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Documentation: Reference Pages (#5)
* Documentation: Reference Pages We have added a new directory `functions` to the `documentation` directory. The `functions` folder contains documentation for these functions and objects: - openAIChat - azureChat - ollamaChat - generate - openAIFunction - addParameter - openAIImages - openAIImages.generate - edit - createVariation - messageHistory - addSystemMessage - addUserMessage - addUserMessageWithImages - addToolMessage - addResponseMessage - removeMessage
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Diff for: ‎doc/functions/addParameter.md

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# addParameter
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Add input argument to `openAIFunction` object
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# Syntax
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`fUpdated = addParameter(f,parameterName)`
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`___ = addParameter(___,Name=Value)`
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# Description
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`fUpdated = addParameter(f,parameterName)` adds an input argument `parameterName` to the `openAIFunction` object `f`.
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`___ = addParameter(___,Name=Value)` specifies additional options using one or more name\-value arguments.
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# Examples
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## Compute Sine Using OpenAI Function Call
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First, specify the OpenAI® API key as an environment variable and save it to a file called `".env"`. Next, load the environment file using the `loadenv` function.
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```matlab
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loadenv(".env")
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```
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Create an `openAIFunction` object that represents the [`sind`](https://www.mathworks.com/help/matlab/ref/sind.html) function. The `sind` function has a single input argument, `x`, representing the input angle in degrees.
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```matlab
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f = openAIFunction("sind","Sine of argument in degrees");
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f = addParameter(f,"x",type="number",description="Angle in degrees");
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```
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Connect to the OpenAI Chat Completion API. Pass the `openAIFunction` object `f` as an input argument.
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```matlab
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model = openAIChat("You are a helpful assistant.",Tools=f);
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```
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Initialize the message history. Add a user message to the message history.
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```matlab
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messages = messageHistory;
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messages = addUserMessage(messages,"What is the sine of thirty?");
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```
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Generate a response based on the message history.
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```matlab
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[~,completeOutput] = generate(model,messages)
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```
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```matlabTextOutput
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completeOutput = struct with fields:
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role: 'assistant'
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content: []
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tool_calls: [1x1 struct]
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refusal: []
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```
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The model has not generated any text. Instead, it has detected a function call, `completeOutput.tool_calls`.
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Add the response to the message history.
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```matlab
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messages = addResponseMessage(messages,completeOutput);
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```
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Extract the tool call ID and the name of the called function.
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```matlab
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toolCallID = string(completeOutput.tool_calls.id)
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```
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```matlabTextOutput
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toolCallID = "call_Scx4xE9whYiL2FbQWYslDgDr"
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```
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```matlab
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functionCalled = string(completeOutput.tool_calls.function.name)
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```
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```matlabTextOutput
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functionCalled = "sind"
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```
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Make sure that the model is calling the correct function. Even with only a single function, large language models can hallucinate function calls to fictitious functions.
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Extract the input argument values from the complete output using the [`jsondecode`](https://www.mathworks.com/help/matlab/ref/jsondecode.html) function. Compute the sine of the generated argument value and add the result to the message history using the `addToolMessage` function.
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```matlab
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if functionCalled == "sind"
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args = jsondecode(completeOutput.tool_calls.function.arguments);
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result = sind(args.x)
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messages = addToolMessage(messages,toolCallID,functionCalled,"x="+result);
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end
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```
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```matlabTextOutput
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result = 0.5000
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```
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Finally, generate a natural language response.
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```matlab
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generatedText = generate(model,messages)
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```
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```matlabTextOutput
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generatedText = "The sine of 30 degrees is 0.5."
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```
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# Input Arguments
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### f — OpenAI function
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[`openAIFunction`](openAIFunction.md) object
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OpenAI function, specified as an `openAIFunction` object.
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### `parameterName` — Name of new input argument
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string scalar | character array
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Specify the name of the new input argument. The name must be a valid MATLAB variable name.
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For more information on variable naming rules in MATLAB, see [https://www.mathworks.com/help/matlab/matlab\_prog/variable\-names.html](https://www.mathworks.com/help/matlab/matlab_prog/variable-names.html).
