Sentiment to structured

change example to using structured output

Author: ccreutzi

examples/AnalyzeSentimentinTextUsingChatGPTinJSONMode.md

@@ -0,0 +1,94 @@
+
+# Analyze Sentiment in Text Using ChatGPT™ and Structured Output
+
+To run the code shown on this page, open the MLX file in MATLAB®: [mlx-scripts/AnalyzeSentimentinTextUsingChatGPTwithStructuredOutput.mlx](mlx-scripts/AnalyzeSentimentinTextUsingChatGPTwithStructuredOutput.mlx) 
+
+This example shows how to use ChatGPT for sentiment analysis and output the results in a desired format. 
+
+
+To run this example, you need a valid API key from a paid OpenAI™ API account.
+
+```matlab
+loadenv(".env")
+addpath('../..')
+```
+
+Define some text to analyze the sentiment.
+
+```matlab
+inputText = ["I can't stand homework.";
+    "This sucks. I'm bored.";
+    "I can't wait for Halloween!!!";
+    "I am neither for nor against the idea.";
+    "My cat is adorable ❤️❤️";
+    "I hate chocolate";
+    "More work. Great.";
+    "More work. Great!"];
+```
+
+Define the system prompt.
+
+```matlab
+systemPrompt = "You are an AI designed to analyze the sentiment of the provided text and  " + ...
+    "Determine whether the sentiment is positive, negative, or neutral " + ...
+    "and provide a confidence score between 0 and 1.";
+prompt = "Analyze the sentiment of the provided text.";
+```
+
+Define the expected output format by providing an example – when supplied with a struct as the `ResponseFormat`, `generate` will return a struct with the same field names and data types. Use a [categorical](https://www.mathworks.com/help/matlab/categorical-arrays.html) to restrict the values that can be returned to the list `["positive","negative","neutral"]`.
+
+```matlab
+prototype = struct(...
+    "sentiment", categorical("positive",["positive","negative","neutral"]),...
+    "confidence", 0.2)
+```
+
+```matlabTextOutput
+prototype = struct with fields:
+     sentiment: positive
+    confidence: 0.2000
+
+```
+
+Create a chat object and set `ResponseFormat` to `prototype`.
+
+```matlab
+chat = openAIChat(systemPrompt, ResponseFormat=prototype);
+```
+
+Concatenate the prompt and input text and generate an answer with the model.
+
+```matlab
+scores = [];
+for i = 1:numel(inputText)
+```
+
+Generate a response from the message. 
+
+```matlab
+    thisResponse = generate(chat,prompt + newline + newline + inputText(i));
+    scores = [scores; thisResponse]; %#ok<AGROW>
+end
+```
+
+Extract the content from the output structure array `scores`.
+
+```matlab
+T = struct2table(scores);
+T.text = inputText;
+T = movevars(T,"text","Before","sentiment")
+```
+| |text|sentiment|confidence|
+|:--:|:--:|:--:|:--:|
+|1|"I can't stand homework."|negative|0.9500|
+|2|"This sucks. I'm bored."|negative|0.9500|
+|3|"I can't wait for Halloween!!!"|positive|0.9500|
+|4|"I am neither for nor against the idea."|neutral|0.9500|
+|5|"My cat is adorable ❤️❤️"|positive|0.9500|
+|6|"I hate chocolate"|negative|0.9500|
+|7|"More work. Great."|negative|0.8500|
+|8|"More work. Great!"|positive|0.9000|
+
+
+*Copyright 2024 The MathWorks, Inc.*
+

examples/AnalyzeSentimentinTextUsingChatGPTwithStructuredOutput.md

@@ -65,9 +65,9 @@ function testAnalyzeScientificPapersUsingFunctionCalls(testCase)
             AnalyzeScientificPapersUsingFunctionCalls;
         end
 
-        function testAnalyzeSentimentinTextUsingChatGPTinJSONMode(testCase)
-            testCase.startCapture("AnalyzeSentimentinTextUsingChatGPTinJSONMode");
-            AnalyzeSentimentinTextUsingChatGPTinJSONMode;
+        function testAnalyzeSentimentinTextUsingChatGPTwithStructuredOutput(testCase)
+            testCase.startCapture("AnalyzeSentimentinTextUsingChatGPTwithStructuredOutput");
+            AnalyzeSentimentinTextUsingChatGPTwithStructuredOutput;
         end
 
         function testAnalyzeTextDataUsingParallelFunctionCallwithChatGPT(testCase)