retreival-augmented-generation
Quira is a next-gen Python RAG framework featuring speculative vector search, Context Tetris for token compression, and differential caching to eliminate redundant API costs.
Local-first Python RAG pipeline with sentence-transformer embeddings, FAISS/BM25 hybrid retrieval, query expansion, reranking, and Ollama-driven generation.
Citation-verified RAG service with deterministic + semantic claim verification.
Build RAG applications that answer questions over your Flatseek keyword indexes and Flatvec semantic indexes using any LLM.
