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A Comprehensive OpenAI Assistants API V2 Wrapper: Simplifying AI Integration

Published at

9/10/2024

Key Features

Complete API Coverage: Includes all options from the Assistants API, providing full functionality.
Simple Streaming: Implements streaming capabilities without relying on external libraries.
Robust Error Handling: Designed to manage and report errors effectively.
Easy Setup: Minimal configuration required to get started.

Getting Started

Setting up the wrapper is straightforward:

git clone https://github.com/RaheesAhmed/openai-assistants-api-v2.git
cd openai-assistants-api-v2
npm install

Configure your environment by setting up a .env file:

OPENAI_API_KEY=your_openai_api_key

Core Functionalities

Creating an Assistant

const createAssistant = async () => {
  const response = await fetch('http://localhost:3000/create-assistant', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      name: "Data Analyst",
      instructions: "You are a data analysis assistant.",
      model: "gpt-4-1106-preview"
    })
  });
  const data = await response.json();
  console.log('Assistant created:', data);
};

Managing Threads and Messages

const createThreadAndMessage = async () => {
  // Create a thread
  const threadResponse = await fetch('http://localhost:3000/create-thread', {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      messages: [{ role: "user", content: "I need help analyzing this dataset." }]
    })
  });
  const thread = await threadResponse.json();

  // Add a message to the thread
  const messageResponse = await fetch(`http://localhost:3000/create-message/${thread.id}`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({
      role: "user",
      content: "Can you identify any trends in this data?"
    })
  });
  const message = await messageResponse.json();

  console.log('Thread and message created:', { thread, message });
};

Running an Assistant

const runAssistant = async (threadId, assistantId) => {
  const response = await fetch(`http://localhost:3000/create-run/${threadId}`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ assistant_id: assistantId })
  });
  const run = await response.json();
  console.log('Run created:', run);
};

Implementing Streaming

One of the key features of this wrapper is its built-in streaming capability:

const streamRun = async (threadId, runId) => {
  const response = await fetch(`http://localhost:3000/stream-run/${threadId}/${runId}`, {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ stream: true })
  });

  const reader = response.body.getReader();
  const decoder = new TextDecoder();

  while (true) {
    const { value, done } = await reader.read();
    if (done) break;
    console.log('Streamed data:', decoder.decode(value));
  }
};

Error Handling

The wrapper includes a global error handling middleware that catches and processes errors, returning them in a consistent format:

{
  "error": {
    "message": "Specific error message"
  }
}

This approach simplifies debugging and improves the overall reliability of your application.

Additional Features

File Operations: Upload, list, retrieve, and delete files associated with assistants.
Vector Stores: Manage vector stores for efficient information retrieval.
Configuration Management: Easily update rate limits, file size restrictions, and API keys.

Practical Applications

This wrapper is suitable for various applications, including:

Chatbots for customer service
Data analysis assistants
Educational tools and tutoring systems
Content generation platforms

Conclusion

This OpenAI Assistants API Wrapper offers a practical solution for developers looking to integrate OpenAI's capabilities into their projects. Its straightforward design, comprehensive coverage of the Assistants API, and built-in streaming support make it a valuable tool for AI-powered application development.

For more information, usage examples, or to contribute to the project, visit the GitHub repository.

Your feedback and contributions are welcome as we continue to improve and expand this tool.

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