- Removed deprecated user_info files and paths from configuration.
- Added user soil data integration in chat context to improve response accuracy.
- Updated build_rag_context and chat_rag_stream functions to include sensor_uuid for user-specific data retrieval.
- Enhanced load_sources function to load user data from the database.
- Implemented filtering in search_with_query and QdrantVectorStore to isolate user data based on sensor_uuid.
- Introduced Celery Beat schedule for periodic user data ingestion.
- Introduced LLM configuration in rag_config.yaml and corresponding LLMConfig class in config.py.
- Updated load_rag_config function to parse LLM settings from the configuration file.
- Added new API route for RAG in urls.py to facilitate access to the chat model.
- Modified QdrantVectorStore to use query_points method for improved functionality.
- Added Qdrant service to both docker-compose files for production and development.
- Updated environment variables in .env.example and settings.py to include Qdrant configuration.
- Included necessary dependencies for Qdrant and ChromaDB in requirements.txt.
- Updated .gitignore to exclude ChromaDB data files.
sajad-dev