Merge pull request #18 from matlab-deep-learning/dev-update-040924models

Reflecting the updated models released on April 9, 2024
matlab-deep-learning · Apr 16, 2024 · d3e7389 · d3e7389
2 parents 2ef309d + e9acd81
commit d3e7389
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Showing 10 changed files with 67 additions and 50 deletions.
diff --git a/+llms/+internal/callOpenAIChatAPI.m b/+llms/+internal/callOpenAIChatAPI.m
@@ -119,18 +119,16 @@
 
 parameters.stream = ~isempty(nvp.StreamFun);
 
-if ~isempty(functions) && ~strcmp(nvp.ModelName,'gpt-4-vision-preview')
+if ~isempty(functions)
     parameters.tools = functions;
 end
 
-if ~isempty(nvp.ToolChoice) && ~strcmp(nvp.ModelName,'gpt-4-vision-preview')
+if ~isempty(nvp.ToolChoice)
     parameters.tool_choice = nvp.ToolChoice;
 end
 
-if ismember(nvp.ModelName,["gpt-3.5-turbo-1106","gpt-4-1106-preview"])
-    if strcmp(nvp.ResponseFormat,"json")
-        parameters.response_format = struct('type','json_object');
-    end
+if strcmp(nvp.ResponseFormat,"json")
+    parameters.response_format = struct('type','json_object');
 end
 
 if ~isempty(nvp.Seed)
@@ -142,15 +140,21 @@
 dict = mapNVPToParameters;
 
 nvpOptions = keys(dict);
-if strcmp(nvp.ModelName,'gpt-4-vision-preview')
-    nvpOptions(ismember(nvpOptions,"StopSequences")) = [];
-end
 
 for opt = nvpOptions.'
     if isfield(nvp, opt)
         parameters.(dict(opt)) = nvp.(opt);
     end
 end
+
+if isempty(nvp.StopSequences)
+    parameters = rmfield(parameters,"stop");
+end
+
+if nvp.MaxNumTokens == Inf
+    parameters = rmfield(parameters,"max_tokens");
+end
+
 end
 
 function dict = mapNVPToParameters()

diff --git a/+llms/+utils/errorMessageCatalog.m b/+llms/+utils/errorMessageCatalog.m
@@ -49,8 +49,10 @@
 catalog("llms:mustBeMessagesOrTxt") = "Messages must be text with one or more characters or an openAIMessages objects.";
 catalog("llms:invalidOptionAndValueForModel") = "'{1}' with value '{2}' is not supported for ModelName '{3}'";
 catalog("llms:invalidOptionForModel") = "{1} is not supported for ModelName '{2}'";
+catalog("llms:invalidContentTypeForModel") = "{1} is not supported for ModelName '{2}'";
 catalog("llms:functionNotAvailableForModel") = "This function is not supported for ModelName '{1}'";
 catalog("llms:promptLimitCharacter") = "Prompt must have a maximum length of {1} characters for ModelName '{2}'";
 catalog("llms:pngExpected") = "Argument must be a PNG image.";
 catalog("llms:warningJsonInstruction") = "When using JSON mode, you must also prompt the model to produce JSON yourself via a system or user message.";
+catalog("llms:apiReturnedError") = "OpenAI API Error: {1}";
 end
diff --git a/README.md b/README.md
@@ -5,11 +5,11 @@ This repository contains example code to demonstrate how to connect MATLAB to th
 The functionality shown here serves as an interface to the ChatGPT and DALL·E APIs. To start using the OpenAI APIs, you first need to obtain OpenAI API keys. You are responsible for any fees OpenAI may charge for the use of their APIs. You should be familiar with the limitations and risks associated with using this technology, and you agree that you shall be solely responsible for full compliance with any terms that may apply to your use of the OpenAI APIs.
 
 Some of the current LLMs supported are:
-- gpt-3.5-turbo, gpt-3.5-turbo-1106
-- gpt-4, gpt-4-1106-preview
-- gpt-4-vision-preview (a.k.a. GPT-4 Turbo with Vision)
+- gpt-3.5-turbo, gpt-3.5-turbo-1106, gpt-3.5-turbo-0125
+- gpt-4-turbo, gpt-4-turbo-2024-04-09 (GPT-4 Turbo with Vision)
+- gpt-4, gpt-4-0613
 - dall-e-2, dall-e-3
-
+                                                        
 For details on the specification of each model, check the official [OpenAI documentation](https://platform.openai.com/docs/models).
 
