get basic Azure connection working

matlab-deep-learning · May 27, 2024 · 8bd236b · 8bd236b
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diff --git a/+llms/+internal/callAzureChatAPI.m b/+llms/+internal/callAzureChatAPI.m
@@ -1,4 +1,4 @@
-function [text, message, response] = callAzureChatAPI(resourceName, deploymentID, messages, functions, nvp)
+function [text, message, response] = callAzureChatAPI(endpoint, deploymentID, messages, functions, nvp)
 %callOpenAIChatAPI Calls the openAI chat completions API.
 %
 %   MESSAGES and FUNCTIONS should be structs matching the json format
@@ -52,7 +52,7 @@
 %   Copyright 2023-2024 The MathWorks, Inc.
 
 arguments
-    resourceName
+    endpoint
     deploymentID
     messages
     functions
@@ -72,11 +72,11 @@
     nvp.StreamFun = []
 end
 
-END_POINT = "https://" + resourceName + ".openai.azure.com/openai/deployments/" + deploymentID + "/chat/completions?api-version=" + nvp.APIVersion;
+URL = endpoint + "openai/deployments/" + deploymentID + "/chat/completions?api-version=" + nvp.APIVersion;
 
 parameters = buildParametersCall(messages, functions, nvp);
 
-[response, streamedText] = llms.internal.sendRequest(parameters,nvp.ApiKey, END_POINT, nvp.TimeOut, nvp.StreamFun);
+[response, streamedText] = llms.internal.sendRequest(parameters,nvp.ApiKey, URL, nvp.TimeOut, nvp.StreamFun);
 
 % If call errors, "choices" will not be part of response.Body.Data, instead
 % we get response.Body.Data.error
@@ -108,9 +108,13 @@
 
 parameters.stream = ~isempty(nvp.StreamFun);
 
-parameters.tools = functions;
+if ~isempty(functions)
+    parameters.tools = functions;
+end
 
-parameters.tool_choice = nvp.ToolChoice;
+if ~isempty(nvp.ToolChoice)
+    parameters.tool_choice = nvp.ToolChoice;
+end
 
 if ~isempty(nvp.Seed)
     parameters.seed = nvp.Seed;

diff --git a/+llms/+internal/sendRequest.m b/+llms/+internal/sendRequest.m
@@ -1,6 +1,6 @@
 function [response, streamedText] = sendRequest(parameters, token, endpoint, timeout, streamFun)
 %sendRequest Sends a request to an ENDPOINT using PARAMETERS and
-%   api key TOKEN. TIMEOUT is the nubmer of seconds to wait for initial
+%   api key TOKEN. TIMEOUT is the number of seconds to wait for initial
 %   server connection. STREAMFUN is an optional callback function.
 
 %   Copyright 2023 The MathWorks, Inc.
@@ -16,7 +16,8 @@
 % Define the headers for the API request
 
 headers = [matlab.net.http.HeaderField('Content-Type', 'application/json')...
-    matlab.net.http.HeaderField('Authorization', "Bearer " + token)];
+    matlab.net.http.HeaderField('Authorization', "Bearer " + token)...
+    matlab.net.http.HeaderField('api-key',token)];
 
 % Define the request message
 request = matlab.net.http.RequestMessage('post',headers,parameters);

diff --git a/azureChat.m b/azureChat.m
@@ -1,8 +1,8 @@
 classdef(Sealed) azureChat < llms.internal.textGenerator
 %azureChat Chat completion API from Azure.
 %
-%   CHAT = azureChat(resourceName, deploymentID) creates an azureChat object with the
-%   resource name and deployment ID path parameters required by Azure to establish the connection.
+%   CHAT = azureChat(endpoint, deploymentID) creates an azureChat object with the
+%   endpoint and deployment ID path parameters required by Azure to establish the connection.
 %
 %   CHAT = azureChat(systemPrompt) creates an azureChatobject with the
 %   specified system prompt.
@@ -74,16 +74,15 @@
 % Copyright 2023-2024 The MathWorks, Inc.
 
     properties(SetAccess=private)
-        ResourceName
-        DeploymentID
-        APIVersion
+        Endpoint     (1,1) string
+        DeploymentID (1,1) string
+        APIVersion   (1,1) string
     end
 
-
     methods
-        function this = azureChat(resourceName, deploymentID, systemPrompt, nvp)
+        function this = azureChat(endpoint, deploymentID, systemPrompt, nvp)
             arguments
-                resourceName                       {mustBeTextScalar}
+                endpoint                           {mustBeTextScalar}
                 deploymentID                       {mustBeTextScalar}
                 systemPrompt                       {llms.utils.mustBeTextOrEmpty} = []
                 nvp.Tools                    (1,:) {mustBeA(nvp.Tools, "openAIFunction")} = openAIFunction.empty
@@ -123,7 +122,7 @@
                 end
             end
 
-            this.ResourceName = resourceName;
+            this.Endpoint = endpoint;
             this.DeploymentID = deploymentID;
             this.APIVersion = nvp.APIVersion;
             this.ResponseFormat = nvp.ResponseFormat;
@@ -181,7 +180,7 @@
             end
 
             toolChoice = convertToolChoice(this, nvp.ToolChoice);
-            [text, message, response] = llms.internal.callAzureChatAPI(this.ResourceName, ...
+            [text, message, response] = llms.internal.callAzureChatAPI(this.Endpoint, ...
                 this.DeploymentID, messagesStruct, this.FunctionsStruct, ...
                 ToolChoice=toolChoice, APIVersion = this.APIVersion, Temperature=this.Temperature, ...
                 TopProbabilityMass=this.TopProbabilityMass, NumCompletions=nvp.NumCompletions,...

diff --git a/tests/tazureChat.m b/tests/tazureChat.m
@@ -3,18 +3,6 @@
 
 %   Copyright 2024 The MathWorks, Inc.
 
