Elevate user interactions with ChatFAQ: your open-source chatbot solution, offering the full spectrum of ChatGPT capabilities. AI + LLM + CMS

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.

LLMs prompt augmentation with RAG by integrating external custom data from a variety of sources, allowing chat with such documents

🤖 Free Search with AI, 💡 Open-Source Perplexity, 📍 Support Ollama/SearXNG, Support Docker deployment. 让AI大模型和搜索引擎回答你的问题，支持本地大模型(Ollama)、聚合搜索引擎SearXNG，支持Docker一键部署。

A simple local Retrieval-Augmented Generation (RAG) chatbot that can answer to questions by acquiring information from personal PDF documents.

A modular graph-based Retrieval-Augmented Generation (RAG) system

AI Powered Search and Chat for Orgs - Think ChatGPT meets Google Search but powered by your data.

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

🔍 LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

Build an efficient Python-based Retrieval-Augmented Generation (RAG) system for contextual query answering over personal data, all with natural language using ChatGoogleGenerativeAI (gemini-pro).

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

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all available foundational models

RAG - LLM

The all-in-one LLM developer platform: prompt management, evaluation, human feedback, and deployment all in one place.

Concise RAG

Neo4j graph construction from unstructured data using LLMs

Open-source RAG Framework for building GenAI Second Brains 🧠 Build productivity assistant (RAG) ⚡️🤖 Chat with your docs (PDF, CSV, ...) & apps using Langchain, GPT 3.5 / 4 turbo, Private, Anthropic, VertexAI, Ollama, LLMs, Groq that you can share with users ! Efficient retrieval augmented generation framework

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.

RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.

GPT-powered chat for documentation, chat with your documents