SeaGOAT is an open-source semantic code search engine designed to help developers explore and understand large codebases more efficiently. Instead of relying solely on traditional keyword search, it uses vector embeddings to represent the meaning of code and queries, allowing users to perform semantic searches that find relevant code even when the exact keywords are not present. The tool runs locally on a developer’s machine and processes repositories using a combination of embedding models and conventional search utilities, enabling both semantic and text-based retrieval methods. By combining vector search with tools like ripgrep, SeaGOAT provides a hybrid approach that supports both natural language queries and precise keyword matching in source files. It is built primarily in Python and is intended to work on common operating systems such as Linux, macOS, and Windows.

Features

  • Semantic code search using vector embeddings
  • Local-first architecture with no external API dependency
  • Hybrid search combining semantic retrieval and traditional grep-style matching
  • Support for multiple operating systems including Linux, macOS, and Windows
  • Integration with tools such as ripgrep and optional syntax highlighting utilities
  • Repository indexing and query server for exploring large codebases

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License

MIT License

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

Registered

4 days ago