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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
The Web Data API for AI - Turn entire websites into LLM-ready markdown or structured data 🔥
Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/
AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
MemFree - Hybrid AI Search Engine & AI Page Generator
A Solution Accelerator for the RAG pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences. This includes most common requirements and best practices.
[COLM’25] DeepRetrieval — 🔥 The First Search Agent Trained by On-Policy Reinforcement Learning
🥥 Coco AI App - Search, Connect, Collaborate, Personal AI Search and Assistant, all in one space.
A simple Python program to implement the search-extract-summarize flow.
Powerful search page powered by LLMs and SearXNG
Oxylabs AI Studio python SDK
🥥 Coco AI Server - Search, Connect, Collaborate, AI-powered Enterprise Search, all in one space.
Discover existing open source projects 10x faster using AI search. This project leverages Vercel AI SDK, OpenAI & Tavily REST API to analyze Github search results and repo contents to find the best repo for your needs. Simply type a prompt and find projects to get started.
🤖🔎 STREAM: Search with Top Result Extraction & Answer Model 🔤📊 SEEKTOPIC 🚜📜 Tractor the Text Extractor 🕸️🖥️ Tardigrade the Web Crawler
Official n8n node for interfacing with Qdrant
A sample app for the Multimodal Retrieval-Augmented Generation pattern running in Azure, using Azure AI Search for retrieval and Azure OpenAI large language models to power Q&A experiences.
A RAG (Retrieval-Augmented Generation) solution Based on Advanced Pre-generated QA Pairs. 基于高级 QA 问答对预生成的 RAG 知识库解决方案
Sample for context-aware Agentic RaG, Q&A with multi-source verification, and self-curating knowledge base. Powered by Azure AI Foundry Agent Service, Azure AI Search with agentic retrieval and query rewrite, Semantic Kernel and LangGraph agents running in Azure Container Apps, and ready for Copilot Studio