R

Retrieval Augmented Generation

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

Gen-AI Chat for Teams - Think ChatGPT if it had access to your team's unique knowledge.

docs.danswer.dev/

https://github.com/run-llama/llama_index LlamaIndex is a data framework for your LLM applications

🔧🔗https://github.com/open-webui/open-webui User-friendly AI Interface (Supports Ollama, OpenAI API, ...)

🕸️🔗https://openwebui.com/

🔧🔗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/getzep/graphiti

Build and query dynamic, temporally-aware Knowledge Graphs

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

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

https://github.com/run-llama/llama_parse Parse files for optimal RAG

🔧🔗https://github.com/patchy631/ai-engineering-hub In-depth tutorials on LLMs, RAGs and real-world AI agent applications.

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

🔧🔗https://github.com/HKUDS/LightRAG

"LightRAG: Simple and Fast Retrieval-Augmented Generation"

🔧🔗https://github.com/getzep/zep-python

Zep: Long-Term Memory for ‍AI Assistants (Python Client)

🔧🔗https://github.com/mendableai/firecrawl 🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

🔧🔗https://github.com/mendableai/firecrawl-app-examples 🔥 This repository contains complete application examples, including websites and other projects, developed using Firecrawl.

https://github.com/Blaizzy/mlx-embeddings MLX-Embeddings is the best package for running Vision and Language Embedding models locally on your Mac using MLX.

🔧🔗https://github.com/mem0ai/mem0 Memory for AI Agents; SOTA in AI Agent Memory; Announcing OpenMemory MCP - local and secure memory management.

https://github.com/InternLM/HuixiangDou HuixiangDou: Overcoming Group Chat Scenarios with LLM-based Technical Assistance

🔧🔗https://github.com/HKUDS/MiniRAG

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

🔧🔗https://github.com/manimohans/obsidian-local-llm-helper Seamlessly integrate your local LLM with Obsidian. Process large text chunks, transform content with AI, chat with your notes and maintain data privacy — all without leaving your notes.

🔧🔗https://github.com/npiv/ragaman A RAG (Retrieval-Augmented Generation) system for notes with support for REST API and Model Context Protocol (MCP).