Building a code search engine with Turso

Codemogger, a tool for semantic code search, leverages Turso's SQLite-based vector and full-text search capabilities to enable efficient code indexing and retrieval locally without external services. This tool addresses the need for searching code by meaning rather than just text, using a process that embeds code chunks and queries into vectors for cosine similarity matching. Codemogger uses Turso’s built-in vector storage to handle embeddings, offering a streamlined solution that integrates vector and full-text search in a single database file. The tool employs a hybrid search approach, combining vector and full-text search results for optimal accuracy, and is designed to operate fully offline, enhancing privacy and control. Its SDK allows for customizable embedding functions, making it adaptable to various semantic search needs, such as documentation search or log analysis, all while maintaining the simplicity and portability of SQLite.

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