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…threads for non-blocking code indexing and search - Introduces a vector database service using ChromaDB for semantic code search. - Implements worker threads to handle embedding generation and database operations in the background, preventing UI blocking. - Uses Gemini embeddings consistently across the application for reliable search results. - Adds support for indexing code snippets, performing semantic searches, and managing the vector database. - Implements VectorDbWorkerManager to manage worker threads and report progress updates.
- Integrate ChromaDB for local vector database storage. - Implement non-blocking worker threads for embedding and indexing operations using . - Introduce smart embedding strategy with immediate, on-demand, background, and bulk processing phases. - Enhance SmartContextExtractor with vector-based semantic search and keyword-based fallback. - Add new documentation files under to describe implementation details, usage and the roadmap.
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