages": [
                  {
                    "role": "system",
                    "content": "You are a helpful assistant."
                  },
                  {
                    "role": "user",
                    "content": "Hello!"
                  }
                ]
              }'
        - lang: cURL
          label: Self-Hosted
          source: |
            curl PORTKEY_ENTERPRISE_URL/v1/chat/completions \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "gpt-4o",
                "messages": [
                  {
                    "role": "system",
                    "content": "You are a helpful assistant."
                  },
                  {
                    "role": "user",
                    "content": "Hello!"
                  }
                ]
              }'              
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = portkey.chat.completions.create(
              model="gpt-4o",
              messages=[
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": "Hello!"}
              ]
            )

            print(response.choices[0].message)
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key = "PORTKEY_API_KEY",
              base_url = "PORTKEY_ENTERPRISE_URL",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = portkey.chat.completions.create(
              model="gpt-4o",
              messages=[
                {"role": "system", "content": "You are a helpful assistant."},
                {"role": "user", "content": "Hello!"}
              ]
            )

            print(response.choices[0].message)
        - lang: javascript
          label: Default
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const response = await client.chat.completions.create({
                messages: [{ role: "system", content: "You are a helpful assistant." }],
                model: "gpt-4o",
              });

              console.log(response.choices[0]);
            }

            main();
        - lang: javascript
          label: Self-Hosted
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseUrl: 'PORTKEY_ENTERPRISE_URL'
            });

            async function main() {
              const response = await client.chat.completions.create({
                messages: [{ role: "system", content: "You are a helpful assistant." }],
                model: "gpt-4o",
              });

              console.log(response.choices[0]);
            }

            main();

  /completions:
    post:
      operationId: createCompletion
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Completions
      summary: Completions
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateCompletionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateCompletionResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/completions \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "gpt-3.5-turbo-instruct",
                "prompt": "Say this is a test",
                "max_tokens": 7,
                "temperature": 0
              }'
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = portkey.completions.create(
              model="gpt-3.5-turbo-instruct",
              prompt="Say this is a test",
              max_tokens=7,
              temperature=0
            )

            print(response)
        - lang: javascript
          label: Default
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const response = await portkey.completions.create({
                model: "gpt-3.5-turbo-instruct",
                prompt: "Say this is a test.",
                max_tokens: 7,
                temperature: 0,
              });

              console.log(response);
            }

            main();
        - lang: javascript
          label: Self-Hosted
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseUrl: 'PORTKEY_ENTERPRISE_URL'
            });

            async function main() {
              const response = await client.completions.create({
                model: "gpt-3.5-turbo-instruct",
                prompt: "Say this is a test.",
                max_tokens: 7,
                temperature: 0,
              });

              console.log(response);
            }

            main();
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY",
              base_url = "PORTKEY_ENTERPRISE_URL"
            )

            response = portkey.completions.create(
              model="gpt-3.5-turbo-instruct",
              prompt="Say this is a test",
              max_tokens=7,
              temperature=0
            )

            print(response)
        - lang: curl
          label: Self-Hosted
          source: |
            curl https://PORTKEY_ENTERPRISE_URL/v1/completions \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "gpt-3.5-turbo-instruct",
                "prompt": "Say this is a test",
                "max_tokens": 7,
                "temperature": 0
              }'

  /prompts/{promptId}/completions:
    post:
      operationId: createPromptCompletion
      servers:
        - url: https://api.portkey.ai/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Prompts
      summary: Prompts Completions
      description: |
        Execute your saved prompt templates on Portkey
      parameters:
        - in: path
          name: promptId
          required: true
          schema:
            type: string
          description: The unique identifier of the prompt template to use
      requestBody:
        required: true
        content:
          application/json:
            schema:
              allOf:
                - type: object
                  required:
                    - variables
                  description: |
                    Note: Although hyperparameters are shown grouped here (like messages, max_tokens, temperature, etc.), they should only be passed at the root level, alongside 'variables' and 'stream'.
                  properties:
                    variables:
                      type: object
                      description: Variables to substitute in the prompt template
                    stream:
                      type: boolean
                      default: False
                      description: "Default: False. Set to True if you want to stream the response"
                    hyperparameters:
                      oneOf:
                        - title: Chat Completions
                          $ref: "#/components/schemas/CreateChatCompletionRequest"
                        - title: Completions
                          $ref: "#/components/schemas/CreateCompletionRequest"
                      description: |
                        **Note**: All hyperparameters are optional. Pass them at the root level, and not nested under `hyperparameters`. Their grouping here is for educational purposes only.

      responses:
        "200":
          description: Successful completion response
          content:
            application/json:
              schema:
                type: object
                properties:
                  status:
                    type: string
                    description: Response status
                  headers:
                    type: object
                    description: Response headers
                  body:
                    oneOf:
                      - title: Chat Completions
                        $ref: "#/components/schemas/CreateChatCompletionResponse"
                      - title: Completions
                        $ref: "#/components/schemas/CreateCompletionResponse"

      x-code-samples:
        - lang: cURL
          label: Default
          source: |
            curl -X POST "https://api.portkey.ai/v1/prompts/YOUR_PROMPT_ID/completions" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -d '{
                "variables": {
                  "user_input": "Hello world"
                },
                "max_tokens": 250,
                "presence_penalty": 0.2
              }'
        - lang: Python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY"
            )

            completion = client.prompts.completions.create(
                prompt_id="YOUR_PROMPT_ID",
                variables={
                    "user_input": "Hello world"
                },
                max_tokens=250,
                presence_penalty=0.2
            )

            print(completion)

        - lang: JavaScript
          label: Default
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY'
            });

            const completion = await portkey.prompts.completions.create({
              promptId: "YOUR_PROMPT_ID",
              variables: {
                user_input: "Hello world"
              },
              max_tokens: 250,
              presence_penalty: 0.2
            });

            console.log(completion);
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/prompts/YOUR_PROMPT_ID/completions" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -d '{
                "variables": {
                  "user_input": "Hello world"
                },
                "max_tokens": 250,
                "presence_penalty": 0.2
              }'
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY",
                base_url="PORTKEY_ENTERPRISE_URL"
            )

            completion = client.prompts.completions.create(
                prompt_id="YOUR_PROMPT_ID",
                variables={
                    "user_input": "Hello world"
                },
                max_tokens=250,
                presence_penalty=0.2
            )

            print(completion)
        - lang: javascript
          label: Self-Hosted
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              baseURL: 'PORTKEY_ENTERPRISE_URL'
            });

            const completion = await portkey.prompts.completions.create({
              promptId: "YOUR_PROMPT_ID",
              variables: {
                user_input: "Hello world"
              },
              max_tokens: 250,
              presence_penalty: 0.2
            });

            console.log(completion);

  /prompts/{promptId}/render:
    post:
      operationId: createPromptRender
      tags:
        - Prompts
      summary: Prompts Render
      description: |
        Renders a prompt template with its variable values filled in
      parameters:
        - in: path
          name: promptId
          required: true
          schema:
            type: string
          description: The unique identifier of the prompt template to render
      requestBody:
        required: true
        content:
          application/json:
            schema:
              allOf:
                - type: object
                  required:
                    - variables
                  description: |
                    Note: Although hyperparameters are shown grouped here (like messages, max_tokens, temperature, etc.), they should only be passed at the root level, alongside 'variables' and 'stream'.
                  properties:
                    variables:
                      type: object
                      description: Variables to substitute in the prompt template
                    hyperparameters:
                      oneOf:
                        - title: Chat Completions
                          $ref: "#/components/schemas/CreateChatCompletionRequest"
                        - title: Completions
                          $ref: "#/components/schemas/CreateCompletionRequest"
                      description: |
                        **Note**: All hyperparameters are optional. Pass them at the root level, and not nested under `hyperparameters`. Their grouping here is for educational purposes only.

      responses:
        "200":
          description: Successful rendered prompt
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/PromptRenderResponse"

      x-code-samples:
        - lang: "cURL"
          source: |
            curl -X POST "https://api.portkey.ai/v1/prompts/YOUR_PROMPT_ID/render" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -d '{
                "variables": {
                  "user_input": "Hello world"
                },
                "max_tokens": 250,
                "presence_penalty": 0.2
              }'
        - lang: Python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY"
            )

            completion = client.prompts.render(
                prompt_id="YOUR_PROMPT_ID",
                variables={
                    "user_input": "Hello world"
                },
                max_tokens=250,
                presence_penalty=0.2
            )

            print(completion)

        - lang: "JavaScript"
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY'
            });

            const completion = await portkey.prompts.render({
              promptId: "YOUR_PROMPT_ID",
              variables: {
                user_input: "Hello world"
              },
              max_tokens: 250,
              presence_penalty: 0.2
            });

            console.log(completion);

  /images/generations:
    post:
      operationId: createImage
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Images
      summary: Create Image
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateImageRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/images/generations \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "dall-e-3",
                "prompt": "A cute baby sea otter",
                "n": 1,
                "size": "1024x1024"
              }'
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.images.generate(
              model="dall-e-3",
              prompt="A cute baby sea otter",
              n=1,
              size="1024x1024"
            )
        - lang: javascript
          label: Default
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const image = await client.images.generate({ model: "dall-e-3", prompt: "A cute baby sea otter" });

              console.log(image.data);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/images/generations" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "dall-e-3",
                "prompt": "A cute baby sea otter",
                "n": 1,
                "size": "1024x1024"
              }'
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY",
                virtual_key="PROVIDER_VIRTUAL_KEY",
                base_url="PORTKEY_ENTERPRISE_URL"
            )

            image = client.images.generate(
                model="dall-e-3",
                prompt="A cute baby sea otter",
                n=1,
                size="1024x1024"
            )

            print(image.data)
        - lang: javascript
          label: Self-Hosted
          source: |
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseURL: 'PORTKEY_ENTERPRISE_URL'
            });

            const image = await portkey.images.generate({
              model: "dall-e-3",
              prompt: "A cute baby sea otter",
              n: 1,
              size: "1024x1024"
            });

            console.log(image.data);

  /images/edits:
    post:
      operationId: createImageEdit
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Images
      summary: Create Image Edit
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateImageEditRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/images/edits \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -F image="@otter.png" \
              -F mask="@mask.png" \
              -F prompt="A cute baby sea otter wearing a beret" \
              -F n=2 \
              -F size="1024x1024"
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.images.edit(
              image=open("otter.png", "rb"),
              mask=open("mask.png", "rb"),
              prompt="A cute baby sea otter wearing a beret",
              n=2,
              size="1024x1024"
            )
        - lang: javascript
          label: Default
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const image = await client.images.edit({
                image: fs.createReadStream("otter.png"),
                mask: fs.createReadStream("mask.png"),
                prompt: "A cute baby sea otter wearing a beret",
              });

              console.log(image.data);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/images/edits" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "image": "@otter.png",
                "mask": "@mask.png",
                "prompt": "A cute baby sea otter wearing a beret",
                "n": 2,
                "size": "1024x1024"
              }'
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY",
                virtual_key="PROVIDER_VIRTUAL_KEY",
                base_url="PORTKEY_ENTERPRISE_URL"
            )

            image = client.images.edit(
                image=open("otter.png", "rb"),
                mask=open("mask.png", "rb"),
                prompt="A cute baby sea otter wearing a beret",
                n=2,
                size="1024x1024"
            )

            print(image.data)
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseURL: 'PORTKEY_ENTERPRISE_URL'
            });

            async function main() {
              const image = await portkey.images.edit({
                image: fs.createReadStream("otter.png"),
                mask: fs.createReadStream("mask.png"),
                prompt: "A cute baby sea otter wearing a beret",
              });

              console.log(image.data);
            }
            main();

  /images/variations:
    post:
      operationId: createImageVariation
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Images
      summary: Creates Image Variation
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateImageVariationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ImagesResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/images/variations \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -F image="@otter.png" \
              -F n=2 \
              -F size="1024x1024"
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = client.images.create_variation(
              image=open("image_edit_original.png", "rb"),
              n=2,
              size="1024x1024"
            )
        - lang: javascript
          label: Default
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const image = await client.images.createVariation({
                image: fs.createReadStream("otter.png"),
              });

              console.log(image.data);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/images/variations" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "image": "@otter.png",
                "n": 2,
                "size": "1024x1024"
              }'
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY",
                virtual_key="PROVIDER_VIRTUAL_KEY",
                base_url="PORTKEY_ENTERPRISE_URL"
            )

            image = client.images.create_variation(
                image=open("otter.png", "rb"),
                n=2,
                size="1024x1024"
            )

            print(image.data)
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseURL: 'PORTKEY_ENTERPRISE_URL'
            });

            async function main() {
              const image = await portkey.images.createVariation({
                image: fs.createReadStream("otter.png"),
              });

              console.log(image.data);
            }
            main();

  /embeddings:
    post:
      operationId: createEmbedding
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Embeddings
      summary: Embeddings
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateEmbeddingRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateEmbeddingResponse"
      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/embeddings \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "input": "The food was delicious and the waiter...",
                "model": "text-embedding-ada-002",
                "encoding_format": "float"
              }'
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.embeddings.create(
              model="text-embedding-ada-002",
              input="The food was delicious and the waiter...",
              encoding_format="float"
            )
        - lang: javascript
          label: Default
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const embedding = await client.embeddings.create({
                model: "text-embedding-ada-002",
                input: "The quick brown fox jumped over the lazy dog",
                encoding_format: "float",
              });

              console.log(embedding);
            }

            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/embeddings" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "input": "The food was delicious and the waiter...",
                "model": "text-embedding-ada-002",
                "encoding_format": "float"
              }'
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
                api_key="PORTKEY_API_KEY",
                virtual_key="PROVIDER_VIRTUAL_KEY",
                base_url="PORTKEY_ENTERPRISE_URL"
            )

            response = client.embeddings.create(
                model="text-embedding-ada-002",
                input="The food was delicious and the waiter...",
                encoding_format="float"
            )

            print(response.data)
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const portkey = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseURL: 'PORTKEY_ENTERPRISE_URL'
            });

            async function main() {
              const embedding = await portkey.embeddings.create({
                model: "text-embedding-ada-002",
                input: "The quick brown fox jumped over the lazy dog",
                encoding_format: "float",
              });

              console.log(embedding);
            }

            main();

  /audio/speech:
    post:
      operationId: createSpeech
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Audio
      summary: Create Speech
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateSpeechRequest"
      responses:
        "200":
          description: OK
          headers:
            Transfer-Encoding:
              schema:
                type: string
              description: chunked
          content:
            application/octet-stream:
              schema:
                type: string
                format: binary

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/audio/speech \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "model": "tts-1",
                "input": "The quick brown fox jumped over the lazy dog.",
                "voice": "alloy"
              }' \
              --output speech.mp3
        - lang: python
          label: Default
          source: |
            from pathlib import Path
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            speech_file_path = Path(__file__).parent / "speech.mp3"
            response = client.audio.speech.create(
              model="tts-1",
              voice="alloy",
              input="The quick brown fox jumped over the lazy dog."
            )
            response.stream_to_file(speech_file_path)
        - lang: javascript
          label: Default
          source: |
            import fs from "fs";
            import path from "path";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            const speechFile = path.resolve("./speech.mp3");

            async function main() {
              const mp3 = await client.audio.speech.create({
                model: "tts-1",
                voice: "alloy",
                input: "Today is a wonderful day to build something people love!",
              });
              console.log(speechFile);
              const buffer = Buffer.from(await mp3.arrayBuffer());
              await fs.promises.writeFile(speechFile, buffer);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/audio/speech" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "tts-1",
                "input": "The quick brown fox jumped over the lazy dog.",
                "voice": "alloy"
              }' \
              --output speech.mp3
        - lang: python
          label: Self-Hosted
          source: |
            from pathlib import Path
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY",
              base_url="PORTKEY_ENTERPRISE_URL"
            )

            speech_file_path = Path(__file__).parent / "speech.mp3"
            response = client.audio.speech.create(
              model="tts-1",
              voice="alloy",
              input="The quick brown fox jumped over the lazy dog."
            )
            response.stream_to_file(speech_file_path)
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import path from "path";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseUrl: 'PORTKEY_ENTERPRISE_URL'
            });

            const speechFile = path.resolve("./speech.mp3");

            async function main() {
              const mp3 = await client.audio.speech.create({
                model: "tts-1",
                voice: "alloy",
                input: "Today is a wonderful day to build something people love!",
              });
              console.log(speechFile);
              const buffer = Buffer.from(await mp3.arrayBuffer());
              await fs.promises.writeFile(speechFile, buffer);
            }
            main();

  /audio/transcriptions:
    post:
      operationId: createTranscription
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Audio
      summary: Create Transcription
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateTranscriptionRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                oneOf:
                  - $ref: "#/components/schemas/CreateTranscriptionResponseJson"
                  - $ref: "#/components/schemas/CreateTranscriptionResponseVerboseJson"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/audio/transcriptions \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: multipart/form-data" \
              -F file="@/path/to/file/audio.mp3" \
              -F model="whisper-1"
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            audio_file = open("speech.mp3", "rb")
            transcript = client.audio.transcriptions.create(
              model="whisper-1",
              file=audio_file
            )
        - lang: javascript
          label: Default
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const transcription = await client.audio.transcriptions.create({
                file: fs.createReadStream("audio.mp3"),
                model: "whisper-1",
              });

              console.log(transcription.text);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/audio/transcriptions" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "whisper-1",
                "file": "@/path/to/file/audio.mp3"
              }' \
              --output transcription.json
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY",
              base_url="PORTKEY_ENTERPRISE_URL"
            )

            audio_file = open("speech.mp3", "rb")
            transcript = client.audio.transcriptions.create(
              model="whisper-1",
              file=audio_file
            )
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseUrl: 'PORTKEY_ENTERPRISE_URL'
            });

            const audioFile = fs.createReadStream("speech.mp3");

            async function main() {
              const transcription = await client.audio.transcriptions.create({
                file: audioFile,
                model: "whisper-1",
              });

              console.log(transcription.text);
            }
            main();

  /audio/translations:
    post:
      operationId: createTranslation
      servers:
        - url: https://api.portkey.ai/v1
        - url: http://localhost:8080/v1
        - url: PORTKEY_ENTERPRISE_URL/v1
      tags:
        - Audio
      summary: Create Translation
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateTranslationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                oneOf:
                  - $ref: "#/components/schemas/CreateTranslationResponseJson"
                  - $ref: "#/components/schemas/CreateTranslationResponseVerboseJson"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          label: Default
          source: |
            curl https://api.portkey.ai/v1/audio/translations \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: multipart/form-data" \
              -F file="@/path/to/file/german.m4a" \
              -F model="whisper-1"
        - lang: python
          label: Default
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            audio_file = open("speech.mp3", "rb")
            transcript = client.audio.translations.create(
              model="whisper-1",
              file=audio_file
            )
        - lang: javascript
          label: Default
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
                const translation = await client.audio.translations.create({
                    file: fs.createReadStream("speech.mp3"),
                    model: "whisper-1",
                });

                console.log(translation.text);
            }
            main();
        - lang: curl
          label: Self-Hosted
          source: |
            curl -X POST "PORTKEY_ENTERPRISE_URL/v1/audio/translations" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "model": "whisper-1",
                "file": "@/path/to/file/german.m4a"
              }' \
              --output translation.json
        - lang: python
          label: Self-Hosted
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY",
              base_url="PORTKEY_ENTERPRISE_URL"
            )

            audio_file = open("speech.mp3", "rb")
            transcript = client.audio.translations.create(
              model="whisper-1",
              file=audio_file
            )
        - lang: javascript
          label: Self-Hosted
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY',
              baseUrl: 'PORTKEY_ENTERPRISE_URL'
            });

            const audioFile = fs.createReadStream("speech.mp3");

            async function main() {
              const translation = await client.audio.translations.create({
                file: audioFile,
                model: "whisper-1",
              });

              console.log(translation.text);
            }
            main();

  /files:
    get:
      operationId: listFiles
      tags:
        - Files
      summary: List Files
      parameters:
        - in: query
          name: purpose
          required: false
          schema:
            type: string
          description: Only return files with the given purpose.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListFilesResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/files \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.files.list()
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const list = await client.files.list();

              for await (const file of list) {
                console.log(file);
              }
            }

            main();

    post:
      operationId: createFile
      tags:
        - Files
      summary: |
        Upload a file to be used across various endpoints, such as Assistant (<2M tokens), Fine-Tuning, and Batch (<100 MB). Total size of your bucket is 100 GB.
      requestBody:
        required: true
        content:
          multipart/form-data:
            schema:
              $ref: "#/components/schemas/CreateFileRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/OpenAIFile"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/files \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -F purpose="fine-tune" \
              -F file="@mydata.jsonl"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.files.create(
              file=open("mydata.jsonl", "rb"),
              purpose="fine-tune"
            )
        - lang: javascript
          source: |
            import fs from "fs";
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const file = await client.files.create({
                file: fs.createReadStream("mydata.jsonl"),
                purpose: "fine-tune",
              });

              console.log(file);
            }

            main();

  /files/{file_id}:
    delete:
      operationId: deleteFile
      tags:
        - Files
      summary: Delete File
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteFileResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/files/file-abc123 \
              -X DELETE \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.files.delete("file-abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const file = await client.files.del("file-abc123");

              console.log(file);
            }

            main();

    get:
      operationId: retrieveFile
      tags:
        - Files
      summary: Returns information about a specific file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/OpenAIFile"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/files/file-abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.files.retrieve("file-abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const file = await client.files.retrieve("file-abc123");

              console.log(file);
            }

            main();

  /files/{file_id}/content:
    get:
      operationId: downloadFile
      tags:
        - Files
      summary: Returns the contents of the specified file.
      parameters:
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to use for this request.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                type: string

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/files/file-abc123/content \
            -H "x-portkey-api-key: $PORTKEY_API_KEY" \
            -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" > file.jsonl
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            content = client.files.content("file-abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const file = await client.files.content("file-abc123");

              console.log(file);
            }

            main();

  /fine_tuning/jobs:
    post:
      operationId: createFineTuningJob
      summary: Create a Finetune Job
      description: Finetune a provider model
      parameters: []
      responses:
        "200":
          description: The request has succeeded.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FineTuningJob"
      tags:
        - Finetune
      requestBody:
        required: true
        content:
          application/json:
            schema:
              anyOf:
                - $ref: "#/components/schemas/OpenAIFinetuneJob"
                - $ref: "#/components/schemas/BedrockFinetuneJob"
                - $ref: "#/components/schemas/PortkeyFinetuneJob"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/fine_tuning/jobs \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "training_file": "file-BK7bzQj3FfZFXr7DbL6xJwfo",
                "model": "gpt-3.5-turbo"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.fine_tuning.jobs.create(
              training_file="file-abc123",
              model="gpt-3.5-turbo"
            )
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const fineTune = await client.fineTuning.jobs.create({
                training_file: "file-abc123"
              });

              console.log(fineTune);
            }

            main();

    get:
      operationId: listPaginatedFineTuningJobs
      tags:
        - Fine-tuning
      summary: |
        List your organization's fine-tuning jobs
      parameters:
        - name: after
          in: query
          description: Identifier for the last job from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of fine-tuning jobs to retrieve.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListPaginatedFineTuningJobsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/fine_tuning/jobs?limit=2 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.fine_tuning.jobs.list()
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const list = await client.fineTuning.jobs.list();

              for await (const fineTune of list) {
                console.log(fineTune);
              }
            }

            main();

  /fine_tuning/jobs/{fine_tuning_job_id}:
    get:
      operationId: retrieveFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Get info about a fine-tuning job.

        [Learn more about fine-tuning](https://platform.openai.com/docs/guides/fine-tuning)
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FineTuningJob"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/fine_tuning/jobs/ft-AF1WoRqd3aJAHsqc9NY7iL8F \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.fine_tuning.jobs.retrieve("ftjob-abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const fineTune = await client.fineTuning.jobs.retrieve("ftjob-abc123");

              console.log(fineTune);
            }

            main();

  /fine_tuning/jobs/{fine_tuning_job_id}/events:
    get:
      operationId: listFineTuningEvents
      tags:
        - Fine-tuning
      summary: |
        Get status updates for a fine-tuning job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to get events for.
        - name: after
          in: query
          description: Identifier for the last event from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of events to retrieve.
          required: false
          schema:
            type: integer
            default: 20
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListFineTuningJobEventsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/fine_tuning/jobs/ftjob-abc123/events \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.fine_tuning.jobs.list_events(
              fine_tuning_job_id="ftjob-abc123",
              limit=2
            )
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const list = await client.fineTuning.list_events(id="ftjob-abc123", limit=2);

              for await (const fineTune of list) {
                console.log(fineTune);
              }
            }

            main();

  /fine_tuning/jobs/{fine_tuning_job_id}/cancel:
    post:
      operationId: cancelFineTuningJob
      tags:
        - Fine-tuning
      summary: |
        Immediately cancel a fine-tune job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to cancel.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FineTuningJob"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl -X POST https://api.portkey.ai/v1/fine_tuning/jobs/ftjob-abc123/cancel \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.fine_tuning.jobs.cancel("ftjob-abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const fineTune = await client.fineTuning.jobs.cancel("ftjob-abc123");

              console.log(fineTune);
            }
            main();

  /fine_tuning/jobs/{fine_tuning_job_id}/checkpoints:
    get:
      operationId: listFineTuningJobCheckpoints
      tags:
        - Fine-tuning
      summary: |
        List checkpoints for a fine-tuning job.
      parameters:
        - in: path
          name: fine_tuning_job_id
          required: true
          schema:
            type: string
            example: ft-AF1WoRqd3aJAHsqc9NY7iL8F
          description: |
            The ID of the fine-tuning job to get checkpoints for.
        - name: after
          in: query
          description: Identifier for the last checkpoint ID from the previous pagination request.
          required: false
          schema:
            type: string
        - name: limit
          in: query
          description: Number of checkpoints to retrieve.
          required: false
          schema:
            type: integer
            default: 10
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListFineTuningJobCheckpointsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/fine_tuning/jobs/ftjob-abc123/checkpoints \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            Reach out to us on portkey.wiki/community
        - lang: javascript
          source: |
            Reach out to us on portkey.wiki/community

  /models:
    get:
      operationId: listModels
      tags:
        - Models
      summary: Lists the currently available models, and provides basic information about each one such as the owner and availability.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListModelsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/models \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.models.list()
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const list = await client.models.list();

              for await (const model of list) {
                console.log(model);
              }
            }
            main();

  /models/{model}:
    get:
      operationId: retrieveModel
      tags:
        - Models
      summary: Retrieves a model instance, providing basic information about the model such as the owner and permissioning.
      parameters:
        - in: path
          name: model
          required: true
          schema:
            type: string
            # ideally this will be an actual ID, so this will always work from browser
            example: gpt-3.5-turbo
          description: The ID of the model to use for this request
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Model"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/models/VAR_model_id \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.models.retrieve("VAR_model_id")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const model = await client.models.retrieve("VAR_model_id");

              console.log(model);
            }

            main();

    delete:
      operationId: deleteModel
      tags:
        - Models
      summary: Delete a fine-tuned model. You must have the Owner role in your organization to delete a model.
      parameters:
        - in: path
          name: model
          required: true
          schema:
            type: string
            example: ft:gpt-3.5-turbo:acemeco:suffix:abc123
          description: The model to delete
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteModelResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/models/ft:gpt-3.5-turbo:acemeco:suffix:abc123 \
              -X DELETE \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.models.delete("ft:gpt-3.5-turbo:acemeco:suffix:abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const model = await client.models.del("ft:gpt-3.5-turbo:acemeco:suffix:abc123");

              console.log(model);
            }
            main();

  /moderations:
    post:
      operationId: createModeration
      tags:
        - Moderations
      summary: |
        Identify potentially harmful content in text and images. **Only** works with [OpenAI's Moderations endpoint](https://platform.openai.com/docs/guides/moderation) currently.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateModerationRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/CreateModerationResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/moderations \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -d '{
                "input": "I want to kill them."
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            moderation = client.moderations.create(input="I want to kill them.")
            print(moderation)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const moderation = await client.moderations.create({ input: "I want to kill them." });

              console.log(moderation);
            }
            main();

  /assistants:
    get:
      operationId: listAssistants
      tags:
        - Assistants
      summary: Returns a list of assistants.
      parameters:
        - name: limit
          in: query
          description: &pagination_limit_param_description |
            A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: &pagination_order_param_description |
            Sort order by the `created_at` timestamp of the objects. `asc` for ascending order and `desc` for descending order.
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: &pagination_after_param_description |
            A cursor for use in pagination. `after` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.
          schema:
            type: string
        - name: before
          in: query
          description: &pagination_before_param_description |
            A cursor for use in pagination. `before` is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListAssistantsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl "https://api.portkey.ai/v1/assistants?order=desc&limit=20" \
                      -H "Content-Type: application/json" \
                      -H "x-portkey-api-key: $PORTKEY_API_KEY" \
                      -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
                      -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_assistants = client.beta.assistants.list(
                order="desc",
                limit="20",
            )
            print(my_assistants.data)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myAssistants = await client.beta.assistants.list({
                order: "desc",
                limit: "20",
              });

              console.log(myAssistants.data);
            }

            main();
          response: &list_assistants_example |
            {
              "object": "list",
              "data": [
                {
                  "id": "asst_abc123",
                  "object": "assistant",
                  "created_at": 1698982736,
                  "name": "Coding Tutor",
                  "description": null,
                  "model": "gpt-4-turbo",
                  "instructions": "You are a helpful assistant designed to make me better at coding!",
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                },
                {
                  "id": "asst_abc456",
                  "object": "assistant",
                  "created_at": 1698982718,
                  "name": "My Assistant",
                  "description": null,
                  "model": "gpt-4-turbo",
                  "instructions": "You are a helpful assistant designed to make me better at coding!",
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                },
                {
                  "id": "asst_abc789",
                  "object": "assistant",
                  "created_at": 1698982643,
                  "name": null,
                  "description": null,
                  "model": "gpt-4-turbo",
                  "instructions": null,
                  "tools": [],
                  "tool_resources": {},
                  "metadata": {},
                  "top_p": 1.0,
                  "temperature": 1.0,
                  "response_format": "auto"
                }
              ],
              "first_id": "asst_abc123",
              "last_id": "asst_abc789",
              "has_more": false
            }

    post:
      operationId: createAssistant
      tags:
        - Assistants
      summary: Create an assistant with a model and instructions.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateAssistantRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/AssistantObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl "https://api.portkey.ai/v1/assistants" \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
                "name": "Math Tutor",
                "tools": [{"type": "code_interpreter"}],
                "model": "gpt-4-turbo"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_assistant = client.beta.assistants.create(
                instructions="You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
                name="Math Tutor",
                tools=[{"type": "code_interpreter"}],
                model="gpt-4-turbo",
            )
            print(my_assistant)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myAssistant = await client.beta.assistants.create({
                instructions:
                  "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
                name: "Math Tutor",
                tools: [{ type: "code_interpreter" }],
                model: "gpt-4-turbo",
              });

              console.log(myAssistant);
            }

            main();
          response: &create_assistants_example |
            {
              "id": "asst_abc123",
              "object": "assistant",
              "created_at": 1698984975,
              "name": "Math Tutor",
              "description": null,
              "model": "gpt-4-turbo",
              "instructions": "You are a personal math tutor. When asked a question, write and run Python code to answer the question.",
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
  /assistants/{assistant_id}:
    get:
      operationId: getAssistant
      tags:
        - Assistants
      summary: Retrieves an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/AssistantObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/assistants/asst_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_assistant = client.beta.assistants.retrieve("asst_abc123")
            print(my_assistant)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myAssistant = await client.beta.assistants.retrieve(
                "asst_abc123"
              );

              console.log(myAssistant);
            }

            main();
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4-turbo",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
    post:
      operationId: modifyAssistant
      tags:
        - Assistants
      summary: Modifies an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/ModifyAssistantRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/AssistantObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/assistants/asst_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
                  "tools": [{"type": "file_search"}],
                  "model": "gpt-4-turbo"
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_updated_assistant = client.beta.assistants.update(
              "asst_abc123",
              instructions="You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
              name="HR Helper",
              tools=[{"type": "file_search"}],
              model="gpt-4-turbo"
            )

            print(my_updated_assistant)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myUpdatedAssistant = await client.beta.assistants.update(
                "asst_abc123",
                {
                  instructions:
                    "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
                  name: "HR Helper",
                  tools: [{ type: "file_search" }],
                  model: "gpt-4-turbo"
                }
              );

              console.log(myUpdatedAssistant);
            }

            main();
          response: |
            {
              "id": "asst_123",
              "object": "assistant",
              "created_at": 1699009709,
              "name": "HR Helper",
              "description": null,
              "model": "gpt-4-turbo",
              "instructions": "You are an HR bot, and you have access to files to answer employee questions about company policies. Always response with info from either of the files.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "tool_resources": {
                "file_search": {
                  "vector_store_ids": []
                }
              },
              "metadata": {},
              "top_p": 1.0,
              "temperature": 1.0,
              "response_format": "auto"
            }
    delete:
      operationId: deleteAssistant
      tags:
        - Assistants
      summary: Delete an assistant.
      parameters:
        - in: path
          name: assistant_id
          required: true
          schema:
            type: string
          description: The ID of the assistant to delete.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteAssistantResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/assistants/asst_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -X DELETE
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = client.beta.assistants.delete("asst_abc123")
            print(response)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const response = await client.beta.assistants.del("asst_abc123");

              console.log(response);
            }
            main();
          response: |
            {
              "id": "asst_abc123",
              "object": "assistant.deleted",
              "deleted": true
            }

  /threads:
    post:
      operationId: createThread
      tags:
        - Assistants
      summary: Create a thread.
      requestBody:
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateThreadRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ThreadObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "messages": [{
                    "role": "user",
                    "content": "Hello, what is AI?"
                  }, {
                    "role": "user",
                    "content": "How does AI work? Explain it in simple terms."
                  }]
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            message_thread = client.beta.threads.create(
              messages=[
                {
                  "role": "user",
                  "content": "Hello, what is AI?"
                },
                {
                  "role": "user",
                  "content": "How does AI work? Explain it in simple terms."
                },
              ]
            )

            print(message_thread)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const messageThread = await client.beta.threads.create({
                messages: [
                  {
                    role: "user",
                    content: "Hello, what is AI?"
                  },
                  {
                    role: "user",
                    content: "How does AI work? Explain it in simple terms.",
                  },
                ],
              });

              console.log(messageThread);
            }

            main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {},
              "tool_resources": {}
            }

  /threads/{thread_id}:
    get:
      operationId: getThread
      tags:
        - Assistants
      summary: Retrieves a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ThreadObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_thread = client.beta.threads.retrieve("thread_abc123")
            print(my_thread)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myThread = await client.beta.threads.retrieve(
                "thread_abc123"
              );

              console.log(myThread);
            }

            main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {},
              "tool_resources": {
                "code_interpreter": {
                  "file_ids": []
                }
              }
            }
    post:
      operationId: modifyThread
      tags:
        - Assistants
      summary: Modifies a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to modify. Only the `metadata` can be modified.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/ModifyThreadRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ThreadObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "metadata": {
                    "modified": "true",
                    "user": "abc123"
                  }
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            my_updated_thread = client.beta.threads.update(
              "thread_abc123",
              metadata={
                "modified": "true",
                "user": "abc123"
              }
            )
            print(my_updated_thread)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const updatedThread = await client.beta.threads.update(
                "thread_abc123",
                {
                  metadata: { modified: "true", user: "abc123" },
                }
              );

              console.log(updatedThread);
            }

            main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread",
              "created_at": 1699014083,
              "metadata": {
                "modified": "true",
                "user": "abc123"
              },
              "tool_resources": {}
            }
    delete:
      operationId: deleteThread
      tags:
        - Assistants
      summary: Delete a thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to delete.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteThreadResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -X DELETE
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            response = client.beta.threads.delete("thread_abc123")
            print(response)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const response = await client.beta.threads.del("thread_abc123");

              console.log(response);
            }
            main();
          response: |
            {
              "id": "thread_abc123",
              "object": "thread.deleted",
              "deleted": true
            }

