Rename Deployment NVP to DeploymentID

For consistency between the constructor NVP and the property name. This does
not break existing code, because the constructor NVP has partial matching.

Author: ccreutzi

+llms/+utils/errorMessageCatalog.m

@@ -45,7 +45,7 @@
 catalog("llms:removeFromEmptyHistory") = "Unable to remove message from empty message history.";
 catalog("llms:stopSequencesMustHaveMax4Elements") = "Number of stop sequences must be less than or equal to 4.";
 catalog("llms:endpointMustBeSpecified") = "Unable to find endpoint. Either set environment variable AZURE_OPENAI_ENDPOINT or specify name-value argument ""Endpoint"".";
-catalog("llms:deploymentMustBeSpecified") = "Unable to find deployment name. Either set environment variable AZURE_OPENAI_DEPLOYMENT or specify name-value argument ""Deployment"".";
+catalog("llms:deploymentMustBeSpecified") = "Unable to find deployment name. Either set environment variable AZURE_OPENAI_DEPLOYMENT or specify name-value argument ""DeploymentID"".";
 catalog("llms:keyMustBeSpecified") = "Unable to find API key. Either set environment variable {1} or specify name-value argument ""APIKey"".";
 catalog("llms:mustHaveMessages") = "Message history must not be empty.";
 catalog("llms:mustSetFunctionsForCall") = "When no functions are defined, ToolChoice must not be specified.";

azureChat.m

@@ -15,7 +15,7 @@
 %                             interface. Needs to be specified or stored in the
 %                             environment variable AZURE_OPENAI_ENDPOINT.
 %
-%   Deployment              - The deployment as defined in the Azure OpenAI Services
+%   DeploymentID            - The deployment as defined in the Azure OpenAI Services
 %                             interface. Needs to be specified or stored in the
 %                             environment variable AZURE_OPENAI_DEPLOYMENT.
 %
@@ -103,7 +103,7 @@
             arguments
                 systemPrompt                       {llms.utils.mustBeTextOrEmpty} = []
                 nvp.Endpoint                 (1,1) string {mustBeNonzeroLengthTextScalar}
-                nvp.Deployment               (1,1) string {mustBeNonzeroLengthTextScalar}
+                nvp.DeploymentID             (1,1) string {mustBeNonzeroLengthTextScalar}
                 nvp.APIKey                         {mustBeNonzeroLengthTextScalar}
                 nvp.Tools                    (1,:) {mustBeA(nvp.Tools, "openAIFunction")} = openAIFunction.empty
                 nvp.APIVersion               (1,1) string {mustBeAPIVersion} = "2024-06-01"
@@ -394,8 +394,8 @@ function mustBeAPIVersion(model)
 end
 
 function deployment = getDeployment(nvp)
-    if isfield(nvp, "Deployment")
-        deployment = nvp.Deployment;
+    if isfield(nvp, "DeploymentID")
+        deployment = nvp.DeploymentID;
     else
         if isenv("AZURE_OPENAI_DEPLOYMENT")
             deployment = getenv("AZURE_OPENAI_DEPLOYMENT");

doc/Azure.md

@@ -31,7 +31,7 @@ loadenv(".env")
 
 ## Establishing a connection to Chat Completions API using Azure
 
-To connect MATLAB® to Chat Completions API via Azure, you will have to create an `azureChat` object. See [the Azure documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart) for details on the setup required and where to find your key, endpoint, and deployment name. As explained above, the endpoint, deployment, and key should be in the environment variables `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_DEPLOYMENYT`, and `AZURE_OPENAI_API_KEY`, or provided as `Endpoint=…`, `Deployment=…`, and `APIKey=…` in the `azureChat` call below.
+To connect MATLAB® to Chat Completions API via Azure, you will have to create an `azureChat` object. See [the Azure documentation](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart) for details on the setup required and where to find your key, endpoint, and deployment name. As explained above, the endpoint, deployment, and key should be in the environment variables `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_DEPLOYMENYT`, and `AZURE_OPENAI_API_KEY`, or provided as `Endpoint=…`, `DeploymentID=…`, and `APIKey=…` in the `azureChat` call below.
 
 In order to create the chat assistant, use the `azureChat` function, optionally providing a system prompt:
 ```matlab
@@ -119,7 +119,7 @@ txt = generate(chat,"What is Model-Based Design and how is it related to Digital
 
 You can use gpt-4o, gpt-4o-mini, or gpt-4-turbo to experiment with image understanding. 
 ```matlab
-chat = azureChat("You are an AI assistant.",Deployment="gpt-4o");
+chat = azureChat("You are an AI assistant.",DeploymentID="gpt-4o");
 image_path = "peppers.png";
 messages = messageHistory;
 messages = addUserMessageWithImages(messages,"What is in the image?",image_path);

doc/functions/azureChat.md

@@ -59,18 +59,6 @@ For more information on connecting to the Azure OpenAI API, see [Azure OpenAI Se
 For more information on keeping sensitive information out of code, see [Keep Sensitive Information Out of Code](https://www.mathworks.com/help/matlab/import_export/keep-sensitive-information-out-of-code.html).
 
