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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Open-source AI capabilities for searching, reading, summarizing, and organizing evidence-backed knowledge.
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
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 đź§ 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
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.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Find secrets with Gitleaks 🔑
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.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
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.
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.
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.
OpenVINO™ is an open source toolkit for optimizing and deploying AI inference
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.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
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.
The Open Source Feature Store for AI/ML
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.
Tiny and powerful JavaScript full-text search engine for browser and Node
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.
The open source platform for AI-native application development.
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.
The easiest way to use Agentic RAG in any enterprise
The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.
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
Native CSS search engine
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
OpenKB: Open LLM Knowledge Base
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.
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"
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.
A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data
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.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Open-source tool to visualise your RAG đź”®
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
Ship RAG based LLM web apps in seconds.
Lite & Super-fast re-ranking for your search & retrieval pipelines. Supports SoTA Listwise and Pairwise reranking based on LLMs and cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
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.
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.
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.
The grainulation ecosystem. Structured research, decision-making, and knowledge management for AI agents.
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.
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.
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.
Index and search Markdown vaults as knowledge graphs to provide AI agents with persistent, structured long-term memory across sessions.
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.
**An open-source cost controller for AI agent loops.**
MCP tool integration project for safely connecting external tools, services, or data sources to an AI host.
Preview local HTML reports, Markdown docs, and static mini apps, then publish
**Cut Claude Code's input tokens by rendering bulky context as images — the same system prompt, tool docs, and history, in a fraction of the tokens.**
Vector retrieval project for checking embedding storage, query semantics, RAG integration, data boundaries, and rollback.