  /threads/{thread_id}/messages:
    get:
      operationId: listMessages
      tags:
        - Assistants
      summary: Returns a list of messages for a given thread.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) the messages belong to.
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
        - name: run_id
          in: query
          description: |
            Filter messages by the run ID that generated them.
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListMessagesResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/messages \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            thread_messages = client.beta.threads.messages.list("thread_abc123")
            print(thread_messages.data)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const threadMessages = await client.beta.threads.messages.list(
                "thread_abc123"
              );

              console.log(threadMessages.data);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "msg_abc123",
                  "object": "thread.message",
                  "created_at": 1699016383,
                  "assistant_id": null,
                  "thread_id": "thread_abc123",
                  "run_id": null,
                  "role": "user",
                  "content": [
                    {
                      "type": "text",
                      "text": {
                        "value": "How does AI work? Explain it in simple terms.",
                        "annotations": []
                      }
                    }
                  ],
                  "attachments": [],
                  "metadata": {}
                },
                {
                  "id": "msg_abc456",
                  "object": "thread.message",
                  "created_at": 1699016383,
                  "assistant_id": null,
                  "thread_id": "thread_abc123",
                  "run_id": null,
                  "role": "user",
                  "content": [
                    {
                      "type": "text",
                      "text": {
                        "value": "Hello, what is AI?",
                        "annotations": []
                      }
                    }
                  ],
                  "attachments": [],
                  "metadata": {}
                }
              ],
              "first_id": "msg_abc123",
              "last_id": "msg_abc456",
              "has_more": false
            }
    post:
      operationId: createMessage
      tags:
        - Assistants
      summary: Create a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to create a message for.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateMessageRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/MessageObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/messages \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "role": "user",
                  "content": "How does AI work? Explain it in simple terms."
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            thread_message = client.beta.threads.messages.create(
              "thread_abc123",
              role="user",
              content="How does AI work? Explain it in simple terms.",
            )
            print(thread_message)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const threadMessages = await client.beta.threads.messages.create(
                "thread_abc123",
                { role: "user", content: "How does AI work? Explain it in simple terms." }
              );

              console.log(threadMessages);
            }

            main();
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1713226573,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "attachments": [],
              "metadata": {}
            }

  /threads/{thread_id}/messages/{message_id}:
    get:
      operationId: getMessage
      tags:
        - Assistants
      summary: Retrieve a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/MessageObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/messages/msg_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            message = client.beta.threads.messages.retrieve(
              message_id="msg_abc123",
              thread_id="thread_abc123",
            )
            print(message)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const message = await client.beta.threads.messages.retrieve(
                "thread_abc123",
                "msg_abc123"
              );

              console.log(message);
            }

            main();
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1699017614,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "attachments": [],
              "metadata": {}
            }
    post:
      operationId: modifyMessage
      tags:
        - Assistants
      summary: Modifies a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/ModifyMessageRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/MessageObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/messages/msg_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "metadata": {
                    "modified": "true",
                    "user": "abc123"
                  }
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            message = client.beta.threads.messages.update(
              message_id="msg_abc12",
              thread_id="thread_abc123",
              metadata={
                "modified": "true",
                "user": "abc123",
              },
            )
            print(message)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const message = await client.beta.threads.messages.update(
                "thread_abc123",
                "msg_abc123",
                {
                  metadata: {
                    modified: "true",
                    user: "abc123",
                  },
                }
              }'
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message",
              "created_at": 1699017614,
              "assistant_id": null,
              "thread_id": "thread_abc123",
              "run_id": null,
              "role": "user",
              "content": [
                {
                  "type": "text",
                  "text": {
                    "value": "How does AI work? Explain it in simple terms.",
                    "annotations": []
                  }
                }
              ],
              "file_ids": [],
              "metadata": {
                "modified": "true",
                "user": "abc123"
              }
            }
    delete:
      operationId: deleteMessage
      tags:
        - Assistants
      summary: Deletes a message.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this message belongs.
        - in: path
          name: message_id
          required: true
          schema:
            type: string
          description: The ID of the message to delete.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteMessageResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl -X DELETE https://api.portkey.ai/v1/threads/thread_abc123/messages/msg_abc123 \
              -H "Content-Type: application/json" \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            deleted_message = client.beta.threads.messages.delete(
              message_id="msg_abc12",
              thread_id="thread_abc123",
            )
            print(deleted_message)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const deletedMessage = await client.beta.threads.messages.del(
                "thread_abc123",
                "msg_abc123"
              );

              console.log(deletedMessage);
            }
          response: |
            {
              "id": "msg_abc123",
              "object": "thread.message.deleted",
              "deleted": true
            }

  /threads/runs:
    post:
      operationId: createThreadAndRun
      tags:
        - Assistants
      summary: Create a thread and run it in one request.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateThreadAndRunRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/runs \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                  "assistant_id": "asst_abc123",
                  "thread": {
                    "messages": [
                      {"role": "user", "content": "Explain deep learning to a 5 year old."}
                    ]
                  }
                }'
        - lang: python
          source: |
            from portkey_ai import Portkey

              client = Portkey(
                api_key = "PORTKEY_API_KEY",
                virtual_key = "PROVIDER_VIRTUAL_KEY"
              )

              run = client.beta.threads.create_and_run(
                assistant_id="asst_abc123",
                thread={
                  "messages": [
                    {"role": "user", "content": "Explain deep learning to a 5 year old."}
                  ]
                }
              )

              print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.createAndRun({
                assistant_id: "asst_abc123",
                thread: {
                  messages: [
                    { role: "user", content: "Explain deep learning to a 5 year old." },
                  ],
                },
              });

              console.log(run);
            }

            main();
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699076792,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "queued",
              "started_at": null,
              "expires_at": 1699077392,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": null,
              "required_action": null,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": "You are a helpful assistant.",
              "tools": [],
              "tool_resources": {},
              "metadata": {},
              "temperature": 1.0,
              "top_p": 1.0,
              "max_completion_tokens": null,
              "max_prompt_tokens": null,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "incomplete_details": null,
              "usage": null,
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }

  /threads/{thread_id}/runs:
    get:
      operationId: listRuns
      tags:
        - Assistants
      summary: Returns a list of runs belonging to a thread.
      parameters:
        - name: thread_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the thread the run belongs to.
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListRunsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            runs = client.beta.threads.runs.list(
              "thread_abc123"
            )

            print(runs)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const runs = await client.beta.threads.runs.list(
                "thread_abc123"
              );

              console.log(runs);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "run_abc123",
                  "object": "thread.run",
                  "created_at": 1699075072,
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "status": "completed",
                  "started_at": 1699075072,
                  "expires_at": null,
                  "cancelled_at": null,
                  "failed_at": null,
                  "completed_at": 1699075073,
                  "last_error": null,
                  "model": "gpt-4-turbo",
                  "instructions": null,
                  "incomplete_details": null,
                  "tools": [
                    {
                      "type": "code_interpreter"
                    }
                  ],
                  "tool_resources": {
                    "code_interpreter": {
                      "file_ids": [
                        "file-abc123",
                        "file-abc456"
                      ]
                    }
                  },
                  "metadata": {},
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  },
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_prompt_tokens": 1000,
                  "max_completion_tokens": 1000,
                  "truncation_strategy": {
                    "type": "auto",
                    "last_messages": null
                  },
                  "response_format": "auto",
                  "tool_choice": "auto",
                  "parallel_tool_calls": true
                },
                {
                  "id": "run_abc456",
                  "object": "thread.run",
                  "created_at": 1699063290,
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "status": "completed",
                  "started_at": 1699063290,
                  "expires_at": null,
                  "cancelled_at": null,
                  "failed_at": null,
                  "completed_at": 1699063291,
                  "last_error": null,
                  "model": "gpt-4-turbo",
                  "instructions": null,
                  "incomplete_details": null,
                  "tools": [
                    {
                      "type": "code_interpreter"
                    }
                  ],
                  "tool_resources": {
                    "code_interpreter": {
                      "file_ids": [
                        "file-abc123",
                        "file-abc456"
                      ]
                    }
                  },
                  "metadata": {},
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  },
                  "temperature": 1.0,
                  "top_p": 1.0,
                  "max_prompt_tokens": 1000,
                  "max_completion_tokens": 1000,
                  "truncation_strategy": {
                    "type": "auto",
                    "last_messages": null
                  },
                  "response_format": "auto",
                  "tool_choice": "auto",
                  "parallel_tool_calls": true
                }
              ],
              "first_id": "run_abc123",
              "last_id": "run_abc456",
              "has_more": false
            }
    post:
      operationId: createRun
      tags:
        - Assistants
      summary: Create a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to run.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateRunRequest"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"
      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "assistant_id": "asst_abc123"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run = client.beta.threads.runs.create(
              thread_id="thread_abc123",
              assistant_id="asst_abc123"
            )

            print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.runs.create(
                "thread_abc123",
                { assistant_id: "asst_abc123" }
              );

              console.log(run);
            }

            main();
          response: &run_object_example |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699063290,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "queued",
              "started_at": 1699063290,
              "expires_at": null,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": 1699063291,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": null,
              "incomplete_details": null,
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "metadata": {},
              "usage": null,
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }

  /threads/{thread_id}/runs/{run_id}:
    get:
      operationId: getRun
      tags:
        - Assistants
      summary: Retrieves a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs/run_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run = client.beta.threads.runs.retrieve(
              thread_id="thread_abc123",
              run_id="run_abc123"
            )

            print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.runs.retrieve(
                "thread_abc123",
                "run_abc123"
              );

              console.log(run);
            }

            main();
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699075072,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "completed",
              "started_at": 1699075072,
              "expires_at": null,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": 1699075073,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": null,
              "incomplete_details": null,
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "metadata": {},
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              },
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }
    post:
      operationId: modifyRun
      tags:
        - Assistants
      summary: Modifies a run.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/ModifyRunRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs/run_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "metadata": {
                  "user_id": "user_abc123"
                }
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run = client.beta.threads.runs.update(
              thread_id="thread_abc123",
              run_id="run_abc123",
              metadata={"user_id": "user_abc123"},
            )

            print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.runs.update(
                "thread_abc123",
                "run_abc123",
                {
                  metadata: {
                    user_id: "user_abc123",
                  },
                }
              );

              console.log(run);
            }

            main();
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699075072,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "completed",
              "started_at": 1699075072,
              "expires_at": null,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": 1699075073,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": null,
              "incomplete_details": null,
              "tools": [
                {
                  "type": "code_interpreter"
                }
              ],
              "tool_resources": {
                "code_interpreter": {
                  "file_ids": [
                    "file-abc123",
                    "file-abc456"
                  ]
                }
              },
              "metadata": {
                "user_id": "user_abc123"
              },
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              },
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }

  /threads/{thread_id}/runs/{run_id}/submit_tool_outputs:
    post:
      operationId: submitToolOuputsToRun
      tags:
        - Assistants
      summary: |
        When a run has the `status: "requires_action"` and `required_action.type` is `submit_tool_outputs`, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) to which this run belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run that requires the tool output submission.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/SubmitToolOutputsRunRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_123/runs/run_123/submit_tool_outputs \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "tool_outputs": [
                  {
                    "tool_call_id": "call_001",
                    "output": "70 degrees and sunny."
                  }
                ]
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

              client = Portkey(
                api_key = "PORTKEY_API_KEY",
                virtual_key = "PROVIDER_VIRTUAL_KEY"
              )

              run = client.beta.threads.runs.submit_tool_outputs(
                thread_id="thread_123",
                run_id="run_123",
                tool_outputs=[
                  {
                    "tool_call_id": "call_001",
                    "output": "70 degrees and sunny."
                  }
                ]
              )

              print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.runs.submitToolOutputs(
                "thread_123",
                "run_123",
                {
                  tool_outputs: [
                    {
                      tool_call_id: "call_001",
                      output: "70 degrees and sunny.",
                    },
                  ],
                }
              );

              console.log(run);
            }

            main();
          response: |
            {
              "id": "run_123",
              "object": "thread.run",
              "created_at": 1699075592,
              "assistant_id": "asst_123",
              "thread_id": "thread_123",
              "status": "queued",
              "started_at": 1699075592,
              "expires_at": 1699076192,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": null,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": null,
              "tools": [
                {
                  "type": "function",
                  "function": {
                    "name": "get_current_weather",
                    "description": "Get the current weather in a given location",
                    "parameters": {
                      "type": "object",
                      "properties": {
                        "location": {
                          "type": "string",
                          "description": "The city and state, e.g. San Francisco, CA"
                        },
                        "unit": {
                          "type": "string",
                          "enum": ["celsius", "fahrenheit"]
                        }
                      },
                      "required": ["location"]
                    }
                  }
                }
              ],
              "metadata": {},
              "usage": null,
              "temperature": 1.0,
              "top_p": 1.0,
              "max_prompt_tokens": 1000,
              "max_completion_tokens": 1000,
              "truncation_strategy": {
                "type": "auto",
                "last_messages": null
              },
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }

  /threads/{thread_id}/runs/{run_id}/cancel:
    post:
      operationId: cancelRun
      tags:
        - Assistants
      summary: Cancels a run that is `in_progress`.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which this run belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to cancel.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs/run_abc123/cancel \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "OpenAI-Beta: assistants=v2" \
              -X POST
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run = client.beta.threads.runs.cancel(
              thread_id="thread_abc123",
              run_id="run_abc123"
            )

            print(run)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const run = await client.beta.threads.runs.cancel(
                "thread_abc123",
                "run_abc123"
              );

              console.log(run);
            }

            main();
          response: |
            {
              "id": "run_abc123",
              "object": "thread.run",
              "created_at": 1699076126,
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "status": "cancelling",
              "started_at": 1699076126,
              "expires_at": 1699076726,
              "cancelled_at": null,
              "failed_at": null,
              "completed_at": null,
              "last_error": null,
              "model": "gpt-4-turbo",
              "instructions": "You summarize books.",
              "tools": [
                {
                  "type": "file_search"
                }
              ],
              "tool_resources": {
                "file_search": {
                  "vector_store_ids": ["vs_123"]
                }
              },
              "metadata": {},
              "usage": null,
              "temperature": 1.0,
              "top_p": 1.0,
              "response_format": "auto",
              "tool_choice": "auto",
              "parallel_tool_calls": true
            }

  /threads/{thread_id}/runs/{run_id}/steps:
    get:
      operationId: listRunSteps
      tags:
        - Assistants
      summary: Returns a list of run steps belonging to a run.
      parameters:
        - name: thread_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the thread the run and run steps belong to.
        - name: run_id
          in: path
          required: true
          schema:
            type: string
          description: The ID of the run the run steps belong to.
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListRunStepsResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs/run_abc123/steps \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run_steps = client.beta.threads.runs.steps.list(
                thread_id="thread_abc123",
                run_id="run_abc123"
            )

            print(run_steps)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const runStep = await client.beta.threads.runs.steps.list(
                "thread_abc123",
                "run_abc123"
              );
              console.log(runStep);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "step_abc123",
                  "object": "thread.run.step",
                  "created_at": 1699063291,
                  "run_id": "run_abc123",
                  "assistant_id": "asst_abc123",
                  "thread_id": "thread_abc123",
                  "type": "message_creation",
                  "status": "completed",
                  "cancelled_at": null,
                  "completed_at": 1699063291,
                  "expired_at": null,
                  "failed_at": null,
                  "last_error": null,
                  "step_details": {
                    "type": "message_creation",
                    "message_creation": {
                      "message_id": "msg_abc123"
                    }
                  },
                  "usage": {
                    "prompt_tokens": 123,
                    "completion_tokens": 456,
                    "total_tokens": 579
                  }
                }
              ],
              "first_id": "step_abc123",
              "last_id": "step_abc456",
              "has_more": false
            }

  /threads/{thread_id}/runs/{run_id}/steps/{step_id}:
    get:
      operationId: getRunStep
      tags:
        - Assistants
      summary: Retrieves a run step.
      parameters:
        - in: path
          name: thread_id
          required: true
          schema:
            type: string
          description: The ID of the thread to which the run and run step belongs.
        - in: path
          name: run_id
          required: true
          schema:
            type: string
          description: The ID of the run to which the run step belongs.
        - in: path
          name: step_id
          required: true
          schema:
            type: string
          description: The ID of the run step to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/RunStepObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/threads/thread_abc123/runs/run_abc123/steps/step_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            run_step = client.beta.threads.runs.steps.retrieve(
                thread_id="thread_abc123",
                run_id="run_abc123",
                step_id="step_abc123"
            )

            print(run_step)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const runStep = await client.beta.threads.runs.steps.retrieve(
                "thread_abc123",
                "run_abc123",
                "step_abc123"
              );
              console.log(runStep);
            }

            main();
          response: &run_step_object_example |
            {
              "id": "step_abc123",
              "object": "thread.run.step",
              "created_at": 1699063291,
              "run_id": "run_abc123",
              "assistant_id": "asst_abc123",
              "thread_id": "thread_abc123",
              "type": "message_creation",
              "status": "completed",
              "cancelled_at": null,
              "completed_at": 1699063291,
              "expired_at": null,
              "failed_at": null,
              "last_error": null,
              "step_details": {
                "type": "message_creation",
                "message_creation": {
                  "message_id": "msg_abc123"
                }
              },
              "usage": {
                "prompt_tokens": 123,
                "completion_tokens": 456,
                "total_tokens": 579
              }
            }

  /vector_stores:
    get:
      operationId: listVectorStores
      tags:
        - Vector Stores
      summary: Returns a list of vector stores.
      parameters:
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListVectorStoresResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_stores = client.beta.vector_stores.list()
            print(vector_stores)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStores = await client.beta.vectorStores.list();
              console.log(vectorStores);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "vs_abc123",
                  "object": "vector_store",
                  "created_at": 1699061776,
                  "name": "Support FAQ",
                  "bytes": 139920,
                  "file_counts": {
                    "in_progress": 0,
                    "completed": 3,
                    "failed": 0,
                    "cancelled": 0,
                    "total": 3
                  }
                },
                {
                  "id": "vs_abc456",
                  "object": "vector_store",
                  "created_at": 1699061776,
                  "name": "Support FAQ v2",
                  "bytes": 139920,
                  "file_counts": {
                    "in_progress": 0,
                    "completed": 3,
                    "failed": 0,
                    "cancelled": 0,
                    "total": 3
                  }
                }
              ],
              "first_id": "vs_abc123",
              "last_id": "vs_abc456",
              "has_more": false
            }
    post:
      operationId: createVectorStore
      tags:
        - Vector Stores
      summary: Create a vector store.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateVectorStoreRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
              -d '{
                "name": "Support FAQ"
            }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store = client.beta.vector_stores.create(
              name="Support FAQ"
            )
            print(vector_store)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStore = await client.beta.vectorStores.create({
                name: "Support FAQ"
              });
              console.log(vectorStore);
            }

            main();
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776,
              "name": "Support FAQ",
              "bytes": 139920,
              "file_counts": {
                "in_progress": 0,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 3
              }
            }

  /vector_stores/{vector_store_id}:
    get:
      operationId: getVectorStore
      tags:
        - Vector Stores
      summary: Retrieves a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to retrieve.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store = client.beta.vector_stores.retrieve(
              vector_store_id="vs_abc123"
            )
            print(vector_store)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStore = await client.beta.vectorStores.retrieve(
                "vs_abc123"
              );
              console.log(vectorStore);
            }

            main();
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776
            }
    post:
      operationId: modifyVectorStore
      tags:
        - Vector Stores
      summary: Modifies a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to modify.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/UpdateVectorStoreRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
              -d '{
                "name": "Support FAQ"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store = client.beta.vector_stores.update(
              vector_store_id="vs_abc123",
              name="Support FAQ"
            )
            print(vector_store)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStore = await client.beta.vectorStores.update(
                "vs_abc123",
                {
                  name: "Support FAQ"
                }
              );
              console.log(vectorStore);
            }

            main();
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store",
              "created_at": 1699061776,
              "name": "Support FAQ",
              "bytes": 139920,
              "file_counts": {
                "in_progress": 0,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 3
              }
            }

    delete:
      operationId: deleteVectorStore
      tags:
        - Vector Stores
      summary: Delete a vector store.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store to delete.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteVectorStoreResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -X DELETE
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            deleted_vector_store = client.beta.vector_stores.delete(
              vector_store_id="vs_abc123"
            )
            print(deleted_vector_store)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const deletedVectorStore = await client.beta.vectorStores.del(
                "vs_abc123"
              );
              console.log(deletedVectorStore);
            }

            main();
          response: |
            {
              "id": "vs_abc123",
              "object": "vector_store.deleted",
              "deleted": true
            }

  /vector_stores/{vector_store_id}/files:
    get:
      operationId: listVectorStoreFiles
      tags:
        - Vector Stores
      summary: Returns a list of vector store files.
      parameters:
        - name: vector_store_id
          in: path
          description: The ID of the vector store that the files belong to.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
        - name: filter
          in: query
          description: "Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`."
          schema:
            type: string
            enum: ["in_progress", "completed", "failed", "cancelled"]
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListVectorStoreFilesResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_files = client.beta.vector_stores.files.list(
              vector_store_id="vs_abc123"
            )
            print(vector_store_files)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStoreFiles = await client.beta.vectorStores.files.list(
                "vs_abc123"
              );
              console.log(vectorStoreFiles);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "file-abc123",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                },
                {
                  "id": "file-abc456",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                }
              ],
              "first_id": "file-abc123",
              "last_id": "file-abc456",
              "has_more": false
            }
    post:
      operationId: createVectorStoreFile
      tags:
        - Vector Stores
      summary: Create a vector store file by attaching a [File](https://platform.openai.com/docs/api-reference/files) to a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object).
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: |
            The ID of the vector store for which to create a File.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateVectorStoreFileRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreFileObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "file_id": "file-abc123"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_file = client.beta.vector_stores.files.create(
              vector_store_id="vs_abc123",
              file_id="file-abc123"
            )
            print(vector_store_file)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myVectorStoreFile = await client.beta.vectorStores.files.create(
                "vs_abc123",
                {
                  file_id: "file-abc123"
                }
              );
              console.log(myVectorStoreFile);
            }

            main();
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "usage_bytes": 1234,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }

  /vector_stores/{vector_store_id}/files/{file_id}:
    get:
      operationId: getVectorStoreFile
      tags:
        - Vector Stores
      summary: Retrieves a vector store file.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store that the file belongs to.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
            example: file-abc123
          description: The ID of the file being retrieved.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreFileObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files/file-abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_file = client.beta.vector_stores.files.retrieve(
              vector_store_id="vs_abc123",
              file_id="file-abc123"
            )
            print(vector_store_file)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStoreFile = await client.beta.vectorStores.files.retrieve(
                "vs_abc123",
                "file-abc123"
              );
              console.log(vectorStoreFile);
            }

            main();
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file",
              "created_at": 1699061776,
              "vector_store_id": "vs_abcd",
              "status": "completed",
              "last_error": null
            }
    delete:
      operationId: deleteVectorStoreFile
      tags:
        - Vector Stores
      summary: Delete a vector store file. This will remove the file from the vector store but the file itself will not be deleted. To delete the file, use the [delete file](https://platform.openai.com/docs/api-reference/files/delete) endpoint.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store that the file belongs to.
        - in: path
          name: file_id
          required: true
          schema:
            type: string
          description: The ID of the file to delete.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DeleteVectorStoreFileResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files/file-abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -X DELETE
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            deleted_vector_store_file = client.beta.vector_stores.files.delete(
                vector_store_id="vs_abc123",
                file_id="file-abc123"
            )
            print(deleted_vector_store_file)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const deletedVectorStoreFile = await client.beta.vectorStores.files.del(
                "vs_abc123",
                "file-abc123"
              );
              console.log(deletedVectorStoreFile);
            }

            main();
          response: |
            {
              "id": "file-abc123",
              "object": "vector_store.file.deleted",
              "deleted": true
            }

  /vector_stores/{vector_store_id}/file_batches:
    post:
      operationId: createVectorStoreFileBatch
      tags:
        - Vector Stores
      summary: Create a vector store file batch.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: |
            The ID of the vector store for which to create a File Batch.
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateVectorStoreFileBatchRequest"
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreFileBatchObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/file_batches \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json \
              -H "OpenAI-Beta: assistants=v2" \
              -d '{
                "file_ids": ["file-abc123", "file-abc456"]
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_file_batch = client.beta.vector_stores.file_batches.create(
              vector_store_id="vs_abc123",
              file_ids=["file-abc123", "file-abc456"]
            )
            print(vector_store_file_batch)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const myVectorStoreFileBatch = await client.beta.vectorStores.fileBatches.create(
                "vs_abc123",
                {
                  file_ids: ["file-abc123", "file-abc456"]
                }
              );
              console.log(myVectorStoreFileBatch);
            }

            main();
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "in_progress",
              "file_counts": {
                "in_progress": 1,
                "completed": 1,
                "failed": 0,
                "cancelled": 0,
                "total": 0,
              }
            }

  /vector_stores/{vector_store_id}/file_batches/{batch_id}:
    get:
      operationId: getVectorStoreFileBatch
      tags:
        - Vector Stores
      summary: Retrieves a vector store file batch.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
            example: vs_abc123
          description: The ID of the vector store that the file batch belongs to.
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
            example: vsfb_abc123
          description: The ID of the file batch being retrieved.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreFileBatchObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_file_batch = client.beta.vector_stores.file_batches.retrieve(
              vector_store_id="vs_abc123",
              batch_id="vsfb_abc123"
            )
            print(vector_store_file_batch)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStoreFileBatch = await client.beta.vectorStores.fileBatches.retrieve(
                "vs_abc123",
                "vsfb_abc123"
              );
              console.log(vectorStoreFileBatch);
            }

            main();
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "in_progress",
              "file_counts": {
                "in_progress": 1,
                "completed": 1,
                "failed": 0,
                "cancelled": 0,
                "total": 0,
              }
            }

  /vector_stores/{vector_store_id}/file_batches/{batch_id}/cancel:
    post:
      operationId: cancelVectorStoreFileBatch
      tags:
        - Vector Stores
      summary: Cancel a vector store file batch. This attempts to cancel the processing of files in this batch as soon as possible.
      parameters:
        - in: path
          name: vector_store_id
          required: true
          schema:
            type: string
          description: The ID of the vector store that the file batch belongs to.
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the file batch to cancel.
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VectorStoreFileBatchObject"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/cancel \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2" \
              -X POST
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            deleted_vector_store_file_batch = client.beta.vector_stores.file_batches.cancel(
                vector_store_id="vs_abc123",
                file_batch_id="vsfb_abc123"
            )
            print(deleted_vector_store_file_batch)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const deletedVectorStoreFileBatch = await client.vector_stores.fileBatches.cancel(
                "vs_abc123",
                "vsfb_abc123"
              );
              console.log(deletedVectorStoreFileBatch);
            }

            main();
          response: |
            {
              "id": "vsfb_abc123",
              "object": "vector_store.file_batch",
              "created_at": 1699061776,
              "vector_store_id": "vs_abc123",
              "status": "cancelling",
              "file_counts": {
                "in_progress": 12,
                "completed": 3,
                "failed": 0,
                "cancelled": 0,
                "total": 15,
              }
            }

  /vector_stores/{vector_store_id}/file_batches/{batch_id}/files:
    get:
      operationId: listFilesInVectorStoreBatch
      tags:
        - Vector Stores
      summary: Returns a list of vector store files in a batch.
      parameters:
        - name: vector_store_id
          in: path
          description: The ID of the vector store that the files belong to.
          required: true
          schema:
            type: string
        - name: batch_id
          in: path
          description: The ID of the file batch that the files belong to.
          required: true
          schema:
            type: string
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
        - name: order
          in: query
          description: *pagination_order_param_description
          schema:
            type: string
            default: desc
            enum: ["asc", "desc"]
        - name: after
          in: query
          description: *pagination_after_param_description
          schema:
            type: string
        - name: before
          in: query
          description: *pagination_before_param_description
          schema:
            type: string
        - name: filter
          in: query
          description: "Filter by file status. One of `in_progress`, `completed`, `failed`, `cancelled`."
          schema:
            type: string
            enum: ["in_progress", "completed", "failed", "cancelled"]
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListVectorStoreFilesResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/vector_stores/vs_abc123/files_batches/vsfb_abc123/files \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -H "OpenAI-Beta: assistants=v2"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            vector_store_files = client.beta.vector_stores.file_batches.list_files(
              vector_store_id="vs_abc123",
              batch_id="vsfb_abc123"
            )
            print(vector_store_files)
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const vectorStoreFiles = await client.beta.vectorStores.fileBatches.listFiles(
                "vs_abc123",
                "vsfb_abc123"
              );
              console.log(vectorStoreFiles);
            }

            main();
          response: |
            {
              "object": "list",
              "data": [
                {
                  "id": "file-abc123",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                },
                {
                  "id": "file-abc456",
                  "object": "vector_store.file",
                  "created_at": 1699061776,
                  "vector_store_id": "vs_abc123"
                }
              ],
              "first_id": "file-abc123",
              "last_id": "file-abc456",
              "has_more": false
            }

  /batches:
    post:
      summary: Creates and executes a batch from an uploaded file of requests
      operationId: createBatch
      tags:
        - Batch
      requestBody:
        required: true
        content:
          application/json:
            schema:
              anyOf:
                - $ref: "#/components/schemas/OpenAIBatchJob"
                - $ref: "#/components/schemas/BedrockBatchJob"
                - $ref: "#/components/schemas/VertexBatchJob"
                - $ref: "#/components/schemas/PortkeyBatchJob"
      responses:
        "200":
          description: Batch created successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Batch"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/batches \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -d '{
                "input_file_id": "file-abc123",
                "endpoint": "/v1/chat/completions",
                "completion_window": "24h"
              }'
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.batches.create(
              input_file_id="file-abc123",
              endpoint="/v1/chat/completions",
              completion_window="24h"
            )
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const batch = await client.batches.create({
                input_file_id: "file-abc123",
                endpoint: "/v1/chat/completions",
                completion_window: "24h"
              });

              console.log(batch);
            }

            main();

    get:
      operationId: listBatches
      tags:
        - Batch
      summary: List your organization's batches.
      parameters:
        - in: query
          name: after
          required: false
          schema:
            type: string
          description: *pagination_after_param_description
        - name: limit
          in: query
          description: *pagination_limit_param_description
          required: false
          schema:
            type: integer
            default: 20
      responses:
        "200":
          description: Batch listed successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ListBatchesResponse"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/batches?limit=2 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json"
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.batches.list()
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const list = await client.batches.list();

              for await (const batch of list) {
                console.log(batch);
              }
            }

            main();

  /batches/{batch_id}:
    get:
      operationId: retrieveBatch
      tags:
        - Batch
      summary: Retrieves a batch.
      parameters:
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the batch to retrieve.
      responses:
        "200":
          description: Batch retrieved successfully.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Batch"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/batches/batch_abc123 \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.batches.retrieve("batch_abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const batch = await client.batches.retrieve("batch_abc123");

              console.log(batch);
            }

            main();

  /batches/{batch_id}/cancel:
    post:
      operationId: cancelBatch
      tags:
        - Batch
      summary: Cancels an in-progress batch. The batch will be in status `cancelling` for up to 10 minutes, before changing to `cancelled`, where it will have partial results (if any) available in the output file.
      parameters:
        - in: path
          name: batch_id
          required: true
          schema:
            type: string
          description: The ID of the batch to cancel.
      responses:
        "200":
          description: Batch is cancelling. Returns the cancelling batch's details.
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Batch"

      security:
        - Portkey-Key: []
          Virtual-Key: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
        - Portkey-Key: []
          Config: []
        - Portkey-Key: []
          Provider-Auth: []
          Provider-Name: []
          Custom-Host: []

      x-code-samples:
        - lang: curl
          source: |
            curl https://api.portkey.ai/v1/batches/batch_abc123/cancel \
              -H "x-portkey-api-key: $PORTKEY_API_KEY" \
              -H "x-portkey-virtual-key: $PORTKEY_PROVIDER_VIRTUAL_KEY" \
              -H "Content-Type: application/json" \
              -X POST
        - lang: python
          source: |
            from portkey_ai import Portkey

            client = Portkey(
              api_key = "PORTKEY_API_KEY",
              virtual_key = "PROVIDER_VIRTUAL_KEY"
            )

            client.batches.cancel("batch_abc123")
        - lang: javascript
          source: |
            import Portkey from 'portkey-ai';

            const client = new Portkey({
              apiKey: 'PORTKEY_API_KEY',
              virtualKey: 'PROVIDER_VIRTUAL_KEY'
            });

            async function main() {
              const batch = await client.batches.cancel("batch_abc123");

              console.log(batch);
            }

            main();

  /configs:
    get:
      summary: List all configs
      tags:
        - Configs
      operationId: listConfigs
      responses:
        "200":
          description: A list of configs
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: array
                    items:
                      type: object
                      properties:
                        id:
                          type: string
                          format: uuid
                        name:
                          type: string
                        slug:
                          type: string
                        organisation_id:
                          type: string
                          format: uuid
                        workspace_id:
                          type: string
                          format: uuid
                        is_default:
                          type: integer
                        status:
                          type: string
                        owner_id:
                          type: string
                          format: uuid
                        updated_by:
                          type: string
                          format: uuid
                        created_at:
                          type: string
                          format: date-time
                        last_updated_at:
                          type: string
                          format: date-time
              examples:
                example-1:
                  value:
                    {
                      "success": true,
                      "data":
                        [
                          {
                            "id": "4e54a1a4-109c-43ee-b0f7-11e7d60b0066",
                            "name": "Pplx Cache Test",
                            "slug": "pc-pplx-c-ca7a87",
                            "organisation_id": "472d2804-d054-4226-b4ae-9d4e2e61e69e",
                            "workspace_id": "472d2804-d054-4226-b4ae-9d4e2e61e69e",
                            "is_default": 0,
                            "status": "active",
                            "owner_id": "c4c7996d-be62-429d-b787-5d48fe94da86",
                            "updated_by": "439268ba-94a2-4031-9ca7-ca88ddda5096",
                            "created_at": "2024-05-12T21:37:06.000Z",
                            "last_updated_at": "2024-05-23T23:36:06.000Z",
                          },
                        ],
                    }
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Retrieve the configuration
            config = portkey.configs.list(
                workspace_id="WORKSPACE_ID"
            )

            print(config)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey:"PORTKEY_API_KEY",
            })

            const config=await portkey.configs.list({
                workspace_id:"WORKSPACE_ID"
            })
            console.log(config);

    post:
      summary: Create a config
      tags:
        - Configs
      operationId: createConfig
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                config:
                  type: object
                isDefault:
                  type: integer
                workspace_id:
                  type: string
                  format: uuid
                  description: optional, when using organisation admin API keys
            examples:
              example-1:
                value:
                  {
                    "name": "New config",
                    "config": { "retry": { "attempts": 3 } },
                    "workspace_id": "",
                    "isDefault": 1,
                  }
      responses:
        "200":
          description: Config created successfully
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      id:
                        type: string
                        format: uuid
                      version_id:
                        type: string
                        format: uuid
              examples:
                example-1:
                  value:
                    {
                      "success": true,
                      "data":
                        {
                          "id": "f3d8d070-f29d-43a3-bf97-3159c60f4ce0",
                          "version_id": "0db4065b-ead2-4daa-bf5e-7e9106585133",
                        },
                    }
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Create a new configuration
            config = portkey.configs.create(
                name="ConfigName_0909",
                config={
                    "retry": {
                        "attempts": 3
                    },
                    "cache": {
                        "mode": "simple"
                    }
                },
                workspace_id="WORKSPACE_ID",
            )

            print(config)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey:"PORTKEY_API_KEY",
            })

            const config=await portkey.configs.create({
                name:"ConfigName_0909",
                config:{
                    "retry": {
                        "attempts": 3
                    },
                    "cache": {
                        "mode": "simple"
                    }
                },
                workspace_id:"WORKSPACE_ID"
            })

            console.log(config);

