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fix: rename variables in lambda (#1586)
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,89 +1,53 @@ | ||
| # AWS CSharp LangServe Example | ||
|
|
||
| ## Installation | ||
| This example demonstrates how to use deploy a simple app using Pulumi in CSharp. | ||
|
|
||
| Install the LangChain CLI if you haven't yet | ||
| ## Prerequisites | ||
|
|
||
| ```bash | ||
| pip install -U langchain-cli | ||
| ``` | ||
| To run this example, you'll need the following tools installed on your machine: | ||
|
|
||
| ## Adding packages | ||
|
|
||
| ```bash | ||
| # adding packages from | ||
| # https://github.com/langchain-ai/langchain/tree/master/templates | ||
| langchain app add $PROJECT_NAME | ||
|
|
||
| # adding custom GitHub repo packages | ||
| langchain app add --repo $OWNER/$REPO | ||
| # or with whole git string (supports other git providers): | ||
| # langchain app add git+https://github.com/hwchase17/chain-of-verification | ||
|
|
||
| # with a custom api mount point (defaults to `/{package_name}`) | ||
| langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag | ||
| ``` | ||
| 1. [Install .NET Core](https://dotnet.microsoft.com/en-us/download) | ||
| 2. [Install Pulumi](https://www.pulumi.com/docs/install/) | ||
| 3. [Configure AWS](https://www.pulumi.com/docs/intro/cloud-providers/aws/setup/) | ||
| 4. [Install Docker](https://docs.docker.com/get-docker/) | ||
| 5. [Install the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) | ||
| 6. [Install the LangChain CLI](https://python.langchain.com/docs/langserve#installation) | ||
|
|
||
| Note: you remove packages by their api path | ||
|
|
||
| ```bash | ||
| langchain app remove my/custom/path/rag | ||
| ``` | ||
|
|
||
| ## Setup LangSmith (Optional) | ||
| LangSmith will help us trace, monitor and debug LangChain applications. | ||
| LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/). | ||
| If you don't have access, you can skip this section | ||
|
|
||
|
|
||
| ```shell | ||
| export LANGCHAIN_TRACING_V2=true | ||
| export LANGCHAIN_API_KEY=<your-api-key> | ||
| export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default" | ||
| ``` | ||
|
|
||
| ## Launch LangServe | ||
|
|
||
| ```bash | ||
| langchain serve | ||
| ``` | ||
|
|
||
| ## Deploying to AWS | ||
| ## Deploying to AWS using Pulumi | ||
|
|
||
| Run the following command to deploy your LangServe app to AWS: | ||
|
|
||
| ```bash | ||
| git clone https://github.com/pulumi/examples.git | ||
| cd examples/aws-cs-langserve | ||
| pulumi stack init <your-stack-name> | ||
| pulumi config set open-api-key --secret # Enter your OpenAI API key | ||
| pulumi up | ||
| ``` | ||
|
|
||
| This will output the URL of your LangServe app. You can use this URL to make requests to your app. | ||
| This last command will show you a preview of the resources that will be created. After reviewing the changes, you will be prompted to continue. Once confirmed, Pulumi will deploy your LangServe app to AWS. | ||
|
|
||
| ## Running in Docker | ||
| The whole deployoment process will take a couple of minutes. Once it's done, you will see the URL of your LangServe app in the output. | ||
|
|
||
| This project folder includes a Dockerfile that allows you to easily build and host your LangServe app. | ||
|
|
||
| ### Building the Image | ||
|
|
||
| To build the image, you simply: | ||
| ```bash | ||
| Outputs: | ||
| url: "http://<dns>.elb.amazonaws.com" | ||
|
|
||
| ```shell | ||
| docker build . -t my-langserve-app | ||
| Resources: | ||
| + 27 created | ||
| ``` | ||
|
|
||
| If you tag your image with something other than `my-langserve-app`, | ||
| note it for use in the next step. | ||
| You can now access the LangServe playground by adding `/openai/playground` to the URL you got from the output. | ||
|
|
||
| ### Running the Image Locally | ||
| > [!NOTE] | ||
| > It may take a few minutes for the load balancer to be ready to accept requests. If you see a 503 error, wait a few minutes and try again. | ||
| To run the image, you'll need to include any environment variables | ||
| necessary for your application. | ||
| ## Clean up | ||
|
|
||
| In the below example, we inject the `OPENAI_API_KEY` environment | ||
| variable with the value set in my local environment | ||
| (`$OPENAI_API_KEY`) | ||
| To clean up the resources created by this example, run the following command: | ||
|
|
||
| We also expose port 8080 with the `-p 8080:8080` option. | ||
|
|
||
| ```shell | ||
| docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app | ||
| ```bash | ||
| pulumi destroy | ||
| ``` | ||
|
|
||
| You will be prompted to confirm the deletion of the resources. Once confirmed, Pulumi will delete all the resources created by this example. |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,89 +1,53 @@ | ||
