Analyzes Python codebases using AST to extract and vectorize code elements, enabling advanced querying, semantic search, visualization, and natural language Q&A via a Model Context Protocol (MCP) server integrated with LLM-powered embeddings and background refinement.
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Distance threshold for semantic search
0.7Batch size for Weaviate operations
100Discover shared experiences
Gemini model for text generation
models/gemini-proLimit for semantic search results
5Weaviate host address
localhostGemini model for embeddings
models/embedding-001Weaviate HTTP port
8080Set to true to enable background LLM description generation and refinement
trueFile watcher polling interval in seconds
5Weaviate gRPC port
50051Your Gemini API key
Max concurrent background LLM tasks (embeddings/descriptions/refinements)
5Security Notice
Your environment variables and credentials are securely stored and encrypted. LangDB never shares these configuration values with third parties.
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