  /configs/{slug}:
    get:
      summary: Get a config
      tags:
        - Configs
      operationId: getConfig
      parameters:
        - name: slug
          in: path
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Config details
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      config:
                        type: object
                        properties:
                          retry:
                            type: object
                            properties:
                              attempts:
                                type: integer
                              on_status_codes:
                                type: array
                                items:
                                  type: integer
                          cache:
                            type: object
                            properties:
                              mode:
                                type: string
                              max_age:
                                type: integer
                          strategy:
                            type: object
                            properties:
                              mode:
                                type: string
                          targets:
                            type: array
                            items:
                              type: object
                              properties:
                                provider:
                                  type: string
                                virtual_key:
                                  type: string
              examples:
                example-1:
                  value:
                    {
                      "success": true,
                      "data":
                        {
                          "config":
                            {
                              "retry":
                                {
                                  "attempts": 5,
                                  "on_status_codes": [429, 529],
                                },
                              "cache": { "mode": "simple", "max_age": 3600 },
                              "strategy": { "mode": "fallback" },
                              "targets":
                                [
                                  {
                                    "provider": "openai",
                                    "virtual_key": "main-258f4d",
                                  },
                                  {
                                    "provider": "azure-openai",
                                    "virtual_key": "azure-test-4110dd",
                                  },
                                ],
                            },
                        },
                    }
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Retrieve the configuration
            config = portkey.configs.retrieve(
                slug='CONFIG_SLUG'
            )

            print(config)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey:"PORTKEY_API_KEY",
            })

            const config=await portkey.configs.retrieve({
                slug:'CONFIG_SLUG'
            })

            console.log(config);

    put:
      summary: Update a config
      tags:
        - Configs
      operationId: updateConfig
      parameters:
        - name: slug
          in: path
          required: true
          schema:
            type: string
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                config:
                  type: object
                  properties:
                    virtual_key:
                      type: string
                status:
                  type: string
            examples:
              example-1:
                value:
                  {
                    "name": "testConf",
                    "config": { "virtual_key": "copy-of-anthrop-b20259" },
                    "status": "active",
                  }
      responses:
        "200":
          description: Config updated successfully
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      version_id:
                        type: string
                        format: uuid
              examples:
                example-1:
                  value:
                    {
                      "success": true,
                      "data":
                        {
                          "version_id": "abe447e2-f6aa-4229-93b7-8ee3183b6667",
                        },
                    }
      x-code-samples:
        - lang: python
          source: |
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update the configuration
            updated_config = portkey.configs.update(
                slug="CONFIG_SLUG",
                name="Updated Config",
                config={
                    "retry": {
                        "attempts": 3
                    },
                    "cache": {
                        "mode": "semantic"
                    }
                }
            )
            print(updated_config)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey:"PORTKEY_API_KEY",
            })

            const config=await portkey.configs.update({
                slug:"CONFIG_SLUG",
                name:"Updated Config",
                config:{
                    "retry": {
                        "attempts": 3
                    },
                    "cache": {
                        "mode": "semantic"
                    }
                },

            })

            console.log(config);

  /feedback:
    post:
      summary: Create new feedback
      description: This endpoint allows users to submit feedback for a particular interaction or response.
      operationId: createFeedback
      tags:
        - Feedback
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/FeedbackRequest"
            examples:
              thumbsUpExample:
                summary: Thumbs Up Feedback
                value:
                  trace_id: "REQUEST_TRACE_ID"
                  value: 1
              thumbsDownExample:
                summary: Thumbs Down Feedback
                value:
                  trace_id: "REQUEST_TRACE_ID"
                  value: 0
      responses:
        "200":
          description: Feedback successfully saved
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FeedbackResponse"

  /feedback/{id}:
    put:
      summary: Updates existing feedback
      description: This endpoint allows users to update existing feedback.
      operationId: updateFeedback
      parameters:
        - name: id
          in: path
          description: Feedback ID
          required: true
          schema:
            type: string
            format: uuid
      tags:
        - Feedback
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/FeedbackUpdateRequest"
            examples:
              thumbsUpExample:
                summary: Thumbs Up Feedback
                value:
                  value: 1
              thumbsDownExample:
                summary: Thumbs Down Feedback
                value:
                  value: 0
      responses:
        "200":
          description: Feedback successfully updated
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/FeedbackResponse"

  /virtual-keys:
    get:
      summary: List All Virtual Keys
      tags:
        - Virtual-keys
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    enum: [list]
                  total:
                    type: integer
                    description: Total number of virtual keys
                  data:
                    type: array
                    items:
                      $ref: "#/components/schemas/VirtualKeys"
        "401":
          description: Unauthorized response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      message:
                        type: string
              example:
                success: false
                data:
                  message: "Unauthorised Request"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # List virtual keys
            virtual_keys = portkey.virtual_keys.list()

            print(virtual_keys)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const virtualKeys=await portkey.virtualKeys.list({})
            console.log(virtualKeys);

    post:
      summary: Create a Virtual Key
      tags:
        - Virtual-keys
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                provider:
                  type: string
                  enum:
                    - openai
                    - azure-openai
                    - ai21
                    - anthropic
                    - anyscale
                    - azure-openai
                    - bedrock
                    - cohere
                    - deepinfra
                    - fireworks-ai
                    - google
                    - groq
                    - hugging-face
                    - jina
                    - lingyi
                    - mistral-ai
                    - monsterapi
                    - moonshot
                    - nomic
                    - novita-ai
                    - open-ai
                    - openrouter
                    - palm
                    - perplexity-ai
                    - predibase
                    - reka-ai
                    - segmind
                    - stability-ai
                    - together-ai
                    - vertex-ai
                    - workers-ai
                    - zhipu
                key:
                  type: string
                note:
                  type: string
                  nullable: true
                apiVersion:
                  type: string
                  nullable: true
                resourceName:
                  type: string
                  nullable: true
                deploymentName:
                  type: string
                  nullable: true
                workspace_id:
                  type: string
                  format: uuid
                  description: optional, needed when using organisation admin API keys
                deploymentConfig:
                  type: array
                  items:
                    type: object
                    properties:
                      apiVersion:
                        type: string
                      alias:
                        type: string
                      is_default:
                        type: boolean
                      deploymentName:
                        type: string
                    required: ["apiVersion", "deploymentName"]
                usage_limits:
                  $ref: "#/components/schemas/UsageLimits"
                rate_limits:
                  $ref: "#/components/schemas/RateLimits"
            examples:
              generic:
                value:
                  name: "My first virtual key"
                  provider: "openai"
                  key: "sk-jhkfkjs8d9f7jksfghkjhfg"
                  note: "Virtual key description"
                  usage_limits:
                    {
                      "credit_limit": 10,
                      "periodic_reset": "monthly",
                      "alert_threshold": 9,
                    }
                  workspace_id: ""
              azure-openai:
                value:
                  provider: "azure-openai"
                  key: "openai-test"
                  name: "Key 1 Azure Open AI"
                  note: "description"
                  deploymentConfig:
                    [
                      {
                        "apiVersion": "a",
                        "alias": "b",
                        "deploymentName": "c",
                        is_default: true,
                      },
                      {
                        "apiVersion": "a",
                        "alias": "b",
                        "deploymentName": "c",
                        is_default: false,
                      },
                    ]
                  resourceName: "c"
              bedrock:
                value:
                  provider: "bedrock"
                  key: "openai-test"
                  name: "Bedrock Key"
                  note: "description"
                  awsAccessKeyId: "a"
                  awsSecretAccessKey: "b"
                  awsRegion: "c"
              vertex-ai:
                value:
                  provider: "vertex-ai"
                  key: "vertex test"
                  name: "Vertex AI Key"
                  note: "description"
                  vertexProjectId: "a"
                  vertexRegion: "b"
              workers-ai:
                value:
                  provider: "vertex-ai"
                  key: "cloudflare test"
                  name: "CF Workers AI Key"
                  note: "description"
                  workersAiAccountId: "a"
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      slug:
                        type: string
        "401":
          description: Unauthorized response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      message:
                        type: string
              example:
                success: false
                data:
                  message: "Unauthorised Request"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Add a new virtual key
            new_virtual_key = portkey.virtual_keys.create(
                name="openaiVKey",
                provider="openai",
                key="PROVIDER_API_KEY"
            )

            print(new_virtual_key)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const newVkey=await portkey.virtualKeys.create({
                name:"openaiVKey",
                provider:"openai",
                key:"PROVIDER_API_KEY",
            })
            console.log(newVkey);

  /virtual-keys/{slug}:
    get:
      summary: Get a Virtual Key
      tags:
        - Virtual-keys
      parameters:
        - in: path
          name: slug
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/VirtualKeys"
        "401":
          description: Unauthorized response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      message:
                        type: string
              example:
                success: false
                data:
                  message: "Unauthorised Request"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get a specific virtual key
            virtual_key = portkey.virtual_keys.retrieve(
                slug='VIRTUAL_KEY_SLUG'
            )

            print(virtual_key)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const vKey=await portkey.virtualKeys.retrieve({
                slug:'VIRTUAL_KEY_SLUG'
            })
            console.log(vKey);

    put:
      summary: Update a Virtual Key
      tags:
        - Virtual-keys
      parameters:
        - in: path
          name: slug
          required: true
          schema:
            type: string
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                key:
                  type: string
                note:
                  type: string
                  nullable: true
                deploymentConfig:
                  type: array
                  items:
                    type: object
                    properties:
                      apiVersion:
                        type: string
                      alias:
                        type: string
                      is_default:
                        type: boolean
                      deploymentName:
                        type: string
                    required: ["apiVersion", "deploymentName"]
                usage_limits:
                  $ref: "#/components/schemas/UsageLimits"
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                type: object

        "401":
          description: Unauthorized response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      message:
                        type: string
              example:
                success: false
                data:
                  message: "Unauthorised Request"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update a specific virtual key
            updated_virtual_key = portkey.virtual_keys.update(
                slug='VIRTUAL_KEY_SLUG',
                name="openaiVKey",
                note="hello",
                rate_limits=[{"type": "requests", "unit": "rpm", "value": 696}]
            )

            print(updated_virtual_key)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const updatedVKey=await portkey.virtualKeys.update({
                slug:'VIRTUAL_KEY_SLUG',
                name:"openaiVKey",
                note:"hello",
                rate_limits: [{type: "requests", unit: "rpm", value: 696}]
            })
            console.log(updatedVKey);

    delete:
      summary: Delete a Virtual Key
      tags:
        - Virtual-keys
      parameters:
        - in: path
          name: slug
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                type: object

        "401":
          description: Unauthorized response
          content:
            application/json:
              schema:
                type: object
                properties:
                  success:
                    type: boolean
                  data:
                    type: object
                    properties:
                      message:
                        type: string
              example:
                success: false
                data:
                  message: "Unauthorised Request"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Delete a specific virtual key
            result = portkey.virtual_keys.delete(
                slug='VIRTUAL_KEY_SLUG'
            )

            print(result)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const result=await portkey.virtualKeys.delete({
                slug:'VIRTUAL_KEY_SLUG',
            })
            console.log(result);

  /admin/users/invites:
    post:
      operationId: Invites_create
      summary: Invite User
      description: Send an invite to user for your organization
      parameters: []
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/SuccessInvite"
      tags:
        - User-invites
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateInvite"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Add a user invite
            user = portkey.admin.users.invites.create(
                email="user@example.com",
                role="member",
                workspaces=[
                    {
                        "id": "WORKSPACE_SLUG",
                        "role": "admin"
                    }
                ],
                workspace_api_key_details={
                    "scopes": [
                        "workspaces.list",
                        "logs.export",
                        "logs.list",
                        "logs.view",
                    ]
                }
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.invites.create({
                email:"user@example.com",
                role: "member",
                workspaces: [
                {
                id:"WORKSPACE_SLUG",
                role:"admin"
                }],
                workspace_api_key_details:{
                    scopes: [
                    "workspaces.list",
                    "logs.export",
                    "logs.list",
                    "logs.view",
                ]
                }
            })

            console.log(user);

    get:
      tags:
        - User-invites
      summary: Get All Invites
      parameters:
        - name: pageSize
          in: query
          schema:
            type: integer
          example: "1"
        - name: currentPage
          in: query
          schema:
            type: integer
          example: "0"
        - name: role
          in: query
          schema:
            type: string
            enum:
              - admin
              - member
          example: "admin"
        - name: email
          in: query
          schema:
            type: string
            format: email
          example: "foo@bar.com"
        - name: status
          in: query
          schema:
            type: string
            enum:
              - pending
              - cancelled
              - accepted
              - expired
          example: "pending"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/InviteList"
              example:
                object: list
                total: 2
                data:
                  - object: invite
                    id: 419641fb-1458-47d6-94d0-e308159b3ec2
                    email: horace.slughorn@example.com
                    role: member
                    created_at: "2023-12-12 13:56:32"
                    expires_at: "2023-12-12 13:56:32"
                    accepted_at: "2023-12-12 13:56:32"
                    status: pending
                    invited_by: a90e74fb-269e-457b-8b59-9426cdd8907e
                    workspaces:
                      - workspace_id: ""
                        role: ""
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # List user invites
            user_invites = portkey.admin.users.invites.list(
                email="user@example.com"
            )

            print(user_invites)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.invites.list({
                email:"user@example.com"
            });
            console.log(user);

  /admin/users/invites/{inviteId}:
    get:
      tags:
        - User-invites
      summary: Get Invite
      parameters:
        - name: inviteId
          in: path
          schema:
            type: string
          required: true
          description: string
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Invite"
              example:
                object: invite
                id: 419641fb-1458-47d6-94d0-e308159b3ec2
                email: horace.slughorn@example.com
                role: member
                created_at: "2023-12-12 13:56:32"
                expires_at: "2023-12-12 13:56:32"
                accepted_at: "2023-12-12 13:56:32"
                status: pending
                invited_by: 8dcfa174-c5ed-42c7-8a63-be755cc6e3123
                workspaces:
                  - workspace_id: ""
                    role: ""
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get a user invite
            user = portkey.admin.users.invites.retrieve(
                invite_id='INVITE_ID'
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.invites.retrieve({
                inviteId: 'INVITE_ID',
            });
            console.log(user);
    delete:
      tags:
        - User-invites
      summary: Delete Invite By ID
      parameters:
        - name: inviteId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )



            # Delete a user invite
            user = portkey.admin.users.invites.delete(
                invite_id="INVITE_ID"
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.invites.delete({
                inviteId:"INVITE_ID"
            })

            console.log(user);

  /admin/users/invites/{inviteId}/resend:
    post:
      tags:
        - User-invites
      summary: Resend Invite
      description: Resend an invite to user for your organization
      parameters:
        - name: inviteId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  inviteLink:
                    type: string
                    format: uri
              example:
                inviteLink: https://app.portkey.ai/invite/some-invite-link
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )



            # Delete a user invite
            user = portkey.admin.users.invites.resend(
                invite_id="INVITE_ID"
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.invites.resend({
                inviteId:"INVITE_ID"
            });

            console.log(user);

  /admin/users:
    get:
      tags:
        - Users
      summary: Get users
      parameters:
        - name: x-portkey-api-key
          in: header
          schema:
            type: string
          example: "{{PORTKEY_API_KEY}}"
        - name: pageSize
          in: query
          schema:
            type: integer
          example: "1"
        - name: currentPage
          in: query
          schema:
            type: integer
          example: "0"
        - name: role
          in: query
          schema:
            type: string
            enum:
              - admin
              - member
              - owner
          example: "admin"
        - name: email
          in: query
          schema:
            type: string
            format: email
          example: "foo@bar.com"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/UserList"
              example:
                total: 2
                object: list
                data:
                  - object: user
                    id: 61e08f60-4822-465e-ba23-39f85cd741cb
                    first_name: horace
                    last_name: slughorn
                    role: member
                    email: horace.slughorn@example.com
                    created_at: "2024-01-25 11:35:07"
                    last_updated_at: "2024-01-25 11:35:07"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # List users
            users = portkey.admin.users.list()

            print(users)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const users=await portkey.admin.users.list({})

            console.log(users);

  /admin/users/{userId}:
    get:
      tags:
        - Users
      summary: Get user
      parameters:
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/User"
              example:
                object: user
                id: 61e08f60-4822-465e-ba23-39f85cd741cb
                first_name: horace
                last_name: slughorn
                role: member
                email: horace.slughorn@example.com
                created_at: "2024-01-25 11:35:07"
                last_updated_at: "2024-01-25 11:35:07"
                workspace_ids: ["ws-shared-123"]
      x-code-sample:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get a specific user
            user = portkey.admin.users.retrieve(
                user_id='USER_ID'
            )

            print(user)

        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })
            const user = await portkey.admin.users.retrieve({
                userId: 'USER_ID',
            });

            console.log(user);

    delete:
      tags:
        - Users
      summary: Remove a user
      parameters:
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Delete a user
            user = portkey.admin.users.delete(
                user_id='USER_ID'
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.users.delete({
                userId: 'USER_ID',
            })

            console.log(user);
    put:
      tags:
        - Users
      summary: Update user
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                role:
                  type: string
                  enum:
                    - admin
                    - member
              example:
                role: admin
      parameters:
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update a user
            user = portkey.admin.users.update(
                user_id='USER_ID',
                role="member"
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user = await portkey.admin.users.update({
                userId: 'USER_ID',
                role: "member"
            })

            console.log(user);

  /admin/workspaces/{workspaceId}/users:
    post:
      tags:
        - Workspaces > Members
      summary: Add workspace member
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                users:
                  type: array
                  items:
                    type: object
                    properties:
                      id:
                        type: string
                        format: uuid
                        example: 25afb7bd-f98a-11ee-85fe-0e27d7367987
                      role:
                        type: string
                        example: member
                        enum:
                          - admin
                          - member
              example:
                users:
                  - id: 419641fb-1458-47d6-94d0-e308159b3ec2
                    role: member
                  - id: 419641fb-1458-47d6-94d0-e308159b3ec3
                    role: member
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Add user to workspace
            user = portkey.admin.workspaces.users.create(
                workspace_id="WORKSPACE_SLUG",
                users=[
                    {
                        "id": "USER_ID",
                        "role": "member"
                    }
                ]
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.workspaces.users.create({
                workspaceId: "WORKSPACE_SLUG",
                users:[{
                    id:"USER_ID",
                    role:'member'
                }]
            })
            console.log(user);

    get:
      tags:
        - Workspaces > Members
      summary: Get workspace members
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
        - name: current_page
          in: query
          schema:
            type: number
            default: 50
          required: false
        - name: page_size
          in: query
          schema:
            type: number
            default: 0
          required: false
        - name: role
          in: query
          schema:
            type: string
            enum: ["admin", "manager", "member"]
          example: "admin"
        - name: email
          in: query
          schema:
            type: string
          example: "foo@bar.com"

      responses:
        "200":
          description: OK
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/WorkspaceMemberList"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get user from workspace
            users = portkey.admin.workspaces.users.list(
                workspace_id="WORKSPACE_SLUG",
            )

            print(users)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.workspaces.users.list({
                workspaceId: 'WORKSPACE_SLUG',
            })
            console.log(user);

  /admin/workspaces/{workspaceId}/users/{userId}:
    put:
      tags:
        - Workspaces > Members
      summary: Update workspace member
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                role:
                  type: string
                  enum:
                    - admin
                    - member
              example:
                role: member
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update user in workspace
            updated_user = portkey.admin.workspaces.users.update(
                workspace_id='WORKSPACE_SLUG',
                user_id="USER_ID",
                role='member'
            )

            print(updated_user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.workspaces.users.update({
                workspaceId: 'WORKSPACE_SLUG',
                userId:"USER_ID",
                role:'member'
            })
            console.log(user);

    delete:
      tags:
        - Workspaces > Members
      summary: Remove workspace member
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Delete user from workspace
            result = portkey.admin.workspaces.users.delete(
                workspace_id='WORKSPACE_SLUG',
                user_id='USER_ID'
            )

            # Print the result (if any)
            print(result)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            user = await portkey.admin.workspaces.users.delete({
                workspaceId: 'WORKSPACE_SLUG',
                userId:'USER_ID'
            })

            console.log(user)

    get:
      tags:
        - Workspaces > Members
      summary: Get member
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
        - name: userId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/WorkspaceMember"
              example:
                object: workspace_member
                user_id: 61e08f60-4822-465e-ba23-39f85cd741cb
                user:
                  object: user
                  id: 61e08f60-4822-465e-ba23-39f85cd741cb
                  first_name: horace
                  last_name: slughorn
                  email: horace.slughorn@example.com
                role: admin
                created_at: "2024-01-25 11:35:07"
                last_updated_at: "2024-01-25 11:35:07"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get user from workspace
            user = portkey.admin.workspaces.users.retrieve(
                workspace_id="WORKSPACE_SLUG",
                user_id="USER_ID"
            )

            print(user)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const user=await portkey.admin.workspaces.users.retrieve({
                workspaceId: 'WORKSPACE_SLUG',
                userId:'USER_ID',
            })
            console.log(user);

  /admin/workspaces:
    post:
      tags:
        - Workspaces
      summary: Create Workspace
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                description:
                  type: string
                defaults:
                  type: object
                  properties:
                    metadata:
                      type: object
                      additionalProperties:
                        type: string
                users:
                  type: array
                  items:
                    type: string
              example:
                name: My Workspace
                description: My Description
                defaults:
                  metadata:
                    environment: production
                    foo: bar
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Workspace"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Add a workspace
            workspace = portkey.admin.workspaces.create(
                name='WORKSPACE_NAME_0909',
                description="WORKSPACE_DESCRIPTION",
                defaults={
                    "metadata": {
                        "environment": "production",
                        "foo": "bar"
                    }
                }
            )

            print(workspace)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const workspace=await portkey.admin.workspaces.create({
                name: 'WORKSPACE_NAME_0909',
                description: "WORKSPACE_DESCRIPTION",
                defaults: {
                    metadata: {
                      environment: "production",
                      foo: "bar"
                    }
                  }
            })
            console.log(workspace);

    get:
      tags:
        - Workspaces
      summary: Get All
      parameters:
        - name: page_size
          in: query
          schema:
            type: integer
          example: "1"
        - name: current_page
          in: query
          schema:
            type: integer
          example: "0"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/WorkspaceList"
              example:
                total: 2
                object: list
                data:
                  - id: test-prod-ws-12345
                    name: Test prod workspace
                    description: This is a production workspace
                    created_at: "2023-07-13 13:51:27"
                    last_updated_at: "2023-07-13 14:51:27"
                    defaults:
                      metadata:
                        foo: bar
                    object: workspace
                  - id: test-prod-ws-12345
                    name: Test prod workspace
                    description: This is a production workspace
                    created_at: "2023-07-13 13:51:27"
                    last_updated_at: "2023-07-13 14:51:27"
                    defaults:
                      metadata:
                        foo: bar
                    object: workspace
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # List workspaces
            workspaces = portkey.admin.workspaces.list()

            print(workspaces)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const workspaces=await portkey.admin.workspaces.list({})
            console.log(workspaces);

  /admin/workspaces/{workspaceId}:
    put:
      tags:
        - Workspaces
      summary: Update Workspace
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                name:
                  type: string
                description:
                  type: string
                defaults:
                  type: object
                  properties:
                    metadata:
                      type: object
                      additionalProperties:
                        type: string
              example:
                name: My Workspace
                description: My Description
                defaults:
                  metadata:
                    foo: bar
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/Workspace"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update workspace
            workspace = portkey.admin.workspaces.update(
                workspace_id='WORKSPACE_ID',
                name='WORKSPACE 0909',
                description='This is a test description',
                defaults={
                    "x": "y"
                }
            )

            print(workspace)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const workspace=await portkey.admin.workspaces.update({
                workspaceId: 'WORKSPACE_ID',
                name: 'WORKSPACE 0909',
                description: 'This is a test description',
                defaults: {
                    x: "y"
                }
            })
            console.log(workspace);

    get:
      tags:
        - Workspaces
      summary: Get workspace
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/WorkspaceWithUsers"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get workspace details
            workspace = portkey.admin.workspaces.retrieve(
                workspace_id='WORKSPACE_SLUG'
            )

            print(workspace)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const workspace=await portkey.admin.workspaces.retrieve({
                workspaceId: 'WORKSPACE_SLUG',
            })
            console.log(workspace);

    delete:
      tags:
        - Workspaces
      summary: Delete a workspace
      parameters:
        - name: workspaceId
          in: path
          schema:
            type: string
          required: true
      responses:
        "200":
          description: OK
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Delete workspace
            result = portkey.admin.workspaces.delete(
                name='WORKSPACE_NAME_0909',
                workspace_id='WORKSPACE_SLUG'
            )

            print(result)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const workspace=await portkey.admin.workspaces.delete({
                name: 'WORKSPACE_NAME_0909',
                workspaceId: 'WORKSPACE_SLUG',
            })
            console.log(workspace);

  /logs:
    post:
      summary: Submit logs
      tags:
        - Logs
      description: Submit one or more log entries
      requestBody:
        required: true
        content:
          application/json:
            schema:
              oneOf:
                - $ref: "#/components/schemas/CustomLog"
                - type: array
                  items:
                    $ref: "#/components/schemas/CustomLog"
      responses:
        "200":
          description: Successful response
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY",
            )

            request = {
              "url": "https://api.someprovider.com/model/generate",
              "method": "POST",
              "headers": {"Content-Type": "application/json"},
              "body": {"prompt": "What is AI?"},
            }
            response = {
              "status": 200,
              "headers": {"Content-Type": "application/json"},
              "body": {"response": "AI stands for Artificial Intelligence..."},
              "response_time": 123,
            }
            metadata = {
              "user_id": "123",
              "user_name": "John Doe",
            }

            result = portkey.logs.create(request=request, response=response, metadata=metadata)

            print(result)

        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const request = {
                url: "https://api.someprovider.com/model/generate",
                method: "POST",
                headers: { "Content-Type": "application/json" },
                body: { prompt: "What is AI?" },
              };
              const response = {
                status: 200,
                headers: { "Content-Type": "application/json" },
                body: { response: "AI stands for Artificial Intelligence..." },
                response_time: 123,
              };
              const metadata = {
                user_id: "123",
                user_name: "John Doe",
              };
              const result = await portkey.logs.create({
                request: request,
                response: response,
                metadata: metadata,
              });
              console.log(result);
            }
            main();

  /logs/exports/{exportId}:
    get:
      tags:
        - Logs Export
      summary: Get a specific logs export
      parameters:
        - name: exportId
          in: path
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ExportItem"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.retrieve(
              export_id="EXPORT_ID"
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const res= await portkey.logs.exports.retrieve({
                exportId:"EXPORT_ID"
              });

              console.log(res);
            }

            main();
    put:
      tags:
        - Logs Export
      summary: Update a logs export
      parameters:
        - name: exportId
          in: path
          required: true
          schema:
            type: string
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                workspace_id:
                  type: string
                filters:
                  $ref: "#/components/schemas/GenerationsFilterSchema"
                requested_data:
                  $ref: "#/components/schemas/LogExportsRequestedData"
              required:
                - filters
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/UpdateExportResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.update(
              export_id="EXPORT_ID",
              workspace_id="WORKSPACE_ID",
              filters={
                "time_of_generation_max": "2024-07-25"
              }
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const res = await portkey.logs.exports.update({
                exportId:"7ef9f738-a93a-xxx-xxx-xxxxx",
                workspaceId: "ws-shared-xxx",
                filters: {
                  "time_of_generation_max": "2024-07-25"
                }
              });

              console.log(res);
            }

            main();
  /logs/exports:
    get:
      tags:
        - Logs Export
      summary: Get all logs exports
      parameters:
        - name: workspace_id
          in: query
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ExportListResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.list(
              workspace_id="WORKSPACE_ID"
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            async function main() {
              const portkey = new Portkey({
                apiKey:"PORTKEY_API_KEY"
              })

              const res = await portkey.logs.exports.list({
                workspaceId:"WORKSPACE_ID"
              });

              console.log(res);
            }

            main();
    post:
      tags:
        - Logs Export
      summary: Create log export
      requestBody:
        content:
          application/json:
            schema:
              type: object
              properties:
                workspace_id:
                  type: string
                filters:
                  $ref: "#/components/schemas/GenerationsFilterSchema"
                requested_data:
                  $ref: "#/components/schemas/LogExportsRequestedData"
              required:
                - filters
                - requested_data
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/UpdateExportResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
               api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.create(
              filters={
                'time_of_generation_min': "2024-10-20",
                'time_of_generation_max': "2024-10-30"
              },
              workspace_id="WORKSPACE_ID",
              description="This is random description",
              requested_data=[
                "id",
                "trace_id",
                "created_at",
                "request",
                "response",
                "is_success",
                "ai_org",
                "ai_model",
                "req_units",
                "res_units",
                "total_units",
                "request_url",
                "cost",
                "cost_currency",
                "response_time",
                "response_status_code",
                "mode",
                "config",
                "prompt_slug",
                "metadata"
              ]
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const res = await portkey.logs.exports.create({
                  filters: {
                    time_of_generation_min: "2024-10-20",
                    time_of_generation_max: "2024-10-30"
                  },
                  "workspaceId": "WORKSPACE_ID",",
                  "description": "This is random description",
                  "requestedData": [
                    "id",
                    "trace_id",
                    "created_at",
                    "request",
                    "response",
                    "is_success",
                    "ai_org",
                    "ai_model",
                    "req_units",
                    "res_units",
                    "total_units",
                    "request_url",
                    "cost",
                    "cost_currency",
                    "response_time",
                    "response_status_code",
                    "mode",
                    "config",
                    "prompt_slug",
                    "metadata"
                  ]
              });

              console.log(res);
            }

            main();
  /logs/exports/{exportId}/start:
    post:
      tags:
        - Logs Export
      summary: Start log export
      parameters:
        - name: exportId
          in: path
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ExportTaskResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.start(
              export_id='EXPORT_ID'
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const res = await portkey.logs.exports.start({
                exportId:'EXPORT_ID'
              });

              console.log(res);
            }

            main();
  /logs/exports/{exportId}/cancel:
    post:
      tags:
        - Logs Export
      summary: Cancel log export
      parameters:
        - name: exportId
          in: path
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ExportTaskResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.cancel(
              export_id='EXPORT_ID'
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY",
            })

            async function main() {
              const res = await portkey.logs.exports.cancel({
                exportId:'EXPORT_ID'
              });

              console.log(res);
            }

            main();
  /logs/exports/{exportId}/download:
    get:
      tags:
        - Logs Export
      summary: Download log export
      parameters:
        - name: exportId
          in: path
          required: true
          schema:
            type: string
      responses:
        "200":
          description: Successful response
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/DownloadLogsResponse"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            portkey = Portkey(
              api_key="PORTKEY_API_KEY"
            )

            res = portkey.logs.exports.download(
              export_id='EXPORT_ID'
            )

            print(res)
        - lang: javascript
          source: |
            import Portkey from "portkey-ai";

            const portkey = new Portkey({
              apiKey:"PORTKEY_API_KEY"
            })

            async function main() {
              const config=await portkey.logs.exports.download({
                exportId:'EXPORT_ID'
              });;

              console.log(config);
            }

            main()

  /api-keys/{type}/{sub-type}:
    post:
      tags:
        - Api-Keys
      summary: Create Api Keys
      parameters:
        - name: type
          in: path
          schema:
            type: string
            enum: ["organisation", "workspace"]
          required: true
        - name: sub-type
          in: path
          schema:
            type: string
            enum: ["user", "service"]
          required: true
      requestBody:
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/CreateApiKeyObject"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  id:
                    type: string
                    format: uuid
                    example: "183f497a-2a7f-4f47-992e-26213fa863we"
                  key:
                    type: string
                    example: "abssofjosfjs"
                  object:
                    type: string
                    enum: ["api-key"]
                    example: "api-key"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Create a new API key
            api_key = portkey.api_keys.create(
                name="API_KEY_NAME_0909",
                type="organisation",
                sub_type="service",
                workspace_id="WORKSPACE_ID",
                scopes=[
                    "logs.export",
                    "logs.list",
                    "logs.view",
                    "configs.create",
                    "configs.update",
                    "configs.delete",
                    "configs.read",
                    "configs.list",
                    "virtual_keys.create",
                    "virtual_keys.update",
                    "virtual_keys.delete",
                    "virtual_keys.read",
                    "virtual_keys.list",
                    "virtual_keys.copy"
                ]
            )

            print(api_key)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const apiKey=await portkey.apiKeys.create({
                name:"API_KEY_NAME_0909",
                type:"organisation",
                "sub-type":"service",
                workspace_id:"WORKSPACE_ID",
                "scopes": [
                    "logs.export",
                    "logs.list",
                    "logs.view",
                    "configs.create",
                    "configs.update",
                    "configs.delete",
                    "configs.read",
                    "configs.list",
                    "virtual_keys.create",
                    "virtual_keys.update",
                    "virtual_keys.delete",
                    "virtual_keys.read",
                    "virtual_keys.list",
                    "virtual_keys.copy"
                ]
            })
            console.log(apiKey);

  /api-keys:
    get:
      tags:
        - Api-Keys
      summary: Get All
      parameters:
        - name: page_size
          in: query
          schema:
            type: integer
          example: "1"
        - name: current_page
          in: query
          schema:
            type: integer
          example: "0"
        - name: workspace_id
          in: query
          schema:
            type: string
          example: "ws-shared-123"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ApiKeyObjectList"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # List API keys
            api_keys = portkey.api_keys.list(
                workspace_id="WORKSPACE_SLUG"
            )

            print(api_keys)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const apiKey=await portkey.apiKeys.list({
                workspace_id:"WORKSPACE_SLUG"
            })

            console.log(apiKey);

  /api-keys/{id}:
    put:
      tags:
        - Api-Keys
      summary: Update Api Keys
      requestBody:
        content:
          application/json:
            schema:
              $ref: "#/components/schemas/UpdateApiKeyObject"
      parameters:
        - name: id
          in: path
          schema:
            type: string
            format: uuid
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Update the API key
            updated_api_key = portkey.api_keys.update(
                id="API_KEY_ID",
                name="API_KEY_NAME_0909",
                rate_limits=[
                    {
                        "type": "requests",
                        "unit": "rpm",
                        "value": 100
                    }
                ],
                scopes=[
                    "organisation_users.create", "organisation_users.read", "organisation_users.update",
                    "organisation_users.delete", "organisation_users.list",
                    "organisation_service_api_keys.create", "organisation_service_api_keys.update",
                    "organisation_service_api_keys.read", "organisation_service_api_keys.delete",
                    "organisation_service_api_keys.list", "workspaces.delete", "workspaces.create",
                    "workspaces.read", "workspaces.update", "workspaces.list", "logs.export",
                    "logs.list", "logs.view", "configs.create", "configs.update", "configs.delete",
                    "configs.read", "configs.list", "virtual_keys.create", "virtual_keys.update",
                    "virtual_keys.delete", "virtual_keys.duplicate", "virtual_keys.read",
                    "virtual_keys.list", "virtual_keys.copy", "workspace_service_api_keys.create",
                    "workspace_service_api_keys.delete", "workspace_service_api_keys.update",
                    "workspace_service_api_keys.read", "workspace_service_api_keys.list",
                    "workspace_user_api_keys.create", "workspace_user_api_keys.delete",
                    "workspace_user_api_keys.update", "workspace_user_api_keys.read",
                    "workspace_user_api_keys.list", "workspace_users.create", "workspace_users.read",
                    "workspace_users.update", "workspace_users.delete", "workspace_users.list",
                    "analytics.view"
                ]
            )

            print(updated_api_key)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const apiKey=await portkey.apiKeys.update({
                id:"API_KEY_ID",
                name:"API_KEY_NAME_0909",
                rate_limits:[        {
                    "type": "requests",
                    "unit": "rpm",
                    "value": 100
                }],
                "scopes": [
                            "organisation_users.create",
                            "organisation_users.read",
                            "organisation_users.update",
                            "organisation_users.delete",
                            "organisation_users.list",
                            "organisation_service_api_keys.create",
                            "organisation_service_api_keys.update",
                            "organisation_service_api_keys.read",
                            "organisation_service_api_keys.delete",
                            "organisation_service_api_keys.list",
                            "workspaces.delete",
                            "workspaces.create",
                            "workspaces.read",
                            "workspaces.update",
                            "workspaces.list",
                            "logs.export",
                            "logs.list",
                            "logs.view",
                            "configs.create",
                            "configs.update",
                            "configs.delete",
                            "configs.read",
                            "configs.list",
                            "virtual_keys.create",
                            "virtual_keys.update",
                            "virtual_keys.delete",
                            "virtual_keys.duplicate",
                            "virtual_keys.read",
                            "virtual_keys.list",
                            "virtual_keys.copy",
                            "workspace_service_api_keys.create",
                            "workspace_service_api_keys.delete",
                            "workspace_service_api_keys.update",
                            "workspace_service_api_keys.read",
                            "workspace_service_api_keys.list",
                            "workspace_user_api_keys.create",
                            "workspace_user_api_keys.delete",
                            "workspace_user_api_keys.update",
                            "workspace_user_api_keys.read",
                            "workspace_user_api_keys.list",
                            "workspace_users.create",
                            "workspace_users.read",
                            "workspace_users.update",
                            "workspace_users.delete",
                            "workspace_users.list",
                            "analytics.view"
                        ],

