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title Qwen2API
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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

Platform differences in authentication token acquisition directly affect chat stability. Read the Platform Comparison first.

Local NodeJS / Docker (Recommended)

These run a full Node runtime and can launch headless Chromium to run the real baxia SDK, producing stable auth tokens that are rarely blocked by upstream.

# Local
npm install
node index.js            # default port 8765 (override with PORT)

# Docker build + run
docker build -t qwen2api .
# NOTE: Chromium inside the container needs enough shared memory -- always add --shm-size
docker run -d -p 8765:8765 --shm-size=2g -e API_TOKENS=your_token qwen2api
  • The image is Debian-based and bundles chromium, ffmpeg, and yt-dlp.
  • CHROME_PATH=/usr/bin/chromium locates the browser automatically (see env table).
  • If Chromium cannot run in your environment, set USE_CHROME_BAXIA=false to fall back to the simplified token (less stable).

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

Deploy with Vercel

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

Vercel is a serverless platform and cannot run Chromium, so it only uses the simplified token path. It may be intermittently blocked by upstream risk control; stability is lower than local/Docker. The Vercel entry (api/index.js) uses the Node.js runtime and shares the same core.js logic as local/Docker and Netlify. Function timeout is set via module.exports.config.maxDuration (60s on Hobby, higher on Pro); SSE streaming is forwarded in real time (Vercel Node functions support streaming).

Netlify

Deploy to Netlify

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

Netlify Functions (Node runtime) are also serverless and cannot run Chromium, so behavior is similar to Vercel: simplified token + automatic retry, limited stability. The function timeout is configured in netlify.toml (max 26s on Pro/Enterprise, 10s on the free Hobby plan); streaming responses are buffered and returned whole.

Cloudflare Workers

# Install wrangler
npm install -g wrangler

# Login
wrangler login

# Deploy
wrangler deploy

Set the environment variable API_TOKENS in the Cloudflare Dashboard.

Cloudflare Workers are also serverless and cannot run Chromium; only the simplified token is available. The Worker entry (worker.js) is a thin wrapper that reuses the same core.js logic as local/Docker, Vercel and Netlify (requires the nodejs_compat compatibility flag, already set in wrangler.toml). SSE streaming is forwarded in real time. Video URL analysis / yt-dlp are not supported on Workers.

Platform Comparison

Aspect Local Node / Docker Vercel / Netlify / CF Workers
Chromium (real baxia SDK) ✅ Yes (stable token) ❌ No
Token acquisition Real T2gAv_ token + cookies (25-min cache) Simplified token (wu.json), low stability
Upstream risk control Rarely blocked Intermittently blocked (mitigated by retry)
Video URL / large files ✅ Supported (needs yt-dlp) ❌ Not supported (serverless limits)
Use case Self-hosted, daily use Quick deploy, light testing

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
CHROME_PATH Path to the Chromium/Chrome executable. Auto-detected from common locations (Windows/macOS/Linux) or PATH; usually not needed No
USE_CHROME_BAXIA Set to false to disable Chromium-based real token acquisition and fall back to the simplified token (for serverless or browser-less environments) 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": "qwen3.8-max",
    "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": "qwen3.8-max",
    "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": "qwen3.8-max",
    "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: qwen3.8-max
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="qwen3.8-max",
    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: 'qwen3.8-max',
  messages: [{ role: 'user', content: 'Hello!' }],
  stream: true
});

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

Supported Models

  • qwen3.8-max
  • qwen3.7-plus
  • qwen3.7-max
  • And other models supported by Qwen Chat

The model list is scraped dynamically from chat.qwen.ai; /v1/models returns the latest available models.

Project Structure

qwen2api/
├── core.js              # Core business logic
├── index.js             # Docker / Local entry point
├── api/
│   └── index.js         # Vercel entry point (Node runtime, reuses core.js)
├── netlify/
│   └── functions/
│       └── api.js       # Netlify Functions (Node) entry point
├── scripts/
│   ├── baxia-token.js   # Get token via real baxia SDK using Chromium (local/Docker)
│   └── tampermonkey.js  # Optional browser script
├── worker.js            # Cloudflare Workers entry point (reuses core.js)
├── 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

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

qwen2api-n.smanx.xx.kg

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