 ## Requirements
@@ -52,15 +52,15 @@ To use this repository with a local installation of MATLAB, first clone the repo
 
 Set up your OpenAI API key. Create a `.env` file in the project root directory with the following content.
 
-    ```
-    OPENAI_API_KEY=<your key>
-    ```
+```
+OPENAI_API_KEY=<your key>
+```
     
-    Then load your `.env` file as follows:
+Then load your `.env` file as follows:
 
-    ```matlab
-    loadenv(".env")
-    ```
+```matlab
+loadenv(".env")
+```
 
 ## Getting Started with Chat Completion API
 
@@ -287,13 +287,13 @@ You can extract the arguments and write the data to a table, for example.
 
 ### Understand the content of an image
 
-You can use gpt-4-vision-preview to experiment with image understanding. 
+You can use gpt-4-turbo to experiment with image understanding. 
 ```matlab
-chat = openAIChat("You are an AI assistant.", ModelName="gpt-4-vision-preview"); 
+chat = openAIChat("You are an AI assistant.", ModelName="gpt-4-turbo");
 image_path = "peppers.png";
 messages = openAIMessages;
 messages = addUserMessageWithImages(messages,"What is in the image?",image_path);
-[txt,response] = generate(chat,messages);
+[txt,response] = generate(chat,messages,MaxNumTokens=4096);
 % Should output the description of the image
 ```
 

diff --git a/examples/AnalyzeSentimentinTextUsingChatGPTinJSONMode.mlx b/examples/AnalyzeSentimentinTextUsingChatGPTinJSONMode.mlx
diff --git a/examples/DescribeImagesUsingChatGPT.mlx b/examples/DescribeImagesUsingChatGPT.mlx
diff --git a/examples/ExampleParallelFunctionCalls.mlx b/examples/ExampleParallelFunctionCalls.mlx
diff --git a/examples/UsingDALLEToEditImages.mlx b/examples/UsingDALLEToEditImages.mlx
diff --git a/examples/UsingDALLEToGenerateImages.mlx b/examples/UsingDALLEToGenerateImages.mlx
diff --git a/openAIChat.m b/openAIChat.m
@@ -114,10 +114,10 @@
             arguments
                 systemPrompt                       {llms.utils.mustBeTextOrEmpty} = []
                 nvp.Tools                    (1,:) {mustBeA(nvp.Tools, "openAIFunction")} = openAIFunction.empty
-                nvp.ModelName                (1,1) {mustBeMember(nvp.ModelName,["gpt-4", "gpt-4-0613", "gpt-4-32k", ...
-                                                        "gpt-3.5-turbo", "gpt-4-1106-preview", ...
-                                                        "gpt-3.5-turbo-1106", "gpt-4-vision-preview", ...
-                                                        "gpt-4-turbo-preview"])} = "gpt-3.5-turbo"
+                nvp.ModelName                (1,1) {mustBeMember(nvp.ModelName,["gpt-4-turbo", ...
+                                                        "gpt-4-turbo-2024-04-09","gpt-4","gpt-4-0613", ...
+                                                        "gpt-3.5-turbo","gpt-3.5-turbo-0125", ...
+                                                        "gpt-3.5-turbo-1106"])} = "gpt-3.5-turbo"
                 nvp.Temperature                    {mustBeValidTemperature} = 1
                 nvp.TopProbabilityMass             {mustBeValidTopP} = 1
                 nvp.StopSequences                  {mustBeValidStop} = {}
@@ -131,10 +131,6 @@
 
             if isfield(nvp,"StreamFun")
                 this.StreamFun = nvp.StreamFun;
-                if strcmp(nvp.ModelName,'gpt-4-vision-preview')
-                    error("llms:invalidOptionForModel", ...
-                       llms.utils.errorMessageCatalog.getMessage("llms:invalidOptionForModel", "StreamFun", nvp.ModelName));
-                end
             else
                 this.StreamFun = [];
             end
@@ -146,10 +142,6 @@
             else
                 this.Tools = nvp.Tools;
                 [this.FunctionsStruct, this.FunctionNames] = functionAsStruct(nvp.Tools);
-                if strcmp(nvp.ModelName,'gpt-4-vision-preview')
-                   error("llms:invalidOptionForModel", ...
-                       llms.utils.errorMessageCatalog.getMessage("llms:invalidOptionForModel", "Tools", nvp.ModelName));
-                end
             end
 
             if ~isempty(systemPrompt)
@@ -163,20 +155,15 @@
             this.Temperature = nvp.Temperature;
             this.TopProbabilityMass = nvp.TopProbabilityMass;
             this.StopSequences = nvp.StopSequences;
-            if ~isempty(nvp.StopSequences) && strcmp(nvp.ModelName,'gpt-4-vision-preview')
-                error("llms:invalidOptionForModel", ...
-                       llms.utils.errorMessageCatalog.getMessage("llms:invalidOptionForModel", "StopSequences", nvp.ModelName));
-            end
-
 
