Minor documentation fixes

Author: MiriamScharnke

examples/AnalyzeSentimentinTextUsingChatGPTinJSONMode.md

@@ -30,7 +30,7 @@ Define the expected output JSON Schema.
 jsonSchema = '{"sentiment": "string (positive, negative, neutral)","confidence_score": "number (0-1)"}';
 ```
 
-Define the the system prompt, combining your instructions and the JSON Schema. In order for the model to output JSON, you need to specify that in the prompt, for example, adding *"designed to output to JSON"*  to the prompt.
+Define the system prompt, combining your instructions and the JSON Schema. In order for the model to output JSON, you need to specify that in the prompt, for example, adding *"designed to output to JSON"*  to the prompt.
 
 ```matlab
 systemPrompt = "You are an AI designed to output to JSON. You analyze the sentiment of the provided text and  " + ...

examples/AnalyzeTextDataUsingParallelFunctionCallwithChatGPT.md

@@ -12,7 +12,7 @@ Function calls allow you to describe a function to ChatGPT in a structured way.
 This example contains four steps:
 
 -  Create an unstructured text document containing fictional customer data. 
--  Create a prompt, asking ChatGPT to extract information about different types customers. 
+-  Create a prompt, asking ChatGPT to extract information about different types of customers. 
 -  Create a function that extracts information about customers. 
 -  Combine the prompt and the function. Use ChatGPT to detect how many function calls are included in the prompt and to generate a JSON object with the function outputs. 
 
@@ -37,7 +37,7 @@ record = ["Customer John Doe, 35 years old. Email: johndoe@email.com";
     "Sofia Russo, 24 years old, email: sofia.russo124@email.com"];
 ```
 
-Define the function that extract data from the customer record.
+Define the function that extracts data from the customer record.
 
 ```matlab
 f = openAIFunction("extractCustomerData", "Extracts data from customer records");
@@ -54,7 +54,7 @@ messages = messageHistory;
 messages = addUserMessage(messages,"Extract data from the record: " + record);
 ```
 
-Create a chat object with a latest model. Only the new models support the parallel function calling.
+Create a chat object. Specify the model to be `"gpt-3.5-turbo"`, which supports parallel function calls.
 
 ```matlab
 model = "gpt-3.5-turbo";
@@ -169,7 +169,7 @@ txt =
 ```
 # Helper functions
 
-Function that searches specific customer based on age range
+Function that searches specific customers based on age range
 
 ```matlab
 function json = searchCustomerData(data, minAge, maxAge)

examples/CreateSimpleChatBot.md

@@ -53,7 +53,7 @@ while true
     disp("User: " + query)
 ```
 
-If the you input the stop word, display a farewell message and exit the loop.
+If you input the stop word, display a farewell message and exit the loop.
 
 ```matlab
     if query == stopWord

examples/DescribeImagesUsingChatGPT.md

@@ -35,10 +35,10 @@ messages = messageHistory;
 messages = addUserMessageWithImages(messages,"What is in the image?", string(image_url));
 ```
 
-Generate a response. By default, the model returns a very short response. To override it, set `MaxNumTokens` to 4096. 
+Generate a response.
 
 ```matlab
-[txt,~,response] = generate(chat,messages,MaxNumTokens=4096);
+[txt,~,response] = generate(chat,messages);
 if response.StatusCode == "OK"
     wrappedText = wrapText(txt)
 else
@@ -48,10 +48,10 @@ end
 
 ```matlabTextOutput
 wrappedText = 
-    "The image depicts a serene landscape featuring a wooden pathway that runs 
-     through a lush, green marsh or meadow. The path is bordered by tall grass and 
-     some shrubs, with a clear blue sky overhead dotted with clouds. The scene 
-     evokes a sense of tranquility and natural beauty."
+    "The image depicts a scenic outdoor landscape featuring a wooden pathway or 
+     boardwalk extending through a lush green field. The field is filled with tall 
+     grass and bordered by greenery, including trees and shrubbery. Above, the sky 
+     is bright and cloudy, creating a serene and tranquil atmosphere."
 
 ```
 # Helper function

examples/DescribeImagesUsingChatGPT_media/figure_0.png

@@ -10,7 +10,7 @@ The example consists of four steps:
 
 -  Download and preprocess text from several MATLAB® documentation pages. 
 -  Embed query document and document corpus using the "text\-embedding\-3\-small" document embedding. 
--  Find the most documentation page most relevant to the query using cosine similarity scores. 
+-  Find the documentation page most relevant to the query using cosine similarity scores. 
 -  Generate an answer to the query based on the most relevant documentation page. 
 
 This process is sometimes referred to as Retrieval\-Augmented Generation (RAG), similar to the application found in the example [ExampleRetrievalAugmentedGeneration.mlx](./ExampleRetrievalAugmentedGeneration.mlx).

examples/InformationRetrievalUsingOpenAIDocumentEmbedding.md

@@ -117,7 +117,7 @@ generate(chat,history);
 
 1.  Adds the basic HTML structure and the JavaScript that process the data change in MATLAB.
 2. The JavaScript gets a reference to the table and changed data and if the 3rd element in the data is "new", adds a new row.
-3. It populates the new row with two cells and update the cells from the first two elements of the data.
+3. It populates the new row with two cells and updates the cells from the first two elements of the data.
 4. The new row is then appended to the table.
 5. Otherwise, the JavaScript gets reference to the last cell of the last row of the table, and update it with the 2nd element of the data.
 ```matlab

examples/ProcessGeneratedTextInRealTimeByUsingOllamaInStreamingMode.md

@@ -97,7 +97,7 @@ addChat(h,"assistant",txt,"current")
 
 1.  Adds the basic HTML structure and the JavaScript that process the data change in MATLAB.
 2. The JavaScript gets a reference to the table and changed data and if the 3rd element in the data is "new", adds a new row.
-3. It populates the new row with two cells and update the cells from the first two elements of the data.
+3. It populates the new row with two cells and updates the cells from the first two elements of the data.
 4. The new row is then appended to the table.
 5. Otherwise, the JavaScript gets reference to the last cell of the last row of the table, and update it with the 2nd element of the data.
 ```matlab