Open-Source RAG Frameworks

Yuxi is a self-hosted AI agent platform for teams that need answers from their documents and agents that can carry out multi-step work. Its browser workspace brings knowledge sources, task progress and generated files into the same conversation.

RESTai is a self-hosted AI platform for developers and teams building document assistants, agents and AI services for other applications. Its web interface manages projects with separate models, prompts and tools, plus a chat playground for testing them.

BotSharp is a C# framework for .NET developers building AI assistants into business applications. It coordinates agents with different responsibilities and keeps track of conversation state.

Kaito manages LLM inference, fine-tuning and document retrieval services in Kubernetes. It's for teams that want to run models in their own cluster with less manual work sizing GPU capacity and managing deployments.

DocsGPT helps teams search company documents and build AI assistants that answer from those materials. It can run inside your network with local models, including an air-gapped deployment where documents and questions stay within that network.

haiku.rag lets you search your own documents and ask questions with answers you can check against the original pages. It's for people building a private document library or giving an AI assistant access to their files.

HippoRAG is a Python memory and retrieval framework for developers building LLM applications that need to connect facts across documents. It uses a knowledge graph to find related information for questions that require several pieces of evidence.

Cognee gives AI agents memory across sessions so they can reuse project context, decisions, and lessons from earlier work. It's for developers building agents and teams whose knowledge sits across documents, code, and conversations.

LightRAG is a self-hosted framework for developers building AI assistants that answer questions across documents. It connects related facts across files, including material where relationships matter, such as legal and financial records.

DSPy is a Python framework for developers building language model applications with local backends such as Ollama on a laptop or SGLang on a GPU server. It connects application code to those model servers, which handle inference on your hardware. It also supports cloud providers, so where model requests go depends on the backend you choose.

RubyLLM is an AI framework for Ruby and Rails developers building chat and agent features into their applications. Its shared API lets you switch between local and hosted models without writing a separate integration for each provider.

Pathway's Live Data Framework is a Python framework for developers building RAG applications and analytics over changing data. It runs locally or on your own servers, including through Docker. Its incremental engine updates results as data arrives, so applications can work with changing documents and events.

UltraRAG is a self-hosted framework for researchers and developers building AI systems that answer questions using their own documents. Its Python application and Docker deployment provide a browser workspace for knowledge bases, workflow design and evaluation. Generation can use local models through vLLM or Hugging Face. Embeddings can use local Sentence Transformers or a configured OpenAI service; the OpenAI cloud connection sends embedding inputs to that service.

SimpleMem is a memory system for developers building AI agents that need to recall past conversations and stored media without passing the full history to a model each time.

Agent Service Toolkit is a Python template for developers building their own AI agent services. It brings together agent logic, an API and a browser chat interface so you don't have to build each part from scratch.

CocoIndex is an open-source AI indexing framework for developers processing codebases and documents on their own hardware. Its code indexing example uses sentence-transformers for embeddings and writes to pgvector or LanceDB, giving it a concrete role in preparing searchable context for agents and LLM apps.

kotaemon is an open source document chat app for people who want to ask questions across their files and inspect the evidence behind an answer. Developers can also use it to build custom document question-answering applications.

RAG-Anything is a Python framework for developers building question-answering systems over documents that mix prose with visual or structured content. Built on LightRAG, it suits research papers, technical manuals and financial reports where answers depend on figures, tables or formulas.

LangChainGo is a Go implementation of LangChain for developers adding language models to their own applications. It provides reusable components for connecting models to documents, tools, and conversation history.

FlashRAG is an open source Python toolkit for researchers and developers comparing retrieval-augmented generation (RAG) methods or building their own. It combines implemented research methods with prepared benchmark datasets and reported results, so experiments don't have to start with a separate codebase for each approach. It uses the MIT license.

PaperQA2 is a Python research assistant for researchers and developers who need answers grounded in scientific literature. It searches a local document collection and connects its answers to evidence through in-text citations.

MiniRAG is a Python framework for developers building question-answering tools over their own data with small language models. It targets on-device applications where larger models and heavier retrieval systems are difficult to use.

LazyLLM is a Python framework for developers building applications with multiple AI agents. It brings application workflows, model training and evaluation together so teams can refine a prototype using task-specific data.

txtai is a Python framework for developers building search, chat with their data, and AI agents on their own hardware. It combines a searchable knowledge store with model workflows, so applications can retrieve context and act on it.

LlamaIndex is a Python framework for developers building AI agents and applications that answer questions using their own data. It provides the connections and retrieval tools needed to give a language model relevant context from documents and other sources.

FastGPT is an AI agent builder for teams creating document-based assistants and business workflows. It suits internal knowledge search, customer support and applications that combine answers with actions.

Kiln is a desktop workbench for teams building and testing AI applications. Engineers, QA staff and subject matter experts can work with the same tasks and datasets, including contributing ratings and examples without writing code.

Haystack is a Python framework for developers building AI agents, document search and applications that answer questions using their own data. Its pipelines give teams control over the information a model receives and the steps that produce an answer.

RuoYi AI is a self-hosted AI assistant platform for teams building assistants that answer questions about their documents or perform tasks with external tools. It has separate user and admin interfaces.

OGX, formerly Llama Stack, is an AI application server for developers building chat apps, document search and AI agents. It brings model access and the services those applications need into a server you can host yourself.

Flexible GraphRAG is a self-hosted platform for teams building document search and AI chat that use both text and relationships between entities. It extracts knowledge graphs from documents and combines graph retrieval with vector similarity and full-text search. You can run it standalone or in Docker. It's open source under Apache 2.0.

Langflow is a visual builder for developers creating AI agents and applications that answer questions using connected data. It lets you assemble workflows visually and customize their components in Python.

Chonkie is a library for developers preparing documents for retrieval-augmented generation (RAG). It brings document preparation and ingestion into one pipeline, with optional components to keep dependencies small.

RocketRide is an AI pipeline builder and runtime for developers creating document processing, search, and agent workflows. Its visual editor sits in VS Code, alongside the application code that uses those workflows.