             % ResponseFormat is only supported in the latest models only
             if (nvp.ResponseFormat == "json")
-                if ismember(this.ModelName,["gpt-3.5-turbo-1106","gpt-4-1106-preview"])
-                    warning("llms:warningJsonInstruction", ...
-                        llms.utils.errorMessageCatalog.getMessage("llms:warningJsonInstruction"))
-                else
+                if ismember(this.ModelName,["gpt-4","gpt-4-0613"])
                     error("llms:invalidOptionAndValueForModel", ...
                         llms.utils.errorMessageCatalog.getMessage("llms:invalidOptionAndValueForModel", "ResponseFormat", "json", this.ModelName));
+                else
+                    warning("llms:warningJsonInstruction", ...
+                        llms.utils.errorMessageCatalog.getMessage("llms:warningJsonInstruction"))
                 end
 
             end
@@ -222,17 +209,20 @@
             end
 
             toolChoice = convertToolChoice(this, nvp.ToolChoice);
-            if ~isempty(nvp.ToolChoice) && strcmp(this.ModelName,'gpt-4-vision-preview')
-                error("llms:invalidOptionForModel", ...
-                       llms.utils.errorMessageCatalog.getMessage("llms:invalidOptionForModel", "ToolChoice", this.ModelName));
-            end
 
             if isstring(messages) && isscalar(messages)
                 messagesStruct = {struct("role", "user", "content", messages)};               
             else
                 messagesStruct = messages.Messages;
             end
 
+            if iscell(messagesStruct{end}.content) && any(cellfun(@(x) isfield(x,"image_url"), messagesStruct{end}.content))
+                if ~ismember(this.ModelName,["gpt-4-turbo","gpt-4-turbo-2024-04-09"]) 
+                 error("llms:invalidContentTypeForModel", ...
+                       llms.utils.errorMessageCatalog.getMessage("llms:invalidContentTypeForModel", "Image content", this.ModelName));
+                end
+            end
+
             if ~isempty(this.SystemPrompt)
                 messagesStruct = horzcat(this.SystemPrompt, messagesStruct);
             end
@@ -244,6 +234,13 @@
                 PresencePenalty=this.PresencePenalty, FrequencyPenalty=this.FrequencyPenalty, ...
                 ResponseFormat=this.ResponseFormat,Seed=nvp.Seed, ...
                 ApiKey=this.ApiKey,TimeOut=this.TimeOut, StreamFun=this.StreamFun);
+
+            if isfield(response.Body.Data,"error")
+                err = response.Body.Data.error.message;
+                text = llms.utils.errorMessageCatalog.getMessage("llms:apiReturnedError",err);
+                message = struct("role","assistant","content",text);
+            end
+
         end
 
         function this = set.Temperature(this, temperature)

diff --git a/tests/topenAIChat.m b/tests/topenAIChat.m
@@ -38,7 +38,7 @@ function generateAcceptsMessagesAsInput(testCase)
         end
 
         function constructMdlWithInvalidParameters(testCase)
-            testCase.verifyError(@()openAIChat(ApiKey="this-is-not-a-real-key", ResponseFormat="json"), "llms:invalidOptionAndValueForModel");
+            testCase.verifyError(@()openAIChat(ApiKey="this-is-not-a-real-key", ModelName="gpt-4", ResponseFormat="json"), "llms:invalidOptionAndValueForModel");
         end
 
         function keyNotFound(testCase)
@@ -100,7 +100,21 @@ function assignValueToProperty(property, value)
             end
 
             testCase.verifyError(@()assignValueToProperty(InvalidValuesSetters.Property,InvalidValuesSetters.Value), InvalidValuesSetters.Error);
-        end      
+        end
+
+        function invalidGenerateInputforModel(testCase)
+            chat = openAIChat(ApiKey="this-is-not-a-real-key");
+            image_path = "peppers.png";
+            emptyMessages = openAIMessages;
+            inValidMessages = addUserMessageWithImages(emptyMessages,"What is in the image?",image_path);
+            testCase.verifyError(@()generate(chat,inValidMessages), "llms:invalidContentTypeForModel")
+        end
+
+        function noStopSequencesNoMaxNumTokens(testCase)
+            chat = openAIChat(ApiKey="this-is-not-a-real-key");
+            testCase.verifyWarningFree(@()generate(chat,"This is okay"));
+        end
+
     end    
 end