            })
            console.log(apiKey);

    get:
      tags:
        - Api-Keys
      summary: Get Api Keys
      parameters:
        - name: id
          in: path
          schema:
            type: string
            format: uuid
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                $ref: "#/components/schemas/ApiKeyObject"
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Get API keys
            api_keys = portkey.api_keys.retrieve(
              id="API_KEY_ID"
            )

            print(api_keys)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const apiKey=await portkey.apiKeys.retrieve({
                id:"API_KEY_ID"
            })

            console.log(apiKey);

    delete:
      tags:
        - Api-Keys
      summary: Remove a Api Key
      parameters:
        - name: id
          in: path
          schema:
            type: string
            format: uuid
          required: true
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
              example: {}
      x-code-samples:
        - lang: python
          source: |
            from portkey_ai import Portkey

            # Initialize the Portkey client
            portkey = Portkey(
                api_key="PORTKEY_API_KEY",
            )

            # Delete the API key
            result = portkey.api_keys.delete(
                id="API_KEY_ID"
            )

            print(result)
        - lang: javascript
          source: |
            import { Portkey } from "portkey-ai";

            const portkey = new Portkey({
                apiKey: "PORTKEY_API_KEY",
            })

            const apiKey=await portkey.apiKeys.delete({
                id:"API_KEY_ID"
            })
            console.log(apiKey);

  /analytics/graphs/requests:
    get:
      tags:
        - Analytics > Graphs
      summary: Get requests graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total requests across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total requests for this data point bucket
                      required:
                        - timestamp
                        - total
                      description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/cost:
    get:
      tags:
        - Analytics > Graphs
      summary: Get cost graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total cost in cents across all data points
                      avg:
                        type: integer
                        description: Average cost per request across all data points
                    required:
                      - total
                      - avg
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total cost in cents for this data point bucket
                        avg:
                          type: integer
                          description: Average cost per request for this data point bucket
                      required:
                        - timestamp
                        - total
                        - avg
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/latency:
    get:
      tags:
        - Analytics > Graphs
      summary: Get latency graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      avg:
                        type: integer
                        description: Average latency in ms across all data points
                      p50:
                        type: integer
                        description: 50th percentile latency in ms across all data points
                      p90:
                        type: integer
                        description: 90th percentile latency in ms across all data points
                      p99:
                        type: integer
                        description: 99th percentile latency in ms across all data points

                    required:
                      - avg
                      - p50
                      - p90
                      - p99
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        avg:
                          type: integer
                          description: Average latency in ms for this data point bucket
                        p50:
                          type: integer
                          description: 50th percentile latency in ms for this data point bucket
                        p90:
                          type: integer
                          description: 90th percentile latency in ms for this data point bucket
                        p99:
                          type: integer
                          description: 99th percentile latency in ms for this data point bucket
                      required:
                        - timestamp
                        - avg
                        - p50
                        - p90
                        - p99
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/tokens:
    get:
      tags:
        - Analytics > Graphs
      summary: Get tokens graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total tokens across all data points
                      avg:
                        type: integer
                        description: Average tokens per request across all data points
                    required:
                      - total
                      - avg
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total tokens for this data point bucket
                        avg:
                          type: integer
                          description: Average tokens per request for this data point bucket
                      required:
                        - timestamp
                        - avg
                        - total
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/users:
    get:
      tags:
        - Analytics > Graphs
      summary: Get users graph. Returns unique user count across different time buckets
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total unique users across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total unique users for this data point bucket
                      required:
                        - timestamp
                        - total
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/users/requests:
    get:
      tags:
        - Analytics > Graphs
      summary: Get users requests graph. Returns average requests per user across different time buckets
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total requests across all data points
                      unique:
                        type: integer
                        description: Total unique users across all data points
                      avg:
                        type: integer
                        description: Average requests per user across all data points
                    required:
                      - total
                      - unique
                      - avg
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        avg:
                          type: integer
                          description: Average requests per user for this data point bucket
                      required:
                        - timestamp
                        - avg
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/errors:
    get:
      tags:
        - Analytics > Graphs
      summary: Get errors graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total errors across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total errors this data point bucket
                      required:
                        - timestamp
                        - total
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/errors/rate:
    get:
      tags:
        - Analytics > Graphs
      summary: Get percentage error rate graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      rate:
                        type: integer
                        description: Percentage error rate across all data points
                    required:
                      - rate
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        rate:
                          type: integer
                          description: Percentage error rate for this data point bucket
                      required:
                        - timestamp
                        - rate
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/errors/stacks:
    get:
      tags:
        - Analytics > Graphs
      summary: Get status code wise stacked error graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total errors across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        stats:
                          type: array
                          items:
                            type: object
                            properties:
                              response_status_code:
                                type: integer
                                description: Response status code
                              count:
                                type: integer
                                description: Total occurences of this response status code
                      required:
                        - timestamp
                        - stats
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/errors/status-codes:
    get:
      tags:
        - Analytics > Graphs
      summary: Get status code wise grouped error graph.
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total_errors:
                        type: integer
                        description: Total errors across all data points
                      unique_error_codes:
                        type: integer
                        description: Unique error codes across all data points
                    required:
                      - total_errors
                      - unique_error_codes
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        status_code:
                          type: integer
                          description: Response status code
                        count:
                          type: integer
                          description: Occurences of this response status code
                      required:
                        - status_code
                        - count
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/requests/rescued:
    get:
      tags:
        - Analytics > Graphs
      summary: Get retry and fallback rescued requests graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      retry:
                        type: integer
                        description: Total requests rescued using retries across all data points
                      fallback:
                        type: integer
                        description: Total requests rescued using fallback across all data points
                    required:
                      - retry
                      - fallback
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        retry:
                          type: array
                          items:
                            type: object
                            properties:
                              retry_success_count:
                                type: integer
                                description: "Retry attempt count at which the request was rescued"
                              count:
                                type: integer
                                description: "Total requests rescued at this retry attempt"
                        fallback:
                          type: integer
                          description: Total requests rescued using fallback for this data point bucket
                      required:
                        - timestamp
                        - retry
                        - fallback
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/cache/hit-rate:
    get:
      tags:
        - Analytics > Graphs
      summary: Get cache hit rate graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total cache hits across all data points
                      rate:
                        type: integer
                        description: Percentage cache hit rate across all data points
                    required:
                      - total
                      - rate
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        simple_hits:
                          type: integer
                          description: Total simple cache hits for this data point bucket
                        semantic_hits:
                          type: integer
                          description: Total semantic cache hits for this data point bucket
                        rate:
                          type: integer
                          description: Percentage cache hit rate for this data point bucket
                        cumulative_simple_cache_savings:
                          type: integer
                          description: Cumulative simple cache cost savings in cents based on all previous data point buckets and this bucket
                        cumulative_semantic_cache_savings:
                          type: integer
                          description: Cumulative semantic cache cost savings in cents based on all previous data point buckets and this bucket
                      required:
                        - timestamp
                        - simple_hits
                        - semantic_hits
                        - rate
                        - cumulative_simple_cache_savings
                        - cumulative_semantic_cache_savings
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/cache/latency:
    get:
      tags:
        - Analytics > Graphs
      summary: Get cache hit latency graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        avg:
                          type: integer
                          description: Average latency (in ms) for cache hit for this data point bucket
                      required:
                        - timestamp
                        - avg
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/feedbacks:
    get:
      tags:
        - Analytics > Graphs
      summary: Get feedbacks graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total feedbacks across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        total:
                          type: integer
                          description: Total feedbacks for this data point bucket
                      required:
                        - timestamp
                        - total
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/feedbacks/scores:
    get:
      tags:
        - Analytics > Graphs
      summary: Get score-wise feedbacks distribution graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      total:
                        type: integer
                        description: Total feedbacks across all data points
                    required:
                      - total
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        score:
                          type: integer
                          description: Feedback value for which total is calculated
                        total:
                          type: integer
                          description: Total feedbacks for this feedback score
                      required:
                        - score
                        - total
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/feedbacks/weighted:
    get:
      tags:
        - Analytics > Graphs
      summary: Get weighted feedbacks graph. Weighted feedback is (value * score)
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      avg:
                        type: integer
                        description: Average weighted feedback across all data points
                    required:
                      - avg
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        timestamp:
                          type: string
                          format: date-time
                          description: The timestamp for the data point bucket
                        avg:
                          type: integer
                          description: Average weighted feedback for this data point bucket
                      required:
                        - timestamp
                        - avg
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/graphs/feedbacks/ai-models:
    get:
      tags:
        - Analytics > Graphs
      summary: Get feedbacks per ai_models graph
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                  data_points:
                    type: array
                    items:
                      type: object
                      properties:
                        ai_model:
                          type: string
                          description: AI model for which feedback data is calculated
                        total:
                          type: integer
                          description: Total feedbacks for this ai_model requests
                        avg_weighted_feedback:
                          type: integer
                          description: Average weighted feedback for this ai_model requests
                      required:
                        - ai_model
                        - total
                        - avg_weighted_feedback
                    description: An array of data points, each with a timestamp and metrics
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-graph]
                required:
                  - summary
                  - data_points
                  - object

  /analytics/summary/cache:
    get:
      tags:
        - Analytics > Summary
      summary: Get cache summary data for the selected time period
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  summary:
                    type: object
                    properties:
                      hits:
                        type: integer
                        description: Total cache hits
                      avg_latency:
                        type: integer
                        description: Average latency for a cache hit
                      total_requests:
                        type: integer
                        description: Total requests
                      cache_speedup:
                        type: integer
                        description: Percentage speedup for cache hits compared to non cache hit requests
                  object:
                    type: string
                    description: The type of object being returned
                    enum: [analytics-summary]
                required:
                  - summary
                  - object

  /analytics/groups/users:
    get:
      tags:
        - Analytics > Groups
      summary: Get metadata users grouped data.
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/CurrentPage"
        - $ref: "#/components/parameters/PageSize"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    enum: [list]
                  total:
                    type: integer
                    description: Total records present across all pages
                  data:
                    type: array
                    items:
                      type: object
                      properties:
                        user:
                          type: string
                          description: The user for which the data is calculated
                        requests:
                          type: string
                          description: Total requests made by this user
                        cost:
                          type: string
                          description: Total cost in cents for the requests made by this user
                        object:
                          type: string
                          description: The type of object being returned
                          enum: [analytics-group]
                required:
                  - total
                  - object
                  - data

  /analytics/groups/ai-models:
    get:
      tags:
        - Analytics > Groups
      summary: Get ai model grouped data.
      parameters:
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/CurrentPage"
        - $ref: "#/components/parameters/PageSize"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    enum: [list]
                  total:
                    type: integer
                    description: Total records present across all pages
                  data:
                    type: array
                    items:
                      type: object
                      properties:
                        ai_model:
                          type: string
                          description: The ai model for which the data is calculated
                        requests:
                          type: string
                          description: Total requests made for this ai model
                        object:
                          type: string
                          description: The type of object being returned
                          enum: [analytics-group]
                required:
                  - total
                  - object
                  - data

  /analytics/groups/metadata/{metadataKey}:
    get:
      tags:
        - Analytics > Groups
      summary: Get metadata key based grouped data.
      parameters:
        - name: metadataKey
          in: path
          schema:
            type: string
          required: true
        - $ref: "#/components/parameters/TimeOfGenerationMin"
        - $ref: "#/components/parameters/TimeOfGenerationMax"
        - $ref: "#/components/parameters/TotalUnitsMin"
        - $ref: "#/components/parameters/TotalUnitsMax"
        - $ref: "#/components/parameters/CostMin"
        - $ref: "#/components/parameters/CostMax"
        - $ref: "#/components/parameters/PromptTokenMin"
        - $ref: "#/components/parameters/PromptTokenMax"
        - $ref: "#/components/parameters/CompletionTokenMin"
        - $ref: "#/components/parameters/CompletionTokenMax"
        - $ref: "#/components/parameters/StatusCode"
        - $ref: "#/components/parameters/WeightedFeedbackMin"
        - $ref: "#/components/parameters/WeightedFeedbackMax"
        - $ref: "#/components/parameters/VirtualKeys"
        - $ref: "#/components/parameters/Configs"
        - $ref: "#/components/parameters/WorkspaceSlug"
        - $ref: "#/components/parameters/ApiKeyIds"
        - $ref: "#/components/parameters/CurrentPage"
        - $ref: "#/components/parameters/PageSize"
        - $ref: "#/components/parameters/Metadata"
        - $ref: "#/components/parameters/AiOrgModel"
        - $ref: "#/components/parameters/TraceId"
        - $ref: "#/components/parameters/SpanId"
        - $ref: "#/components/parameters/PromptSlug"
      responses:
        "200":
          description: OK
          headers:
            Content-Type:
              schema:
                type: string
                example: application/json
          content:
            application/json:
              schema:
                type: object
                properties:
                  object:
                    type: string
                    enum: [list]
                  total:
                    type: integer
                    description: Total records present across all pages
                  data:
                    type: array
                    items:
                      type: object
                      properties:
                        metadata_value:
                          type: string
                          description: Value of the metadata on which grouping has been done
                        requests:
                          type: integer
                          description: Total requests made with this metadata
                        cost:
                          type: integer
                          description: Total cost for all requests made with this metadata
                        avg_tokens:
                          type: integer
                          description: Average tokens per request for all requests made with this metadata
                        avg_weighted_feedback:
                          type: integer
                          description: Average weighted feedback for all requests made with this metadata
                        requests_with_feedback:
                          type: integer
                          description: Total requests with feedback
                        last_seen:
                          type: string
                          format: date-time
                          description: The last seen timestamp for this metadata
                        object:
                          type: string
                          description: The type of object being returned
                          enum: [analytics-group]
                required:
                  - total
                  - object
                  - data

components:
  securitySchemes:
    Portkey-Key:
      type: apiKey
      in: header
      name: x-portkey-api-key
    Virtual-Key:
      type: apiKey
      in: header
      name: x-portkey-virtual-key
    Provider-Auth:
      type: http
      scheme: "bearer"
    Provider-Name:
      type: apiKey
      in: header
      name: x-portkey-provider
    Config:
      type: apiKey
      in: header
      name: x-portkey-config
    Custom-Host:
      type: apiKey
      in: header
      name: x-portkey-custom-host

  parameters:
    TimeOfGenerationMin:
      in: query
      name: time_of_generation_min
      required: true
      schema:
        type: string
        format: date-time
      description: Minimum time of generation (ISO8601 format)
      example: "2024-08-23T15:50:23+05:30"
    TimeOfGenerationMax:
      in: query
      name: time_of_generation_max
      required: true
      schema:
        type: string
        format: date-time
      description: Maximum time of generation (ISO8601 format)
      example: "2024-08-23T15:50:23+05:30"
    TotalUnitsMin:
      in: query
      name: total_units_min
      schema:
        type: integer
        minimum: 0
      description: Minimum total units (tokens)
    TotalUnitsMax:
      in: query
      name: total_units_max
      schema:
        type: integer
        minimum: 0
      description: Maximum total units (tokens)
    CostMin:
      in: query
      name: cost_min
      schema:
        type: number
        minimum: 0
      description: Minimum cost (in cents)
    CostMax:
      in: query
      name: cost_max
      schema:
        type: number
        minimum: 0
      description: Maximum cost (in cents)
    PromptTokenMin:
      in: query
      name: prompt_token_min
      schema:
        type: integer
        minimum: 0
      description: Minimum number of prompt tokens
    PromptTokenMax:
      in: query
      name: prompt_token_max
      schema:
        type: integer
        minimum: 0
      description: Maximum number of prompt tokens
    CompletionTokenMin:
      in: query
      name: completion_token_min
      schema:
        type: integer
        minimum: 0
      description: Minimum number of completion tokens
    CompletionTokenMax:
      in: query
      name: completion_token_max
      schema:
        type: integer
        minimum: 0
      description: Maximum number of completion tokens
    StatusCode:
      in: query
      name: status_code
      schema:
        type: string
      description: Comma separated response status codes
      example: 401,403
    PageSize:
      in: query
      name: page_size
      schema:
        type: integer
        minimum: 0
      description: Number of items per page
    CurrentPage:
      in: query
      name: current_page
      schema:
        type: integer
        minimum: 0
      description: Current page number
    WeightedFeedbackMin:
      in: query
      name: weighted_feedback_min
      schema:
        type: number
        minimum: -10
        maximum: 10
      description: Minimum weighted feedback score
    WeightedFeedbackMax:
      in: query
      name: weighted_feedback_max
      schema:
        type: number
        minimum: -10
        maximum: 10
      description: Maximum weighted feedback score
    OrderBy:
      in: query
      name: order_by
      schema:
        type: string
      description: Field to order results by
    OrderByType:
      in: query
      name: order_by_type
      schema:
        type: string
      description: Type of ordering (e.g., asc, desc)
    VirtualKeys:
      in: query
      name: virtual_keys
      schema:
        type: string
      description: Comma separated virtual key slugs
      example: vk-slug-1,vk-slug-2
    Configs:
      in: query
      name: configs
      schema:
        type: string
      description: Comma separated config slugs
      example: pc-config-slug-1,pc-config-slug-2
    WorkspaceSlug:
      in: query
      name: workspace_slug
      schema:
        type: string
      description: Workspace slug filter. If a workspace API key is being used, this filter will not be taken into consideration. If an organisation API key is used and no workspace slug is passed, default workspace will be used.
    ApiKeyIds:
      in: query
      name: api_key_ids
      schema:
        type: string
      description: Comma separated API key UUIDs
      example: 765768a9-b4ec-4694-962c-d55f40cdb0dc,7c22af5a-8119-46b8-8d9b-bad3ad382387
    Metadata:
      in: query
      name: metadata
      schema:
        type: string
      description: Stringifed json object with key value metadata pairs
      example: '{"_user":"user_1", "env": "staging"}'
    AiOrgModel:
      in: query
      name: ai_org_model
      schema:
        type: string
      description: Comma separated ai provider and model combination. Double underscore (__) should be used as a separator for each provider and model combination
      example: openai__gpt-3.5-turbo,azure-openai__gpt-35-turbo
    TraceId:
      in: query
      name: trace_id
      schema:
        type: string
      description: Comma separated trace IDs
      example: my-unique-trace-1,my-unique-trace-2
    SpanId:
      in: query
      name: span_id
      schema:
        type: string
      description: Comma separated span IDs
      example: my-unique-span-1,my-unique-span-2
    PromptSlug:
      in: query
      name: prompt_slug
      schema:
        type: string
      description: Comma separated prompt slugs
      example: prompt-slug-1,prompt-slug-2
    PortkeyTraceId:
      in: header
      name: x-portkey-trace-id
      schema:
        type: string
      description: An ID you can pass to refer to one or more requests later on. If not provided, Portkey generates a trace ID automatically for each request. [Docs](https://portkey.ai/docs/product/observability/traces)
      required: false
    PortkeySpanId:
      in: header
      name: x-portkey-span-id
      schema:
        type: string
      description: An ID you can pass to refer to a span under a trace.
      required: false
    PortkeySpanName:
      in: header
      name: x-portkey-span-name
      schema:
        type: string
      description: Name for the Span ID
      required: false
    PortkeyParentSpanId:
      in: header
      name: x-portkey-parent-span-id
      schema:
        type: string
      description: Link a child span to a parent span
      required: false
    PortkeyMetadata:
      in: header
      name: x-portkey-metadata
      schema:
        type: object
      description: Pass any arbitrary metadata along with your request
      required: false
    PortkeyCacheNamespace:
      in: header
      name: x-portkey-cache-namespace
      schema:
        type: string
      description: Partition your Portkey cache store based on custom strings, ignoring metadata and other headers
    PortkeyCacheForceRefresh:
      in: header
      name: x-portkey-cache-force-refresh
      schema:
        type: boolean
      description: Forces a cache refresh for your request by making a new API call and storing the updated value

  schemas:
    Error:
      type: object
      properties:
        code:
          type: string
          nullable: true
        message:
          type: string
          nullable: false
        param:
          type: string
          nullable: true
        type:
          type: string
          nullable: false
      required:
        - type
        - message
        - param
        - code
    ErrorResponse:
      type: object
      properties:
        error:
          $ref: "#/components/schemas/Error"
      required:
        - error

    CreateInvite:
      type: object
      required:
        - email
        - workspaces
        - role
      properties:
        email:
          type: string
        workspaces:
          type: array
          items:
            $ref: "#/components/schemas/WorkspaceInvite"
        role:
          $ref: "#/components/schemas/InviteRole"
        workspace_api_key_details:
          type: object
          properties:
            scopes:
              type: array
              items:
                type: string
          required:
            - scopes
      example:
        email: test@john.doe
        role: admin
        workspaces:
          - id: ws-slug
            role: member
    InviteRole:
      type: string
      enum:
        - admin
        - member
    WorkspaceInvite:
      type: object
      required:
        - id
        - role
      properties:
        id:
          type: string
          description: Workspace Slug
        role:
          $ref: "#/components/schemas/WorkspaceInviteRole"
    WorkspaceInviteRole:
      type: string
      enum:
        - admin
        - member
        - manager
    WorkspaceInviteType:
      type: string
      enum:
        - update
        - add
        - remove
    SuccessInvite:
      type: object
      required:
        - id
        - invite_link
      properties:
        id:
          type: string
        invite_link:
          type: string
      example:
        id: a286286b-633d-4c4f-bddb-86b84a50a25c
        invite_link: https://app.portkey.ai/invite_id
    ListModelsResponse:
      type: object
      properties:
        object:
          type: string
          enum: [list]
        data:
          type: array
          items:
            $ref: "#/components/schemas/Model"
      required:
        - object
        - data
    DeleteModelResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
      required:
        - id
        - object
        - deleted

    CreateCompletionRequest:
      type: object
      properties:
        model:
          description: &model_description |
            ID of the model to use. You can use the [List models](https://platform.openai.com/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](https://platform.openai.com/docs/models/overview) for descriptions of them.
          anyOf:
            - type: string
            - type: string
              enum: ["gpt-3.5-turbo-instruct", "davinci-002", "babbage-002"]
          x-oaiTypeLabel: string
        prompt:
          description: &completions_prompt_description |
            The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.

            Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.
          default: "<|endoftext|>"
          nullable: true
          oneOf:
            - type: string
              default: ""
              example: "This is a test."
            - type: array
              items:
                type: string
                default: ""
                example: "This is a test."
            - type: array
              minItems: 1
              items:
                type: integer
              example: "[1212, 318, 257, 1332, 13]"
            - type: array
              minItems: 1
              items:
                type: array
                minItems: 1
                items:
                  type: integer
              example: "[[1212, 318, 257, 1332, 13]]"
        best_of:
          type: integer
          default: 1
          minimum: 0
          maximum: 20
          nullable: true
          description: &completions_best_of_description |
            Generates `best_of` completions server-side and returns the "best" (the one with the highest log probability per token). Results cannot be streamed.

            When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`.

            **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
        echo:
          type: boolean
          default: false
          nullable: true
          description: &completions_echo_description >
            Echo back the prompt in addition to the completion
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: &completions_frequency_penalty_description |
            Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

            [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
        logit_bias: &completions_logit_bias
          type: object
          x-oaiTypeLabel: map
          default: null
          nullable: true
          additionalProperties:
            type: integer
          description: &completions_logit_bias_description |
            Modify the likelihood of specified tokens appearing in the completion.

            Accepts a JSON object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](https://platform.openai.com/tokenizer?view=bpe) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

            As an example, you can pass `{"50256": -100}` to prevent the <|endoftext|> token from being generated.
        logprobs: &completions_logprobs_configuration
          type: integer
          minimum: 0
          maximum: 5
          default: null
          nullable: true
          description: &completions_logprobs_description |
            Include the log probabilities on the `logprobs` most likely output tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.

            The maximum value for `logprobs` is 5.
        max_tokens:
          type: integer
          minimum: 0
          default: 16
          example: 16
          nullable: true
          description: &completions_max_tokens_description |
            The maximum number of [tokens](https://platform.openai.com/tokenizer?view=bpe) that can be generated in the completion.

            The token count of your prompt plus `max_tokens` cannot exceed the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
        n:
          type: integer
          minimum: 1
          maximum: 128
          default: 1
          example: 1
          nullable: true
          description: &completions_completions_description |
            How many completions to generate for each prompt.

            **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.
        presence_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: &completions_presence_penalty_description |
            Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

            [See more information about frequency and presence penalties.](https://platform.openai.com/docs/guides/text-generation/parameter-details)
        seed: &completions_seed_param
          type: integer
          minimum: -9223372036854775808
          maximum: 9223372036854775807
          nullable: true
          description: |
            If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.

            Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.
        stop:
          description: &completions_stop_description >
            Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.
          default: null
          nullable: true
          oneOf:
            - type: string
              default: <|endoftext|>
              example: "\n"
              nullable: true
            - type: array
              minItems: 1
              maxItems: 4
              items:
                type: string
                example: '["\n"]'
        stream:
          description: >
            Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-UShttps://platform.openai.com/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
            as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
          type: boolean
          nullable: true
          default: false
        stream_options:
          $ref: "#/components/schemas/ChatCompletionStreamOptions"
        suffix:
          description: |
            The suffix that comes after a completion of inserted text.

            This parameter is only supported for `gpt-3.5-turbo-instruct`.
          default: null
          nullable: true
          type: string
          example: "test."
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: &completions_temperature_description |
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

            We generally recommend altering this or `top_p` but not both.
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: &completions_top_p_description |
            An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

            We generally recommend altering this or `temperature` but not both.
        user: &end_user_param_configuration
          type: string
          example: user-1234
          description: |
            A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids).
      required:
        - model
        - prompt

    CreateCompletionResponse:
      type: object
      description: |
        Represents a completion response from the API. Note: both the streamed and non-streamed response objects share the same shape (unlike the chat endpoint).
      properties:
        id:
          type: string
          description: A unique identifier for the completion.
        choices:
          type: array
          description: The list of completion choices the model generated for the input prompt.
          items:
            type: object
            required:
              - finish_reason
              - index
              - logprobs
              - text
            properties:
              finish_reason:
                type: string
                description: &completion_finish_reason_description |
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,
                  `length` if the maximum number of tokens specified in the request was reached,
                  or `content_filter` if content was omitted due to a flag from our content filters.
                enum: ["stop", "length", "content_filter"]
              index:
                type: integer
              logprobs:
                type: object
                nullable: true
                properties:
                  text_offset:
                    type: array
                    items:
                      type: integer
                  token_logprobs:
                    type: array
                    items:
                      type: number
                  tokens:
                    type: array
                    items:
                      type: string
                  top_logprobs:
                    type: array
                    items:
                      type: object
                      additionalProperties:
                        type: number
              text:
                type: string
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the completion was created.
        model:
          type: string
          description: The model used for completion.
        system_fingerprint:
          type: string
          description: |
            This fingerprint represents the backend configuration that the model runs with.

            Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always "text_completion"
          enum: [text_completion]
        usage:
          $ref: "#/components/schemas/CompletionUsage"
      required:
        - id
        - object
        - created
        - model
        - choices
      x-code-samples:
        name: The completion object
        legacy: true
        example: |
          {
            "id": "cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7",
            "object": "text_completion",
            "created": 1589478378,
            "model": "gpt-4-turbo",
            "choices": [
              {
                "text": "\n\nThis is indeed a test",
                "index": 0,
                "logprobs": null,
                "finish_reason": "length"
              }
            ],
            "usage": {
              "prompt_tokens": 5,
              "completion_tokens": 7,
              "total_tokens": 12
            }
          }

    ChatCompletionRequestMessageContentPart:
      oneOf:
        - $ref: "#/components/schemas/ChatCompletionRequestMessageContentPartText"
        - $ref: "#/components/schemas/ChatCompletionRequestMessageContentPartImage"
      x-oaiExpandable: true

    ChatCompletionRequestMessageContentPartImage:
      type: object
      title: Image content part
      properties:
        type:
          type: string
          enum: ["image_url"]
          description: The type of the content part.
        image_url:
          type: object
          properties:
            url:
              type: string
              description: Either a URL of the image or the base64 encoded image data.
              format: uri
            detail:
              type: string
              description: Specifies the detail level of the image. Learn more in the [Vision guide](https://platform.openai.com/docs/guides/vision/low-or-high-fidelity-image-understanding).
              enum: ["auto", "low", "high"]
              default: "auto"
          required:
            - url
      required:
        - type
        - image_url

    ChatCompletionRequestMessageContentPartText:
      type: object
      title: Text content part
      properties:
        type:
          type: string
          enum: ["text"]
          description: The type of the content part.
        text:
          type: string
          description: The text content.
      required:
        - type
        - text

    ChatCompletionRequestMessage:
      oneOf:
        - $ref: "#/components/schemas/ChatCompletionRequestSystemMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestUserMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestAssistantMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestToolMessage"
        - $ref: "#/components/schemas/ChatCompletionRequestFunctionMessage"
      x-oaiExpandable: true

    ChatCompletionRequestSystemMessage:
      type: object
      title: System message
      properties:
        content:
          description: The contents of the system message.
          type: string
        role:
          type: string
          enum: ["system"]
          description: The role of the messages author, in this case `system`.
        name:
          type: string
          description: An optional name for the participant. Provides the model information to differentiate between participants of the same role.
      required:
        - content
        - role

    ChatCompletionRequestUserMessage:
      type: object
      title: User message
      properties:
        content:
          description: |
            The contents of the user message.
          oneOf:
            - type: string
              description: The text contents of the message.
              title: Text content
            - type: array
              description: An array of content parts with a defined type, each can be of type `text` or `image_url` when passing in images. You can pass multiple images by adding multiple `image_url` content parts. Image input is only supported when using the `gpt-4-visual-preview` model.
              title: Array of content parts
              items:
                $ref: "#/components/schemas/ChatCompletionRequestMessageContentPart"
              minItems: 1
          x-oaiExpandable: true
        role:
          type: string
          enum: ["user"]
          description: The role of the messages author, in this case `user`.
        name:
          type: string
          description: An optional name for the participant. Provides the model information to differentiate between participants of the same role.
      required:
        - content
        - role

    ChatCompletionRequestAssistantMessage:
      type: object
      title: Assistant message
      properties:
        content:
          nullable: true
          type: string
          description: |
            The contents of the assistant message. Required unless `tool_calls` or `function_call` is specified.
        role:
          type: string
          enum: ["assistant"]
          description: The role of the messages author, in this case `assistant`.
        name:
          type: string
          description: An optional name for the participant. Provides the model information to differentiate between participants of the same role.
        tool_calls:
          $ref: "#/components/schemas/ChatCompletionMessageToolCalls"
        function_call:
          type: object
          deprecated: true
          description: "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model."
          nullable: true
          properties:
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
          required:
            - arguments
            - name
      required:
        - role

    # TODO(apeng): This is only because we don't support tools yet. Use allOf once we do.
    FineTuneChatCompletionRequestAssistantMessage:
      type: object
      title: Assistant message
      properties:
        content:
          nullable: true
          type: string
          description: |
            The contents of the assistant message. Required unless `function_call` is specified.
        role:
          type: string
          enum: ["assistant"]
          description: The role of the messages author, in this case `assistant`.
        name:
          type: string
          description: An optional name for the participant. Provides the model information to differentiate between participants of the same role.
        function_call:
          type: object
          description: The name and arguments of a function that should be called, as generated by the model.
          nullable: true
          properties:
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
          required:
            - arguments
            - name
        weight:
          type: integer
          enum: [0, 1]
          description: "Controls whether the assistant message is trained against (0 or 1)"
      required:
        - role

    ChatCompletionRequestToolMessage:
      type: object
      title: Tool message
      properties:
        role:
          type: string
          enum: ["tool"]
          description: The role of the messages author, in this case `tool`.
        content:
          type: string
          description: The contents of the tool message.
        tool_call_id:
          type: string
          description: Tool call that this message is responding to.
      required:
        - role
        - content
        - tool_call_id

    ChatCompletionRequestFunctionMessage:
      type: object
      title: Function message
      deprecated: true
      properties:
        role:
          type: string
          enum: ["function"]
          description: The role of the messages author, in this case `function`.
        content:
          nullable: true
          type: string
          description: The contents of the function message.
        name:
          type: string
          description: The name of the function to call.
      required:
        - role
        - content
        - name

    # TODO(apeng): This is only because we don't support tools yet. Add back deprecated once we do.
    FineTuneChatCompletionRequestFunctionMessage:
      allOf:
        - type: object
          title: Function message
          deprecated: false
        - $ref: "#/components/schemas/ChatCompletionRequestFunctionMessage"

    FunctionParameters:
      type: object
      description: "The parameters the functions accepts, described as a JSON Schema object. See the [guide](https://platform.openai.com/docs/guides/function-calling) for examples, and the [JSON Schema reference](https://json-schema.org/understanding-json-schema/) for documentation about the format. \n\nOmitting `parameters` defines a function with an empty parameter list."
      additionalProperties: true

    ChatCompletionFunctions:
      type: object
      deprecated: true
      properties:
        description:
          type: string
          description: A description of what the function does, used by the model to choose when and how to call the function.
        name:
          type: string
          description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
        parameters:
          $ref: "#/components/schemas/FunctionParameters"
      required:
        - name

    ChatCompletionFunctionCallOption:
      type: object
      description: >
        Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.
      properties:
        name:
          type: string
          description: The name of the function to call.
      required:
        - name

    ChatCompletionTool:
      type: object
      properties:
        type:
          type: string
          enum: ["function"]
          description: The type of the tool. Currently, only `function` is supported.
        function:
          $ref: "#/components/schemas/FunctionObject"
      required:
        - type
        - function

    FunctionObject:
      type: object
      properties:
        description:
          type: string
          description: A description of what the function does, used by the model to choose when and how to call the function.
        name:
          type: string
          description: The name of the function to be called. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
        parameters:
          $ref: "#/components/schemas/FunctionParameters"
      required:
        - name

    ChatCompletionToolChoiceOption:
      description: |
        Controls which (if any) tool is called by the model.
        `none` means the model will not call any tool and instead generates a message.
        `auto` means the model can pick between generating a message or calling one or more tools.
        `required` means the model must call one or more tools.
        Specifying a particular tool via `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool.

        `none` is the default when no tools are present. `auto` is the default if tools are present.
      oneOf:
        - type: string
          description: >
            `none` means the model will not call any tool and instead generates a message.
            `auto` means the model can pick between generating a message or calling one or more tools.
            `required` means the model must call one or more tools.
          enum: [none, auto, required]
        - $ref: "#/components/schemas/ChatCompletionNamedToolChoice"
      x-oaiExpandable: true

    ChatCompletionNamedToolChoice:
      type: object
      description: Specifies a tool the model should use. Use to force the model to call a specific function.
      properties:
        type:
          type: string
          enum: ["function"]
          description: The type of the tool. Currently, only `function` is supported.
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
      required:
        - type
        - function

    ParallelToolCalls:
      description: Whether to enable [parallel function calling](https://platform.openai.com/docs/guides/function-calling/parallel-function-calling) during tool use.
      type: boolean
      default: true

    ChatCompletionMessageToolCalls:
      type: array
      description: The tool calls generated by the model, such as function calls.
      items:
        $ref: "#/components/schemas/ChatCompletionMessageToolCall"

    ChatCompletionMessageToolCall:
      type: object
      properties:
        # TODO: index included when streaming
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          enum: ["function"]
          description: The type of the tool. Currently, only `function` is supported.
        function:
          type: object
          description: The function that the model called.
          properties:
            name:
              type: string
              description: The name of the function to call.
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
          required:
            - name
            - arguments
      required:
        - id
        - type
        - function

    ChatCompletionMessageToolCallChunk:
      type: object
      properties:
        index:
          type: integer
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          enum: ["function"]
          description: The type of the tool. Currently, only `function` is supported.
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
      required:
        - index

    # Note, this isn't referenced anywhere, but is kept as a convenience to record all possible roles in one place.
    ChatCompletionRole:
      type: string
      description: The role of the author of a message
      enum:
        - system
        - user
        - assistant
        - tool
        - function

    ChatCompletionStreamOptions:
      description: |
        Options for streaming response. Only set this when you set `stream: true`.
      type: object
      nullable: true
      default: null
      properties:
        include_usage:
          type: boolean
          description: |
            If set, an additional chunk will be streamed before the `data: [DONE]` message. The `usage` field on this chunk shows the token usage statistics for the entire request, and the `choices` field will always be an empty array. All other chunks will also include a `usage` field, but with a null value.

