All-in-one infrastructure for building search, recommendations, and RAG. Trieve combines search language models with tools for tuning ranking and relevance.

Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on LLMs. 一个由工具、基准/数据、演示、排行榜和大模型等组成的精选列表，主要面向基础大模型评测，旨在探求生成式AI的技术边界.

Memory for AI agents

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

A python wrapper for the Doc2X API and comes with native PDF processing (to improve PDF recall in RAG).Doc2X API的python封装，同时附带本地的PDF处理(提升PDF在RAG中的召回率)。

RagE (RAG Engine) - A tool supporting the construction and training of components of the Retrieval-Augmented-Generation (RAG) model. It also facilitates the rapid development of Q&A systems and chatbots following the RAG model.

Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

Streamer-Sales 销冠 —— 卖货主播 LLM 大模型🛒🎁，一个能够根据给定的商品特点从激发用户购买意愿角度出发进行商品解说的卖货主播大模型。🚀⭐内含详细的数据生成流程❗ 📦另外还集成了 LMDeploy 加速推理🚀、RAG检索增强生成 📚、TTS文字转语音🔊、数字人生成 🦸、 Agent 使用网络查询实时信息🌐、ASR 语音转文字🎙️

Distributed vector search for AI-native applications

Indox is an advanced search and retrieval technique that efficiently extracts data from diverse document types, including PDFs and HTML, using online or offline large language models such as Openai, Hugging Face , etc.

User-friendly WebUI for LLMs (Formerly Ollama WebUI)

Wren AI makes your database RAG-ready. Implement Text-to-SQL more accurately and securely.

An LLM app that allows you to chat with WolfStreet articles

LlamaIndex is a data framework for your LLM applications

production-ready RAG engine with a sh*t ton of features.

🔥 Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

appbuilder-sdk, 千帆AppBuilder-SDK帮助开发者灵活、快速的搭建AI原生应用

Easyest and lazyest way for building multi-agent LLMs applications.

Test your prompts, agents, and RAGs. Use LLM evals to improve your app's quality and catch problems. Compare performance of GPT, Claude, Gemini, Llama, and more. Simple declarative configs with command line and CI/CD integration.