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
redevops-io/redevops-rag
redevops-rag offers a robust Retrieval-Augmented Generation (RAG) pipeline designed for efficient information retrieval in AI applications. It combines dense vector search using Sentence-Transformers embeddings stored in DuckDB with sparse BM25 keyword matching. The system leverages Reciprocal Rank Fusion (RRF) to blend the results from both dense and sparse retrieval, further enhanced by recency and keyword priors to improve relevance. Optionally, it can integrate a cross-encoder reranker (e.g., BAAI/bge-reranker-v2-m3) for refining the top-k results. The project is specifically carved out from a multi-tenant SaaS platform, making it a standalone, installable library and CLI tool. It is designed to index content from local folders like documentation trees, code repositories, or personal vaults, providing a simple interface to chunk, embed, and index data. For answer synthesis, it is compatible with any OpenAI-compatible LLM endpoint, allowing users to connect to local servers, OpenAI, or Anthropic. This tool focuses purely on the retrieval and generation aspects of RAG, making it a highly relevant piece of infrastructure for AI inference workflows.
https://github.com/redevops-io/redevops-rag
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