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## Name\-Value Arguments
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### `RequiredParameter` — Flag to require argument
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`true` (default) | `false`
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Specify whether the argument is required (`true`) or optional (`false`).
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### `description` — Argument description
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string scalar | character vector
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Natural language description of the input argument, specified as a string or character array.
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### `type` — Argument type
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string scalar | string vector | character vector
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Data type or types of the input argument, specified as JSON data type. The possible argument types and their corresponding MATLAB data types are:
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- `"string"` — character vector
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- `"number"` — scalar double
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- `"integer"` — scalar integer
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- `"object"` — scalar structure
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- `"boolean"` — scalar logical
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- `"null"` — `NaN` or empty double
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For more information on how to decode JSON\-formatted data in MATLAB, see [jsondecode](https://www.mathworks.com/help/matlab/ref/jsondecode.html).
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### `enum` — List of possible argument values
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string vector
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List of all possible values of an input argument.
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**Example**: `["on" "off" "auto"]`
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# Output Argument
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### `fUpdated` — Updated OpenAI function
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`openAIFunction` object
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Updated OpenAI function, specified as an `openAIFunction` object.
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# See Also
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[`openAIFunction`](openAIFunction.md) | [`openAIChat`](openAIChat.md) | [`generate`](generate.md) | [`addToolMessage`](addToolMessage.md)
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- [Analyze Scientific Papers Using ChatGPT Function Calls](../../examples/AnalyzeScientificPapersUsingFunctionCalls.md)
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- [Analyze Text Data Using Parallel Function Calls with ChatGPT](../../examples/AnalyzeTextDataUsingParallelFunctionCallwithChatGPT.md)
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*Copyright 2024 The MathWorks, Inc.*
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Diff for: ‎doc/functions/addResponseMessage.md

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# addResponseMessage
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Add response message to message history
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`updatedMessages = addResponseMessage(messages,completeOutput)`
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# Description
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`updatedMessages = addResponseMessage(messages,completeOutput)` adds the generated output of a large language model to the `messageHistory` object `messages`.
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# Examples
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## Add Response Message to Message History
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First, specify the OpenAI® API key as an environment variable and save it to a file called `".env"`. Next, load the environment file using the `loadenv` function.
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```matlab
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loadenv(".env")
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```
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Connect to the OpenAI Chat Completion API.
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```matlab
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model = openAIChat("You are a helpful assistant.");
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```
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Initialize the message history.
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```matlab
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messages = messageHistory;
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```
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Add a user message to the message history.
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```matlab
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messages = addUserMessage(messages,"Why is a raven like a writing desk?");
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Generate a response.
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```matlab
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[generatedText,completeOutput,httpResponse] = generate(model,messages);
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```
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Add the response to the message history.
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```matlab
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messages = addResponseMessage(messages,completeOutput);
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messages.Messages{end}
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```
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```matlabTextOutput
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ans = struct with fields:
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role: "assistant"
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content: "The question "Why is a raven like a writing desk?" is famously posed by the Mad Hatter in Lewis Carroll's "Alice's Adventures in Wonderland." Initially, it is presented as a riddle without a clear answer, contributing to the absurdity and nonsensical nature of the story. However, over time, various interpretations and answers have been suggested, such as:↵↵1. **Both can produce notes**: Ravens can "caw" or make sounds like a note, and writing desks are used for writing notes or letters.↵2. **Both are associated with writing**: Ravense have historically been linked to writers (like Edgar Allan Poe's famous poem "The Raven"), and desks are where writing is done.↵3. **The riddle is inherently nonsensical**: The whole point may be that some riddles don't have answers, fitting into the whimsical and illogical world of Wonderland.↵↵Carroll himself later suggested that the riddle was meant to be without an answer, thus adding to its charm and mystique in the context of his work."
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```
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## Compute Sine Using OpenAI Function Call
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First, specify the OpenAI® API key as an environment variable and save it to a file called `".env"`. Next, load the environment file using the `loadenv` function.