-    methods (TestClassSetup)
-        function saveEnvVar(testCase)
-            % Ensures key is not in environment variable for tests
-            azureKeyVar = "AZURE_OPENAI_API_KEY";
-            if isenv(azureKeyVar)
-                key = getenv(azureKeyVar);
-                unsetenv(azureKeyVar);
-                testCase.addTeardown(@(x) setenv(azureKeyVar, x), key);
-            end
-        end
-    end
-
     properties(TestParameter)
         InvalidConstructorInput = iGetInvalidConstructorInput;
         InvalidGenerateInput = iGetInvalidGenerateInput;
@@ -24,11 +12,14 @@ function saveEnvVar(testCase)
     methods(Test)
         % Test methods
         function keyNotFound(testCase)
-            testCase.verifyError(@()azureChat("My_resource", "Deployment"), "llms:keyMustBeSpecified");
+            import matlab.unittest.fixtures.EnvironmentVariableFixture
+            testCase.applyFixture(EnvironmentVariableFixture("AZURE_OPENAI_API_KEY","dummy"));
+            unsetenv("AZURE_OPENAI_API_KEY");
+            testCase.verifyError(@()azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT")), "llms:keyMustBeSpecified");
         end
 
         function constructChatWithAllNVP(testCase)
-            resourceName = "resource";
+            endpoint = getenv("AZURE_OPENAI_ENDPOINT");
             deploymentID = "hello";
             functions = openAIFunction("funName");
             temperature = 0;
@@ -39,7 +30,7 @@ function constructChatWithAllNVP(testCase)
             frequenceP = 2;
             systemPrompt = "This is a system prompt";
             timeout = 3;
-            chat = azureChat(resourceName, deploymentID, systemPrompt, Tools=functions, ...
+            chat = azureChat(endpoint, deploymentID, systemPrompt, Tools=functions, ...
                 Temperature=temperature, TopProbabilityMass=topP, StopSequences=stop, ApiKey=apiKey,...
                 FrequencyPenalty=frequenceP, PresencePenalty=presenceP, TimeOut=timeout);
             testCase.verifyEqual(chat.Temperature, temperature);
@@ -49,28 +40,36 @@ function constructChatWithAllNVP(testCase)
             testCase.verifyEqual(chat.PresencePenalty, presenceP);
         end
 
+        function doGenerate(testCase)
+            testCase.assumeTrue(isenv("AZURE_OPENAI_API_KEY"),"end-to-end test requires environment variables AZURE_OPENAI_API_KEY, AZURE_OPENAI_ENDPOINT, and AZURE_OPENAI_DEPLOYMENT.");
+            chat = azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"));
+            response = testCase.verifyWarningFree(@() generate(chat,"hi"));
+            testCase.verifyClass(response,'string');
+            testCase.verifyGreaterThan(strlength(response),0);
+        end
+
         function verySmallTimeOutErrors(testCase)
-            chat = azureChat("My_resource", "Deployment", TimeOut=0.0001, ApiKey="false-key");
+            chat = azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"), TimeOut=0.0001, ApiKey="false-key");
             testCase.verifyError(@()generate(chat, "hi"), "MATLAB:webservices:Timeout")
         end
 
         function errorsWhenPassingToolChoiceWithEmptyTools(testCase)
-            chat = azureChat("My_resource", "Deployment", ApiKey="this-is-not-a-real-key");
+            chat = azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"), ApiKey="this-is-not-a-real-key");
             testCase.verifyError(@()generate(chat,"input", ToolChoice="bla"), "llms:mustSetFunctionsForCall");
         end
 
         function invalidInputsConstructor(testCase, InvalidConstructorInput)
-            testCase.verifyError(@()azureChat("My_resource", "Deployment", InvalidConstructorInput.Input{:}), InvalidConstructorInput.Error);
+            testCase.verifyError(@()azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"), InvalidConstructorInput.Input{:}), InvalidConstructorInput.Error);
         end
 
         function invalidInputsGenerate(testCase, InvalidGenerateInput)
             f = openAIFunction("validfunction");
-            chat = azureChat("My_resource", "Deployment", Tools=f, ApiKey="this-is-not-a-real-key");
+            chat = azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"), Tools=f, ApiKey="this-is-not-a-real-key");
             testCase.verifyError(@()generate(chat,InvalidGenerateInput.Input{:}), InvalidGenerateInput.Error);
         end
 
         function invalidSetters(testCase, InvalidValuesSetters)
-            chat = azureChat("My_resource", "Deployment", ApiKey="this-is-not-a-real-key");
+            chat = azureChat(getenv("AZURE_OPENAI_ENDPOINT"), getenv("AZURE_OPENAI_DEPLOYMENT"), ApiKey="this-is-not-a-real-key");
             function assignValueToProperty(property, value)
                 chat.(property) = value;
             end