7 open-source RAG repos around GPT-6 Astra
A seven-layer toolchain for turning company docs into a recallable knowledge base: parsing, chunking, vector store, graph retrieval, memory, evaluation and tracing, with the model swappable at any time.
7 GitHub repos around GPT 6 Astra turn company docs into a knowledge system that actually recalls 01 Docling ▸ https://github.com/docling-project/docling → parses PDFs and Office into structured model input 02 Chonkie ▸ https://github.com/chonkie-inc/chonkie → chunks and ships documents for retrieval 03 Qdrant ▸ https://github.com/qdrant/qdrant → stores embeddings for fast similarity search 04 LightRAG ▸ https://github.com/HKUDS/LightRAG → mixes graph and vector retrieval in one pipeline 05 Zep ▸ https://github.com/getzep/zep → keeps agent memory and context across sessions 06 Ragas ▸ https://github.com/explodinggradients/ragas → scores whether the retrieval answers are any good 07 Opik ▸ https://github.com/comet-ml/opik → traces the full run when answers go wrong Astra should spend tokens on judgment, not rediscovering the same PDF Parsing, chunking, search, memory and evals stay in dedicated layers Replace the model tomorrow and the knowledge stack still holds
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