 
-### `Deployment` — Deployment ID
-
-character vector | string scalar
-
-
-Select a deployed model by specifying the corresponding deployment ID. Specifying the deployment ID also sets the `DeploymentID` property.
-
-
-Instead of using the `Deployment` name\-value argument, you can also set the environment variable AZURE\_OPENAI\_DEPLOYMENT. For more information, see [Azure OpenAI Services API](../Azure.md).
-
-
-**Example**: `"my-gpt-35-turbo-deployment"`
 
 ### `Tools` — Functions to call during output generation
 
@@ -112,6 +100,21 @@ Instead of using the `Endpoint` name\-value argument, you can also set the envir
 
 For more information on how to obtain an Azure endpoint, see [https://learn.microsoft.com/en\-us/azure/ai\-services/openai/chatgpt\-quickstart?tabs=command\-line%2Cpython\-new&pivots=rest\-api\#set\-up](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart?tabs=command-line%2Cpython-new&pivots=rest-api#set-up).
 
+### `DeploymentID` — Deployment ID
+
+character vector | string scalar
+
+
+After construction, this property is read\-only.
+
+
+The deployment ID, also known as deployment name, specifies the Azure OpenAI deployment to use for generation. 
+
+
+Instead of using the `DeploymentID` name\-value argument, you can also set the environment variable AZURE\_OPENAI\_DEPLOYMENT. For more information, see [Azure OpenAI Services API](../Azure.md).
+
+**Example**: `"my-gpt-35-turbo-deployment"`
+
 ### `APIVersion` — API Version
 
 `"2024-06-01"` (default) | `"2024-02-01"` | `"2023-05-15"` | `"2024-05-01-preview"` | `"2024-04-01-preview"` | ...
@@ -227,19 +230,6 @@ This property is read\-only.
 
 Names of the custom functions specified in the `Tools` name\-value argument.
 
-### `DeploymentID` — Deployment ID
-
-character vector | string scalar
-
-
-This property is read\-only.
-
-
-The deployment ID specifies the model to use for generation.
-
-
-Set the `DeploymentID` property at construction either by using the `Deployment` name\-value argument, or by setting the environment variable AZURE\_OPENAI\_DEPLOYMENT. For more information, see [Azure OpenAI Services API](../Azure.md).
-
 # Object Functions
 
 [`generate`](generate.md) — Generate output from large language models

functionSignatures.json

@@ -56,7 +56,7 @@
         [
             {"name":"systemPrompt","kind":"ordered","type":["string","scalar"]},
             {"name":"Endpoint","kind":"namevalue","type":["string","scalar"]},
-            {"name":"Deployment","kind":"namevalue","type":["string","scalar"]},
+            {"name":"DeploymentID","kind":"namevalue","type":["string","scalar"]},
             {"name":"APIKey","kind":"namevalue","type":["string","scalar"]},
             {"name":"Tools","kind":"namevalue","type":"openAIFunction"},
             {"name":"APIVersion","kind":"namevalue","type":"choices=llms.azure.apiVersions"},

tests/tazureChat.m

@@ -23,7 +23,7 @@ function constructChatWithAllNVP(testCase)
             frequenceP = 2;
             systemPrompt = "This is a system prompt";
             timeout = 3;
-            chat = azureChat(systemPrompt, Deployment=deploymentID, Tools=functions, ...
+            chat = azureChat(systemPrompt, DeploymentID=deploymentID, Tools=functions, ...
                 Temperature=temperature, TopP=topP, StopSequences=stop, APIKey=apiKey,...
                 FrequencyPenalty=frequenceP, PresencePenalty=presenceP, TimeOut=timeout);
             testCase.verifyEqual(chat.Temperature, temperature);
@@ -56,7 +56,7 @@ function generateMultipleResponses(testCase)
         end
 
         function generateWithImage(testCase)
-            chat = azureChat(Deployment="gpt-4o");
+            chat = azureChat(DeploymentID="gpt-4o");
             image_path = "peppers.png";
             emptyMessages = messageHistory;
             messages = addUserMessageWithImages(emptyMessages,"What is in the image?",image_path);
@@ -67,7 +67,7 @@ function generateWithImage(testCase)
 
         function generateWithMultipleImages(testCase)
             import matlab.unittest.constraints.ContainsSubstring
-            chat = azureChat(Deployment="gpt-4o");
+            chat = azureChat(DeploymentID="gpt-4o");
             image_path = "peppers.png";
             emptyMessages = messageHistory;
             messages = addUserMessageWithImages(emptyMessages,"Compare these images.",[image_path,image_path]);