Codebase Index
Indexes codebases using Qdrant vector storage and Google Gemini embeddings to provide semantic search capabilities over code with intelligent chunking, incremental updates, and natural language queries.
About
Codebase indexing server that integrates Qdrant Cloud vector storage with Google Gemini embedding models (text-embedding-004 or gemini-embedding-001) to enable natural language code search. Features incremental indexing with file change detection to reduce reprocessing time by 90%, intelligent code chunking by language-specific patterns (functions, classes) across Python, TypeScript, JavaScript, Java, Go, Rust, and Dart, and real-time file watching for automatic updates. Includes daily quota management to respect API limits, complexity scoring for code context, and 2D/3D vector visualization capabilities. Useful for understanding large projects, finding specific implementations, code review assistance, and developer onboarding.
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