- Integrate NVIDIA API as alternative to Ollama for graph queries
- Implement thinking tokens API with /think system message
- Add min_thinking_tokens (1024) and max_thinking_tokens (2048)
- Format reasoning_content with <think> tags for UI parsing
- Support dynamic model/provider selection per query
- Maintain Ollama fallback for backward compatibility
This enables Traditional Graph to use NVIDIA's reasoning models
(e.g., nvidia-nemotron-nano-9b-v2) with visible chain-of-thought.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Migrate from Pinecone to Qdrant vector database for native ARM64 support
- Add Qdrant service with automatic collection initialization in docker-compose
- Implement QdrantService with UUID-based point IDs to meet Qdrant requirements
- Update all API routes and frontend components to use Qdrant
- Enhance Storage Connections UI with detailed stats (vectors, status, dimensions)
- Add icons and tooltips to Vector DB section matching Graph DB UX
- Add queryWithLLM method to BackendService
- Retrieves top K triples from graph and uses LLM to generate answers
- Supports configurable LLM model and provider selection
- Uses research-backed prompt structure for KG-enhanced RAG
- Includes fallback handling for LLM errors
