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rag GitHub repositories

Explore 275 tracked GitHub repositories tagged rag. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-28. The collection gained 6,567 stars since the previous daily snapshot.

Tracked repositories
275
Total stars
2,987,440
Stars gained · 7 days
+36,112
Stars gained · 30 days
+112,577

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Star activity for rag repositories on this page
RepositoryTotal starsToday7 days30 days
askimo-ai/askimo538+0+5+32
Jakedismo/codegraph-rust907+0+5+19
Muvon/octocode518+0+5+11
modelscope/ms-cookbook507+0+5+5
FalkorDB/GraphRAG-SDK1.0K+0+4+25

Explore repositories

Showing 201–250 of 275 tracked repositories.

TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.

benmaster82/Kwipu

Ask questions across your Markdown notes using a fully local Graph RAG engine. Built for Obsidian vaults, works with any folder of Markdown files. Extracts entity-relation triples from wikilinks & YAML frontmatter, retrieves answers via hybrid search (vector + BM25 + temporal). Multilingual. No cloud. Runs on Ollama.

docsagent/docsagent

⚡ DocsAgent — give your AI agents instant, private access to your personal knowledge base (Zotero, Obsidian, Apple Notes supported now, local docs on the road). Native C++ search core: BM25 + passage ranking in ~15 ms. MCP server for Claude, Cursor, Cline & any MCP client.

Bessouat40/RAGLight

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

MemoriLabs/Memori

Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems. Built for enterprise, Memori works with the data infrastructure you already run, no rip-and-replace, and deploys across managed cloud, single-tenant cloud, VPC, and on-premises.