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QUICK_REFERENCE.md

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-# Quick Reference - Qwen3 Docker Deployment
-
-## 🚀 Deploy to Hugging Face Spaces
-
-```bash
-# 1. Login to Hugging Face
-huggingface-cli login --token YOUR_TOKEN
-
-# 2. Deploy using script
-./deploy-to-hf.sh
-
-# 3. Or manually upload files
-huggingface-cli upload YOUR_USERNAME/YOUR_SPACE_NAME ./app.py app.py
-huggingface-cli upload YOUR_USERNAME/YOUR_SPACE_NAME ./Dockerfile Dockerfile
-huggingface-cli upload YOUR_USERNAME/YOUR_SPACE_NAME ./requirements.txt requirements.txt
-huggingface-cli upload YOUR_USERNAME/YOUR_SPACE_NAME ./README.md README.md
-```
-
-## 🔧 Update PansGPT App
-
-1. **Update .env file:**
-   ```env
-   QWEN_API_URL=https://your-username-your-space-name.hf.space/api/predict
-   ```
-
-2. **Replace embedding service:**
-   - Copy `qwen-embedding-service-docker.ts` to `src/lib/`
-   - Update imports in your app
-
-3. **Test the integration:**
-   ```bash
-   node test-pansgpt-api.js
-   ```
-
-## 📊 API Endpoints
-
-- **Main API**: `POST /api/predict`
-- **Health Check**: `GET /health`
-- **Web Interface**: Your space URL
-
-## 🎯 Model Info
-
-- **Model**: Qwen3-Embedding-0.6B
-- **Dimensions**: 1024
-- **Languages**: 100+
-- **Context**: 32K tokens
-
-## 🔍 Quick Test
-
-```bash
-# Test health
-curl https://your-space.hf.space/health
-
-# Test embedding
-curl -X POST "https://your-space.hf.space/api/predict" \
-  -H "Content-Type: application/json" \
-  -d '{"data": ["Hello world"]}'
-```
-
-## 📁 Files in This Folder
-
-- `app.py` - Main FastAPI application
-- `Dockerfile` - Docker configuration
-- `requirements.txt` - Python dependencies
-- `qwen-embedding-service-docker.ts` - PansGPT integration
-- `test-pansgpt-api.js` - Test script
-- `deploy-to-hf.sh` - Deployment script
-- `README.md` - Full documentation