    ChatCompletionResponseMessage:
      type: object
      description: A chat completion message generated by the model.
      properties:
        content:
          type: string
          description: The contents of the message.
          nullable: true
        tool_calls:
          $ref: "#/components/schemas/ChatCompletionMessageToolCalls"
        role:
          type: string
          enum: ["assistant"]
          description: The role of the author of this message.
        function_call:
          type: object
          deprecated: true
          description: "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model."
          properties:
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
            - arguments
      required:
        - role
        - content

    ChatCompletionStreamResponseDelta:
      type: object
      description: A chat completion delta generated by streamed model responses.
      properties:
        content:
          type: string
          description: The contents of the chunk message.
          nullable: true
        function_call:
          deprecated: true
          type: object
          description: "Deprecated and replaced by `tool_calls`. The name and arguments of a function that should be called, as generated by the model."
          properties:
            arguments:
              type: string
              description: The arguments to call the function with, as generated by the model in JSON format. Note that the model does not always generate valid JSON, and may hallucinate parameters not defined by your function schema. Validate the arguments in your code before calling your function.
            name:
              type: string
              description: The name of the function to call.
        tool_calls:
          type: array
          items:
            $ref: "#/components/schemas/ChatCompletionMessageToolCallChunk"
        role:
          type: string
          enum: ["system", "user", "assistant", "tool"]
          description: The role of the author of this message.

    CreateChatCompletionRequest:
      type: object
      properties:
        messages:
          description: A list of messages comprising the conversation so far. [Example Python code](https://cookbook.openai.com/examples/how_to_format_inputs_to_chatgpt_models).
          type: array
          minItems: 1
          items:
            $ref: "#/components/schemas/ChatCompletionRequestMessage"
        model:
          description: ID of the model to use. See the [model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility) table for details on which models work with the Chat API.
          example: "gpt-4-turbo"
          anyOf:
            - type: string
            - type: string
              enum:
                [
                  "gpt-4o",
                  "gpt-4o-2024-05-13",
                  "gpt-4-turbo",
                  "gpt-4-turbo-2024-04-09",
                  "gpt-4-0125-preview",
                  "gpt-4-turbo-preview",
                  "gpt-4-1106-preview",
                  "gpt-4-vision-preview",
                  "gpt-4",
                  "gpt-4-0314",
                  "gpt-4-0613",
                  "gpt-4-32k",
                  "gpt-4-32k-0314",
                  "gpt-4-32k-0613",
                  "gpt-3.5-turbo",
                  "gpt-3.5-turbo-16k",
                  "gpt-3.5-turbo-0301",
                  "gpt-3.5-turbo-0613",
                  "gpt-3.5-turbo-1106",
                  "gpt-3.5-turbo-0125",
                  "gpt-3.5-turbo-16k-0613",
                ]
          x-oaiTypeLabel: string
        frequency_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: *completions_frequency_penalty_description
        logit_bias:
          type: object
          x-oaiTypeLabel: map
          default: null
          nullable: true
          additionalProperties:
            type: integer
          description: |
            Modify the likelihood of specified tokens appearing in the completion.

            Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.
        logprobs:
          description: Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the `content` of `message`.
          type: boolean
          default: false
          nullable: true
        top_logprobs:
          description: An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. `logprobs` must be set to `true` if this parameter is used.
          type: integer
          minimum: 0
          maximum: 20
          nullable: true
        max_tokens:
          description: |
            The maximum number of [tokens](https://platform.openai.com/tokenizer?view=bpe) that can be generated in the chat completion.

            The total length of input tokens and generated tokens is limited by the model's context length. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
          type: integer
          nullable: true
        n:
          type: integer
          minimum: 1
          maximum: 128
          default: 1
          example: 1
          nullable: true
          description: How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep `n` as `1` to minimize costs.
        presence_penalty:
          type: number
          default: 0
          minimum: -2
          maximum: 2
          nullable: true
          description: *completions_presence_penalty_description
        response_format:
          type: object
          description: |
            An object specifying the format that the model must output.

            Setting to `{ "type": "json_schema", "json_schema": {...} }`enables Structured Outputs which ensures the model will match your
            supplied JSON schema. Works across all the providers that support this functionality. [OpenAI & Azure OpenAI](/integrations/llms/openai/structured-outputs), [Gemini & Vertex AI](/integrations/llms/vertex-ai/controlled-generations).

            Setting to `{ "type": "json_object" }` enables the older JSON mode, which ensures the message the model generates is valid JSON.

            Using `json_schema` is preferred for models that support it.
          oneOf:
            - $ref: "#/components/schemas/ResponseFormatText"
            - $ref: "#/components/schemas/ResponseFormatJsonSchema"
            - $ref: "#/components/schemas/ResponseFormatJsonObject"
        seed:
          type: integer
          minimum: -9223372036854775808
          maximum: 9223372036854775807
          nullable: true
          description: |
            This feature is in Beta.
            If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same `seed` and parameters should return the same result.
            Determinism is not guaranteed, and you should refer to the `system_fingerprint` response parameter to monitor changes in the backend.
          x-code-samples:
            beta: true
        stop:
          description: |
            Up to 4 sequences where the API will stop generating further tokens.
          default: null
          oneOf:
            - type: string
              nullable: true
            - type: array
              minItems: 1
              maxItems: 4
              items:
                type: string
        stream:
          description: >
            If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-UShttps://platform.openai.com/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)
            as they become available, with the stream terminated by a `data: [DONE]` message. [Example Python code](https://cookbook.openai.com/examples/how_to_stream_completions).
          type: boolean
          nullable: true
          default: false
        stream_options:
          $ref: "#/components/schemas/ChatCompletionStreamOptions"
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *completions_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *completions_top_p_description
        tools:
          type: array
          description: >
            A list of tools the model may call. Currently, only functions are supported as a tool.
            Use this to provide a list of functions the model may generate JSON inputs for. A max of 128 functions are supported.
          items:
            $ref: "#/components/schemas/ChatCompletionTool"
        tool_choice:
          $ref: "#/components/schemas/ChatCompletionToolChoiceOption"
        parallel_tool_calls:
          $ref: "#/components/schemas/ParallelToolCalls"
        user: *end_user_param_configuration
        function_call:
          deprecated: true
          description: |
            Deprecated in favor of `tool_choice`.

            Controls which (if any) function is called by the model.
            `none` means the model will not call a function and instead generates a message.
            `auto` means the model can pick between generating a message or calling a function.
            Specifying a particular function via `{"name": "my_function"}` forces the model to call that function.

            `none` is the default when no functions are present. `auto` is the default if functions are present.
          oneOf:
            - type: string
              description: >
                `none` means the model will not call a function and instead generates a message.
                `auto` means the model can pick between generating a message or calling a function.
              enum: [none, auto]
            - $ref: "#/components/schemas/ChatCompletionFunctionCallOption"
          x-oaiExpandable: true
        functions:
          deprecated: true
          description: |
            Deprecated in favor of `tools`.

            A list of functions the model may generate JSON inputs for.
          type: array
          minItems: 1
          maxItems: 128
          items:
            $ref: "#/components/schemas/ChatCompletionFunctions"

      required:
        - model
        - messages

    CreateChatCompletionResponse:
      type: object
      description: Represents a chat completion response returned by model, based on the provided input.
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion.
        choices:
          type: array
          description: A list of chat completion choices. Can be more than one if `n` is greater than 1.
          items:
            type: object
            required:
              - finish_reason
              - index
              - message
              - logprobs
            properties:
              finish_reason:
                type: string
                description: &chat_completion_finish_reason_description |
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence,
                  `length` if the maximum number of tokens specified in the request was reached,
                  `content_filter` if content was omitted due to a flag from our content filters,
                  `tool_calls` if the model called a tool, or `function_call` (deprecated) if the model called a function.
                enum:
                  [
                    "stop",
                    "length",
                    "tool_calls",
                    "content_filter",
                    "function_call",
                  ]
              index:
                type: integer
                description: The index of the choice in the list of choices.
              message:
                $ref: "#/components/schemas/ChatCompletionResponseMessage"
              logprobs: &chat_completion_response_logprobs
                description: Log probability information for the choice.
                type: object
                nullable: true
                properties:
                  content:
                    description: A list of message content tokens with log probability information.
                    type: array
                    items:
                      $ref: "#/components/schemas/ChatCompletionTokenLogprob"
                    nullable: true
                required:
                  - content
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created.
        model:
          type: string
          description: The model used for the chat completion.
        system_fingerprint:
          type: string
          description: |
            This fingerprint represents the backend configuration that the model runs with.

            Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always `chat.completion`.
          enum: [chat.completion]
        usage:
          $ref: "#/components/schemas/CompletionUsage"
      required:
        - choices
        - created
        - id
        - model
        - object

    CreateChatCompletionFunctionResponse:
      type: object
      description: Represents a chat completion response returned by model, based on the provided input.
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion.
        choices:
          type: array
          description: A list of chat completion choices. Can be more than one if `n` is greater than 1.
          items:
            type: object
            required:
              - finish_reason
              - index
              - message
              - logprobs
            properties:
              finish_reason:
                type: string
                description:
                  &chat_completion_function_finish_reason_description |
                  The reason the model stopped generating tokens. This will be `stop` if the model hit a natural stop point or a provided stop sequence, `length` if the maximum number of tokens specified in the request was reached, `content_filter` if content was omitted due to a flag from our content filters, or `function_call` if the model called a function.
                enum: ["stop", "length", "function_call", "content_filter"]
              index:
                type: integer
                description: The index of the choice in the list of choices.
              message:
                $ref: "#/components/schemas/ChatCompletionResponseMessage"
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created.
        model:
          type: string
          description: The model used for the chat completion.
        system_fingerprint:
          type: string
          description: |
            This fingerprint represents the backend configuration that the model runs with.

            Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always `chat.completion`.
          enum: [chat.completion]
        usage:
          $ref: "#/components/schemas/CompletionUsage"
      required:
        - choices
        - created
        - id
        - model
        - object

    ChatCompletionTokenLogprob:
      type: object
      properties:
        token: &chat_completion_response_logprobs_token
          description: The token.
          type: string
        logprob: &chat_completion_response_logprobs_token_logprob
          description: The log probability of this token, if it is within the top 20 most likely tokens. Otherwise, the value `-9999.0` is used to signify that the token is very unlikely.
          type: number
        bytes: &chat_completion_response_logprobs_bytes
          description: A list of integers representing the UTF-8 bytes representation of the token. Useful in instances where characters are represented by multiple tokens and their byte representations must be combined to generate the correct text representation. Can be `null` if there is no bytes representation for the token.
          type: array
          items:
            type: integer
          nullable: true
        top_logprobs:
          description: List of the most likely tokens and their log probability, at this token position. In rare cases, there may be fewer than the number of requested `top_logprobs` returned.
          type: array
          items:
            type: object
            properties:
              token: *chat_completion_response_logprobs_token
              logprob: *chat_completion_response_logprobs_token_logprob
              bytes: *chat_completion_response_logprobs_bytes
            required:
              - token
              - logprob
              - bytes
      required:
        - token
        - logprob
        - bytes
        - top_logprobs

    ListPaginatedFineTuningJobsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJob"
        has_more:
          type: boolean
        object:
          type: string
          enum: [list]
      required:
        - object
        - data
        - has_more

    CreateChatCompletionStreamResponse:
      type: object
      description: Represents a streamed chunk of a chat completion response returned by model, based on the provided input.
      properties:
        id:
          type: string
          description: A unique identifier for the chat completion. Each chunk has the same ID.
        choices:
          type: array
          description: |
            A list of chat completion choices. Can contain more than one elements if `n` is greater than 1. Can also be empty for the
            last chunk if you set `stream_options: {"include_usage": true}`.
          items:
            type: object
            required:
              - delta
              - finish_reason
              - index
            properties:
              delta:
                $ref: "#/components/schemas/ChatCompletionStreamResponseDelta"
              logprobs: *chat_completion_response_logprobs
              finish_reason:
                type: string
                description: *chat_completion_finish_reason_description
                enum:
                  [
                    "stop",
                    "length",
                    "tool_calls",
                    "content_filter",
                    "function_call",
                  ]
                nullable: true
              index:
                type: integer
                description: The index of the choice in the list of choices.
        created:
          type: integer
          description: The Unix timestamp (in seconds) of when the chat completion was created. Each chunk has the same timestamp.
        model:
          type: string
          description: The model to generate the completion.
        system_fingerprint:
          type: string
          description: |
            This fingerprint represents the backend configuration that the model runs with.
            Can be used in conjunction with the `seed` request parameter to understand when backend changes have been made that might impact determinism.
        object:
          type: string
          description: The object type, which is always `chat.completion.chunk`.
          enum: [chat.completion.chunk]
        usage:
          type: object
          description: |
            An optional field that will only be present when you set `stream_options: {"include_usage": true}` in your request.
            When present, it contains a null value except for the last chunk which contains the token usage statistics for the entire request.
          properties:
            completion_tokens:
              type: integer
              description: Number of tokens in the generated completion.
            prompt_tokens:
              type: integer
              description: Number of tokens in the prompt.
            total_tokens:
              type: integer
              description: Total number of tokens used in the request (prompt + completion).
          required:
            - prompt_tokens
            - completion_tokens
            - total_tokens
      required:
        - choices
        - created
        - id
        - model
        - object

    CreateChatCompletionImageResponse:
      type: object
      description: Represents a streamed chunk of a chat completion response returned by model, based on the provided input.

    CreateImageRequest:
      type: object
      properties:
        prompt:
          description: A text description of the desired image(s). The maximum length is 1000 characters for `dall-e-2` and 4000 characters for `dall-e-3`.
          type: string
          example: "A cute baby sea otter"
        model:
          anyOf:
            - type: string
            - type: string
              enum: ["dall-e-2", "dall-e-3"]
          x-oaiTypeLabel: string
          default: "dall-e-2"
          example: "dall-e-3"
          nullable: true
          description: The model to use for image generation.
        n: &images_n
          type: integer
          minimum: 1
          maximum: 10
          default: 1
          example: 1
          nullable: true
          description: The number of images to generate. Must be between 1 and 10. For `dall-e-3`, only `n=1` is supported.
        quality:
          type: string
          enum: ["standard", "hd"]
          default: "standard"
          example: "standard"
          description: The quality of the image that will be generated. `hd` creates images with finer details and greater consistency across the image. This param is only supported for `dall-e-3`.
        response_format: &images_response_format
          type: string
          enum: ["url", "b64_json"]
          default: "url"
          example: "url"
          nullable: true
          description: The format in which the generated images are returned. Must be one of `url` or `b64_json`. URLs are only valid for 60 minutes after the image has been generated.
        size: &images_size
          type: string
          enum: ["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"]
          default: "1024x1024"
          example: "1024x1024"
          nullable: true
          description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024` for `dall-e-2`. Must be one of `1024x1024`, `1792x1024`, or `1024x1792` for `dall-e-3` models.
        style:
          type: string
          enum: ["vivid", "natural"]
          default: "vivid"
          example: "vivid"
          nullable: true
          description: The style of the generated images. Must be one of `vivid` or `natural`. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images. This param is only supported for `dall-e-3`.
        user: *end_user_param_configuration
      required:
        - prompt

    ImagesResponse:
      properties:
        created:
          type: integer
        data:
          type: array
          items:
            $ref: "#/components/schemas/Image"
      required:
        - created
        - data

    Image:
      type: object
      description: Represents the url or the content of an image generated by the Portkey API.
      properties:
        b64_json:
          type: string
          description: The base64-encoded JSON of the generated image, if `response_format` is `b64_json`.
        url:
          type: string
          description: The URL of the generated image, if `response_format` is `url` (default).
        revised_prompt:
          type: string
          description: The prompt that was used to generate the image, if there was any revision to the prompt.
      x-code-samples:
        name: The image object
        example: |
          {
            "url": "...",
            "revised_prompt": "..."
          }

    CreateImageEditRequest:
      type: object
      properties:
        image:
          description: The image to edit. Must be a valid PNG file, less than 4MB, and square. If mask is not provided, image must have transparency, which will be used as the mask.
          type: string
          format: binary
        prompt:
          description: A text description of the desired image(s). The maximum length is 1000 characters.
          type: string
          example: "A cute baby sea otter wearing a beret"
        mask:
          description: An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where `image` should be edited. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.
          type: string
          format: binary
        model:
          anyOf:
            - type: string
            - type: string
              enum: ["dall-e-2"]
          x-oaiTypeLabel: string
          default: "dall-e-2"
          example: "dall-e-2"
          nullable: true
          description: The model to use for image generation. Only `dall-e-2` is supported at this time.
        n:
          type: integer
          minimum: 1
          maximum: 10
          default: 1
          example: 1
          nullable: true
          description: The number of images to generate. Must be between 1 and 10.
        size: &dalle2_images_size
          type: string
          enum: ["256x256", "512x512", "1024x1024"]
          default: "1024x1024"
          example: "1024x1024"
          nullable: true
          description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`.
        response_format: *images_response_format
        user: *end_user_param_configuration
      required:
        - prompt
        - image

    CreateImageVariationRequest:
      type: object
      properties:
        image:
          description: The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square.
          type: string
          format: binary
        model:
          anyOf:
            - type: string
            - type: string
              enum: ["dall-e-2"]
          x-oaiTypeLabel: string
          default: "dall-e-2"
          example: "dall-e-2"
          nullable: true
          description: The model to use for image generation. Only `dall-e-2` is supported at this time.
        n: *images_n
        response_format: *images_response_format
        size: *dalle2_images_size
        user: *end_user_param_configuration
      required:
        - image

    CreateModerationRequest:
      type: object
      properties:
        input:
          description: The input text to classify
          oneOf:
            - type: string
              default: ""
              example: "I want to kill them."
            - type: array
              items:
                type: string
                default: ""
                example: "I want to kill them."
        model:
          description: |
            Two content moderations models are available: `text-moderation-stable` and `text-moderation-latest`.

            The default is `text-moderation-latest` which will be automatically upgraded over time. This ensures you are always using our most accurate model. If you use `text-moderation-stable`, we will provide advanced notice before updating the model. Accuracy of `text-moderation-stable` may be slightly lower than for `text-moderation-latest`.
          nullable: false
          default: "text-moderation-latest"
          example: "text-moderation-stable"
          anyOf:
            - type: string
            - type: string
              enum: ["text-moderation-latest", "text-moderation-stable"]
          x-oaiTypeLabel: string
      required:
        - input

    CreateModerationResponse:
      type: object
      description: Represents if a given text input is potentially harmful.
      properties:
        id:
          type: string
          description: The unique identifier for the moderation request.
        model:
          type: string
          description: The model used to generate the moderation results.
        results:
          type: array
          description: A list of moderation objects.
          items:
            type: object
            properties:
              flagged:
                type: boolean
                description: Whether any of the below categories are flagged.
              categories:
                type: object
                description: A list of the categories, and whether they are flagged or not.
                properties:
                  hate:
                    type: boolean
                    description: Content that expresses, incites, or promotes hate based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste. Hateful content aimed at non-protected groups (e.g., chess players) is harassment.
                  hate/threatening:
                    type: boolean
                    description: Hateful content that also includes violence or serious harm towards the targeted group based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste.
                  harassment:
                    type: boolean
                    description: Content that expresses, incites, or promotes harassing language towards any target.
                  harassment/threatening:
                    type: boolean
                    description: Harassment content that also includes violence or serious harm towards any target.
                  self-harm:
                    type: boolean
                    description: Content that promotes, encourages, or depicts acts of self-harm, such as suicide, cutting, and eating disorders.
                  self-harm/intent:
                    type: boolean
                    description: Content where the speaker expresses that they are engaging or intend to engage in acts of self-harm, such as suicide, cutting, and eating disorders.
                  self-harm/instructions:
                    type: boolean
                    description: Content that encourages performing acts of self-harm, such as suicide, cutting, and eating disorders, or that gives instructions or advice on how to commit such acts.
                  sexual:
                    type: boolean
                    description: Content meant to arouse sexual excitement, such as the description of sexual activity, or that promotes sexual services (excluding sex education and wellness).
                  sexual/minors:
                    type: boolean
                    description: Sexual content that includes an individual who is under 18 years old.
                  violence:
                    type: boolean
                    description: Content that depicts death, violence, or physical injury.
                  violence/graphic:
                    type: boolean
                    description: Content that depicts death, violence, or physical injury in graphic detail.
                required:
                  - hate
                  - hate/threatening
                  - harassment
                  - harassment/threatening
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
              category_scores:
                type: object
                description: A list of the categories along with their scores as predicted by model.
                properties:
                  hate:
                    type: number
                    description: The score for the category 'hate'.
                  hate/threatening:
                    type: number
                    description: The score for the category 'hate/threatening'.
                  harassment:
                    type: number
                    description: The score for the category 'harassment'.
                  harassment/threatening:
                    type: number
                    description: The score for the category 'harassment/threatening'.
                  self-harm:
                    type: number
                    description: The score for the category 'self-harm'.
                  self-harm/intent:
                    type: number
                    description: The score for the category 'self-harm/intent'.
                  self-harm/instructions:
                    type: number
                    description: The score for the category 'self-harm/instructions'.
                  sexual:
                    type: number
                    description: The score for the category 'sexual'.
                  sexual/minors:
                    type: number
                    description: The score for the category 'sexual/minors'.
                  violence:
                    type: number
                    description: The score for the category 'violence'.
                  violence/graphic:
                    type: number
                    description: The score for the category 'violence/graphic'.
                required:
                  - hate
                  - hate/threatening
                  - harassment
                  - harassment/threatening
                  - self-harm
                  - self-harm/intent
                  - self-harm/instructions
                  - sexual
                  - sexual/minors
                  - violence
                  - violence/graphic
            required:
              - flagged
              - categories
              - category_scores
      required:
        - id
        - model
        - results

    ListFilesResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/OpenAIFile"
        object:
          type: string
          enum: [list]
      required:
        - object
        - data

    CreateFileRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: |
            The File object (not file name) to be uploaded.
          type: string
          format: binary
        purpose:
          description: |
            The intended purpose of the uploaded file.

            Use "assistants" for [Assistants](https://platform.openai.com/docs/api-reference/assistants) and [Message](https://platform.openai.com/docs/api-reference/messages) files, "vision" for Assistants image file inputs, "batch" for [Batch API](https://platform.openai.com/docs/guides/batch), and "fine-tune" for [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning).
          type: string
          enum: ["assistants", "batch", "fine-tune", "vision"]
      required:
        - file
        - purpose

    DeleteFileResponse:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum: [file]
        deleted:
          type: boolean
      required:
        - id
        - object
        - deleted

    BedrockFinetuneJob:
      type: object
      description: Gateway supported body params for bedrock fine-tuning.
      title: Bedrock Params
      properties:
        job_name:
          type: string
          description: Job name for the bedrock finetune job
        role_arn:
          type: string
          description: Role ARN for the bedrock finetune job
        output_file:
          type: string
          description: Finetune job's output s3 location, will be constructed based on `training_file` if not provided
      allOf:
        - $ref: "#/components/schemas/OpenAIFinetuneJob"

    OpenAIFinetuneJob:
      type: object
      description: Gateway supported body params for OpenAI, Azure OpenAI and VertexAI.
      title: OpenAI Params
      required:
        - model
        - training_file
        - suffix
        - method
      properties:
        model:
          type: string
          description: The base model to finetune
        training_file:
          type: string
          description: The training file to use for the finetune job
        validation_file:
          type: string
          description: The validation file to use for the finetune job
        suffix:
          type: string
          description: The suffix to append to the fine-tuned model name
        method:
          type: object
          properties:
            type:
              type: string
              enum:
                - supervised
                - dpo
            supervised:
              type: object
              properties:
                hyperparameters:
                  type: object
                  properties:
                    n_epochs:
                      type: integer
                      format: int32
                    learning_rate_multiplier:
                      type: number
                      format: float
                    batch_size:
                      type: integer
                      format: int32
                  required:
                    - n_epochs
                    - learning_rate_multiplier
                    - batch_size
              required:
                - hyperparameters
            dpo:
              type: object
              properties:
                hyperparameters:
                  type: object
                  properties:
                    n_epochs:
                      type: integer
                      format: int32
                    learning_rate_multiplier:
                      type: number
                      format: float
                    batch_size:
                      type: integer
                      format: int32
                  required:
                    - n_epochs
                    - learning_rate_multiplier
                    - batch_size
              required:
                - hyperparameters
          required:
            - type
          description: Hyperparameters for the finetune job

    BedrockParams:
      type: object
      properties:
        job_name:
          type: string
          description: Job name for the bedrock finetune job
        role_arn:
          type: string
          description: Role ARN for the bedrock finetune job
        output_file:
          type: string
          description: Finetune job's output s3 location, will be constructed based on `training_file` if not provided

    PortkeyFinetuneJob:
      type: object
      properties:
        job_name:
          type: string
          description: Job name for the bedrock finetune job
        role_arn:
          type: string
          description: Role ARN for the bedrock finetune job
        output_file:
          type: string
          description: Finetune job's output s3 location, will be constructed based on `training_file` if not provided
        portkey_options:
          allOf:
            - $ref: "#/components/schemas/PortkeyOptions"
          description: Portkey Gateway Provider specific headers to be passed to the provider, if portkey is used as a provider
        provider_options:
          allOf:
            - $ref: "#/components/schemas/BedrockParams"
          description: Provider specific options to be passed to the provider, optional can be passed directly as well. Can be skipped if same keys are passed at top the level.
      allOf:
        - $ref: "#/components/schemas/OpenAIFinetuneJob"
      description: Gateway supported body params for portkey managed fine-tuning.
      title: Portkey Params
    PortkeyOptions:
      type: object
      required:
        - x-portkey-virtual-key
      properties:
        x-portkey-virtual-key:
          type: string
          description: The virtual key to communicate with the provider
        x-portkey-aws-s3-bucket:
          type: string
          description: The AWS S3 bucket to use for file upload during finetune
        x-portkey-vertex-storage-bucket-name:
          type: string
          description: Google Storage bucket to use for file upload during finetune
      example:
        x-portkey-virtual-key: vkey-1234567890
        x-portkey-aws-s3-bucket: my-bucket
        x-portkey-vertex-storage-bucket-name: my-bucket
      description: Options to be passed to the provider, supports all options supported by the provider from gateway.

    VertexFinetuneJob:
      type: object
      allOf:
        - $ref: "#/components/schemas/OpenAIFinetuneJob"

    ListFineTuningJobEventsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJobEvent"
        object:
          type: string
          enum: [list]
      required:
        - object
        - data

    ListFineTuningJobCheckpointsResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/FineTuningJobCheckpoint"
        object:
          type: string
          enum: [list]
        first_id:
          type: string
          nullable: true
        last_id:
          type: string
          nullable: true
        has_more:
          type: boolean
      required:
        - object
        - data
        - has_more

    CreateEmbeddingRequest:
      type: object
      additionalProperties: false
      properties:
        input:
          description: |
            Input text to embed, encoded as a string or array of tokens. To embed multiple inputs in a single request, pass an array of strings or array of token arrays. The input must not exceed the max input tokens for the model (8192 tokens for `text-embedding-ada-002`), cannot be an empty string, and any array must be 2048 dimensions or less. [Example Python code](https://cookbook.openai.com/examples/how_to_count_tokens_with_tiktoken) for counting tokens.
          example: "The quick brown fox jumped over the lazy dog"
          oneOf:
            - type: string
              title: string
              description: The string that will be turned into an embedding.
              default: ""
              example: "This is a test."
            - type: array
              title: array
              description: The array of strings that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: string
                default: ""
                example: "['This is a test.']"
            - type: array
              title: array
              description: The array of integers that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: integer
              example: "[1212, 318, 257, 1332, 13]"
            - type: array
              title: array
              description: The array of arrays containing integers that will be turned into an embedding.
              minItems: 1
              maxItems: 2048
              items:
                type: array
                minItems: 1
                items:
                  type: integer
              example: "[[1212, 318, 257, 1332, 13]]"
          x-oaiExpandable: true
        model:
          description: *model_description
          example: "text-embedding-3-small"
          anyOf:
            - type: string
            - type: string
              enum:
                [
                  "text-embedding-ada-002",
                  "text-embedding-3-small",
                  "text-embedding-3-large",
                ]
          x-oaiTypeLabel: string
        encoding_format:
          description: "The format to return the embeddings in. Can be either `float` or [`base64`](https://pypi.org/project/pybase64/)."
          example: "float"
          default: "float"
          type: string
          enum: ["float", "base64"]
        dimensions:
          description: |
            The number of dimensions the resulting output embeddings should have. Only supported in `text-embedding-3` and later models.
          type: integer
          minimum: 1
        user: *end_user_param_configuration
      required:
        - model
        - input

    CreateEmbeddingResponse:
      type: object
      properties:
        data:
          type: array
          description: The list of embeddings generated by the model.
          items:
            $ref: "#/components/schemas/Embedding"
        model:
          type: string
          description: The name of the model used to generate the embedding.
        object:
          type: string
          description: The object type, which is always "list".
          enum: [list]
        usage:
          type: object
          description: The usage information for the request.
          properties:
            prompt_tokens:
              type: integer
              description: The number of tokens used by the prompt.
            total_tokens:
              type: integer
              description: The total number of tokens used by the request.
          required:
            - prompt_tokens
            - total_tokens
      required:
        - object
        - model
        - data
        - usage

    CreateTranscriptionRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: |
            The audio file object (not file name) to transcribe, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
          type: string
          x-oaiTypeLabel: file
          format: binary
        model:
          description: |
            ID of the model to use. Only `whisper-1` (which is powered by our open source Whisper V2 model) is currently available.
          example: whisper-1
          anyOf:
            - type: string
            - type: string
              enum: ["whisper-1"]
          x-oaiTypeLabel: string
        language:
          description: |
            The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will improve accuracy and latency.
          type: string
        prompt:
          description: |
            An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text/prompting) should match the audio language.
          type: string
        response_format:
          description: |
            The format of the transcript output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.
          type: string
          enum:
            - json
            - text
            - srt
            - verbose_json
            - vtt
          default: json
        temperature:
          description: |
            The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.
          type: number
          default: 0
        timestamp_granularities[]:
          description: |
            The timestamp granularities to populate for this transcription. `response_format` must be set `verbose_json` to use timestamp granularities. Either or both of these options are supported: `word`, or `segment`. Note: There is no additional latency for segment timestamps, but generating word timestamps incurs additional latency.
          type: array
          items:
            type: string
            enum:
              - word
              - segment
          default: [segment]
      required:
        - file
        - model

    # Note: This does not currently support the non-default response format types.
    CreateTranscriptionResponseJson:
      type: object
      description: Represents a transcription response returned by model, based on the provided input.
      properties:
        text:
          type: string
          description: The transcribed text.
      required:
        - text

    TranscriptionSegment:
      type: object
      properties:
        id:
          type: integer
          description: Unique identifier of the segment.
        seek:
          type: integer
          description: Seek offset of the segment.
        start:
          type: number
          format: float
          description: Start time of the segment in seconds.
        end:
          type: number
          format: float
          description: End time of the segment in seconds.
        text:
          type: string
          description: Text content of the segment.
        tokens:
          type: array
          items:
            type: integer
          description: Array of token IDs for the text content.
        temperature:
          type: number
          format: float
          description: Temperature parameter used for generating the segment.
        avg_logprob:
          type: number
          format: float
          description: Average logprob of the segment. If the value is lower than -1, consider the logprobs failed.
        compression_ratio:
          type: number
          format: float
          description: Compression ratio of the segment. If the value is greater than 2.4, consider the compression failed.
        no_speech_prob:
          type: number
          format: float
          description: Probability of no speech in the segment. If the value is higher than 1.0 and the `avg_logprob` is below -1, consider this segment silent.
      required:
        - id
        - seek
        - start
        - end
        - text
        - tokens
        - temperature
        - avg_logprob
        - compression_ratio
        - no_speech_prob

    TranscriptionWord:
      type: object
      properties:
        word:
          type: string
          description: The text content of the word.
        start:
          type: number
          format: float
          description: Start time of the word in seconds.
        end:
          type: number
          format: float
          description: End time of the word in seconds.
      required: [word, start, end]

    CreateTranscriptionResponseVerboseJson:
      type: object
      description: Represents a verbose json transcription response returned by model, based on the provided input.
      properties:
        language:
          type: string
          description: The language of the input audio.
        duration:
          type: string
          description: The duration of the input audio.
        text:
          type: string
          description: The transcribed text.
        words:
          type: array
          description: Extracted words and their corresponding timestamps.
          items:
            $ref: "#/components/schemas/TranscriptionWord"
        segments:
          type: array
          description: Segments of the transcribed text and their corresponding details.
          items:
            $ref: "#/components/schemas/TranscriptionSegment"
      required: [language, duration, text]

    CreateTranslationRequest:
      type: object
      additionalProperties: false
      properties:
        file:
          description: |
            The audio file object (not file name) translate, in one of these formats: flac, mp3, mp4, mpeg, mpga, m4a, ogg, wav, or webm.
          type: string
          x-oaiTypeLabel: file
          format: binary
        model:
          description: |
            ID of the model to use. Only `whisper-1` (which is powered by our open source Whisper V2 model) is currently available.
          example: whisper-1
          anyOf:
            - type: string
            - type: string
              enum: ["whisper-1"]
          x-oaiTypeLabel: string
        prompt:
          description: |
            An optional text to guide the model's style or continue a previous audio segment. The [prompt](https://platform.openai.com/docs/guides/speech-to-text/prompting) should be in English.
          type: string
        response_format:
          description: |
            The format of the transcript output, in one of these options: `json`, `text`, `srt`, `verbose_json`, or `vtt`.
          type: string
          default: json
        temperature:
          description: |
            The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.
          type: number
          default: 0
      required:
        - file
        - model

    # Note: This does not currently support the non-default response format types.
    CreateTranslationResponseJson:
      type: object
      properties:
        text:
          type: string
      required:
        - text

    CreateTranslationResponseVerboseJson:
      type: object
      properties:
        language:
          type: string
          description: The language of the output translation (always `english`).
        duration:
          type: string
          description: The duration of the input audio.
        text:
          type: string
          description: The translated text.
        segments:
          type: array
          description: Segments of the translated text and their corresponding details.
          items:
            $ref: "#/components/schemas/TranscriptionSegment"
      required: [language, duration, text]

    CreateSpeechRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: |
            One of the available [TTS models](https://platform.openai.com/docs/models/tts): `tts-1` or `tts-1-hd`
          anyOf:
            - type: string
            - type: string
              enum: ["tts-1", "tts-1-hd"]
          x-oaiTypeLabel: string
        input:
          type: string
          description: The text to generate audio for. The maximum length is 4096 characters.
          maxLength: 4096
        voice:
          description: The voice to use when generating the audio. Supported voices are `alloy`, `echo`, `fable`, `onyx`, `nova`, and `shimmer`. Previews of the voices are available in the [Text to speech guide](https://platform.openai.com/docs/guides/text-to-speech/voice-options).
          type: string
          enum: ["alloy", "echo", "fable", "onyx", "nova", "shimmer"]
        response_format:
          description: "The format to audio in. Supported formats are `mp3`, `opus`, `aac`, `flac`, `wav`, and `pcm`."
          default: "mp3"
          type: string
          enum: ["mp3", "opus", "aac", "flac", "wav", "pcm"]
        speed:
          description: "The speed of the generated audio. Select a value from `0.25` to `4.0`. `1.0` is the default."
          type: number
          default: 1.0
          minimum: 0.25
          maximum: 4.0
      required:
        - model
        - input
        - voice

    Model:
      title: Model
      description: Describes an OpenAI model offering that can be used with the API.
      properties:
        id:
          type: string
          description: The model identifier, which can be referenced in the API endpoints.
        created:
          type: integer
          description: The Unix timestamp (in seconds) when the model was created.
        object:
          type: string
          description: The object type, which is always "model".
          enum: [model]
        owned_by:
          type: string
          description: The organization that owns the model.
      required:
        - id
        - object
        - created
        - owned_by

    OpenAIFile:
      title: OpenAIFile
      description: The `File` object represents a document that has been uploaded to OpenAI.
      properties:
        id:
          type: string
          description: The file identifier, which can be referenced in the API endpoints.
        bytes:
          type: integer
          description: The size of the file, in bytes.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the file was created.
        filename:
          type: string
          description: The name of the file.
        object:
          type: string
          description: The object type, which is always `file`.
          enum: ["file"]
        purpose:
          type: string
          description: The intended purpose of the file. Supported values are `assistants`, `assistants_output`, `batch`, `batch_output`, `fine-tune`, `fine-tune-results` and `vision`.
          enum:
            [
              "assistants",
              "assistants_output",
              "batch",
              "batch_output",
              "fine-tune",
              "fine-tune-results",
              "vision",
            ]
        status:
          type: string
          deprecated: true
          description: Deprecated. The current status of the file, which can be either `uploaded`, `processed`, or `error`.
          enum: ["uploaded", "processed", "error"]
        status_details:
          type: string
          deprecated: true
          description: Deprecated. For details on why a fine-tuning training file failed validation, see the `error` field on `fine_tuning.job`.
      required:
        - id
        - object
        - bytes
        - created_at
        - filename
        - purpose
        - status
      x-code-samples:
        name: The file object
        example: |
          {
            "id": "file-abc123",
            "object": "file",
            "bytes": 120000,
            "created_at": 1677610602,
            "filename": "salesOverview.pdf",
            "purpose": "assistants",
          }
    Embedding:
      type: object
      description: |
        Represents an embedding vector returned by embedding endpoint.
      properties:
        index:
          type: integer
          description: The index of the embedding in the list of embeddings.
        embedding:
          type: array
          description: |
            The embedding vector, which is a list of floats. The length of vector depends on the model as listed in the [embedding guide](https://platform.openai.com/docs/guides/embeddings).
          items:
            type: number
        object:
          type: string
          description: The object type, which is always "embedding".
          enum: [embedding]
      required:
        - index
        - object
        - embedding
      x-code-samples:
        name: The embedding object
        example: |
          {
            "object": "embedding",
            "embedding": [
              0.0023064255,
              -0.009327292,
              .... (1536 floats total for ada-002)
              -0.0028842222,
            ],
            "index": 0
          }

    FineTuningJob:
      type: object
      title: FineTuningJob
      description: |
        The `fine_tuning.job` object represents a fine-tuning job that has been created through the API.
      properties:
        id:
          type: string
          description: The object identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the fine-tuning job was created.
        error:
          type: object
          nullable: true
          description: For fine-tuning jobs that have `failed`, this will contain more information on the cause of the failure.
          properties:
            code:
              type: string
              description: A machine-readable error code.
            message:
              type: string
              description: A human-readable error message.
            param:
              type: string
              description: The parameter that was invalid, usually `training_file` or `validation_file`. This field will be null if the failure was not parameter-specific.
              nullable: true
          required:
            - code
            - message
            - param
        fine_tuned_model:
          type: string
          nullable: true
          description: The name of the fine-tuned model that is being created. The value will be null if the fine-tuning job is still running.
        finished_at:
          type: integer
          nullable: true
          description: The Unix timestamp (in seconds) for when the fine-tuning job was finished. The value will be null if the fine-tuning job is still running.
        hyperparameters:
          type: object
          description: The hyperparameters used for the fine-tuning job. See the [fine-tuning guide](https://platform.openai.com/docs/guides/fine-tuning) for more details.
          properties:
            n_epochs:
              oneOf:
                - type: string
                  enum: [auto]
                - type: integer
                  minimum: 1
                  maximum: 50
              default: auto
              description:
                The number of epochs to train the model for. An epoch refers to one full cycle through the training dataset.

