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-# Qwen3 Docker Deployment for PansGPT
-
-This folder contains all the files needed to deploy a stable, Docker-based Qwen3 embedding API to Hugging Face Spaces for your PansGPT application.
-
-## 📁 Files Overview
-
-### Core Application Files
-- **`app.py`** - Main FastAPI application with Qwen3-Embedding-0.6B model
-- **`Dockerfile`** - Optimized Docker configuration for Hugging Face Spaces
-- **`requirements.txt`** - Python dependencies for the application
-
-### Integration Files
-- **`qwen-embedding-service-docker.ts`** - TypeScript service for your PansGPT app
-- **`test-pansgpt-api.js`** - Test script to verify the deployed API
-
-### Deployment Files
-- **`deploy-to-hf.sh`** - Automated deployment script for Hugging Face Spaces
-
-## 🚀 Quick Start
-
-### 1. Deploy to Hugging Face Spaces
-
-```bash
-# Make sure you're logged in to Hugging Face
-huggingface-cli login --token YOUR_TOKEN
-
-# Deploy using the script
-./deploy-to-hf.sh
-```
-
-### 2. Manual Deployment
-
-```bash
-# Clone your space
-git clone https://YOUR_TOKEN@huggingface.co/spaces/YOUR_USERNAME/YOUR_SPACE_NAME
-
-# Copy files to the space directory
-cp app.py Dockerfile requirements.txt README.md YOUR_SPACE_NAME/
-
-# Commit and push
-cd YOUR_SPACE_NAME
-git add .
-git commit -m "Add Qwen3 embedding API"
-git push
-```
-
-### 3. Test the Deployment
-
-```bash
-# Test the deployed API
-node test-pansgpt-api.js
-```
-
-## 🔧 Integration with PansGPT
-
-### Update Your .env File
-```env
-QWEN_API_URL=https://your-username-your-space-name.hf.space/api/predict
-```
-
-### Replace Your Embedding Service
-1. Copy `qwen-embedding-service-docker.ts` to `src/lib/`
-2. Update your imports to use the new service
-3. The new service uses direct HTTP calls instead of Gradio client
-
-### Example Usage
-```typescript
-import { generateEmbeddings } from './qwen-embedding-service-docker';
-
-// Generate embeddings
-const embeddings = await generateEmbeddings(["Your text here"]);
-```
-
-## 📊 API Endpoints
-
-- **Main API**: `POST /api/predict`
-- **Health Check**: `GET /health`
-- **Web Interface**: Available at your space URL
-
-### API Usage Examples
-
-#### Single Text Embedding
-```bash
-curl -X POST "https://your-space.hf.space/api/predict" \
-  -H "Content-Type: application/json" \
-  -d '{"data": ["Your text here"]}'
-```
-
-#### Batch Text Embedding
-```bash
-curl -X POST "https://your-space.hf.space/api/predict" \
-  -H "Content-Type: application/json" \
-  -d '{"data": [["Text 1", "Text 2", "Text 3"]]}'
-```
-
-## 🎯 Model Information
-
-- **Model**: Qwen3-Embedding-0.6B
-- **Dimensions**: 1024
-- **Context Length**: 32K tokens
-- **Languages**: 100+ languages supported
-- **Performance**: State-of-the-art on MTEB benchmark
-
-## 🔍 Troubleshooting
-
-### Common Issues
-
-1. **Space Not Building**
-   - Check the space logs in Hugging Face
-   - Ensure all files are properly uploaded
-   - Verify Dockerfile syntax
-
-2. **API Not Responding**
-   - Wait 2-5 minutes for the space to fully start
-   - Check the health endpoint: `/health`
-   - Verify the space is running (not sleeping)
-
-3. **Embedding Errors**
-   - Check model loading in the logs
-   - Verify input text format
-   - Ensure text is not too long (max 512 tokens)
-
-### Health Check
-```bash
-curl https://your-space.hf.space/health
-```
-
-Expected response:
-```json
-{
-  "status": "healthy",
-  "model_loaded": true
-}
-```
-
-## 📈 Performance
-
-- **Response Time**: 100-500ms per request
-- **Memory Usage**: 2-4GB RAM
-- **Concurrent Requests**: Multiple simultaneous requests supported
-- **Uptime**: Much more stable than Gradio client connections
-
-## 🔄 Updates
-
-To update your deployed space:
-
-1. Make changes to the files in this folder
-2. Upload the updated files to your Hugging Face Space
-3. The space will automatically rebuild with the new changes
-
-## 📝 Notes
-
-- This Docker-based deployment is much more stable than the previous Gradio client approach
-- The Qwen3 model provides better embeddings than the previous Qwen2.5 model
-- All files are optimized for Hugging Face Spaces deployment
-- The service includes comprehensive error handling and fallback mechanisms
-
-## 🆘 Support
-
-If you encounter issues:
-1. Check the space logs in Hugging Face
-2. Verify your API URL is correct
-3. Ensure the space is running and not sleeping
-4. Test with the provided test script
-
----
-
-**Deployment Status**: ✅ Ready for production use
-**Last Updated**: September 2025
-**Model Version**: Qwen3-Embedding-0.6B