@llama_index
Our OSS engineer @itsclelia recently built ๐น๐ถ๐๐ฒ๐๐ฒ๐ฎ๐ฟ๐ฐ๐ต, a fully local document ingestion and retrieval CLI/TUI application powered by LiteParse โก litesearch demonstrates how developers can assemble a high-performance, local-first retrieval pipeline using open tools from across the ecosystem: โข Parsing: LiteParse, the fast and accurate document parser we recently open sourced โข Chunking: @ChonkieAI โข Embeddings: A local @nomic_ai model via @huggingface transformers.js โข Vector storage: A local @qdrant_engine edge shard (custom-built in Rust and compiled as a native add-on) โข Retrieval: Query stored files with optional path-based filtering and configurable relevance thresholds โข Runtime: @bunjavascript for speed and versatility ๐ป Check out the repository and try it yourself: https://t.co/N0TyLbwvpm ๐ LiteParse docs: https://t.co/4C5ky7iIOa