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@llama_index

Our OSS engineer @itsclelia recently built ๐—น๐—ถ๐˜๐—ฒ๐˜€๐—ฒ๐—ฎ๐—ฟ๐—ฐ๐—ต, a fully local document ingestion and retrieval CLI/TUI application powered by LiteParse โšก litesearch demonstrates how developers can assemble a high-performance, local-first retrieval pipeline using open tools from across the ecosystem: โ€ข Parsing: LiteParse, the fast and accurate document parser we recently open sourced โ€ข Chunking: @ChonkieAI โ€ข Embeddings: A local @nomic_ai model via @huggingface transformers.js โ€ข Vector storage: A local @qdrant_engine edge shard (custom-built in Rust and compiled as a native add-on) โ€ข Retrieval: Query stored files with optional path-based filtering and configurable relevance thresholds โ€ข Runtime: @bunjavascript for speed and versatility ๐Ÿ’ป Check out the repository and try it yourself: https://t.co/N0TyLbwvpm ๐Ÿ“š LiteParse docs: https://t.co/4C5ky7iIOa

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