pathwaycom/llm-app
Ready-to-run cloud templates for building real-time RAG, AI pipelines, and enterprise search applications that synchronize with various live data sources.
Awesome Infra for AI › Vector Databases & Retrieval Infrastructure
RyanCodrai/turbovec
TurboVec is an efficient vector index engineered in Rust with Python bindings, leveraging Google Research's TurboQuant algorithm. Its primary purpose is to provide highly compressed and fast approximate nearest neighbor (ANN) search for vector embeddings, significantly reducing memory footprint while often outperforming alternatives like FAISS in search speed. Key features include online ingestion without a separate training phase or rebuilds as the corpus grows, fast SIMD-optimized search kernels (NEON for ARM, AVX-512BW for x86), and powerful search-time filtering capabilities that honor allowlists to ensure recall with selective filters. Designed for local, air-gapped RAG stacks, TurboVec offers a pure local solution for privacy-sensitive, memory-constrained, or latency-critical applications. It provides direct integrations as drop-in replacements for in-memory vector stores in popular frameworks like LangChain, LlamaIndex, Haystack, and Agno, making it easy to swap into existing pipelines. The project emphasizes performance benchmarks, demonstrating superior recall, memory compression, and search speeds compared to baselines such as FAISS across various embedding dimensions and bit widths.
https://github.com/RyanCodrai/turbovec
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