R

Retrieval Augmented Generation

https://github.com/topoteretes/cognee Deterministic LLMs Outputs for AI Applications and AI Agents

🔧🔗https://github.com/getzep/graphiti

Build and query dynamic, temporally-aware Knowledge Graphs

🔧🔗https://github.com/modelscope/evalscope A streamlined and customizable framework for efficient large model evaluation and performance benchmarking

🔧🔗https://github.com/maragudk/gai-starter-kit Get started with LLMs, FTS and vector search, RAG, and more, in Go!

A multi-user ChatGPT for any LLMs and vector database. Unlimited documents, messages, and storage in one privacy-focused app. Now available as a desktop application with a built-in LLM!

🔧🔗https://github.com/VictoriaMetrics-Community/mcp-victoriametrics

The implementation of Model Context Protocol (MCP) server for VictoriaMetrics

🔧🔗https://github.com/modelscope/modelscope-agent

ModelScope-Agent: An agent framework connecting models in ModelScope with the world

🔧🔗https://github.com/HKUDS/MiniRAG

"MiniRAG: Making RAG Simpler with Small and Free Language Models"

🔧🔗https://github.com/llmware-ai/llmware

Unified framework for building enterprise RAG pipelines with small, specialized models

🕸️🔗https://llmware-ai.github.io/llmware/

🔧🔗https://github.com/decodingml/production-llm-rag-course

Second Brain Semantic AI Engine: Powered by LLMs & RAG

🔧🔗https://github.com/Gurubase/gurubase Gurubase lets you add an "Ask AI" button to your technical docs, turning your content into an AI assistant. It uses web pages, PDFs, YouTube videos, and GitHub repos as sources to generate instant, accurate answers with references. Deploy it via Slack, Discord, GitHub or a web widget.

🤖 𝗟𝗲𝗮𝗿𝗻 for 𝗳𝗿𝗲𝗲 how to 𝗯𝘂𝗶𝗹𝗱 an end-to-end 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗿𝗲𝗮𝗱𝘆 𝗟𝗟𝗠 & 𝗥𝗔𝗚 𝘀𝘆𝘀𝘁𝗲𝗺 using 𝗟𝗟𝗠𝗢𝗽𝘀 best practices: ~ 𝘴𝘰𝘶𝘳𝘤𝘦 𝘤𝘰𝘥𝘦 + 11 𝘩𝘢𝘯𝘥𝘴-𝘰𝘯 𝘭𝘦𝘴𝘴𝘰𝘯𝘴 https://github.com/decodingml/llm-twin-course