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```matlab
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loadenv(".env")
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```
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Create an `openAIFunction` object that represents the [`sind`](https://www.mathworks.com/help/matlab/ref/sind.html) function. The `sind` function has a single input argument, `x`, representing the input angle in degrees.
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```matlab
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f = openAIFunction("sind","Sine of argument in degrees");
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f = addParameter(f,"x",type="number",description="Angle in degrees");
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```
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Connect to the OpenAI Chat Completion API. Pass the `openAIFunction` object `f` as an input argument.
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```matlab
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model = openAIChat("You are a helpful assistant.",Tools=f);
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```
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Initialize the message history. Add a user message to the message history.
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```matlab
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messages = messageHistory;
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messages = addUserMessage(messages,"What is the sine of thirty?");
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```
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Generate a response based on the message history.
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```matlab
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[~,completeOutput] = generate(model,messages)
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```
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```matlabTextOutput
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completeOutput = struct with fields:
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role: 'assistant'
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content: []
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tool_calls: [1x1 struct]
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refusal: []
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```
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The model has not generated any text. Instead, it has detected a function call, `completeOutput.tool_calls`.
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Add the response to the message history.
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```matlab
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messages = addResponseMessage(messages,completeOutput);
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```
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Extract the tool call ID and the name of the called function.
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```matlab
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toolCallID = string(completeOutput.tool_calls.id)
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```
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```matlabTextOutput
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toolCallID = "call_VLRxaOUTDEyzCY4c8rDnq0jM"
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```
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```matlab
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functionCalled = string(completeOutput.tool_calls.function.name)
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```
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```matlabTextOutput
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functionCalled = "sind"
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```
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Make sure that the model is calling the correct function. Even with only a single function, large language models can hallucinate function calls to fictitious functions.
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Extract the input argument values from the complete output using the [`jsondecode`](https://www.mathworks.com/help/matlab/ref/jsondecode.html) function. Compute the sine of the generated argument value and add the result to the message history using the `addToolMessage` function.
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```matlab
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if functionCalled == "sind"
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args = jsondecode(completeOutput.tool_calls.function.arguments);
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result = sind(args.x)
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messages = addToolMessage(messages,toolCallID,functionCalled,"x="+result);
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end
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```
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```matlabTextOutput
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result = 0.5000
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```
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Finally, generate a natural language response.
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```matlab
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generatedText = generate(model,messages)
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```
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```matlabTextOutput
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generatedText = "The sine of thirty degrees is 0.5."
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```
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# Input Arguments
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### `messages` — Message history
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`messageHistory` object
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Message history, specified as a [`messageHistory`](messageHistory.md) object.
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### completeOutput — Complete output
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structure array
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Complete output generated from a large language model using the [`generate`](generate.md) function, specified as a structure array.
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The type and name of the fields in the structure depend on the API, the model, whether you use function calls, and whether you stream the output.
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# Output Argument
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### `updatedMessages` — Updated message history
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`messageHistory` object
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Updated message history, specified as a [`messageHistory`](messageHistory.md) object.
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The updated message history includes a new structure array with these fields:
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- role —`"assistant"`
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- content — Set by the `content` input argument
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If the generated response includes a function call, then the updated message history also includes this field:
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- tool\_calls — `completeOutput.tool_calls` structure array
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# See Also
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[`generate`](generate.md) | [`messageHistory`](messageHistory.md) | [`openAIChat`](openAIChat.md) | [`ollamaChat`](ollamaChat.md) | [`azureChat`](azureChat.md) | [`addUserMessage`](addUserMessage.md) | [`addUserMessageWithImage`](addUserMessageWithImage.md) | [`addToolMessage`](addToolMessage.md) | [`addSystemMessage`](addSystemMessage.md)
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- [Analyze Text Data Using Parallel Function Calls with ChatGPT](../../examples/AnalyzeTextDataUsingParallelFunctionCallwithChatGPT.md)
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*Copyright 2024 The MathWorks, Inc.*
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