                "auto" decides the optimal number of epochs based on the size of the dataset. If setting the number manually, we support any number between 1 and 50 epochs.
          required:
            - n_epochs
        model:
          type: string
          description: The base model that is being fine-tuned.
        object:
          type: string
          description: The object type, which is always "fine_tuning.job".
          enum: [fine_tuning.job]
        organization_id:
          type: string
          description: The organization that owns the fine-tuning job.
        result_files:
          type: array
          description: The compiled results file ID(s) for the fine-tuning job. You can retrieve the results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
          items:
            type: string
            example: file-abc123
        status:
          type: string
          description: The current status of the fine-tuning job, which can be either `validating_files`, `queued`, `running`, `succeeded`, `failed`, or `cancelled`.
          enum:
            [
              "validating_files",
              "queued",
              "running",
              "succeeded",
              "failed",
              "cancelled",
            ]
        trained_tokens:
          type: integer
          nullable: true
          description: The total number of billable tokens processed by this fine-tuning job. The value will be null if the fine-tuning job is still running.
        training_file:
          type: string
          description: The file ID used for training. You can retrieve the training data with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
        validation_file:
          type: string
          nullable: true
          description: The file ID used for validation. You can retrieve the validation results with the [Files API](https://platform.openai.com/docs/api-reference/files/retrieve-contents).
        integrations:
          type: array
          nullable: true
          description: A list of integrations to enable for this fine-tuning job.
          maxItems: 5
          items:
            oneOf:
              - $ref: "#/components/schemas/FineTuningIntegration"
            x-oaiExpandable: true
        seed:
          type: integer
          description: The seed used for the fine-tuning job.
        estimated_finish:
          type: integer
          nullable: true
          description: The Unix timestamp (in seconds) for when the fine-tuning job is estimated to finish. The value will be null if the fine-tuning job is not running.
      required:
        - created_at
        - error
        - finished_at
        - fine_tuned_model
        - hyperparameters
        - id
        - model
        - object
        - organization_id
        - result_files
        - status
        - trained_tokens
        - training_file
        - validation_file
        - seed

    FineTuningIntegration:
      type: object
      title: Fine-Tuning Job Integration
      required:
        - type
        - wandb
      properties:
        type:
          type: string
          description: "The type of the integration being enabled for the fine-tuning job"
          enum: ["wandb"]
        wandb:
          type: object
          description: |
            The settings for your integration with Weights and Biases. This payload specifies the project that
            metrics will be sent to. Optionally, you can set an explicit display name for your run, add tags
            to your run, and set a default entity (team, username, etc) to be associated with your run.
          required:
            - project
          properties:
            project:
              description: |
                The name of the project that the new run will be created under.
              type: string
              example: "my-wandb-project"
            name:
              description: |
                A display name to set for the run. If not set, we will use the Job ID as the name.
              nullable: true
              type: string
            entity:
              description: |
                The entity to use for the run. This allows you to set the team or username of the WandB user that you would
                like associated with the run. If not set, the default entity for the registered WandB API key is used.
              nullable: true
              type: string
            tags:
              description: |
                A list of tags to be attached to the newly created run. These tags are passed through directly to WandB. Some
                default tags are generated by OpenAI: "openai/finetune", "openai/{base-model}", "openai/{ftjob-abcdef}".
              type: array
              items:
                type: string
                example: "custom-tag"

    FineTuningJobEvent:
      type: object
      description: Fine-tuning job event object
      properties:
        id:
          type: string
        created_at:
          type: integer
        level:
          type: string
          enum: ["info", "warn", "error"]
        message:
          type: string
        object:
          type: string
          enum: [fine_tuning.job.event]
      required:
        - id
        - object
        - created_at
        - level
        - message
      x-code-samples:
        name: The fine-tuning job event object
        example: |
          {
            "object": "fine_tuning.job.event",
            "id": "ftevent-abc123"
            "created_at": 1677610602,
            "level": "info",
            "message": "Created fine-tuning job"
          }

    FineTuningJobCheckpoint:
      type: object
      title: FineTuningJobCheckpoint
      description: |
        The `fine_tuning.job.checkpoint` object represents a model checkpoint for a fine-tuning job that is ready to use.
      properties:
        id:
          type: string
          description: The checkpoint identifier, which can be referenced in the API endpoints.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the checkpoint was created.
        fine_tuned_model_checkpoint:
          type: string
          description: The name of the fine-tuned checkpoint model that is created.
        step_number:
          type: integer
          description: The step number that the checkpoint was created at.
        metrics:
          type: object
          description: Metrics at the step number during the fine-tuning job.
          properties:
            step:
              type: number
            train_loss:
              type: number
            train_mean_token_accuracy:
              type: number
            valid_loss:
              type: number
            valid_mean_token_accuracy:
              type: number
            full_valid_loss:
              type: number
            full_valid_mean_token_accuracy:
              type: number
        fine_tuning_job_id:
          type: string
          description: The name of the fine-tuning job that this checkpoint was created from.
        object:
          type: string
          description: The object type, which is always "fine_tuning.job.checkpoint".
          enum: [fine_tuning.job.checkpoint]
      required:
        - created_at
        - fine_tuning_job_id
        - fine_tuned_model_checkpoint
        - id
        - metrics
        - object
        - step_number
      x-code-samples:
        name: The fine-tuning job checkpoint object
        example: |
          {
            "object": "fine_tuning.job.checkpoint",
            "id": "ftckpt_qtZ5Gyk4BLq1SfLFWp3RtO3P",
            "created_at": 1712211699,
            "fine_tuned_model_checkpoint": "ft:gpt-3.5-turbo-0125:my-org:custom_suffix:9ABel2dg:ckpt-step-88",
            "fine_tuning_job_id": "ftjob-fpbNQ3H1GrMehXRf8cO97xTN",
            "metrics": {
              "step": 88,
              "train_loss": 0.478,
              "train_mean_token_accuracy": 0.924,
              "valid_loss": 10.112,
              "valid_mean_token_accuracy": 0.145,
              "full_valid_loss": 0.567,
              "full_valid_mean_token_accuracy": 0.944
            },
            "step_number": 88
          }

    FinetuneChatRequestInput:
      type: object
      description: The per-line training example of a fine-tuning input file for chat models
      properties:
        messages:
          type: array
          minItems: 1
          items:
            oneOf:
              - $ref: "#/components/schemas/ChatCompletionRequestSystemMessage"
              - $ref: "#/components/schemas/ChatCompletionRequestUserMessage"
              - $ref: "#/components/schemas/FineTuneChatCompletionRequestAssistantMessage"
              - $ref: "#/components/schemas/FineTuneChatCompletionRequestFunctionMessage"
            x-oaiExpandable: true
        functions:
          description: A list of functions the model may generate JSON inputs for.
          type: array
          minItems: 1
          maxItems: 128
          items:
            $ref: "#/components/schemas/ChatCompletionFunctions"
      x-code-samples:
        name: Training format for chat models
        example: |
          {"messages":[{"role":"user","content":"What is the weather in San Francisco?"},{"role":"assistant","function_call":{"name":"get_current_weather","arguments":"{\"location\": \"San Francisco, USA\", \"format\": \"celsius\"}"}}],"functions":[{"name":"get_current_weather","description":"Get the current weather","parameters":{"type":"object","properties":{"location":{"type":"string","description":"The city and country, eg. San Francisco, USA"},"format":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location","format"]}}]}

    FinetuneCompletionRequestInput:
      type: object
      description: The per-line training example of a fine-tuning input file for completions models
      properties:
        prompt:
          type: string
          description: The input prompt for this training example.
        completion:
          type: string
          description: The desired completion for this training example.
      x-code-samples:
        name: Training format for completions models
        example: |
          {"prompt": "What is the answer to 2+2", "completion": "4"}

    CompletionUsage:
      type: object
      description: Usage statistics for the completion request.
      properties:
        completion_tokens:
          type: integer
          description: Number of tokens in the generated completion.
        prompt_tokens:
          type: integer
          description: Number of tokens in the prompt.
        total_tokens:
          type: integer
          description: Total number of tokens used in the request (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens

    RunCompletionUsage:
      type: object
      description: Usage statistics related to the run. This value will be `null` if the run is not in a terminal state (i.e. `in_progress`, `queued`, etc.).
      properties:
        completion_tokens:
          type: integer
          description: Number of completion tokens used over the course of the run.
        prompt_tokens:
          type: integer
          description: Number of prompt tokens used over the course of the run.
        total_tokens:
          type: integer
          description: Total number of tokens used (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens
      nullable: true

    RunStepCompletionUsage:
      type: object
      description: Usage statistics related to the run step. This value will be `null` while the run step's status is `in_progress`.
      properties:
        completion_tokens:
          type: integer
          description: Number of completion tokens used over the course of the run step.
        prompt_tokens:
          type: integer
          description: Number of prompt tokens used over the course of the run step.
        total_tokens:
          type: integer
          description: Total number of tokens used (prompt + completion).
      required:
        - prompt_tokens
        - completion_tokens
        - total_tokens
      nullable: true

    AssistantsApiResponseFormatOption:
      description: |
        Specifies the format that the model must output. Compatible with [GPT-4o](https://platform.openai.com/docs/models/gpt-4o), [GPT-4 Turbo](https://platform.openai.com/docs/models/gpt-4-turbo-and-gpt-4), and all GPT-3.5 Turbo models since `gpt-3.5-turbo-1106`.

        Setting to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON.

        **Important:** when using JSON mode, you **must** also instruct the model to produce JSON yourself via a system or user message. Without this, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content may be partially cut off if `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length.
      oneOf:
        - type: string
          description: >
            `auto` is the default value
          enum: [none, auto]
        - $ref: "#/components/schemas/AssistantsApiResponseFormat"
      x-oaiExpandable: true

    AssistantsApiResponseFormat:
      type: object
      description: |
        An object describing the expected output of the model. If `json_object` only `function` type `tools` are allowed to be passed to the Run. If `text` the model can return text or any value needed.
      properties:
        type:
          type: string
          enum: ["text", "json_object"]
          example: "json_object"
          default: "text"
          description: Must be one of `text` or `json_object`.

    AssistantObject:
      type: object
      title: Assistant
      description: Represents an `assistant` that can call the model and use tools.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `assistant`.
          type: string
          enum: [assistant]
        created_at:
          description: The Unix timestamp (in seconds) for when the assistant was created.
          type: integer
        name:
          description: &assistant_name_param_description |
            The name of the assistant. The maximum length is 256 characters.
          type: string
          maxLength: 256
          nullable: true
        description:
          description: &assistant_description_param_description |
            The description of the assistant. The maximum length is 512 characters.
          type: string
          maxLength: 512
          nullable: true
        model:
          description: *model_description
          type: string
        instructions:
          description: &assistant_instructions_param_description |
            The system instructions that the assistant uses. The maximum length is 256,000 characters.
          type: string
          maxLength: 256000
          nullable: true
        tools:
          description: &assistant_tools_param_description |
            A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types `code_interpreter`, `file_search`, or `function`.
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        tool_resources:
          type: object
          description: |
            A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter`` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          description: &metadata_description |
            Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: &run_temperature_description |
            What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: &run_top_p_description |
            An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.

            We generally recommend altering this or temperature but not both.
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - id
        - object
        - created_at
        - name
        - description
        - model
        - instructions
        - tools
        - metadata
      x-code-samples:
        name: The assistant object
        beta: true
        example: *create_assistants_example

    CreateAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: *model_description
          example: "gpt-4-turbo"
          anyOf:
            - type: string
            - type: string
              enum:
                [
                  "gpt-4o",
                  "gpt-4o-2024-05-13",
                  "gpt-4-turbo",
                  "gpt-4-turbo-2024-04-09",
                  "gpt-4-0125-preview",
                  "gpt-4-turbo-preview",
                  "gpt-4-1106-preview",
                  "gpt-4-vision-preview",
                  "gpt-4",
                  "gpt-4-0314",
                  "gpt-4-0613",
                  "gpt-4-32k",
                  "gpt-4-32k-0314",
                  "gpt-4-32k-0613",
                  "gpt-3.5-turbo",
                  "gpt-3.5-turbo-16k",
                  "gpt-3.5-turbo-0613",
                  "gpt-3.5-turbo-1106",
                  "gpt-3.5-turbo-0125",
                  "gpt-3.5-turbo-16k-0613",
                ]
          x-oaiTypeLabel: string
        name:
          description: *assistant_name_param_description
          type: string
          nullable: true
          maxLength: 256
        description:
          description: *assistant_description_param_description
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: *assistant_instructions_param_description
          type: string
          nullable: true
          maxLength: 256000
        tools:
          description: *assistant_tools_param_description
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        tool_resources:
          type: object
          description: |
            A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
                vector_stores:
                  type: array
                  description: |
                    A helper to create a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids and attach it to this assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: object
                    properties:
                      file_ids:
                        type: array
                        description: |
                          A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to the vector store. There can be a maximum of 10000 files in a vector store.
                        maxItems: 10000
                        items:
                          type: string
                      chunking_strategy:
                        # Ideally we'd reuse the chunking strategy schema here, but it doesn't expand properly
                        type: object
                        description: The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.
                        oneOf:
                          - type: object
                            title: Auto Chunking Strategy
                            description: The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `auto`.
                                enum: ["auto"]
                            required:
                              - type
                          - type: object
                            title: Static Chunking Strategy
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `static`.
                                enum: ["static"]
                              static:
                                type: object
                                additionalProperties: false
                                properties:
                                  max_chunk_size_tokens:
                                    type: integer
                                    minimum: 100
                                    maximum: 4096
                                    description: The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`.
                                  chunk_overlap_tokens:
                                    type: integer
                                    description: |
                                      The number of tokens that overlap between chunks. The default value is `400`.

                                      Note that the overlap must not exceed half of `max_chunk_size_tokens`.
                                required:
                                  - max_chunk_size_tokens
                                  - chunk_overlap_tokens
                            required:
                              - type
                              - static
                        x-oaiExpandable: true
                      metadata:
                        type: object
                        description: |
                          Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
                        x-oaiTypeLabel: map
              oneOf:
                - required: [vector_store_ids]
                - required: [vector_stores]
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: *run_temperature_description
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *run_top_p_description
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - model

    ModifyAssistantRequest:
      type: object
      additionalProperties: false
      properties:
        model:
          description: *model_description
          anyOf:
            - type: string
        name:
          description: *assistant_name_param_description
          type: string
          nullable: true
          maxLength: 256
        description:
          description: *assistant_description_param_description
          type: string
          nullable: true
          maxLength: 512
        instructions:
          description: *assistant_instructions_param_description
          type: string
          nullable: true
          maxLength: 256000
        tools:
          description: *assistant_tools_param_description
          default: []
          type: array
          maxItems: 128
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        tool_resources:
          type: object
          description: |
            A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    Overrides the list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    Overrides the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          description: *run_temperature_description
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *run_top_p_description
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true

    DeleteAssistantResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [assistant.deleted]
      required:
        - id
        - object
        - deleted

    ListAssistantsResponse:
      type: object
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/AssistantObject"
        first_id:
          type: string
          example: "asst_abc123"
        last_id:
          type: string
          example: "asst_abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
      x-code-samples:
        name: List assistants response object
        group: chat
        example: *list_assistants_example

    AssistantToolsCode:
      type: object
      title: Code interpreter tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `code_interpreter`"
          enum: ["code_interpreter"]
      required:
        - type

    AssistantToolsFileSearch:
      type: object
      title: FileSearch tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `file_search`"
          enum: ["file_search"]
        file_search:
          type: object
          description: Overrides for the file search tool.
          properties:
            max_num_results:
              type: integer
              minimum: 1
              maximum: 50
              description: |
                The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.

                Note that the file search tool may output fewer than `max_num_results` results. See the [file search tool documentation](https://platform.openai.com/docs/assistants/tools/file-search/number-of-chunks-returned) for more information.
      required:
        - type

    AssistantToolsFileSearchTypeOnly:
      type: object
      title: FileSearch tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `file_search`"
          enum: ["file_search"]
      required:
        - type

    AssistantToolsFunction:
      type: object
      title: Function tool
      properties:
        type:
          type: string
          description: "The type of tool being defined: `function`"
          enum: ["function"]
        function:
          $ref: "#/components/schemas/FunctionObject"
      required:
        - type
        - function

    TruncationObject:
      type: object
      title: Thread Truncation Controls
      description: Controls for how a thread will be truncated prior to the run. Use this to control the intial context window of the run.
      properties:
        type:
          type: string
          description: The truncation strategy to use for the thread. The default is `auto`. If set to `last_messages`, the thread will be truncated to the n most recent messages in the thread. When set to `auto`, messages in the middle of the thread will be dropped to fit the context length of the model, `max_prompt_tokens`.
          enum: ["auto", "last_messages"]
        last_messages:
          type: integer
          description: The number of most recent messages from the thread when constructing the context for the run.
          minimum: 1
          nullable: true
      required:
        - type

    AssistantsApiToolChoiceOption:
      description: |
        Controls which (if any) tool is called by the model.
        `none` means the model will not call any tools and instead generates a message.
        `auto` is the default value and means the model can pick between generating a message or calling one or more tools.
        `required` means the model must call one or more tools before responding to the user.
        Specifying a particular tool like `{"type": "file_search"}` or `{"type": "function", "function": {"name": "my_function"}}` forces the model to call that tool.

      oneOf:
        - type: string
          description: >
            `none` means the model will not call any tools and instead generates a message.
            `auto` means the model can pick between generating a message or calling one or more tools.
            `required` means the model must call one or more tools before responding to the user.
          enum: [none, auto, required]
        - $ref: "#/components/schemas/AssistantsNamedToolChoice"
      x-oaiExpandable: true

    AssistantsNamedToolChoice:
      type: object
      description: Specifies a tool the model should use. Use to force the model to call a specific tool.
      properties:
        type:
          type: string
          enum: ["function", "code_interpreter", "file_search"]
          description: The type of the tool. If type is `function`, the function name must be set
        function:
          type: object
          properties:
            name:
              type: string
              description: The name of the function to call.
          required:
            - name
      required:
        - type

    RunObject:
      type: object
      title: A run on a thread
      description: Represents an execution run on a [thread](https://platform.openai.com/docs/api-reference/threads).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run`.
          type: string
          enum: ["thread.run"]
        created_at:
          description: The Unix timestamp (in seconds) for when the run was created.
          type: integer
        thread_id:
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was executed on as a part of this run.
          type: string
        assistant_id:
          description: The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for execution of this run.
          type: string
        status:
          description: The status of the run, which can be either `queued`, `in_progress`, `requires_action`, `cancelling`, `cancelled`, `failed`, `completed`, `incomplete`, or `expired`.
          type: string
          enum:
            [
              "queued",
              "in_progress",
              "requires_action",
              "cancelling",
              "cancelled",
              "failed",
              "completed",
              "incomplete",
              "expired",
            ]
        required_action:
          type: object
          description: Details on the action required to continue the run. Will be `null` if no action is required.
          nullable: true
          properties:
            type:
              description: For now, this is always `submit_tool_outputs`.
              type: string
              enum: ["submit_tool_outputs"]
            submit_tool_outputs:
              type: object
              description: Details on the tool outputs needed for this run to continue.
              properties:
                tool_calls:
                  type: array
                  description: A list of the relevant tool calls.
                  items:
                    $ref: "#/components/schemas/RunToolCallObject"
              required:
                - tool_calls
          required:
            - type
            - submit_tool_outputs
        last_error:
          type: object
          description: The last error associated with this run. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error`, `rate_limit_exceeded`, or `invalid_prompt`.
              enum: ["server_error", "rate_limit_exceeded", "invalid_prompt"]
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        expires_at:
          description: The Unix timestamp (in seconds) for when the run will expire.
          type: integer
          nullable: true
        started_at:
          description: The Unix timestamp (in seconds) for when the run was started.
          type: integer
          nullable: true
        cancelled_at:
          description: The Unix timestamp (in seconds) for when the run was cancelled.
          type: integer
          nullable: true
        failed_at:
          description: The Unix timestamp (in seconds) for when the run failed.
          type: integer
          nullable: true
        completed_at:
          description: The Unix timestamp (in seconds) for when the run was completed.
          type: integer
          nullable: true
        incomplete_details:
          description: Details on why the run is incomplete. Will be `null` if the run is not incomplete.
          type: object
          nullable: true
          properties:
            reason:
              description: The reason why the run is incomplete. This will point to which specific token limit was reached over the course of the run.
              type: string
              enum: ["max_completion_tokens", "max_prompt_tokens"]
        model:
          description: The model that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.
          type: string
        instructions:
          description: The instructions that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.
          type: string
        tools:
          description: The list of tools that the [assistant](https://platform.openai.com/docs/api-reference/assistants) used for this run.
          default: []
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        usage:
          $ref: "#/components/schemas/RunCompletionUsage"
        temperature:
          description: The sampling temperature used for this run. If not set, defaults to 1.
          type: number
          nullable: true
        top_p:
          description: The nucleus sampling value used for this run. If not set, defaults to 1.
          type: number
          nullable: true
        max_prompt_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of prompt tokens specified to have been used over the course of the run.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of completion tokens specified to have been used over the course of the run.
          minimum: 256
        truncation_strategy:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        parallel_tool_calls:
          $ref: "#/components/schemas/ParallelToolCalls"
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - id
        - object
        - created_at
        - thread_id
        - assistant_id
        - status
        - required_action
        - last_error
        - expires_at
        - started_at
        - cancelled_at
        - failed_at
        - completed_at
        - model
        - instructions
        - tools
        - metadata
        - usage
        - incomplete_details
        - max_prompt_tokens
        - max_completion_tokens
        - truncation_strategy
        - tool_choice
        - parallel_tool_calls
        - response_format
      x-code-samples:
        name: The run object
        beta: true
        example: |
          {
            "id": "run_abc123",
            "object": "thread.run",
            "created_at": 1698107661,
            "assistant_id": "asst_abc123",
            "thread_id": "thread_abc123",
            "status": "completed",
            "started_at": 1699073476,
            "expires_at": null,
            "cancelled_at": null,
            "failed_at": null,
            "completed_at": 1699073498,
            "last_error": null,
            "model": "gpt-4-turbo",
            "instructions": null,
            "tools": [{"type": "file_search"}, {"type": "code_interpreter"}],
            "metadata": {},
            "incomplete_details": null,
            "usage": {
              "prompt_tokens": 123,
              "completion_tokens": 456,
              "total_tokens": 579
            },
            "temperature": 1.0,
            "top_p": 1.0,
            "max_prompt_tokens": 1000,
            "max_completion_tokens": 1000,
            "truncation_strategy": {
              "type": "auto",
              "last_messages": null
            },
            "response_format": "auto",
            "tool_choice": "auto",
            "parallel_tool_calls": true
          }
    CreateRunRequest:
      type: object
      additionalProperties: false
      properties:
        assistant_id:
          description: The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.
          type: string
        model:
          description: The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.
          example: "gpt-4-turbo"
          anyOf:
            - type: string
            - type: string
              enum:
                [
                  "gpt-4o",
                  "gpt-4o-2024-05-13",
                  "gpt-4-turbo",
                  "gpt-4-turbo-2024-04-09",
                  "gpt-4-0125-preview",
                  "gpt-4-turbo-preview",
                  "gpt-4-1106-preview",
                  "gpt-4-vision-preview",
                  "gpt-4",
                  "gpt-4-0314",
                  "gpt-4-0613",
                  "gpt-4-32k",
                  "gpt-4-32k-0314",
                  "gpt-4-32k-0613",
                  "gpt-3.5-turbo",
                  "gpt-3.5-turbo-16k",
                  "gpt-3.5-turbo-0613",
                  "gpt-3.5-turbo-1106",
                  "gpt-3.5-turbo-0125",
                  "gpt-3.5-turbo-16k-0613",
                ]
          x-oaiTypeLabel: string
          nullable: true
        instructions:
          description: Overrides the [instructions](https://platform.openai.com/docs/api-reference/assistants/createAssistant) of the assistant. This is useful for modifying the behavior on a per-run basis.
          type: string
          nullable: true
        additional_instructions:
          description: Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.
          type: string
          nullable: true
        additional_messages:
          description: Adds additional messages to the thread before creating the run.
          type: array
          items:
            $ref: "#/components/schemas/CreateMessageRequest"
          nullable: true
        tools:
          description: Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.
          nullable: true
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
            x-oaiExpandable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *run_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *run_top_p_description
        stream:
          type: boolean
          nullable: true
          description: |
            If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.
        max_prompt_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        truncation_strategy:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        parallel_tool_calls:
          $ref: "#/components/schemas/ParallelToolCalls"
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - thread_id
        - assistant_id
    ListRunsResponse:
      type: object
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/RunObject"
        first_id:
          type: string
          example: "run_abc123"
        last_id:
          type: string
          example: "run_abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more
    ModifyRunRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
    SubmitToolOutputsRunRequest:
      type: object
      additionalProperties: false
      properties:
        tool_outputs:
          description: A list of tools for which the outputs are being submitted.
          type: array
          items:
            type: object
            properties:
              tool_call_id:
                type: string
                description: The ID of the tool call in the `required_action` object within the run object the output is being submitted for.
              output:
                type: string
                description: The output of the tool call to be submitted to continue the run.
        stream:
          type: boolean
          nullable: true
          description: |
            If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.
      required:
        - tool_outputs

    RunToolCallObject:
      type: object
      description: Tool call objects
      properties:
        id:
          type: string
          description: The ID of the tool call. This ID must be referenced when you submit the tool outputs in using the [Submit tool outputs to run](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) endpoint.
        type:
          type: string
          description: The type of tool call the output is required for. For now, this is always `function`.
          enum: ["function"]
        function:
          type: object
          description: The function definition.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments that the model expects you to pass to the function.
          required:
            - name
            - arguments
      required:
        - id
        - type
        - function

    CreateThreadAndRunRequest:
      type: object
      additionalProperties: false
      properties:
        assistant_id:
          description: The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) to use to execute this run.
          type: string
        thread:
          $ref: "#/components/schemas/CreateThreadRequest"
          description: If no thread is provided, an empty thread will be created.
        model:
          description: The ID of the [Model](https://platform.openai.com/docs/api-reference/models) to be used to execute this run. If a value is provided here, it will override the model associated with the assistant. If not, the model associated with the assistant will be used.
          example: "gpt-4-turbo"
          anyOf:
            - type: string
            - type: string
              enum:
                [
                  "gpt-4o",
                  "gpt-4o-2024-05-13",
                  "gpt-4-turbo",
                  "gpt-4-turbo-2024-04-09",
                  "gpt-4-0125-preview",
                  "gpt-4-turbo-preview",
                  "gpt-4-1106-preview",
                  "gpt-4-vision-preview",
                  "gpt-4",
                  "gpt-4-0314",
                  "gpt-4-0613",
                  "gpt-4-32k",
                  "gpt-4-32k-0314",
                  "gpt-4-32k-0613",
                  "gpt-3.5-turbo",
                  "gpt-3.5-turbo-16k",
                  "gpt-3.5-turbo-0613",
                  "gpt-3.5-turbo-1106",
                  "gpt-3.5-turbo-0125",
                  "gpt-3.5-turbo-16k-0613",
                ]
          x-oaiTypeLabel: string
          nullable: true
        instructions:
          description: Override the default system message of the assistant. This is useful for modifying the behavior on a per-run basis.
          type: string
          nullable: true
        tools:
          description: Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.
          nullable: true
          type: array
          maxItems: 20
          items:
            oneOf:
              - $ref: "#/components/schemas/AssistantToolsCode"
              - $ref: "#/components/schemas/AssistantToolsFileSearch"
              - $ref: "#/components/schemas/AssistantToolsFunction"
        tool_resources:
          type: object
          description: |
            A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        temperature:
          type: number
          minimum: 0
          maximum: 2
          default: 1
          example: 1
          nullable: true
          description: *run_temperature_description
        top_p:
          type: number
          minimum: 0
          maximum: 1
          default: 1
          example: 1
          nullable: true
          description: *run_top_p_description
        stream:
          type: boolean
          nullable: true
          description: |
            If `true`, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a `data: [DONE]` message.
        max_prompt_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of prompt tokens that may be used over the course of the run. The run will make a best effort to use only the number of prompt tokens specified, across multiple turns of the run. If the run exceeds the number of prompt tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        max_completion_tokens:
          type: integer
          nullable: true
          description: |
            The maximum number of completion tokens that may be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status `incomplete`. See `incomplete_details` for more info.
          minimum: 256
        truncation_strategy:
          $ref: "#/components/schemas/TruncationObject"
          nullable: true
        tool_choice:
          $ref: "#/components/schemas/AssistantsApiToolChoiceOption"
          nullable: true
        parallel_tool_calls:
          $ref: "#/components/schemas/ParallelToolCalls"
        response_format:
          $ref: "#/components/schemas/AssistantsApiResponseFormatOption"
          nullable: true
      required:
        - thread_id
        - assistant_id

    ThreadObject:
      type: object
      title: Thread
      description: Represents a thread that contains [messages](https://platform.openai.com/docs/api-reference/messages).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread`.
          type: string
          enum: ["thread"]
        created_at:
          description: The Unix timestamp (in seconds) for when the thread was created.
          type: integer
        tool_resources:
          type: object
          description: |
            A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      required:
        - id
        - object
        - created_at
        - tool_resources
        - metadata
      x-code-samples:
        name: The thread object
        beta: true
        example: |
          {
            "id": "thread_abc123",
            "object": "thread",
            "created_at": 1698107661,
            "metadata": {}
          }

    CreateThreadRequest:
      type: object
      additionalProperties: false
      properties:
        messages:
          description: A list of [messages](https://platform.openai.com/docs/api-reference/messages) to start the thread with.
          type: array
          items:
            $ref: "#/components/schemas/CreateMessageRequest"
        tool_resources:
          type: object
          description: |
            A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
                vector_stores:
                  type: array
                  description: |
                    A helper to create a [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) with file_ids and attach it to this thread. There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: object
                    properties:
                      file_ids:
                        type: array
                        description: |
                          A list of [file](https://platform.openai.com/docs/api-reference/files) IDs to add to the vector store. There can be a maximum of 10000 files in a vector store.
                        maxItems: 10000
                        items:
                          type: string
                      chunking_strategy:
                        # Ideally we'd reuse the chunking strategy schema here, but it doesn't expand properly
                        type: object
                        description: The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.
                        oneOf:
                          - type: object
                            title: Auto Chunking Strategy
                            description: The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `auto`.
                                enum: ["auto"]
                            required:
                              - type
                          - type: object
                            title: Static Chunking Strategy
                            additionalProperties: false
                            properties:
                              type:
                                type: string
                                description: Always `static`.
                                enum: ["static"]
                              static:
                                type: object
                                additionalProperties: false
                                properties:
                                  max_chunk_size_tokens:
                                    type: integer
                                    minimum: 100
                                    maximum: 4096
                                    description: The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`.
                                  chunk_overlap_tokens:
                                    type: integer
                                    description: |
                                      The number of tokens that overlap between chunks. The default value is `400`.

