ragflow
RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
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RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Data and AI pipeline project for checking inputs, outputs, state, latency, recovery, and deployment boundaries.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
LlamaIndex is the leading document agent and OCR platform
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Developer workflow project for checking task state, code/agent collaboration, permissions, and delivery boundaries.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Opiniated RAG for integrating GenAI in your apps 🧠 Focus on your product rather than the RAG. Easy integration in existing products with customisation! Any LLM: GPT4, Groq, Llama. Any Vectorstore: PGVector, Faiss. Any Files. Anyway you want.
[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"
A modular graph-based Retrieval-Augmented Generation (RAG) system
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Event Driven Orchestration & Scheduling Platform for Mission Critical Applications
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.
Self-hosted LLM web UI covering Docker deployment, auth, model backends, OAI/Ollama endpoints, and reverse proxy checks.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
LLM application framework for checking model, prompt, tool, retrieval, and chain integration boundaries.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Memori is agent-native memory infrastructure. A LLM-agnostic layer that turns agent execution and conversation into structured, persistent state for production systems.
Frontend agent and generative UI project for checking React/Angular integration, app actions, UI state, and UX boundaries.
Structured Outputs
From workspace to agent memory
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Convert any URL to an LLM-friendly input with a simple prefix https://r.jina.ai/
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
Incremental engine for long horizon agents 🌟 Star if you like it!
Observability and evaluation project for turning logs, quality metrics, drift, or experiment results into reviewable signals.
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings
High accuracy RAG for answering questions from scientific documents with citations
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Self-hosted LLM web UI covering Docker deployment, auth, model backends, OAI/Ollama endpoints, and reverse proxy checks.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Large Action Model framework to develop AI Web Agents
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
The easiest way to use Agentic RAG in any enterprise
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
A simple, easy-to-hack GraphRAG implementation
Easiest and laziest way for building multi-agent LLMs applications.
Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.
🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
🔍 Tiny, full-text search engine for static websites built with Rust and Wasm
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
The AI-Native Search Database. Best for agent storage, it unifies vector, text, structured, and semi-structured data into a single engine. This all-in-one database makes agents smarter, easier to run, and more stable.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
OpenKB: Open LLM Knowledge Base
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
[ACL2026] "MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
LLM application framework for checking model, prompt, tool, retrieval, and chain integration boundaries.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.
File Storage & Sandbox Backends for Pydantic AI: console tools for file operations, Docker-isolated sandboxes for safe execution, and permission system with presets for access control. Enables secure multi-user handling and testing in agents via in-memory, local, or containerized storage.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Filecoin Pin
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
The grainulation ecosystem. Structured research, decision-making, and knowledge management for AI agents.
Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.