title	Qwen2API
emoji	🚀
colorFrom	blue
colorTo	indigo
sdk	docker
pinned	false

Qwen2API

中文文档 | English

A proxy service that converts Qwen Chat to an OpenAI-compatible API.

Features

• 🔄 OpenAI API compatible format
• 🚀 Streaming response support (SSE)
• 🔐 Optional API Token authentication
• 🌐 Multi-platform deployment support
• 🖼️ Image generation support
• 🎬📄 Video analysis, image and document parsing support
• 💬 Built-in web chat interface

Deployment

Docker

# Build image
docker build -t qwen2api .

# Run container
docker run -d -p 8765:8765 -e API_TOKENS=your_token qwen2api

Hugging Face Spaces (Docker)

1. Create a new Docker Space on Hugging Face.
2. Push this repository to the Space.
3. Optional: set API_TOKENS in Space Variables/Secrets.
4. The app listens on port 7860 in container mode (already configured in Dockerfile).

Vercel

1. Fork this repository
2. Import the project in Vercel
3. Optional: Set environment variable API_TOKENS

Netlify

1. Fork this repository
2. Import the project in Netlify
3. Optional: Set environment variable API_TOKENS

Cloudflare Workers

# Install wrangler
npm install -g wrangler

# Login
wrangler login

# Deploy
wrangler deploy

Set the environment variable API_TOKENS in the Cloudflare Dashboard.

Public Services

Two public services are available for testing:

Service URL	Platform
https://qwen2api-n.smanx.xx.kg	Netlify
https://qwen2api-v.smanx.xx.kg	Vercel (Usage limit exceeded, service stopped)

• No API Token required (leave key empty)
• Self-deployment is recommended for more stable service

Important Notes

• ✅ The /v1/chat/completions endpoint now supports attachments and multimodal message parts, including image/file/audio inputs.
• ✅ Supports image understanding and document parsing workflows in chat requests.
• ⚠️ Attachments are uploaded to Qwen OSS through the same workflow used by Qwen Web, so request latency increases when sending large files.
• ❌ Tool calling is not supported - The project does not implement OpenAI-style tool/function calling capabilities.

Limitations (Video URL / Large Files)

• Video URL analysis and large-file analysis are not supported on serverless function deployments (e.g. Vercel / Netlify Functions / Cloudflare Workers). These environments typically have strict limits on runtime, request body size, and filesystem/process access.
• Video URL analysis requires yt-dlp to be installed on the host machine. Use the Docker/local Express deployment if you need this feature.

Attachment Compatibility (OpenAI-style)

You can use these message content part formats in messages[].content arrays:

• {"type":"text","text":"..."} / {"type":"input_text","input_text":"..."}
• {"type":"image_url","image_url":{"url":"https://..."}}
• {"type":"input_image","image_url":"https://..."}
• {"type":"file","file_data":"data:...base64,...","filename":"a.pdf"}
• {"type":"input_file","file_data":"<base64>","filename":"a.txt"}
• {"type":"audio","file_data":"https://..."} / {"type":"input_audio", ...}

The proxy also accepts legacy message-level files / attachments arrays for compatibility.

Environment Variables

Variable	Description	Required
API_TOKENS	API keys, multiple keys separated by commas	No
CHAT_DETAIL_LOG	Enable detailed chat/upload logs (true/1/on/yes to enable, default off)	No
JSON_BODY_LIMIT	Express JSON body size limit (default 20mb, only for local/Docker Express runtime)	No

Note: Web search is now enabled by default for all models. The ENABLE_SEARCH variable has been deprecated.

Usage

API Endpoints

Endpoint	Method	Description
/v1/models	GET	Get model list
/v1/chat/completions	POST	Chat completion
/v1/images/generations	POST	Image generation
/chat	GET	Built-in web chat UI
/	GET	Health check

Web Chat UI

Open https://your-domain/chat in a browser to use the built-in chat page.

• Supports streaming output, attachments, and an optional video URL (auto switches to video analysis when a URL is provided)
• Logs panel can be toggled on/off; when enabled the request uses /v1/chat/completions/log
• Language toggle (ZH/EN) is available in the top bar

Request Examples

# Get model list
curl https://your-domain/v1/models \
  -H "Authorization: Bearer your_token"

# Chat completion
curl https://your-domain/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your_token" \
  -d '{
    "model": "qwen3.5-plus",
    "messages": [{"role": "user", "content": "Hello!"}],
    "stream": true
  }'

# Image generation (ratio string format)
curl https://your-domain/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your_token" \
  -d '{
    "model": "qwen3.5-plus",
    "prompt": "A cute kitten in a garden",
    "n": 1,
    "size": "1:1",
    "response_format": "url"
  }'

# Image generation (OpenAI size format)
curl https://your-domain/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your_token" \
  -d '{
    "model": "qwen3.5-plus",
    "prompt": "A beautiful landscape",
    "n": 1,
    "size": "1024x1024",
    "response_format": "b64_json"
  }'

Image Generation Parameter Reference

Request Parameters

Parameter	Type	Required	Description
model	string	No	Model name, default: qwen3.5-plus
prompt	string	Yes	Image description text
n	number	No	Number of images to generate, default: 1, max: 10
size	string	No	Image size/ratio, default: 1:1
response_format	string	No	Response format: url (default) or b64_json

Supported size parameter formats

Format 1: Ratio string (recommended)

• 1:1 - Square
• 16:9 - Widescreen (landscape)
• 9:16 - Portrait (vertical)
• 4:3 - Traditional ratio (landscape)
• 3:4 - Traditional ratio (portrait)

Format 2: OpenAI compatible size format

• 1024x1024 - Automatically maps to closest ratio (1:1)
• 1920x1080 - Automatically maps to closest ratio (16:9)
• Any other width/height combination will automatically map to a supported ratio

Response Formats

url format (default):

{
  "created": 1234567890,
  "data": [
    {
      "url": "https://example.com/image.png"
    }
  ]
}

b64_json format:

{
  "created": 1234567890,
  "data": [
    {
      "b64_json": "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJ..."
    }
  ]
}

OpenAI SDK Examples

from openai import OpenAI

client = OpenAI(
    api_key="your_token",
    base_url="https://your-domain/v1"
)

response = client.chat.completions.create(
    model="qwen3.5-plus",
    messages=[{"role": "user", "content": "Hello!"}],
    stream=True
)

for chunk in response:
    print(chunk.choices[0].delta.content, end="")

import OpenAI from 'openai';

const client = new OpenAI({
  apiKey: 'your_token',
  baseURL: 'https://your-domain/v1'
});

const stream = await client.chat.completions.create({
  model: 'qwen3.5-plus',
  messages: [{ role: 'user', content: 'Hello!' }],
  stream: true
});

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content || '');
}

Supported Models

• qwen3.5-plus
• qwen3.5-flash
• qwen3.5-turbo
• And other models supported by Qwen Chat

Project Structure

qwen2api/
├── core.js              # Core business logic
├── index.js             # Docker / Local entry point
├── api/
│   └── index.js         # Vercel entry point
├── netlify/
│   └── functions/
│       └── api.js       # Netlify entry point
├── worker.js            # Cloudflare Workers entry point
├── Dockerfile
├── vercel.json
├── netlify.toml
└── wrangler.toml

Local Development

# Install dependencies
npm install

# Start development server
npm run dev

# Server runs at http://localhost:8765

Disclaimer

This project is for learning and testing purposes only. Do not use it in production or commercial environments. Users are solely responsible for any consequences arising from the use of this project, and the project author assumes no liability.

License

MIT