Add RAG (Retrieval Augmented Generation) tools for storing documentation
in Qdrant vector database and querying with semantic search. This replaces
the Python tools/rag implementation with a native Go solution.
New commands:
- core rag ingest [directory] - Ingest markdown files into Qdrant
- core rag query [question] - Query vector database with semantic search
- core rag collections - List and manage Qdrant collections
Features:
- Markdown chunking by sections and paragraphs with overlap
- UTF-8 safe text handling for international content
- Automatic category detection from file paths
- Multiple output formats: text, JSON, LLM context injection
- Environment variable support for host configuration
Dependencies:
- github.com/qdrant/go-client (gRPC client)
- github.com/ollama/ollama/api (embeddings API)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
