RAG

A PHP framework for building generative AI applications and retrieval-augmented search, compatible with Symfony and Laravel and inspired by LangChain.

• Agent frameworks
• RAG

A CLI and MCP server that converts Korean government and office documents (HWP, HWPX, PDF, Office formats and scanned images) into Markdown, with table reconstruction, form filling and document diffing for AI agents to read and act on.

• MCP servers
• RAG

A PostgreSQL extension for scalable, disk-friendly vector search, the successor to pgvecto.rs, that compresses vectors with RaBitQ and autonomous reranking to cut storage cost while preserving search quality.

• RAG
• Databases

A step-by-step guide and interactive notebook for building and scaling a retrieval-augmented generation LLM application for production, from ingesting documents through serving and evaluation.

• RAG
• Tutorials

A GPU-accelerated reference architecture for building video analytics agents that search, summarize and answer questions over live or recorded video using vision-language and language models plus retrieval-augmented generation.

• Agent frameworks
• RAG

A bilingual and crosslingual embedding and reranker model pair for retrieval-augmented generation in English and Chinese, developed by NetEase Youdao and used in its own RAG products.

• RAG
• Models

A Rust search engine offering sub-millisecond native vector and lexical (BM25) search, usable as an in-process library or a multi-tenancy server, with a query planner that fuses both search modes.

• RAG
• Databases

A project generator that scaffolds a production-ready FastAPI and Next.js application with a choice of AI agent framework, a RAG pipeline and more than 20 enterprise integrations.

• Agent frameworks
• RAG

A local retrieval-augmented generation app that answers questions about your own PDFs, Word files and text using Ollama, citing the file and page each answer came from.

• RAG

A Ruby framework for building LLM-powered applications, providing a unified interface across providers such as Anthropic, AWS Bedrock, Google Gemini and OpenAI for embeddings, prompt completions, chat and retrieval-augmented generation.

• Agent frameworks
• RAG

A community-maintained directory of Retrieval-Augmented Generation frameworks, engines, evaluation tools and resources, with guidance on choosing between a RAG framework you integrate and a RAG engine you run as a standalone platform.

• RAG
• Curated lists

A CVPR 2025 benchmark for evaluating document-parsing systems across 1,651 pages of diverse real-world documents, with detailed block- and span-level annotations and evaluation code.

• RAG
• AI evals

An open-source, model-agnostic RAG platform with end-to-end tooling for ingestion, chunking, embeddings and retrieval, a chat playground with citations, multi-tenant hosting and a typed API, available hosted or self-hosted.

• RAG

A technique and library for distilling any sentence-transformer model into a small, fast static embedding model, cutting size by up to 50 times and inference time by up to 500 times for a small drop in accuracy.

• RAG
• Models

An archived Microsoft research project demonstrating a multi-modal memory service for LLM applications, indexing documents into embeddings for retrieval-augmented generation with citations.

• Agent memory
• RAG

A conversational data-analysis system that turns natural-language questions into validated SQL, runs them against a database, and renders the results as charts, using retrieval-augmented generation and a multi-agent pipeline.

• RAG
• Data engineering

An open-source knowledge base application, built on an original retrieval architecture called SAG, that turns uploaded documents into a searchable, source-traced knowledge graph and answers questions with citations back to the original text.

• RAG

Tutorials, demos and example notebooks for building applications on the Milvus vector database, covering retrieval-augmented generation, semantic and hybrid search, recommendation and other unstructured-data search use cases.

• RAG
• Tutorials

A cross-platform semantic memory layer for AI coding agents that stores conversations as Markdown files and indexes them in Milvus for hybrid vector and keyword search, so memory carries over between Claude Code, Codex, OpenClaw and other agents.

• Agent memory
• RAG

A code library for training and running vision-language document retrieval models such as ColPali, ColQwen2, and ColSmol that embed and search documents by their visual layout as well as their text.

• RAG
• Models

A MySQL-compatible embedded or server database that unifies vector, full-text, and structured search in one engine, designed as a fast, forkable state store for AI agents.

• RAG
• Databases

An open-source conversational knowledge base that answers questions over a graph-based retrieval-augmented-generation pipeline built on TiDB's vector storage.

• RAG
• Databases

An open-source federated search and retrieval-augmented-generation tool that queries an organization's existing apps and data sources live, without copying data into a vector database.

• RAG

A six-module open-source course that teaches how to build a production-ready retrieval-augmented-generation AI assistant over a personal knowledge base, using agents, LLMs and LLMOps practice.

• RAG
• Tutorials