                                      Note that the overlap must not exceed half of `max_chunk_size_tokens`.
                                required:
                                  - max_chunk_size_tokens
                                  - chunk_overlap_tokens
                            required:
                              - type
                              - static
                        x-oaiExpandable: true
                      metadata:
                        type: object
                        description: |
                          Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maxium of 512 characters long.
                        x-oaiTypeLabel: map
                    x-oaiExpandable: true
              oneOf:
                - required: [vector_store_ids]
                - required: [vector_stores]
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    ModifyThreadRequest:
      type: object
      additionalProperties: false
      properties:
        tool_resources:
          type: object
          description: |
            A set of resources that are made available to the assistant's tools in this thread. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs.
          properties:
            code_interpreter:
              type: object
              properties:
                file_ids:
                  type: array
                  description: |
                    A list of [file](https://platform.openai.com/docs/api-reference/files) IDs made available to the `code_interpreter` tool. There can be a maximum of 20 files associated with the tool.
                  default: []
                  maxItems: 20
                  items:
                    type: string
            file_search:
              type: object
              properties:
                vector_store_ids:
                  type: array
                  description: |
                    The [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) attached to this thread. There can be a maximum of 1 vector store attached to the thread.
                  maxItems: 1
                  items:
                    type: string
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    DeleteThreadResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [thread.deleted]
      required:
        - id
        - object
        - deleted

    ListThreadsResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/ThreadObject"
        first_id:
          type: string
          example: "asst_abc123"
        last_id:
          type: string
          example: "asst_abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more

    MessageObject:
      type: object
      title: The message object
      description: Represents a message within a [thread](https://platform.openai.com/docs/api-reference/threads).
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.message`.
          type: string
          enum: ["thread.message"]
        created_at:
          description: The Unix timestamp (in seconds) for when the message was created.
          type: integer
        thread_id:
          description: The [thread](https://platform.openai.com/docs/api-reference/threads) ID that this message belongs to.
          type: string
        status:
          description: The status of the message, which can be either `in_progress`, `incomplete`, or `completed`.
          type: string
          enum: ["in_progress", "incomplete", "completed"]
        incomplete_details:
          description: On an incomplete message, details about why the message is incomplete.
          type: object
          properties:
            reason:
              type: string
              description: The reason the message is incomplete.
              enum:
                [
                  "content_filter",
                  "max_tokens",
                  "run_cancelled",
                  "run_expired",
                  "run_failed",
                ]
          nullable: true
          required:
            - reason
        completed_at:
          description: The Unix timestamp (in seconds) for when the message was completed.
          type: integer
          nullable: true
        incomplete_at:
          description: The Unix timestamp (in seconds) for when the message was marked as incomplete.
          type: integer
          nullable: true
        role:
          description: The entity that produced the message. One of `user` or `assistant`.
          type: string
          enum: ["user", "assistant"]
        content:
          description: The content of the message in array of text and/or images.
          type: array
          items:
            oneOf:
              - $ref: "#/components/schemas/MessageContentImageFileObject"
              - $ref: "#/components/schemas/MessageContentImageUrlObject"
              - $ref: "#/components/schemas/MessageContentTextObject"
            x-oaiExpandable: true
        assistant_id:
          description: If applicable, the ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) that authored this message.
          type: string
          nullable: true
        run_id:
          description: The ID of the [run](https://platform.openai.com/docs/api-reference/runs) associated with the creation of this message. Value is `null` when messages are created manually using the create message or create thread endpoints.
          type: string
          nullable: true
        attachments:
          type: array
          items:
            type: object
            properties:
              file_id:
                type: string
                description: The ID of the file to attach to the message.
              tools:
                description: The tools to add this file to.
                type: array
                items:
                  oneOf:
                    - $ref: "#/components/schemas/AssistantToolsCode"
                    - $ref: "#/components/schemas/AssistantToolsFileSearchTypeOnly"
                  x-oaiExpandable: true
          description: A list of files attached to the message, and the tools they were added to.
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      required:
        - id
        - object
        - created_at
        - thread_id
        - status
        - incomplete_details
        - completed_at
        - incomplete_at
        - role
        - content
        - assistant_id
        - run_id
        - attachments
        - metadata
      x-code-samples:
        name: The message object
        beta: true
        example: |
          {
            "id": "msg_abc123",
            "object": "thread.message",
            "created_at": 1698983503,
            "thread_id": "thread_abc123",
            "role": "assistant",
            "content": [
              {
                "type": "text",
                "text": {
                  "value": "Hi! How can I help you today?",
                  "annotations": []
                }
              }
            ],
            "assistant_id": "asst_abc123",
            "run_id": "run_abc123",
            "attachments": [],
            "metadata": {}
          }

    MessageDeltaObject:
      type: object
      title: Message delta object
      description: |
        Represents a message delta i.e. any changed fields on a message during streaming.
      properties:
        id:
          description: The identifier of the message, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.message.delta`.
          type: string
          enum: ["thread.message.delta"]
        delta:
          description: The delta containing the fields that have changed on the Message.
          type: object
          properties:
            role:
              description: The entity that produced the message. One of `user` or `assistant`.
              type: string
              enum: ["user", "assistant"]
            content:
              description: The content of the message in array of text and/or images.
              type: array
              items:
                oneOf:
                  - $ref: "#/components/schemas/MessageDeltaContentImageFileObject"
                  - $ref: "#/components/schemas/MessageDeltaContentTextObject"
                  - $ref: "#/components/schemas/MessageDeltaContentImageUrlObject"
                x-oaiExpandable: true
      required:
        - id
        - object
        - delta
      x-code-samples:
        name: The message delta object
        beta: true
        example: |
          {
            "id": "msg_123",
            "object": "thread.message.delta",
            "delta": {
              "content": [
                {
                  "index": 0,
                  "type": "text",
                  "text": { "value": "Hello", "annotations": [] }
                }
              ]
            }
          }

    CreateMessageRequest:
      type: object
      additionalProperties: false
      required:
        - role
        - content
      properties:
        role:
          type: string
          enum: ["user", "assistant"]
          description: |
            The role of the entity that is creating the message. Allowed values include:
            - `user`: Indicates the message is sent by an actual user and should be used in most cases to represent user-generated messages.
            - `assistant`: Indicates the message is generated by the assistant. Use this value to insert messages from the assistant into the conversation.
        content:
          oneOf:
            - type: string
              description: The text contents of the message.
              title: Text content
            - type: array
              description: An array of content parts with a defined type, each can be of type `text` or images can be passed with `image_url` or `image_file`. Image types are only supported on [Vision-compatible models](https://platform.openai.com/docs/models/overview).
              title: Array of content parts
              items:
                oneOf:
                  - $ref: "#/components/schemas/MessageContentImageFileObject"
                  - $ref: "#/components/schemas/MessageContentImageUrlObject"
                  - $ref: "#/components/schemas/MessageRequestContentTextObject"
                x-oaiExpandable: true
              minItems: 1
          x-oaiExpandable: true
        attachments:
          type: array
          items:
            type: object
            properties:
              file_id:
                type: string
                description: The ID of the file to attach to the message.
              tools:
                description: The tools to add this file to.
                type: array
                items:
                  oneOf:
                    - $ref: "#/components/schemas/AssistantToolsCode"
                    - $ref: "#/components/schemas/AssistantToolsFileSearchTypeOnly"
                  x-oaiExpandable: true
          description: A list of files attached to the message, and the tools they should be added to.
          required:
            - file_id
            - tools
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    ModifyMessageRequest:
      type: object
      additionalProperties: false
      properties:
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    DeleteMessageResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [thread.message.deleted]
      required:
        - id
        - object
        - deleted

    ListMessagesResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/MessageObject"
        first_id:
          type: string
          example: "msg_abc123"
        last_id:
          type: string
          example: "msg_abc123"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more

    MessageContentImageFileObject:
      title: Image file
      type: object
      description: References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a message.
      properties:
        type:
          description: Always `image_file`.
          type: string
          enum: ["image_file"]
        image_file:
          type: object
          properties:
            file_id:
              description: The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the message content. Set `purpose="vision"` when uploading the File if you need to later display the file content.
              type: string
            detail:
              type: string
              description: Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you can opt in to high resolution using `high`.
              enum: ["auto", "low", "high"]
              default: "auto"
          required:
            - file_id
      required:
        - type
        - image_file

    MessageDeltaContentImageFileObject:
      title: Image file
      type: object
      description: References an image [File](https://platform.openai.com/docs/api-reference/files) in the content of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `image_file`.
          type: string
          enum: ["image_file"]
        image_file:
          type: object
          properties:
            file_id:
              description: The [File](https://platform.openai.com/docs/api-reference/files) ID of the image in the message content. Set `purpose="vision"` when uploading the File if you need to later display the file content.
              type: string
            detail:
              type: string
              description: Specifies the detail level of the image if specified by the user. `low` uses fewer tokens, you can opt in to high resolution using `high`.
              enum: ["auto", "low", "high"]
              default: "auto"
      required:
        - index
        - type

    MessageContentImageUrlObject:
      title: Image URL
      type: object
      description: References an image URL in the content of a message.
      properties:
        type:
          type: string
          enum: ["image_url"]
          description: The type of the content part.
        image_url:
          type: object
          properties:
            url:
              type: string
              description: "The external URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp."
              format: uri
            detail:
              type: string
              description: Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high resolution using `high`. Default value is `auto`
              enum: ["auto", "low", "high"]
              default: "auto"
          required:
            - url
      required:
        - type
        - image_url

    MessageDeltaContentImageUrlObject:
      title: Image URL
      type: object
      description: References an image URL in the content of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `image_url`.
          type: string
          enum: ["image_url"]
        image_url:
          type: object
          properties:
            url:
              description: "The URL of the image, must be a supported image types: jpeg, jpg, png, gif, webp."
              type: string
            detail:
              type: string
              description: Specifies the detail level of the image. `low` uses fewer tokens, you can opt in to high resolution using `high`.
              enum: ["auto", "low", "high"]
              default: "auto"
      required:
        - index
        - type

    MessageContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        type:
          description: Always `text`.
          type: string
          enum: ["text"]
        text:
          type: object
          properties:
            value:
              description: The data that makes up the text.
              type: string
            annotations:
              type: array
              items:
                oneOf:
                  - $ref: "#/components/schemas/MessageContentTextAnnotationsFileCitationObject"
                  - $ref: "#/components/schemas/MessageContentTextAnnotationsFilePathObject"
                x-oaiExpandable: true
          required:
            - value
            - annotations
      required:
        - type
        - text

    MessageRequestContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        type:
          description: Always `text`.
          type: string
          enum: ["text"]
        text:
          type: string
          description: Text content to be sent to the model
      required:
        - type
        - text

    MessageContentTextAnnotationsFileCitationObject:
      title: File citation
      type: object
      description: A citation within the message that points to a specific quote from a specific File associated with the assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
      properties:
        type:
          description: Always `file_citation`.
          type: string
          enum: ["file_citation"]
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_citation:
          type: object
          properties:
            file_id:
              description: The ID of the specific File the citation is from.
              type: string
            quote:
              description: The specific quote in the file.
              type: string
          required:
            - file_id
            - quote
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - type
        - text
        - file_citation
        - start_index
        - end_index

    MessageContentTextAnnotationsFilePathObject:
      title: File path
      type: object
      description: A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a file.
      properties:
        type:
          description: Always `file_path`.
          type: string
          enum: ["file_path"]
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_path:
          type: object
          properties:
            file_id:
              description: The ID of the file that was generated.
              type: string
          required:
            - file_id
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - type
        - text
        - file_path
        - start_index
        - end_index

    MessageDeltaContentTextObject:
      title: Text
      type: object
      description: The text content that is part of a message.
      properties:
        index:
          type: integer
          description: The index of the content part in the message.
        type:
          description: Always `text`.
          type: string
          enum: ["text"]
        text:
          type: object
          properties:
            value:
              description: The data that makes up the text.
              type: string
            annotations:
              type: array
              items:
                oneOf:
                  - $ref: "#/components/schemas/MessageDeltaContentTextAnnotationsFileCitationObject"
                  - $ref: "#/components/schemas/MessageDeltaContentTextAnnotationsFilePathObject"
                x-oaiExpandable: true
      required:
        - index
        - type

    MessageDeltaContentTextAnnotationsFileCitationObject:
      title: File citation
      type: object
      description: A citation within the message that points to a specific quote from a specific File associated with the assistant or the message. Generated when the assistant uses the "file_search" tool to search files.
      properties:
        index:
          type: integer
          description: The index of the annotation in the text content part.
        type:
          description: Always `file_citation`.
          type: string
          enum: ["file_citation"]
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_citation:
          type: object
          properties:
            file_id:
              description: The ID of the specific File the citation is from.
              type: string
            quote:
              description: The specific quote in the file.
              type: string
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - index
        - type

    MessageDeltaContentTextAnnotationsFilePathObject:
      title: File path
      type: object
      description: A URL for the file that's generated when the assistant used the `code_interpreter` tool to generate a file.
      properties:
        index:
          type: integer
          description: The index of the annotation in the text content part.
        type:
          description: Always `file_path`.
          type: string
          enum: ["file_path"]
        text:
          description: The text in the message content that needs to be replaced.
          type: string
        file_path:
          type: object
          properties:
            file_id:
              description: The ID of the file that was generated.
              type: string
        start_index:
          type: integer
          minimum: 0
        end_index:
          type: integer
          minimum: 0
      required:
        - index
        - type

    RunStepObject:
      type: object
      title: Run steps
      description: |
        Represents a step in execution of a run.
      properties:
        id:
          description: The identifier of the run step, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run.step`.
          type: string
          enum: ["thread.run.step"]
        created_at:
          description: The Unix timestamp (in seconds) for when the run step was created.
          type: integer
        assistant_id:
          description: The ID of the [assistant](https://platform.openai.com/docs/api-reference/assistants) associated with the run step.
          type: string
        thread_id:
          description: The ID of the [thread](https://platform.openai.com/docs/api-reference/threads) that was run.
          type: string
        run_id:
          description: The ID of the [run](https://platform.openai.com/docs/api-reference/runs) that this run step is a part of.
          type: string
        type:
          description: The type of run step, which can be either `message_creation` or `tool_calls`.
          type: string
          enum: ["message_creation", "tool_calls"]
        status:
          description: The status of the run step, which can be either `in_progress`, `cancelled`, `failed`, `completed`, or `expired`.
          type: string
          enum: ["in_progress", "cancelled", "failed", "completed", "expired"]
        step_details:
          type: object
          description: The details of the run step.
          oneOf:
            - $ref: "#/components/schemas/RunStepDetailsMessageCreationObject"
            - $ref: "#/components/schemas/RunStepDetailsToolCallsObject"
          x-oaiExpandable: true
        last_error:
          type: object
          description: The last error associated with this run step. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error` or `rate_limit_exceeded`.
              enum: ["server_error", "rate_limit_exceeded"]
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        expired_at:
          description: The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.
          type: integer
          nullable: true
        cancelled_at:
          description: The Unix timestamp (in seconds) for when the run step was cancelled.
          type: integer
          nullable: true
        failed_at:
          description: The Unix timestamp (in seconds) for when the run step failed.
          type: integer
          nullable: true
        completed_at:
          description: The Unix timestamp (in seconds) for when the run step completed.
          type: integer
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
        usage:
          $ref: "#/components/schemas/RunStepCompletionUsage"
      required:
        - id
        - object
        - created_at
        - assistant_id
        - thread_id
        - run_id
        - type
        - status
        - step_details
        - last_error
        - expired_at
        - cancelled_at
        - failed_at
        - completed_at
        - metadata
        - usage
      x-code-samples:
        name: The run step object
        beta: true
        example: *run_step_object_example

    RunStepDeltaObject:
      type: object
      title: Run step delta object
      description: |
        Represents a run step delta i.e. any changed fields on a run step during streaming.
      properties:
        id:
          description: The identifier of the run step, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `thread.run.step.delta`.
          type: string
          enum: ["thread.run.step.delta"]
        delta:
          description: The delta containing the fields that have changed on the run step.
          type: object
          properties:
            step_details:
              type: object
              description: The details of the run step.
              oneOf:
                - $ref: "#/components/schemas/RunStepDeltaStepDetailsMessageCreationObject"
                - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsObject"
              x-oaiExpandable: true
      required:
        - id
        - object
        - delta
      x-code-samples:
        name: The run step delta object
        beta: true
        example: |
          {
            "id": "step_123",
            "object": "thread.run.step.delta",
            "delta": {
              "step_details": {
                "type": "tool_calls",
                "tool_calls": [
                  {
                    "index": 0,
                    "id": "call_123",
                    "type": "code_interpreter",
                    "code_interpreter": { "input": "", "outputs": [] }
                  }
                ]
              }
            }
          }

    ListRunStepsResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/RunStepObject"
        first_id:
          type: string
          example: "step_abc123"
        last_id:
          type: string
          example: "step_abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more

    RunStepDetailsMessageCreationObject:
      title: Message creation
      type: object
      description: Details of the message creation by the run step.
      properties:
        type:
          description: Always `message_creation`.
          type: string
          enum: ["message_creation"]
        message_creation:
          type: object
          properties:
            message_id:
              type: string
              description: The ID of the message that was created by this run step.
          required:
            - message_id
      required:
        - type
        - message_creation

    RunStepDeltaStepDetailsMessageCreationObject:
      title: Message creation
      type: object
      description: Details of the message creation by the run step.
      properties:
        type:
          description: Always `message_creation`.
          type: string
          enum: ["message_creation"]
        message_creation:
          type: object
          properties:
            message_id:
              type: string
              description: The ID of the message that was created by this run step.
      required:
        - type

    RunStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum: ["tool_calls"]
        tool_calls:
          type: array
          description: |
            An array of tool calls the run step was involved in. These can be associated with one of three types of tools: `code_interpreter`, `file_search`, or `function`.
          items:
            oneOf:
              - $ref: "#/components/schemas/RunStepDetailsToolCallsCodeObject"
              - $ref: "#/components/schemas/RunStepDetailsToolCallsFileSearchObject"
              - $ref: "#/components/schemas/RunStepDetailsToolCallsFunctionObject"
            x-oaiExpandable: true
      required:
        - type
        - tool_calls

    RunStepDeltaStepDetailsToolCallsObject:
      title: Tool calls
      type: object
      description: Details of the tool call.
      properties:
        type:
          description: Always `tool_calls`.
          type: string
          enum: ["tool_calls"]
        tool_calls:
          type: array
          description: |
            An array of tool calls the run step was involved in. These can be associated with one of three types of tools: `code_interpreter`, `file_search`, or `function`.
          items:
            oneOf:
              - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeObject"
              - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsFileSearchObject"
              - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsFunctionObject"
            x-oaiExpandable: true
      required:
        - type

    RunStepDetailsToolCallsCodeObject:
      title: Code Interpreter tool call
      type: object
      description: Details of the Code Interpreter tool call the run step was involved in.
      properties:
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
          enum: ["code_interpreter"]
        code_interpreter:
          type: object
          description: The Code Interpreter tool call definition.
          required:
            - input
            - outputs
          properties:
            input:
              type: string
              description: The input to the Code Interpreter tool call.
            outputs:
              type: array
              description: The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (`logs`) or images (`image`). Each of these are represented by a different object type.
              items:
                type: object
                oneOf:
                  - $ref: "#/components/schemas/RunStepDetailsToolCallsCodeOutputLogsObject"
                  - $ref: "#/components/schemas/RunStepDetailsToolCallsCodeOutputImageObject"
                x-oaiExpandable: true
      required:
        - id
        - type
        - code_interpreter

    RunStepDeltaStepDetailsToolCallsCodeObject:
      title: Code interpreter tool call
      type: object
      description: Details of the Code Interpreter tool call the run step was involved in.
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call.
        type:
          type: string
          description: The type of tool call. This is always going to be `code_interpreter` for this type of tool call.
          enum: ["code_interpreter"]
        code_interpreter:
          type: object
          description: The Code Interpreter tool call definition.
          properties:
            input:
              type: string
              description: The input to the Code Interpreter tool call.
            outputs:
              type: array
              description: The outputs from the Code Interpreter tool call. Code Interpreter can output one or more items, including text (`logs`) or images (`image`). Each of these are represented by a different object type.
              items:
                type: object
                oneOf:
                  - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject"
                  - $ref: "#/components/schemas/RunStepDeltaStepDetailsToolCallsCodeOutputImageObject"
                x-oaiExpandable: true
      required:
        - index
        - type

    RunStepDetailsToolCallsCodeOutputLogsObject:
      title: Code Interpreter log output
      type: object
      description: Text output from the Code Interpreter tool call as part of a run step.
      properties:
        type:
          description: Always `logs`.
          type: string
          enum: ["logs"]
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - type
        - logs

    RunStepDeltaStepDetailsToolCallsCodeOutputLogsObject:
      title: Code interpreter log output
      type: object
      description: Text output from the Code Interpreter tool call as part of a run step.
      properties:
        index:
          type: integer
          description: The index of the output in the outputs array.
        type:
          description: Always `logs`.
          type: string
          enum: ["logs"]
        logs:
          type: string
          description: The text output from the Code Interpreter tool call.
      required:
        - index
        - type

    RunStepDetailsToolCallsCodeOutputImageObject:
      title: Code Interpreter image output
      type: object
      properties:
        type:
          description: Always `image`.
          type: string
          enum: ["image"]
        image:
          type: object
          properties:
            file_id:
              description: The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.
              type: string
          required:
            - file_id
      required:
        - type
        - image

    RunStepDeltaStepDetailsToolCallsCodeOutputImageObject:
      title: Code interpreter image output
      type: object
      properties:
        index:
          type: integer
          description: The index of the output in the outputs array.
        type:
          description: Always `image`.
          type: string
          enum: ["image"]
        image:
          type: object
          properties:
            file_id:
              description: The [file](https://platform.openai.com/docs/api-reference/files) ID of the image.
              type: string
      required:
        - index
        - type

    RunStepDetailsToolCallsFileSearchObject:
      title: File search tool call
      type: object
      properties:
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `file_search` for this type of tool call.
          enum: ["file_search"]
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
      required:
        - id
        - type
        - file_search

    RunStepDeltaStepDetailsToolCallsFileSearchObject:
      title: File search tool call
      type: object
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `file_search` for this type of tool call.
          enum: ["file_search"]
        file_search:
          type: object
          description: For now, this is always going to be an empty object.
          x-oaiTypeLabel: map
      required:
        - index
        - type
        - file_search

    RunStepDetailsToolCallsFunctionObject:
      type: object
      title: Function tool call
      properties:
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `function` for this type of tool call.
          enum: ["function"]
        function:
          type: object
          description: The definition of the function that was called.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments passed to the function.
            output:
              type: string
              description: The output of the function. This will be `null` if the outputs have not been [submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.
              nullable: true
          required:
            - name
            - arguments
            - output
      required:
        - id
        - type
        - function

    RunStepDeltaStepDetailsToolCallsFunctionObject:
      type: object
      title: Function tool call
      properties:
        index:
          type: integer
          description: The index of the tool call in the tool calls array.
        id:
          type: string
          description: The ID of the tool call object.
        type:
          type: string
          description: The type of tool call. This is always going to be `function` for this type of tool call.
          enum: ["function"]
        function:
          type: object
          description: The definition of the function that was called.
          properties:
            name:
              type: string
              description: The name of the function.
            arguments:
              type: string
              description: The arguments passed to the function.
            output:
              type: string
              description: The output of the function. This will be `null` if the outputs have not been [submitted](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs) yet.
              nullable: true
      required:
        - index
        - type

    VectorStoreExpirationAfter:
      type: object
      title: Vector store expiration policy
      description: The expiration policy for a vector store.
      properties:
        anchor:
          description: "Anchor timestamp after which the expiration policy applies. Supported anchors: `last_active_at`."
          type: string
          enum: ["last_active_at"]
        days:
          description: The number of days after the anchor time that the vector store will expire.
          type: integer
          minimum: 1
          maximum: 365
      required:
        - anchor
        - days

    VectorStoreObject:
      type: object
      title: Vector store
      description: A vector store is a collection of processed files can be used by the `file_search` tool.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store`.
          type: string
          enum: ["vector_store"]
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store was created.
          type: integer
        name:
          description: The name of the vector store.
          type: string
        usage_bytes:
          description: The total number of bytes used by the files in the vector store.
          type: integer
        file_counts:
          type: object
          properties:
            in_progress:
              description: The number of files that are currently being processed.
              type: integer
            completed:
              description: The number of files that have been successfully processed.
              type: integer
            failed:
              description: The number of files that have failed to process.
              type: integer
            cancelled:
              description: The number of files that were cancelled.
              type: integer
            total:
              description: The total number of files.
              type: integer
          required:
            - in_progress
            - completed
            - failed
            - cancelled
            - total
        status:
          description: The status of the vector store, which can be either `expired`, `in_progress`, or `completed`. A status of `completed` indicates that the vector store is ready for use.
          type: string
          enum: ["expired", "in_progress", "completed"]
        expires_after:
          $ref: "#/components/schemas/VectorStoreExpirationAfter"
        expires_at:
          description: The Unix timestamp (in seconds) for when the vector store will expire.
          type: integer
          nullable: true
        last_active_at:
          description: The Unix timestamp (in seconds) for when the vector store was last active.
          type: integer
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - status
        - last_active_at
        - name
        - file_counts
        - metadata
      x-code-samples:
        name: The vector store object
        beta: true
        example: |
          {
            "id": "vs_123",
            "object": "vector_store",
            "created_at": 1698107661,
            "usage_bytes": 123456,
            "last_active_at": 1698107661,
            "name": "my_vector_store",
            "status": "completed",
            "file_counts": {
              "in_progress": 0,
              "completed": 100,
              "cancelled": 0,
              "failed": 0,
              "total": 100
            },
            "metadata": {},
            "last_used_at": 1698107661
          }

    CreateVectorStoreRequest:
      type: object
      additionalProperties: false
      properties:
        file_ids:
          description: A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store should use. Useful for tools like `file_search` that can access files.
          type: array
          maxItems: 500
          items:
            type: string
        name:
          description: The name of the vector store.
          type: string
        expires_after:
          $ref: "#/components/schemas/VectorStoreExpirationAfter"
        chunking_strategy:
          type: object
          description: The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy. Only applicable if `file_ids` is non-empty.
          oneOf:
            - $ref: "#/components/schemas/AutoChunkingStrategyRequestParam"
            - $ref: "#/components/schemas/StaticChunkingStrategyRequestParam"
          x-oaiExpandable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    UpdateVectorStoreRequest:
      type: object
      additionalProperties: false
      properties:
        name:
          description: The name of the vector store.
          type: string
          nullable: true
        expires_after:
          $ref: "#/components/schemas/VectorStoreExpirationAfter"
          nullable: true
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true

    ListVectorStoresResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/VectorStoreObject"
        first_id:
          type: string
          example: "vs_abc123"
        last_id:
          type: string
          example: "vs_abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more

    DeleteVectorStoreResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [vector_store.deleted]
      required:
        - id
        - object
        - deleted

    VectorStoreFileObject:
      type: object
      title: Vector store files
      description: A list of files attached to a vector store.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store.file`.
          type: string
          enum: ["vector_store.file"]
        usage_bytes:
          description: The total vector store usage in bytes. Note that this may be different from the original file size.
          type: integer
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store file was created.
          type: integer
        vector_store_id:
          description: The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.
          type: string
        status:
          description: The status of the vector store file, which can be either `in_progress`, `completed`, `cancelled`, or `failed`. The status `completed` indicates that the vector store file is ready for use.
          type: string
          enum: ["in_progress", "completed", "cancelled", "failed"]
        last_error:
          type: object
          description: The last error associated with this vector store file. Will be `null` if there are no errors.
          nullable: true
          properties:
            code:
              type: string
              description: One of `server_error` or `rate_limit_exceeded`.
              enum:
                [
                  "internal_error",
                  "file_not_found",
                  "parsing_error",
                  "unhandled_mime_type",
                ]
            message:
              type: string
              description: A human-readable description of the error.
          required:
            - code
            - message
        chunking_strategy:
          type: object
          description: The strategy used to chunk the file.
          oneOf:
            - $ref: "#/components/schemas/StaticChunkingStrategyResponseParam"
            - $ref: "#/components/schemas/OtherChunkingStrategyResponseParam"
          x-oaiExpandable: true
      required:
        - id
        - object
        - usage_bytes
        - created_at
        - vector_store_id
        - status
        - last_error
      x-code-samples:
        name: The vector store file object
        beta: true
        example: |
          {
            "id": "file-abc123",
            "object": "vector_store.file",
            "usage_bytes": 1234,
            "created_at": 1698107661,
            "vector_store_id": "vs_abc123",
            "status": "completed",
            "last_error": null,
            "chunking_strategy": {
              "type": "static",
              "static": {
                "max_chunk_size_tokens": 800,
                "chunk_overlap_tokens": 400
              }
            }
          }

    OtherChunkingStrategyResponseParam:
      type: object
      title: Other Chunking Strategy
      description: This is returned when the chunking strategy is unknown. Typically, this is because the file was indexed before the `chunking_strategy` concept was introduced in the API.
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `other`.
          enum: ["other"]
      required:
        - type

    StaticChunkingStrategyResponseParam:
      type: object
      title: Static Chunking Strategy
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `static`.
          enum: ["static"]
        static:
          $ref: "#/components/schemas/StaticChunkingStrategy"
      required:
        - type
        - static

    StaticChunkingStrategy:
      type: object
      additionalProperties: false
      properties:
        max_chunk_size_tokens:
          type: integer
          minimum: 100
          maximum: 4096
          description: The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`.
        chunk_overlap_tokens:
          type: integer
          description: |
            The number of tokens that overlap between chunks. The default value is `400`.

            Note that the overlap must not exceed half of `max_chunk_size_tokens`.
      required:
        - max_chunk_size_tokens
        - chunk_overlap_tokens

    AutoChunkingStrategyRequestParam:
      type: object
      title: Auto Chunking Strategy
      description: The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`.
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `auto`.
          enum: ["auto"]
      required:
        - type

    StaticChunkingStrategyRequestParam:
      type: object
      title: Static Chunking Strategy
      additionalProperties: false
      properties:
        type:
          type: string
          description: Always `static`.
          enum: ["static"]
        static:
          $ref: "#/components/schemas/StaticChunkingStrategy"
      required:
        - type
        - static

    ChunkingStrategyRequestParam:
      type: object
      description: The chunking strategy used to chunk the file(s). If not set, will use the `auto` strategy.
      oneOf:
        - $ref: "#/components/schemas/AutoChunkingStrategyRequestParam"
        - $ref: "#/components/schemas/StaticChunkingStrategyRequestParam"
      x-oaiExpandable: true

    CreateVectorStoreFileRequest:
      type: object
      additionalProperties: false
      properties:
        file_id:
          description: A [File](https://platform.openai.com/docs/api-reference/files) ID that the vector store should use. Useful for tools like `file_search` that can access files.
          type: string
        chunking_strategy:
          $ref: "#/components/schemas/ChunkingStrategyRequestParam"
      required:
        - file_id

    ListVectorStoreFilesResponse:
      properties:
        object:
          type: string
          example: "list"
        data:
          type: array
          items:
            $ref: "#/components/schemas/VectorStoreFileObject"
        first_id:
          type: string
          example: "file-abc123"
        last_id:
          type: string
          example: "file-abc456"
        has_more:
          type: boolean
          example: false
      required:
        - object
        - data
        - first_id
        - last_id
        - has_more

    DeleteVectorStoreFileResponse:
      type: object
      properties:
        id:
          type: string
        deleted:
          type: boolean
        object:
          type: string
          enum: [vector_store.file.deleted]
      required:
        - id
        - object
        - deleted

    VectorStoreFileBatchObject:
      type: object
      title: Vector store file batch
      description: A batch of files attached to a vector store.
      properties:
        id:
          description: The identifier, which can be referenced in API endpoints.
          type: string
        object:
          description: The object type, which is always `vector_store.file_batch`.
          type: string
          enum: ["vector_store.files_batch"]
        created_at:
          description: The Unix timestamp (in seconds) for when the vector store files batch was created.
          type: integer
        vector_store_id:
          description: The ID of the [vector store](https://platform.openai.com/docs/api-reference/vector-stores/object) that the [File](https://platform.openai.com/docs/api-reference/files) is attached to.
          type: string
        status:
          description: The status of the vector store files batch, which can be either `in_progress`, `completed`, `cancelled` or `failed`.
          type: string
          enum: ["in_progress", "completed", "cancelled", "failed"]
        file_counts:
          type: object
          properties:
            in_progress:
              description: The number of files that are currently being processed.
              type: integer
            completed:
              description: The number of files that have been processed.
              type: integer
            failed:
              description: The number of files that have failed to process.
              type: integer
            cancelled:
              description: The number of files that where cancelled.
              type: integer
            total:
              description: The total number of files.
              type: integer
          required:
            - in_progress
            - completed
            - cancelled
            - failed
            - total
      required:
        - id
        - object
        - created_at
        - vector_store_id
        - status
        - file_counts
      x-code-samples:
        name: The vector store files batch object
        beta: true
        example: |
          {
            "id": "vsfb_123",
            "object": "vector_store.files_batch",
            "created_at": 1698107661,
            "vector_store_id": "vs_abc123",
            "status": "completed",
            "file_counts": {
              "in_progress": 0,
              "completed": 100,
              "failed": 0,
              "cancelled": 0,
              "total": 100
            }
          }

    CreateVectorStoreFileBatchRequest:
      type: object
      additionalProperties: false
      properties:
        file_ids:
          description: A list of [File](https://platform.openai.com/docs/api-reference/files) IDs that the vector store should use. Useful for tools like `file_search` that can access files.
          type: array
          minItems: 1
          maxItems: 500
          items:
            type: string
        chunking_strategy:
          $ref: "#/components/schemas/ChunkingStrategyRequestParam"
      required:
        - file_ids

    AssistantStreamEvent:
      description: |
        Represents an event emitted when streaming a Run.

        Each event in a server-sent events stream has an `event` and `data` property:

        ```
        event: thread.created
        data: {"id": "thread_123", "object": "thread", ...}
        ```

        We emit events whenever a new object is created, transitions to a new state, or is being
        streamed in parts (deltas). For example, we emit `thread.run.created` when a new run
        is created, `thread.run.completed` when a run completes, and so on. When an Assistant chooses
        to create a message during a run, we emit a `thread.message.created event`, a
        `thread.message.in_progress` event, many `thread.message.delta` events, and finally a
        `thread.message.completed` event.

