Showing 1-20 of 46 projects
RAGFlow is an open-source RAG engine with agent capabilities for LLM context layering
AI pipelines for RAG, enterprise search, and document indexing with real-time data sync
RAG & Agent app for LLMs with local knowledge base support
LightRAG is a fast and simple Retrieval-Augmented Generation (RAG) framework for efficient knowledge retrieval and generation.
LLM-powered knowledge curation system for generating research reports with citations
AI orchestration framework for building LLM applications with pipelines and agents
Unified framework for building enterprise RAG pipelines with small, specialized models
An all-in-one Retrieval-Augmented Generation (RAG) framework for building multi-modal AI applications.
A Rust-based memory layer for AI agents, enabling serverless, single-file memory with instant retrieval and long-term storage.
All-in-one AI framework for semantic search, LLM orchestration and language model workflows
A Python repository for retrieval and retrieval-augmented LLMs
A Python library for efficient RAG (Retrieval-Augmented Generation) applications with AI-powered vector database and private storage.
A lightweight LLM framework that allows developers to build their own AI agents and workflows
An open agentic framework that enables computers to act like humans
A production-ready AI retrieval system with a RESTful API, built using Agentic Retrieval-Augmented Generation (RAG).
A comprehensive collection of resources for large language models, including AI coding tools, MCP frameworks, and more.
An OS-level memory layer for large language models, AI agents, and multi-agent systems with long-term, working, and external memory.
Open-source context retrieval layer for AI agents
An open-source platform for building AI-native applications using LLMs, agents, and retrieval-augmented generation.
A RAG (Retrieval Augmented Generation) framework for building modular, open-source AI applications by TrueFoundry.
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