Spaces:
Sleeping
Sleeping
File size: 4,821 Bytes
5fd4bb2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 | # Migration Summary: Ollama → Hugging Face Spaces
## Overview
Successfully migrated the RAG system from local Ollama to Hugging Face Inference API for free, permanent cloud hosting.
## Changes Made
### 1. Core Files Modified
#### `llm_handler.py` ✅
- **Before**: Used `ollama` library for local LLM inference
- **After**: Uses `huggingface_hub.InferenceClient` for cloud inference
- **Key changes**:
- Replaced `ollama.Client` with `InferenceClient`
- Updated streaming logic for HF API
- Added token authentication
- Changed model to `meta-llama/Llama-3.2-3B-Instruct`
#### `config.py` ✅
- **Removed**:
```python
OLLAMA_MODEL = "llama3.2"
OLLAMA_BASE_URL = "http://localhost:11434"
```
- **Added**:
```python
HF_MODEL = "meta-llama/Llama-3.2-3B-Instruct"
HF_TOKEN = os.getenv("HF_TOKEN", "")
```
#### `requirements.txt` ✅
- **Removed**:
- `ollama==0.4.4`
- `langchain-ollama==0.2.2`
- **Added**:
- `huggingface_hub==0.20.3`
#### `main.py` ✅
- Added HF token validation on startup
- Updated error messages
- Removed Ollama-specific checks
### 2. New Files Created
#### `app.py` ✅
- Entry point for Hugging Face Spaces
- Validates HF_TOKEN from environment/secrets
- Provides clear setup instructions if token missing
- Launches Gradio interface with HF-specific settings
#### `README_HF.md` ✅
- Hugging Face Spaces README with YAML frontmatter
- Setup instructions for HF Spaces
- Usage examples
- Architecture diagram
- Rate limits and limitations
- Links to documentation
#### `ENV_SETUP.md` ✅
- Complete environment variables documentation
- Step-by-step token setup guide
- Examples for different platforms
- Verification commands
#### `test_hf_integration.py` ✅
- Comprehensive test suite
- Tests HF token, imports, API connection
- Tests LLM handler and vector store
- Provides clear pass/fail results
#### `DEPLOYMENT_GUIDE.md` ✅
- Step-by-step deployment instructions
- Local testing guide
- HF Spaces setup process
- Troubleshooting section
- Cost considerations
- Security best practices
### 3. Files Unchanged
- `document_converter.py` ✅ (no changes needed)
- `text_splitter.py` ✅ (no changes needed)
- `vector_store.py` ✅ (no changes needed)
- `README.md` ✅ (kept for local development)
- All documentation files ✅
## Architecture Comparison
### Before (Ollama)
```
User → Gradio → Vector Store → Ollama (Local) → Response
```
### After (HF Spaces)
```
User → Gradio → Vector Store → HF Inference API (Cloud) → Response
```
## Key Differences
| Aspect | Ollama (Before) | HF Spaces (After) |
|--------|----------------|-------------------|
| **Hosting** | Local only | Cloud (free) |
| **LLM** | llama3.2 (local) | Llama-3.2-3B-Instruct (cloud) |
| **Setup** | Install Ollama + model | Just HF token |
| **Cost** | Free (local compute) | Free (with rate limits) |
| **Availability** | Only when PC on | 24/7 |
| **Rate Limits** | None | ~1000 req/hour |
| **Scalability** | Limited by hardware | Managed by HF |
## Testing Checklist
Before deploying to HF Spaces, run:
```bash
# 1. Set HF token
export HF_TOKEN=hf_your_token_here
# 2. Install dependencies
pip install -r requirements.txt
# 3. Run tests
python test_hf_integration.py
# 4. Test locally
python app.py
```
## Deployment Steps
1. ✅ **Get HF Token**: https://huggingface.co/settings/tokens
2. ✅ **Test Locally**: Run `python test_hf_integration.py`
3. ⏳ **Create Space**: https://huggingface.co/new-space
4. ⏳ **Add Secret**: Space Settings → Repository secrets → `HF_TOKEN`
5. ⏳ **Push Code**: `git push hf main`
6. ⏳ **Verify**: Check Space URL and test
## Next Steps
### Immediate
1. Get Hugging Face token
2. Run local tests
3. Create HF Space
4. Deploy and verify
### Future Enhancements
- [ ] Add file upload functionality
- [ ] Support multiple documents
- [ ] Add conversation history
- [ ] Custom model selection
- [ ] Advanced filtering
- [ ] Export conversations
## Resources
- **HF Spaces Docs**: https://huggingface.co/docs/hub/spaces
- **HF Inference API**: https://huggingface.co/docs/api-inference/
- **Get Token**: https://huggingface.co/settings/tokens
- **Pricing**: https://huggingface.co/pricing
## Rollback Plan
If you need to revert to Ollama:
```bash
# Checkout previous commit
git log --oneline # Find commit before migration
git checkout <commit-hash>
# Or restore specific files
git checkout HEAD~1 llm_handler.py config.py requirements.txt
```
## Support
- **Documentation**: See `DEPLOYMENT_GUIDE.md`
- **Issues**: https://github.com/monsara/rag-python-rag/issues
- **HF Community**: https://discuss.huggingface.co/
---
**Migration completed**: ✅ All code changes done
**Ready to deploy**: ⏳ Awaiting HF Space creation and token setup
**Status**: Ready for testing and deployment
|