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juandisay

code-memory-rs

by juandisay

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    • A
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      Enables semantic and keyword search over a local codebase by chunking source files along function and class boundaries, embedding them offline, and fusing vector and BM25 results. Runs entirely on your machine in a single SQLite file, so AI coding agents can find relevant code with no API keys, telemetry, or cloud calls.
      7
      19 npm
      MIT
    • A
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      Enables semantic code search across multiple repositories using AST-aware chunking and relationship tracking. Supports local LLM embeddings, real-time indexing, and cross-codebase dependency analysis through vector and graph databases.
      3
      MIT
    • A
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      Enables coding agents to search a locally indexed repository and get back a token-budgeted deck of ranked code and doc snippets instead of a full-tree grep dump, with lexical, semantic, and prose-answering modes plus index status reporting. Runs fully offline for lexical queries and optionally uses an OpenAI-compatible provider for semantic or ask modes.
      MIT
    • A
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      quality
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      Enables semantic code search for AI assistants by indexing codebases with embeddings and Tree-sitter, returning relevant snippets via natural language queries.
      15
      MIT
    • A
      license
      A
      quality
      A
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      Enables AI coding assistants to perform local semantic code search using AST parsing and embeddings, finding code by meaning with exact file and line locations, plus AST-based usage lookup.
      4
      MIT