- Create LLMSelectorCompact component for model selection
- Support Ollama and NVIDIA models
- Load available models from localStorage
- Persist selected model and dispatch selection events
- Compact design suitable for inline placement
- Update metrics endpoint to use getGraphDbService utility
- Support both ArangoDB and Neo4j database types
- Initialize graph database based on selected type
- Retrieve graph stats from the active database
- 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
- Create new /api/graph-query-llm endpoint for graph search + LLM generation
- Retrieves triples using graph search and generates answers using LLM
- Supports both traditional and vector-based graph search
- Makes traditional graph search comparable to RAG for benchmarking