        We may add additional events over time, so we recommend handling unknown events gracefully
        in your code. See the [Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn how to
        integrate the Assistants API with streaming.
      oneOf:
        - $ref: "#/components/schemas/ThreadStreamEvent"
        - $ref: "#/components/schemas/RunStreamEvent"
        - $ref: "#/components/schemas/RunStepStreamEvent"
        - $ref: "#/components/schemas/MessageStreamEvent"
        - $ref: "#/components/schemas/ErrorEvent"
        - $ref: "#/components/schemas/DoneEvent"
      x-code-samples:
        name: Assistant stream events
        beta: true

    ThreadStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.created"]
            data:
              $ref: "#/components/schemas/ThreadObject"
          required:
            - event
            - data
          description: Occurs when a new [thread](https://platform.openai.com/docs/api-reference/threads/object) is created.
          x-code-samples:
            dataDescription: "`data` is a [thread](https://platform.openai.com/docs/api-reference/threads/object)"

    RunStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.created"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a new [run](https://platform.openai.com/docs/api-reference/runs/object) is created.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.queued"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `queued` status.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.in_progress"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to an `in_progress` status.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.requires_action"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `requires_action` status.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.completed"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is completed.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.incomplete"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) ends with status `incomplete`.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.failed"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) fails.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.cancelling"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) moves to a `cancelling` status.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.cancelled"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) is cancelled.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.expired"]
            data:
              $ref: "#/components/schemas/RunObject"
          required:
            - event
            - data
          description: Occurs when a [run](https://platform.openai.com/docs/api-reference/runs/object) expires.
          x-code-samples:
            dataDescription: "`data` is a [run](https://platform.openai.com/docs/api-reference/runs/object)"

    RunStepStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.created"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) is created.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.in_progress"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) moves to an `in_progress` state.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.delta"]
            data:
              $ref: "#/components/schemas/RunStepDeltaObject"
          required:
            - event
            - data
          description: Occurs when parts of a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) are being streamed.
          x-code-samples:
            dataDescription: "`data` is a [run step delta](https://platform.openai.com/docs/api-reference/assistants-streaming/run-step-delta-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.completed"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) is completed.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.failed"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) fails.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.cancelled"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) is cancelled.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.run.step.expired"]
            data:
              $ref: "#/components/schemas/RunStepObject"
          required:
            - event
            - data
          description: Occurs when a [run step](https://platform.openai.com/docs/api-reference/runs/step-object) expires.
          x-code-samples:
            dataDescription: "`data` is a [run step](https://platform.openai.com/docs/api-reference/runs/step-object)"

    MessageStreamEvent:
      oneOf:
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.message.created"]
            data:
              $ref: "#/components/schemas/MessageObject"
          required:
            - event
            - data
          description: Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is created.
          x-code-samples:
            dataDescription: "`data` is a [message](https://platform.openai.com/docs/api-reference/messages/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.message.in_progress"]
            data:
              $ref: "#/components/schemas/MessageObject"
          required:
            - event
            - data
          description: Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) moves to an `in_progress` state.
          x-code-samples:
            dataDescription: "`data` is a [message](https://platform.openai.com/docs/api-reference/messages/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.message.delta"]
            data:
              $ref: "#/components/schemas/MessageDeltaObject"
          required:
            - event
            - data
          description: Occurs when parts of a [Message](https://platform.openai.com/docs/api-reference/messages/object) are being streamed.
          x-code-samples:
            dataDescription: "`data` is a [message delta](https://platform.openai.com/docs/api-reference/assistants-streaming/message-delta-object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.message.completed"]
            data:
              $ref: "#/components/schemas/MessageObject"
          required:
            - event
            - data
          description: Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) is completed.
          x-code-samples:
            dataDescription: "`data` is a [message](https://platform.openai.com/docs/api-reference/messages/object)"
        - type: object
          properties:
            event:
              type: string
              enum: ["thread.message.incomplete"]
            data:
              $ref: "#/components/schemas/MessageObject"
          required:
            - event
            - data
          description: Occurs when a [message](https://platform.openai.com/docs/api-reference/messages/object) ends before it is completed.
          x-code-samples:
            dataDescription: "`data` is a [message](https://platform.openai.com/docs/api-reference/messages/object)"

    ErrorEvent:
      type: object
      properties:
        event:
          type: string
          enum: ["error"]
        data:
          $ref: "#/components/schemas/Error"
      required:
        - event
        - data
      description: Occurs when an [error](https://platform.openai.com/docs/guides/error-codes/api-errors) occurs. This can happen due to an internal server error or a timeout.
      x-code-samples:
        dataDescription: "`data` is an [error](https://platform.openai.com/docs/guides/error-codes/api-errors)"

    DoneEvent:
      type: object
      properties:
        event:
          type: string
          enum: ["done"]
        data:
          type: string
          enum: ["[DONE]"]
      required:
        - event
        - data
      description: Occurs when a stream ends.
      x-code-samples:
        dataDescription: "`data` is `[DONE]`"

    Batch:
      type: object
      properties:
        id:
          type: string
        object:
          type: string
          enum: [batch]
          description: The object type, which is always `batch`.
        endpoint:
          type: string
          description: The Portkey API endpoint used by the batch.

        errors:
          type: object
          properties:
            object:
              type: string
              description: The object type, which is always `list`.
            data:
              type: array
              items:
                type: object
                properties:
                  code:
                    type: string
                    description: An error code identifying the error type.
                  message:
                    type: string
                    description: A human-readable message providing more details about the error.
                  param:
                    type: string
                    description: The name of the parameter that caused the error, if applicable.
                    nullable: true
                  line:
                    type: integer
                    description: The line number of the input file where the error occurred, if applicable.
                    nullable: true
        input_file_id:
          type: string
          description: The ID of the input file for the batch.
        completion_window:
          type: string
          description: The time frame within which the batch should be processed.
        status:
          type: string
          description: The current status of the batch.
          enum:
            - validating
            - failed
            - in_progress
            - finalizing
            - completed
            - expired
            - cancelling
            - cancelled
        output_file_id:
          type: string
          description: The ID of the file containing the outputs of successfully executed requests.
        error_file_id:
          type: string
          description: The ID of the file containing the outputs of requests with errors.
        created_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was created.
        in_progress_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started processing.
        expires_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch will expire.
        finalizing_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started finalizing.
        completed_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was completed.
        failed_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch failed.
        expired_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch expired.
        cancelling_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch started cancelling.
        cancelled_at:
          type: integer
          description: The Unix timestamp (in seconds) for when the batch was cancelled.
        request_counts:
          type: object
          properties:
            total:
              type: integer
              description: Total number of requests in the batch.
            completed:
              type: integer
              description: Number of requests that have been completed successfully.
            failed:
              type: integer
              description: Number of requests that have failed.
          required:
            - total
            - completed
            - failed
          description: The request counts for different statuses within the batch.
        metadata:
          description: *metadata_description
          type: object
          x-oaiTypeLabel: map
          nullable: true
      required:
        - id
        - object
        - endpoint
        - input_file_id
        - completion_window
        - status
        - created_at

    BatchRequestInput:
      type: object
      description: The per-line object of the batch input file
      properties:
        custom_id:
          type: string
          description: A developer-provided per-request id that will be used to match outputs to inputs. Must be unique for each request in a batch.
        method:
          type: string
          enum: ["POST"]
          description: The HTTP method to be used for the request. Currently only `POST` is supported.
        url:
          type: string
          description: The Portkey API relative URL to be used for the request. Currently `/v1/chat/completions`, `/v1/embeddings`, and `/v1/completions` are supported.
      x-code-samples:
        name: The request input object
        example: |
          {"custom_id": "request-1", "method": "POST", "url": "/v1/chat/completions", "body": {"model": "gpt-3.5-turbo", "messages": [{"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "What is 2+2?"}]}}

    BatchRequestOutput:
      type: object
      description: The per-line object of the batch output and error files
      properties:
        id:
          type: string
        custom_id:
          type: string
          description: A developer-provided per-request id that will be used to match outputs to inputs.
        response:
          type: object
          nullable: true
          properties:
            status_code:
              type: integer
              description: The HTTP status code of the response
            request_id:
              type: string
              description: An unique identifier for the provider API request. Please include this request ID when contacting your provider support.
            body:
              type: object
              x-oaiTypeLabel: map
              description: The JSON body of the response
        error:
          type: object
          nullable: true
          description: For requests that failed with a non-HTTP error, this will contain more information on the cause of the failure.
          properties:
            code:
              type: string
              description: A machine-readable error code.
            message:
              type: string
              description: A human-readable error message.
      x-code-samples:
        name: The request output object
        example: |
          {"id": "batch_req_wnaDys", "custom_id": "request-2", "response": {"status_code": 200, "request_id": "req_c187b3", "body": {"id": "chatcmpl-9758Iw", "object": "chat.completion", "created": 1711475054, "model": "gpt-3.5-turbo", "choices": [{"index": 0, "message": {"role": "assistant", "content": "2 + 2 equals 4."}, "finish_reason": "stop"}], "usage": {"prompt_tokens": 24, "completion_tokens": 15, "total_tokens": 39}, "system_fingerprint": null}}, "error": null}

    ListBatchesResponse:
      type: object
      properties:
        data:
          type: array
          items:
            $ref: "#/components/schemas/Batch"
        first_id:
          type: string
          example: "batch_abc123"
        last_id:
          type: string
          example: "batch_abc456"
        has_more:
          type: boolean
        object:
          type: string
          enum: [list]
      required:
        - object
        - data
        - has_more

    FeedbackRequest:
      type: object
      required:
        - trace_id
        - value
      properties:
        trace_id:
          type: string
          description: Unique identifier for the request trace.
        value:
          type: integer
          description: Feedback value, an integer between -10 and 10.
          minimum: -10
          maximum: 10
        weight:
          type: number
          format: float
          description: Weight of the feedback, a float between 0 and 1. Default is 1.0.
          minimum: 0
          maximum: 1
          default: 1.0
        metadata:
          type: object
          additionalProperties: true
          description: Additional metadata for the feedback.

    FeedbackResponse:
      type: object
      properties:
        status:
          type: string
          description: success or failure
        message:
          type: string
          description: Confirmation message indicating successful feedback submission.
        feedback_ids:
          type: array
          description: Ids of Feedbacks created returned in the same order as input
          items:
            type: string

    FeedbackUpdateRequest:
      type: object
      required:
        - value
      properties:
        value:
          type: integer
          description: Feedback value, an integer between -10 and 10.
          minimum: -10
          maximum: 10
        weight:
          type: number
          format: float
          description: Weight of the feedback, a float between 0 and 1. Default is 1.0.
          minimum: 0
          maximum: 1
          default: 1.0
        metadata:
          type: object
          additionalProperties: true
          description: Additional metadata for the feedback.

    RateLimits:
      type: object
      properties:
        type:
          type: string
          enum: ["requests"]
        unit:
          type: string
          enum: ["rpm"]
        value:
          type: integer
    UsageLimits:
      type: object
      properties:
        credit_limit:
          type: integer
          description: Credit Limit. Used for tracking usage
          minimum: 1
          default: null
        alert_threshold:
          type: integer
          description: Alert Threshold. Used for alerting when usage reaches more than this
          minimum: 1
          default: null
        periodic_reset:
          type: string
          description: Reset the usage periodically.
          enum: ["monthly"]
      example:
        credit_limit: 10
        periodic_reset: monthly
        alert_threshold: 8

    VirtualKeys:
      type: object
      properties:
        name:
          type: string
          example: "Open AI Workspace"
        note:
          type: string
          nullable: true
          example: "randomness"
        status:
          type: string
          enum: [active, exhausted]
        usage_limits:
          $ref: "#/components/schemas/UsageLimits"
        reset_usage:
          type: number
          nullable: true
          example: 0
        created_at:
          type: string
          format: date-time
        slug:
          type: string
        model_config:
          type: object
        rate_limits:
          type: array
          items:
            $ref: "#/components/schemas/RateLimits"
          nullable: true
        object:
          type: string
          enum: [virtual-key]

    Invite:
      type: object
      properties:
        object:
          type: string
          example: invite
        id:
          type: string
          format: uuid
        email:
          type: string
          format: email
        role:
          type: string
          enum:
            - admin
            - member
        created_at:
          type: string
          format: date-time
        expires_at:
          type: string
          format: date-time
        accepted_at:
          type: string
          format: date-time
        status:
          type: string
          enum:
            - pending
            - cancelled
            - accepted
            - expired
        invited_by:
          type: string
          format: uuid
    InviteList:
      type: object
      properties:
        object:
          type: string
          enum:
            - list
        total:
          type: integer
        data:
          type: array
          items:
            $ref: "#/components/schemas/Invite"

    User:
      type: object
      properties:
        object:
          type: string
          enum:
            - user
        id:
          type: string
          format: uuid
        first_name:
          type: string
        last_name:
          type: string
        role:
          type: string
          enum:
            - admin
            - member
            - owner
        email:
          type: string
          format: email
        created_at:
          type: string
          format: date-time
        last_updated_at:
          type: string
          format: date-time
        workspace_ids:
          type: array

          items:
            type: string
    UserList:
      type: object
      properties:
        total:
          type: integer
          example: 2
        object:
          type: string
          enum:
            - list
        data:
          type: array
          items:
            $ref: "#/components/schemas/User"

    WorkspaceMember:
      type: object
      properties:
        object:
          type: string
          example: workspace-user
          enum:
            - workspace-user
        id:
          type: string
          format: uuid
          example: 25afb7bd-f98a-11ee-85fe-0e27d7367987
        first_name:
          type: string
          example: John
        last_name:
          type: string
          example: Doe
        org_role:
          type: string
          example: member
          enum:
            - admin
            - member
            - owner
        role:
          type: string
          example: member
          enum:
            - admin
            - member
            - manager
        created_at:
          type: string
          example: 2024-01-01T00:00:00.000Z
          format: date-time
        last_updated_at:
          type: string
          example: 2024-01-01T00:00:00.000Z
          format: date-time
        status:
          type: string
          example: active
          enum:
            - active
    WorkspaceMemberList:
      type: object
      properties:
        total:
          type: integer
          example: 2
        object:
          type: string
          example: list
          enum:
            - list
        data:
          type: array
          items:
            $ref: "#/components/schemas/WorkspaceMember"

    Workspace:
      type: object
      properties:
        id:
          type: string
          example: ws-test-a-174eb1
        slug:
          type: string
          example: ws-test-a-174eb1
        name:
          type: string
          example: New Workspace
        description:
          type: string
          nullable: true
          example: null
        created_at:
          type: string
          format: date-time
          example: 2024-07-30T13:27:29.000Z
        last_updated_at:
          type: string
          format: date-time
          example: 2024-07-30T13:27:29.000Z
        defaults:
          type: object
          nullable: true
          properties:
            metadata:
              type: object
              additionalProperties:
                type: string
              example:
                foo: bar
            is_default:
              type: integer
              example: 0
            object:
              type: string
              enum:
                - workspace

    WorkspaceList:
      type: object
      properties:
        total:
          type: integer
          example: 2
        object:
          type: string
          enum:
            - list
        data:
          type: array
          items:
            $ref: "#/components/schemas/Workspace"

    WorkspaceWithUsers:
      type: object
      properties:
        id:
          type: string
          example: ws-test-a-174eb1
        slug:
          type: string
          example: ws-test-a-174eb1
        name:
          type: string
          example: New Workspace
        description:
          type: string
          nullable: true
          example: null
        created_at:
          type: string
          format: date-time
          example: 2024-07-30T13:27:29.000Z
        last_updated_at:
          type: string
          format: date-time
          example: 2024-07-30T13:27:29.000Z
        defaults:
          type: object
          nullable: true
          properties:
            metadata:
              type: object
              additionalProperties:
                type: string
              example:
                foo: bar
            is_default:
              type: integer
              example: 0
            object:
              type: string
              enum:
                - workspace
        users:
          type: array
          items:
            type: object
            $ref: "#/components/schemas/WorkspaceMember"

    CustomLog:
      type: object
      properties:
        request:
          type: object
          properties:
            url:
              type: string
            method:
              type: string
            headers:
              type: object
              additionalProperties:
                type: string
            body:
              type: object
          required:
            - url
            - body
        response:
          type: object
          properties:
            status:
              type: integer
            headers:
              type: object
              additionalProperties:
                type: string
            body:
              type: object
            response_time:
              type: integer
          required:
            - body
        metadata:
          type: object
          properties:
            trace_id:
              type: string
            span_id:
              type: string
            span_name:
              type: string
            additionalProperties:
              type: string
      required:
        - request
        - response

    ExportListResponse:
      type: object
      properties:
        object:
          type: string
          enum: [list]
        total:
          type: integer
        data:
          type: array
          items:
            $ref: "#/components/schemas/ExportItem"
    ExportItem:
      type: object
      properties:
        id:
          type: string
          format: uuid
        organisation_id:
          type: string
          format: uuid
        filters:
          $ref: "#/components/schemas/GenerationsFilterSchema"
        requested_data:
          $ref: "#/components/schemas/LogExportsRequestedData"
        status:
          type: string
          enum:
            - draft
            - in_progress
            - success
            - failed
            - stopped
        description:
          type: string
        created_at:
          type: string
          format: date-time
        last_updated_at:
          type: string
          format: date-time
        created_by:
          type: string
          format: uuid
        workspace_id:
          type: string
          format: uuid
        object:
          type: string
          enum: [export]
      required:
        - id
        - organisation_id
        - filters
        - requested_data
        - status
        - description
        - created_at
        - last_updated_at
        - created_by
        - workspace_id
        - object
    UpdateExportResponse:
      type: object
      properties:
        id:
          type: string
          format: uuid
          description: The unique identifier of the updated export
        total:
          type: integer
          description: The total number of items in the export
        object:
          type: string
          enum: [export]
          description: The type of the object
      required:
        - id
        - total
        - object
    ExportTaskResponse:
      type: object
      properties:
        message:
          type: string
          description: A message indicating the status of the export task
        object:
          type: string
          enum: [export]
          description: The type of the object
      required:
        - message
        - object
    DownloadLogsResponse:
      type: object
      properties:
        signed_url:
          type: string
          format: uri
          description: A pre-signed URL for downloading the exported logs
      required:
        - signed_url
    GenerationsFilterSchema:
      type: object
      properties:
        time_of_generation_min:
          type: string
          format: date-time
        time_of_generation_max:
          type: string
          format: date-time
        total_units_min:
          type: integer
        total_units_max:
          type: integer
        cost_min:
          type: number
        cost_max:
          type: number
        ai_model:
          type: string
        prompt_token_min:
          type: integer
        prompt_token_max:
          type: integer
        completion_token_min:
          type: integer
        completion_token_max:
          type: integer
        status_code:
          type: string
        metadata:
          type: object
          additionalProperties: true
        ai_org_model:
          type: string
          example: "openai__gpt-3.5-turbo, anthropic__claude-2.1"
        weighted_feedback_min:
          type: number
        weighted_feedback_max:
          type: number
        virtual_keys:
          type: string
        trace_id:
          type: string
        configs:
          type: string
        workspace_slug:
          type: string
        prompt_slug:
          type: string

    LogExportsRequestedData:
      type: array
      items:
        type: string
        enum:
          - id
          - trace_id
          - created_at
          - request
          - response
          - is_success
          - ai_org
          - ai_model
          - req_units
          - res_units
          - total_units
          - request_url
          - cost
          - cost_currency
          - response_time
          - response_status_code
          - mode
          - config
          - prompt_slug
          - metadata

    ApiKeyObject:
      type: object
      properties:
        id:
          type: string
          format: uuid
          example: "f47ac10b-58cc-4372-a567-0e02b2c3d479"
        key:
          type: string
          example: "Xk*******S4"
        name:
          type: string
          example: "Development API Key"
        description:
          type: string
          example: "API key for development environment"
        type:
          type: string
          enum: ["organisation-service", "workspace-service", "workspace-user"]
          example: "organisation-service"
        organisation_id:
          type: string
          format: uuid
          example: "a1b2c3d4-e5f6-4a5b-8c7d-9e0f1a2b3c4d"
        workspace_id:
          type: string
          example: "ws-myworkspace"
        user_id:
          type: string
          format: uuid
          example: "c3d4e5f6-a7b8-6c7d-0e1f-2a3b4c5d6e7f"
        status:
          type: string
          enum: ["active", "exhausted"]
          example: "active"
        created_at:
          type: string
          format: date-time
          example: "2023-09-15T10:30:00Z"
        last_updated_at:
          type: string
          format: date-time
          example: "2023-09-15T10:30:00Z"
        creation_mode:
          type: string
          enum: ["ui", "api", "auto"]
          example: "ui"
        rate_limits:
          type: array
          items:
            type: object
            properties:
              type:
                type: string
                example: "requests"
              unit:
                type: string
                example: "rpm"
              value:
                type: integer
                example: 100
        usage_limits:
          $ref: "#/components/schemas/UsageLimits"
        reset_usage:
          type: number
          example: 0
        scopes:
          type: array
          items:
            type: string
          example: ["completions.write"]
        defaults:
          type: object
          properties:
            metadata:
              type: object
              additionalProperties: true
              example:
                environment: "development"
                team: "backend"
            config_id:
              type: string
              example: config-abc
        alert_emails:
          type: array
          items:
            type: string
            format: email
            example: "foo@bar.com"
        object:
          type: string
          enum: ["api-key"]
          example: "api-key"

    ApiKeyObjectList:
      type: object
      properties:
        total:
          type: integer
          example: 2
        object:
          type: string
          enum:
            - list
        data:
          type: array
          items:
            $ref: "#/components/schemas/ApiKeyObject"

    CreateApiKeyObject:
      type: object
      properties:
        name:
          type: string
          example: "Development API Key"
        description:
          type: string
          example: "API key for development environment"
        workspace_id:
          type: string
          example: "ws-myworkspace"
        user_id:
          type: string
          format: uuid
          example: "c3d4e5f6-a7b8-6c7d-0e1f-2a3b4c5d6e7f"
        rate_limits:
          type: array
          items:
            type: object
            properties:
              type:
                type: string
                example: "requests"
              unit:
                type: string
                example: "rpm"
              value:
                type: integer
                example: 100
        usage_limits:
          $ref: "#/components/schemas/UsageLimits"
        scopes:
          type: array
          items:
            type: string
          example: ["completions.write"]
        defaults:
          type: object
          properties:
            metadata:
              type: object
              additionalProperties: true
              example:
                environment: "development"
                team: "backend"
            config_id:
              type: string
              example: config-abc
        alert_emails:
          type: array
          items:
            type: string
            format: email
            example: "foo@bar.com"

    UpdateApiKeyObject:
      type: object
      properties:
        name:
          type: string
          example: "Development API Key"
        description:
          type: string
          example: "API key for development environment"
        rate_limits:
          type: array
          items:
            type: object
            properties:
              type:
                type: string
                example: "requests"
              unit:
                type: string
                example: "rpm"
              value:
                type: integer
                example: 100
        usage_limits:
          $ref: "#/components/schemas/UsageLimits"
        scopes:
          type: array
          items:
            type: string
          example: ["completions.write"]
        defaults:
          type: object
          properties:
            metadata:
              type: object
              additionalProperties: true
              example:
                environment: "development"
                team: "backend"
            config_id:
              type: string
              example: config-abc
        alert_emails:
          type: array
          items:
            type: string
            format: email
            example: "foo@bar.com"

    PromptRenderResponse:
      type: object
      required:
        - success
        - data
      properties:
        success:
          type: boolean
          description: Indicates if the render was successful
        data:
          oneOf:
            - title: Chat Completions
              $ref: "#/components/schemas/CreateChatCompletionRequest"
            - title: Completions
              $ref: "#/components/schemas/CreateCompletionRequest"

    BedrockBatchJob:
      type: object
      required:
        - model
        - role_arn
      properties:
        job_name:
          type: string
          description: Job name for the batch job
        output_data_config:
          type: string
          description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
        model:
          type: string
          description: Model to start batch job with
        role_arn:
          type: string
          description: Role ARN for the bedrock batch job
      allOf:
        - $ref: "#/components/schemas/OpenAIBatchJob"
      description: Gateway supported body params for bedrock fine-tuning.
      title: Bedrock Params
    BedrockBatchParams:
      type: object
      properties:
        role_arn:
          type: string
          description: Role ARN for the bedrock batch job
    CommonBatchParams:
      type: object
      required:
        - model
      properties:
        job_name:
          type: string
          description: Job name for the batch job
        output_data_config:
          type: string
          description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
        model:
          type: string
          description: Model to start batch job with

    OpenAIBatchJob:
      type: object
      required:
        - input_file_id
        - completion_window
        - endpoint
      properties:
        input_file_id:
          type: string
          description: The input file to use for the batch job
        completion_window:
          type: string
          enum:
            - immediate
            - 24h
          description: Completion window for the batch job, `immediate` is only supported with Portkey Managed Batching.
        endpoint:
          type: string
          enum:
            - /v1/chat/completions
            - /v1/completions
            - /v1/embeddings
          description: Inference endpoint
        metadata:
          description: metadata related for the batch job
          nullable: true
      description: Gateway supported body params for OpenAI, Azure OpenAI and VertexAI.
      title: OpenAI Params

    PortkeyBatchJob:
      type: object
      required:
        - model
      properties:
        job_name:
          type: string
          description: Job name for the batch job
        output_data_config:
          type: string
          description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
        model:
          type: string
          description: Model to start batch job with
        role_arn:
          type: string
          description: Role ARN for the bedrock batch job
        portkey_options:
          allOf:
            - $ref: "#/components/schemas/PortkeyBatchOptions"
          description: Portkey Gateway Provider specific headers to be passed to the provider, if portkey is used as a provider
        provider_options:
          anyOf:
            - type: object
              title: Bedrock Options
              properties:
                job_name:
                  type: string
                  description: Job name for the batch job
                output_data_config:
                  type: string
                  description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
                model:
                  type: string
                  description: Model to start batch job with
                role_arn:
                  type: string
                  description: Role ARN for the bedrock batch job
              required:
                - model
                - role_arn
            - type: object
              title: Vertex Options
              properties:
                job_name:
                  type: string
                  description: Job name for the batch job
                output_data_config:
                  type: string
                  description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
                model:
                  type: string
                  description: Model to start batch job with
              required:
                - model
          description: Provider specific options to be passed to the provider, optional can be passed directly as well.
      allOf:
        - $ref: "#/components/schemas/OpenAIBatchJob"
      description: Gateway supported body params for portkey managed batching.
      title: Portkey Params

    PortkeyBatchOptions:
      type: object
      required:
        - x-portkey-virtual-key
      properties:
        x-portkey-virtual-key:
          type: string
          description: The virtual key to communicate with the provider
        x-portkey-aws-s3-bucket:
          type: string
          description: The AWS S3 bucket to use for file upload during finetune
        x-portkey-vertex-storage-bucket-name:
          type: string
          description: Google Storage bucket to use for file upload during finetune
        x-portkey-provider-model:
          type: string
          description: Model to use for the batch job also for file transformation for model specific inference input.
      example:
        x-portkey-virtual-key: vkey-1234567890
        x-portkey-aws-s3-bucket: my-bucket
        x-portkey-provider-model: meta.llama3-1-8b-instruct-v1:0
        x-portkey-vertex-storage-bucket-name: my-bucket
      description: Options to be passed to the provider, supports all options supported by the provider from gateway.

    VertexBatchJob:
      type: object
      required:
        - model
      properties:
        job_name:
          type: string
          description: Job name for the batch job
        output_data_config:
          type: string
          description: Batch job's output storage location, will be constructed based on `input_file_id` if not provided
        model:
          type: string
          description: Model to start batch job with
      allOf:
        - $ref: "#/components/schemas/OpenAIBatchJob"
      description: Gateway supported body params for Vertext fine-tuning.
      title: Vertex Params
    VertexBatchParams:
      type: object
    ResponseFormatJsonObject:
      type: object
      title: JSON object
      description: |
        JSON object response format. An older method of generating JSON responses.

        Using `json_schema` is recommended for models that support it. Note that the model will not generate JSON without a system or user message instructing it to do so.
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `json_object`.
          enum:
            - json_object
      required:
        - type
    ResponseFormatJsonSchema:
      type: object
      title: JSON schema
      description: |
        JSON Schema response format. Used to generate structured JSON responses.
        Learn more about [Structured Outputs](/integrations/llms/openai/structured-outputs).
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `json_schema`.
          enum:
            - json_schema
        json_schema:
          type: object
          title: JSON schema
          description: |
            Structured Outputs configuration options, including a JSON Schema.
          properties:
            description:
              type: string
              description: |
                A description of what the response format is for, used by the
                model to determine how to respond in the format.
            name:
              type: string
              description: |
                The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64.
            schema:
              $ref: "#/components/schemas/ResponseFormatJsonSchemaSchema"
            strict:
              type: boolean
              nullable: true
              default: false
              description: |
                Whether to enable strict schema adherence when generating the
                output. If set to true, the model will always follow the exact schema
                defined in the `schema` field. Only a subset of JSON Schema is supported
                when `strict` is `true`.
          required:
            - name
      required:
        - type
        - json_schema
    ResponseFormatJsonSchemaSchema:
      type: object
      title: JSON schema
      description: |
        The schema for the response format, described as a JSON Schema object.
        Learn how to build JSON schemas [here](https://json-schema.org/).
      additionalProperties: true
    ResponseFormatText:
      type: object
      title: Text
      description: |
        Default response format. Used to generate text responses.
      properties:
        type:
          type: string
          description: The type of response format being defined. Always `text`.
          enum:
            - text
      required:
        - type

security:
  - Portkey-Key: []

x-code-samples:
  navigationGroups:
    - id: endpoints
      title: Endpoints
    - id: assistants
      title: Assistants
    - id: legacy
      title: Legacy
  groups:
    # > General Notes
    # The `groups` section is used to generate the API reference pages and navigation, in the same
    # order listed below. Additionally, each `group` can have a list of `sections`, each of which
    # will become a navigation subroute and subsection under the group. Each section has:
    #  - `type`: Currently, either an `endpoint` or `object`, depending on how the section needs to
    #            be rendered
    #  - `key`: The reference key that can be used to lookup the section definition
    #  - `path`: The path (url) of the section, which is used to generate the navigation link.
    #
    # > The `object` sections maps to a schema component and the following fields are read for rendering
    # - `x-oaiMeta.name`: The name of the object, which will become the section title
    # - `x-oaiMeta.example`: The example object, which will be used to generate the example sample (always JSON)
    # - `description`: The description of the object, which will be used to generate the section description
    #
    # > The `endpoint` section maps to an operation path and the following fields are read for rendering:
    # - `x-oaiMeta.name`: The name of the endpoint, which will become the section title
    # - `x-oaiMeta.examples`: The endpoint examples, which can be an object (meaning a single variation, most
    #                         endpoints, or an array of objects, meaning multiple variations, e.g. the
    #                         chat completion and completion endpoints, with streamed and non-streamed examples.
    # - `x-oaiMeta.returns`: text describing what the endpoint returns.
    # - `summary`: The summary of the endpoint, which will be used to generate the section description
    - id: audio
      title: Audio
      description: |
        Learn how to turn audio into text or text into audio.

        Related guide: [Speech to text](https://platform.openai.com/docs/guides/speech-to-text)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createSpeech
          path: createSpeech
        - type: endpoint
          key: createTranscription
          path: createTranscription
        - type: endpoint
          key: createTranslation
          path: createTranslation
        - type: object
          key: CreateTranscriptionResponseJson
          path: json-object
        - type: object
          key: CreateTranscriptionResponseVerboseJson
          path: verbose-json-object
    - id: chat
      title: Chat
      description: |
        Given a list of messages comprising a conversation, the model will return a response.

        Related guide: [Chat Completions](https://platform.openai.com/docs/guides/text-generation)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createChatCompletion
          path: create
        - type: object
          key: CreateChatCompletionResponse
          path: object
        - type: object
          key: CreateChatCompletionStreamResponse
          path: streaming
    - id: embeddings
      title: Embeddings
      description: |
        Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.

        Related guide: [Embeddings](https://platform.openai.com/docs/guides/embeddings)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createEmbedding
          path: create
        - type: object
          key: Embedding
          path: object
    - id: fine-tuning
      title: Fine-tuning
      description: |
        Manage fine-tuning jobs to tailor a model to your specific training data.

        Related guide: [Fine-tune models](https://platform.openai.com/docs/guides/fine-tuning)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createFineTuningJob
          path: create
        - type: endpoint
          key: listPaginatedFineTuningJobs
          path: list
        - type: endpoint
          key: listFineTuningEvents
          path: list-events
        - type: endpoint
          key: listFineTuningJobCheckpoints
          path: list-checkpoints
        - type: endpoint
          key: retrieveFineTuningJob
          path: retrieve
        - type: endpoint
          key: cancelFineTuningJob
          path: cancel
        - type: object
          key: FinetuneChatRequestInput
          path: chat-input
        - type: object
          key: FinetuneCompletionRequestInput
          path: completions-input
        - type: object
          key: FineTuningJob
          path: object
        - type: object
          key: FineTuningJobEvent
          path: event-object
        - type: object
          key: FineTuningJobCheckpoint
          path: checkpoint-object
    - id: batch
      title: Batch
      description: |
        Create large batches of API requests for asynchronous processing. The Batch API returns completions within 24 hours for a 50% discount.

        Related guide: [Batch](https://platform.openai.com/docs/guides/batch)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createBatch
          path: create
        - type: endpoint
          key: retrieveBatch
          path: retrieve
        - type: endpoint
          key: cancelBatch
          path: cancel
        - type: endpoint
          key: listBatches
          path: list
        - type: object
          key: Batch
          path: object
        - type: object
          key: BatchRequestInput
          path: request-input
        - type: object
          key: BatchRequestOutput
          path: request-output
    - id: files
      title: Files
      description: |
        Files are used to upload documents that can be used with features like [Assistants](https://platform.openai.com/docs/api-reference/assistants), [Fine-tuning](https://platform.openai.com/docs/api-reference/fine-tuning), and [Batch API](https://platform.openai.com/docs/guides/batch).
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createFile
          path: create
        - type: endpoint
          key: listFiles
          path: list
        - type: endpoint
          key: retrieveFile
          path: retrieve
        - type: endpoint
          key: deleteFile
          path: delete
        - type: endpoint
          key: downloadFile
          path: retrieve-contents
        - type: object
          key: OpenAIFile
          path: object
    - id: images
      title: Images
      description: |
        Given a prompt and/or an input image, the model will generate a new image.

        Related guide: [Image generation](https://platform.openai.com/docs/guides/images)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createImage
          path: create
        - type: endpoint
          key: createImageEdit
          path: createEdit
        - type: endpoint
          key: createImageVariation
          path: createVariation
        - type: object
          key: Image
          path: object
    - id: models
      title: Models
      description: |
        List and describe the various models available in the API. You can refer to the [Models](https://platform.openai.com/docs/models) documentation to understand what models are available and the differences between them.
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: listModels
          path: list
        - type: endpoint
          key: retrieveModel
          path: retrieve
        - type: endpoint
          key: deleteModel
          path: delete
        - type: object
          key: Model
          path: object
    - id: moderations
      title: Moderations
      description: |
        Given some input text, outputs if the model classifies it as potentially harmful across several categories.

        Related guide: [Moderations](https://platform.openai.com/docs/guides/moderation)
      navigationGroup: endpoints
      sections:
        - type: endpoint
          key: createModeration
          path: create
        - type: object
          key: CreateModerationResponse
          path: object
    - id: assistants
      title: Assistants
      beta: true
      description: |
        Build assistants that can call models and use tools to perform tasks.

        [Get started with the Assistants API](https://platform.openai.com/docs/assistants)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createAssistant
          path: createAssistant
        - type: endpoint
          key: listAssistants
          path: listAssistants
        - type: endpoint
          key: getAssistant
          path: getAssistant
        - type: endpoint
          key: modifyAssistant
          path: modifyAssistant
        - type: endpoint
          key: deleteAssistant
          path: deleteAssistant
        - type: object
          key: AssistantObject
          path: object
    - id: threads
      title: Threads
      beta: true
      description: |
        Create threads that assistants can interact with.

        Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createThread
          path: createThread
        - type: endpoint
          key: getThread
          path: getThread
        - type: endpoint
          key: modifyThread
          path: modifyThread
        - type: endpoint
          key: deleteThread
          path: deleteThread
        - type: object
          key: ThreadObject
          path: object
    - id: messages
      title: Messages
      beta: true
      description: |
        Create messages within threads

        Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createMessage
          path: createMessage
        - type: endpoint
          key: listMessages
          path: listMessages
        - type: endpoint
          key: getMessage
          path: getMessage
        - type: endpoint
          key: modifyMessage
          path: modifyMessage
        - type: endpoint
          key: deleteMessage
          path: deleteMessage
        - type: object
          key: MessageObject
          path: object
    - id: runs
      title: Runs
      beta: true
      description: |
        Represents an execution run on a thread.

        Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createRun
          path: createRun
        - type: endpoint
          key: createThreadAndRun
          path: createThreadAndRun
        - type: endpoint
          key: listRuns
          path: listRuns
        - type: endpoint
          key: getRun
          path: getRun
        - type: endpoint
          key: modifyRun
          path: modifyRun
        - type: endpoint
          key: submitToolOuputsToRun
          path: submitToolOutputs
        - type: endpoint
          key: cancelRun
          path: cancelRun
        - type: object
          key: RunObject
          path: object
    - id: run-steps
      title: Run Steps
      beta: true
      description: |
        Represents the steps (model and tool calls) taken during the run.

        Related guide: [Assistants](https://platform.openai.com/docs/assistants/overview)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: listRunSteps
          path: listRunSteps
        - type: endpoint
          key: getRunStep
          path: getRunStep
        - type: object
          key: RunStepObject
          path: step-object
    - id: vector-stores
      title: Vector Stores
      beta: true
      description: |
        Vector stores are used to store files for use by the `file_search` tool.

        Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createVectorStore
          path: create
        - type: endpoint
          key: listVectorStores
          path: list
        - type: endpoint
          key: getVectorStore
          path: retrieve
        - type: endpoint
          key: modifyVectorStore
          path: modify
        - type: endpoint
          key: deleteVectorStore
          path: delete
        - type: object
          key: VectorStoreObject
          path: object
    - id: vector-stores-files
      title: Vector Store Files
      beta: true
      description: |
        Vector store files represent files inside a vector store.

        Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createVectorStoreFile
          path: createFile
        - type: endpoint
          key: listVectorStoreFiles
          path: listFiles
        - type: endpoint
          key: getVectorStoreFile
          path: getFile
        - type: endpoint
          key: deleteVectorStoreFile
          path: deleteFile
        - type: object
          key: VectorStoreFileObject
          path: file-object
    - id: vector-stores-file-batches
      title: Vector Store File Batches
      beta: true
      description: |
        Vector store file batches represent operations to add multiple files to a vector store.

        Related guide: [File Search](https://platform.openai.com/docs/assistants/tools/file-search)
      navigationGroup: assistants
      sections:
        - type: endpoint
          key: createVectorStoreFileBatch
          path: createBatch
        - type: endpoint
          key: getVectorStoreFileBatch
          path: getBatch
        - type: endpoint
          key: cancelVectorStoreFileBatch
          path: cancelBatch
        - type: endpoint
          key: listFilesInVectorStoreBatch
          path: listBatchFiles
        - type: object
          key: VectorStoreFileBatchObject
          path: batch-object
    - id: assistants-streaming
      title: Streaming
      beta: true
      description: |
        Stream the result of executing a Run or resuming a Run after submitting tool outputs.

        You can stream events from the [Create Thread and Run](https://platform.openai.com/docs/api-reference/runs/createThreadAndRun),
        [Create Run](https://platform.openai.com/docs/api-reference/runs/createRun), and [Submit Tool Outputs](https://platform.openai.com/docs/api-reference/runs/submitToolOutputs)
        endpoints by passing `"stream": true`. The response will be a [Server-Sent events](https://html.spec.whatwg.org/multipage/server-sent-events.html#server-sent-events) stream.

        Our Node and Python SDKs provide helpful utilities to make streaming easy. Reference the
        [Assistants API quickstart](https://platform.openai.com/docs/assistants/overview) to learn more.
      navigationGroup: assistants
      sections:
        - type: object
          key: MessageDeltaObject
          path: message-delta-object
        - type: object
          key: RunStepDeltaObject
          path: run-step-delta-object
        - type: object
          key: AssistantStreamEvent
          path: events
    - id: completions
      title: Completions
      legacy: true
      navigationGroup: legacy
      description: |
        Given a prompt, the model will return one or more predicted completions along with the probabilities of alternative tokens at each position. Most developer should use our [Chat Completions API](https://platform.openai.com/docs/guides/text-generation/text-generation-models) to leverage our best and newest models.
      sections:
        - type: endpoint
          key: createCompletion
          path: create
        - type: object
          key: CreateCompletionResponse
          path: object