| # AWS Go LangServe Example | ||
|
|
||
| ## Installation | ||
| This example demonstrates how to use deploy a simple app using Pulumi in Go. | ||
|
|
||
| Install the LangChain CLI if you haven't yet | ||
| ## Prerequisites | ||
|
|
||
| ```bash | ||
| pip install -U langchain-cli | ||
| ``` | ||
| To run this example, you'll need the following tools installed on your machine: | ||
|
|
||
| ## Adding packages | ||
|
|
||
| ```bash | ||
| # adding packages from | ||
| # https://github.com/langchain-ai/langchain/tree/master/templates | ||
| langchain app add $PROJECT_NAME | ||
|
|
||
| # adding custom GitHub repo packages | ||
| langchain app add --repo $OWNER/$REPO | ||
| # or with whole git string (supports other git providers): | ||
| # langchain app add git+https://github.com/hwchase17/chain-of-verification | ||
|
|
||
| # with a custom api mount point (defaults to `/{package_name}`) | ||
| langchain app add $PROJECT_NAME --api_path=/my/custom/path/rag | ||
| ``` | ||
| 1. [Install Go](https://golang.org/doc/install) | ||
| 2. [Install Pulumi](https://www.pulumi.com/docs/install/) | ||
| 3. [Configure AWS](https://www.pulumi.com/docs/intro/cloud-providers/aws/setup/) | ||
| 4. [Install Docker](https://docs.docker.com/get-docker/) | ||
| 5. [Install the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) | ||
| 6. [Install the LangChain CLI](https://python.langchain.com/docs/langserve#installation) | ||
|
|
||
| Note: you remove packages by their api path | ||
|
|
||
| ```bash | ||
| langchain app remove my/custom/path/rag | ||
| ``` | ||
|
|
||
| ## Setup LangSmith (Optional) | ||
| LangSmith will help us trace, monitor and debug LangChain applications. | ||
| LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/). | ||
| If you don't have access, you can skip this section | ||
|
|
||
|
|
||
| ```shell | ||
| export LANGCHAIN_TRACING_V2=true | ||
| export LANGCHAIN_API_KEY=<your-api-key> | ||
| export LANGCHAIN_PROJECT=<your-project> # if not specified, defaults to "default" | ||
| ``` | ||
|
|
||
| ## Launch LangServe | ||
|
|
||
| ```bash | ||
| langchain serve | ||
| ``` | ||
|
|
||
| ## Deploying to AWS | ||
| ## Deploying to AWS using Pulumi | ||
|
|
||
| Run the following command to deploy your LangServe app to AWS: | ||
|
|
||
| ```bash | ||
| git clone https://github.com/pulumi/examples.git | ||
| cd examples/aws-go-langserve | ||
| pulumi stack init <your-stack-name> | ||
| pulumi config set open-api-key --secret # Enter your OpenAI API key | ||
| pulumi up | ||
| ``` | ||
|
|
||
| This will output the URL of your LangServe app. You can use this URL to make requests to your app. | ||
| This last command will show you a preview of the resources that will be created. After reviewing the changes, you will be prompted to continue. Once confirmed, Pulumi will deploy your LangServe app to AWS. | ||
|
|
||
| ## Running in Docker | ||
| The whole deployoment process will take a couple of minutes. Once it's done, you will see the URL of your LangServe app in the output. | ||
|
|
||
| This project folder includes a Dockerfile that allows you to easily build and host your LangServe app. | ||
|
|
||
| ### Building the Image | ||
|
|
||
| To build the image, you simply: | ||
| ```bash | ||
| Outputs: | ||
| url: "http://<dns>.elb.amazonaws.com" | ||
|
|
||
| ```shell | ||
| docker build . -t my-langserve-app | ||
| Resources: | ||
| + 27 created | ||
| ``` | ||
|
|
||
| If you tag your image with something other than `my-langserve-app`, | ||
| note it for use in the next step. | ||
| You can now access the LangServe playground by adding `/openai/playground` to the URL you got from the output. | ||
|
|
||
| ### Running the Image Locally | ||
| > [!NOTE] | ||
| > It may take a few minutes for the load balancer to be ready to accept requests. If you see a 503 error, wait a few minutes and try again. | ||
| To run the image, you'll need to include any environment variables | ||
| necessary for your application. | ||
| ## Clean up | ||
|
|
||
| In the below example, we inject the `OPENAI_API_KEY` environment | ||
| variable with the value set in my local environment | ||
| (`$OPENAI_API_KEY`) | ||
| To clean up the resources created by this example, run the following command: | ||
|
|
||
| We also expose port 8080 with the `-p 8080:8080` option. | ||
|
|
||
| ```shell | ||
| docker run -e OPENAI_API_KEY=$OPENAI_API_KEY -p 8080:8080 my-langserve-app | ||
| ```bash | ||
| pulumi destroy | ||
| ``` | ||
|
|
||
| You will be prompted to confirm the deletion of the resources. Once confirmed, Pulumi will delete all the resources created by this example. |
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Learn more about bidirectional Unicode characters
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