OpenAI Assistants with Function Calling in JavaScript
This page was automatically generated by AI; not yet reviewed for accuracy...
The content and code samples on this page were generated by using the ai CLI with customized prompts in this repository.
It's cool, but, it's experimental. 😁
Please review the content and code before using it in your application.
This sample demonstrates how to use the OpenAI Assistants API with function calling in a JavaScript application.
main.js
OpenAIAssistantsCustomFunctions.js
OpenAIAssistantsFunctionsStreamingClass.js
How to generate this sample
Output
AI - Azure AI CLI, Version 1.0.0
Copyright (c) 2024 Microsoft Corporation. All Rights Reserved.
This PUBLIC PREVIEW version may change at any time.
See: https://aka.ms/azure-ai-cli-public-preview
Generating 'openai-asst-streaming-with-functions' in 'openai-asst-streaming-with-functions-js' (3 files)...
OpenAIAssistantsFunctionsStreamingClass.js
OpenAIAssistantsCustomFunctions.js
main.js
Generating 'openai-asst-streaming-with-functions' in 'openai-asst-streaming-with-functions-js' (3 files)... DONE!
main.js
STEP 1: Read the configuration settings from environment variables.
main.js
const ASSISTANT_ID = process.env.ASSISTANT_ID ?? "<insert your OpenAI assistant ID here>";
const AZURE_OPENAI_API_KEY = process.env.AZURE_OPENAI_API_KEY ?? "<insert your Azure OpenAI API key here>";
const AZURE_OPENAI_API_VERSION = process.env.AZURE_OPENAI_API_VERSION ?? "<insert your Azure OpenAI API version here>";
const AZURE_OPENAI_ENDPOINT = process.env.AZURE_OPENAI_ENDPOINT ?? "<insert your Azure OpenAI endpoint here>";
const AZURE_OPENAI_BASE_URL = `${AZURE_OPENAI_ENDPOINT.replace(/\/+$, '')}/openai`;
STEP 2: Validate the environment variables.
main.js
const azureOk =
AZURE_OPENAI_API_KEY != null && !AZURE_OPENAI_API_KEY.startsWith('<insert') &&
AZURE_OPENAI_API_VERSION != null && !AZURE_OPENAI_API_VERSION.startsWith('<insert') &&
AZURE_OPENAI_ENDPOINT != null && !AZURE_OPENAI_ENDPOINT.startsWith('<insert');
const ok = azureOk &&
ASSISTANT_ID != null && !ASSISTANT_ID.startsWith('<insert');
if (!ok) {
console.error(
'To use Azure OpenAI, set the following environment variables:\n' +
'\n ASSISTANT_ID' +
'\n AZURE_OPENAI_API_KEY' +
'\n AZURE_OPENAI_API_VERSION' +
'\n AZURE_OPENAI_ENDPOINT'
);
console.error(
'\nYou can easily do that using the Azure AI CLI by doing one of the following:\n' +
'\n ai init' +
'\n ai dev shell' +
'\n node main.js' +
'\n' +
'\n or' +
'\n' +
'\n ai init' +
'\n ai dev shell --run "node main.js"'
);
process.exit(1);
}
STEP 3: Create the OpenAI client.
main.js
const openai = new OpenAI({
apiKey: AZURE_OPENAI_API_KEY,
baseURL: AZURE_OPENAI_BASE_URL,
defaultQuery: { 'api-version': AZURE_OPENAI_API_VERSION },
defaultHeaders: { 'api-key': AZURE_OPENAI_API_KEY },
});
STEP 4: Initialize the assistant's streaming helper class.
main.js
const assistant = new OpenAIAssistantsFunctionsStreamingClass(ASSISTANT_ID, factory, openai);
STEP 5: Create or retrieve a thread and display its messages.
main.js
if (threadId === null) {
await assistant.createThread()
} else {
await assistant.retrieveThread(threadId);
await assistant.getThreadMessages((role, content) => {
role = role.charAt(0).toUpperCase() + role.slice(1);
process.stdout.write(`${role}: ${content}`);
});
}
STEP 6: Loop to get user input and get the assistant's response.
main.js
while (true) {
const input = await readline.question('User: ');
if (input === 'exit' || input === '') break;
process.stdout.write('\nAssistant: ');
await assistant.getResponse(input, (content) => {
process.stdout.write(content);
});
process.stdout.write('\n\n');
}
OpenAIAssistantsCustomFunctions.js
STEP 1: Define the function and its schema, then add it to the function factory.
