- Add protobuf>=3.20.0 to requirements.txt (required for DeepSeek tokenizer)
- Add warning suppression for FutureWarning and rope_scaling messages
- Suppress slow image processor warnings
- These changes address the tokenizer loading issues with the new DeepSeek model
Update model to unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF
ndc8
c6f7b75
- Changed current_model in backend_service.py
- Updated ChatCompletionRequest default model
- Updated all test files to use new model
- Updated requirements.txt comment
- DeepSeek R1-0528 is a more modern and capable model than the previous gemma model
Revert model back to gemma-3n-E4B-it-GGUF
ndc8
88c3c6c
- Keep the original model as requested
- Maintain the fix for deprecated use_auth_token parameter
Fix: Update to valid HuggingFace model and fix deprecation warnings
ndc8
04d695c
- Changed model from 'gemma-3n-E4B-it-GGUF' to 'microsoft/DialoGPT-medium'
- Fixed deprecated 'use_auth_token' parameter to 'token'
- Updated test file to use the correct model name
upd
ndc8
2cd680b
fix
ndc8
255b6fc
fix
ndc8
84eb396
update
ndc8
e46cec3
upd
ndc8
68f41f4
update
ndc8
83df634
fix
ndc8
4599528
Ignore Hugging Face cache directory
ndc8
385d87b
fix
ndc8
e6598e6
Add API response endpoint and tests
ndc8
09c9042
Set gemma-3n-E4B-it-GGUF as main model for all text generation endpoints
- Update README metadata to use 'docker' SDK (required by HF Spaces)
- Add Dockerfile for containerized deployment
- Set correct app_port for FastAPI service
- Remove unsupported fastapi SDK configuration
This enables deployment to HuggingFace Spaces with Docker runtime.
🚀 Add multimodal AI capabilities with image-text-to-text pipeline
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4e10023
✨ Features:
- Integrated transformers pipeline for image analysis
- Added Salesforce BLIP model for image captioning
- Enhanced FastAPI backend with multimodal support
- OpenAI Vision API compatible message format
- Dual model architecture (text + vision)
- Comprehensive testing suite
🔧 Technical:
- Added Pydantic models for multimodal content
- Image processing utilities for URL handling
- Automatic request routing (text-only vs multimodal)
- Error handling and fallback mechanisms
- Updated dependencies for transformers, torch, PIL
📚 Documentation:
- Complete integration guide
- Updated README with multimodal examples
- Comprehensive testing documentation
- Usage examples for all endpoints
✅ Tested and validated:
- All 4 test categories passing
- Text-only chat functionality preserved
- Image analysis working perfectly
- Multimodal chat combining image + text