OpenAIAssistantsCustomFunctions.js
function getCurrentWeather(function_arguments) {
const location = JSON.parse(function_arguments).location;
return `The weather in ${location} is 72 degrees and sunny.`;
};
const getCurrentWeatherSchema = {
name: "get_current_weather",
description: "Get the current weather in a given location",
parameters: {
type: "object",
properties: {
location: {
type: "string",
description: "The city and state, e.g. San Francisco, CA",
},
unit: {
type: "string",
enum: ["celsius", "fahrenheit"],
},
},
required: ["location"],
},
};
factory.addFunction(getCurrentWeatherSchema, getCurrentWeather);
STEP 2: Add more functions following the same pattern.
OpenAIAssistantsCustomFunctions.js
function getCurrentDate() {
const date = new Date();
return `${date.getFullYear()}-${date.getMonth() + 1}-${date.getDate()}`;
}
const getCurrentDateSchema = {
name: "get_current_date",
description: "Get the current date",
parameters: {
type: "object",
properties: {},
},
};
factory.addFunction(getCurrentDateSchema, getCurrentDate);
function getCurrentTime() {
const date = new Date();
return `${date.getHours()}:${date.getMinutes()}:${date.getSeconds()}`;
}
const getCurrentTimeSchema = {
name: "get_current_time",
description: "Get the current time",
parameters: {
type: "object",
properties: {},
},
};
factory.addFunction(getCurrentTimeSchema, getCurrentTime);
OpenAIAssistantsFunctionsStreamingClass.js
STEP 1: Create the constructor to initialize the class.
OpenAIAssistantsFunctionsStreamingClass.js
constructor(openAIAssistantId, functionFactory, openai, simulateTypingDelay = 0) {
this.simulateTypingDelay = simulateTypingDelay;
this.openAIAssistantId = openAIAssistantId;
this.functionFactory = functionFactory;
this.thread = null;
this.openai = openai;
}
STEP 2: Implement methods to create/retrieve threads and get messages.
OpenAIAssistantsFunctionsStreamingClass.js
async createThread() {
this.thread = await this.openai.beta.threads.create();
return this.thread;
}
async retrieveThread(threadId) {
this.thread = await this.openai.beta.threads.retrieve(threadId);
return this.thread;
}
async getThreadMessages(callback) {
const messages = await this.openai.beta.threads.messages.list(this.thread.id);
messages.data.reverse();
for (const message of messages.data) {
let content = message.content.map(item => item.text.value).join('') + '\n\n';
callback(message.role, content);
}
}
STEP 3: Implement the method to get the assistant's response.
OpenAIAssistantsFunctionsStreamingClass.js
async getResponse(userInput, callback) {
if (this.thread == null) {
await this.createThread();
}
await this.openai.beta.threads.messages.create(this.thread.id, { role: "user", content: userInput });
let stream = await this.openai.beta.threads.runs.stream(this.thread.id, {
assistant_id: this.openAIAssistantId,
tools: this.functionFactory.getTools()
});
let runCompletedPromise = new Promise((resolve) => {
this.resolveRunCompletedPromise = resolve;
});
await this.handleStreamEvents(stream, callback);
await runCompletedPromise;
runCompletedPromise = null;
}
STEP 4: Handle stream events and tool calls.
OpenAIAssistantsFunctionsStreamingClass.js
async handleStreamEvents(stream, callback) {
stream.on('textDelta', async (textDelta, snapshot) => await this.onTextDelta(textDelta, callback));
stream.on('event', async (event) => {
if (event.event == 'thread.run.completed') {
this.resolveRunCompletedPromise();
}
else if (event.event == 'thread.run.failed') {
console.log(JSON.stringify(event));
throw new Error('Run failed');
}
else if (event.event == 'thread.run.requires_action') {
await this.onThreadRunRequiresAction(event, callback);
}
});
}
async onTextDelta(textDelta, callback) {
let content = textDelta.value;
if (content != null) {
if(callback != null) {
callback(content);
if (this.simulateTypingDelay > 0) {
await new Promise(r => setTimeout(r, this.simulateTypingDelay));
}
}
}
}
async onThreadRunRequiresAction(event, callback) {
let toolCalls = event.data?.required_action?.submit_tool_outputs?.tool_calls;
if (toolCalls != null) {
let tool_outputs = this.getToolOutputs(toolCalls);
let stream = await this.openai.beta.threads.runs.submitToolOutputsStream(this.thread.id, event.data.id, { tool_outputs: tool_outputs})
await this.handleStreamEvents(stream, callback);
}
}
getToolOutputs(toolCalls) {
let tool_outputs = [];
for (let toolCall of toolCalls) {
if (toolCall.type == 'function') {
let result = this.functionFactory.tryCallFunction(toolCall.function?.name, toolCall.function?.arguments);
tool_outputs.push({
output: result,
tool_call_id: toolCall.id
});
}
}
return tool_outputs;
}