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Zeng haolong
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66
README.md
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README.md
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@ -30,11 +30,15 @@
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<a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
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<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
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</a>
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<a href="https://deepwiki.com/infiniflow/ragflow">
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<img alt="Ask DeepWiki" src="https://deepwiki.com/badge.svg">
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</a>
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</p>
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<div align="center">
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[](https://deepwiki.com/infiniflow/ragflow)
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[](https://zread.ai/infiniflow/ragflow)
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</div>
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<h4 align="center">
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<a href="https://ragflow.io/docs/dev/">Document</a> |
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<a href="https://github.com/infiniflow/ragflow/issues/4214">Roadmap</a> |
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@ -61,8 +65,8 @@
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- 🔎 [System Architecture](#-system-architecture)
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- 🎬 [Get Started](#-get-started)
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- 🔧 [Configurations](#-configurations)
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- 🔧 [Build a Docker image](#-build-a-docker-image)
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- 🔨 [Launch service from source for development](#-launch-service-from-source-for-development)
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- 🔧 [Build a Docker Image](#-build-a-docker-image)
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- 🔨 [Launch Service from Source for Development](#-launch-service-from-source-for-development)
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- 📚 [Documentation](#-documentation)
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- 📜 [Roadmap](#-roadmap)
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- 🏄 [Community](#-community)
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@ -72,7 +76,7 @@
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## 💡 What is RAGFlow?
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[RAGFlow](https://ragflow.io/) 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. It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged context engine and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.
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[RAGFlow](https://ragflow.io/) is a leading open-source Retrieval-Augmented Generation (RAG) engine that combines cutting-edge RAG techniques with Agent capabilities to create a superior context layer for Large Language Models (LLMs). It offers a streamlined RAG workflow adaptable to enterprises of any scale. Powered by a converged context engine and pre-built agent templates, RAGFlow enables developers to transform complex data into high-fidelity, production-ready AI systems with exceptional efficiency and precision.
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## 🎮 Demo
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@ -85,8 +89,8 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
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## 🔥 Latest Updates
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- 2025-11-19 Supports Gemini 3 Pro.
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- 2025-11-12 Supports data synchronization from Confluence, S3, Notion, Discord, Google Drive.
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- 2025-11-19 Supports Google's latest Gemini 3 Pro.
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- 2025-11-12 Supports data synchronization from Confluence, S3, Notion, Discord, and Google Drive.
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- 2025-10-23 Supports MinerU & Docling as document parsing methods.
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- 2025-10-15 Supports orchestrable ingestion pipeline.
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- 2025-08-08 Supports OpenAI's latest GPT-5 series models.
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@ -97,8 +101,7 @@ Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
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## 🎉 Stay Tuned
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⭐️ Star our repository to stay up-to-date with exciting new features and improvements! Get instant notifications for new
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releases! 🌟
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🌟 Star our repository to stay up-to-date with exciting new features and improvements, and receive instant notifications for new releases! 🌟
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<div align="center" style="margin-top:20px;margin-bottom:20px;">
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<img src="https://github.com/user-attachments/assets/18c9707e-b8aa-4caf-a154-037089c105ba" width="1200"/>
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@ -115,9 +118,9 @@ releases! 🌟
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### 🍱 **Template-based chunking**
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- Intelligent and explainable.
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- Plenty of template options to choose from.
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- A variety of template options are available for you to choose from.
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### 🌱 **Grounded citations with reduced hallucinations**
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### 🌱 **Grounded citations reduce hallucinations**
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- Visualization of text chunking to allow human intervention.
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- Quick view of the key references and traceable citations to support grounded answers.
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@ -129,7 +132,7 @@ releases! 🌟
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### 🛀 **Automated and effortless RAG workflow**
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- Streamlined RAG orchestration catered to both personal and large businesses.
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- Configurable LLMs as well as embedding models.
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- Configurable LLMs as well as Embedding models.
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- Multiple recall paired with fused re-ranking.
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- Intuitive APIs for seamless integration with business.
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@ -143,14 +146,14 @@ releases! 🌟
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### 📝 Prerequisites
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- CPU >= 4 cores
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- CPU >= 4 Cores
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- RAM >= 16 GB
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- Disk >= 50 GB
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- Docker >= 24.0.0 & Docker Compose >= v2.26.1
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- Docker >= v24.0.0 & Docker Compose >= v2.26.1
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- [gVisor](https://gvisor.dev/docs/user_guide/install/): Required only if you intend to use the code executor (sandbox) feature of RAGFlow.
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> [!TIP]
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> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
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> If you have not installed Docker on your local machine (Windows, Mac, or Linux), please see [Install Docker Engine](https://docs.docker.com/engine/install/).
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### 🚀 Start up the server
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> [!CAUTION]
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> All Docker images are built for x86 platforms. We don't currently offer Docker images for ARM64.
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> If you are on an ARM64 platform, follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.
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> If you are on an ARM64 platform, please follow [this guide](https://ragflow.io/docs/dev/build_docker_image) to build a Docker image compatible with your system.
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> The command below downloads the `v0.22.1` edition of the RAGFlow Docker image. See the following table for descriptions of different RAGFlow editions. To download a RAGFlow edition different from `v0.22.1`, update the `RAGFLOW_IMAGE` variable accordingly in **docker/.env** before using `docker compose` to start the server.
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# docker compose -f docker-compose.yml up -d
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```
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> Note: Prior to `v0.22.0`, we provided both images with embedding models and slim images without embedding models. Details as follows:
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> Note: Prior to version `v0.22.0`, we offered both images with embedding models and slim images without embedding models. The details are as follows:
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| RAGFlow image tag | Image size (GB) | Has embedding models? | Stable? |
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| ----------------- | --------------- | --------------------- | ------------------------ |
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| v0.21.1 | ≈9 | ✔️ | Stable release |
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| v0.21.1-slim | ≈2 | ❌ | Stable release |
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> Starting with `v0.22.0`, we ship only the slim edition and no longer append the **-slim** suffix to the image tag.
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> Beginning with version `v0.22.0`, we now ship only the slim edition and have discontinued appending the **-slim** suffix to the image tag.
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4. Check the server status after having the server up and running:
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### Switch doc engine from Elasticsearch to Infinity
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RAGFlow uses Elasticsearch by default for storing full text and vectors. To switch to [Infinity](https://github.com/infiniflow/infinity/), follow these steps:
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RAGFlow uses **Elasticsearch** by default for storing full text and vectors. To switch to [Infinity](https://github.com/infiniflow/infinity/), follow these steps:
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1. Stop all running containers:
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> [!WARNING]
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> Switching to Infinity on a Linux/arm64 machine is not yet officially supported.
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## 🔧 Build a Docker image
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## 🔧 Build a Docker Image
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This image is approximately 2 GB in size and relies on external LLM and embedding services.
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This docker image is approximately 2 GB in size and relies on external LLM and Embedding services.
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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docker build --platform linux/amd64 -f Dockerfile -t infiniflow/ragflow:nightly .
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```
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## 🔨 Launch service from source for development
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## 🔨 Launch Service from Source for Development
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1. Install `uv` and `pre-commit`, or skip this step if they are already installed:
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```bash
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git clone https://github.com/infiniflow/ragflow.git
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cd ragflow/
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uv sync --python 3.10 # install RAGFlow dependent python modules
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uv sync --python 3.10 # install RAGFlow dependent python modules
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uv run download_deps.py
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pre-commit install
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```
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```
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127.0.0.1 es01 infinity mysql minio redis sandbox-executor-manager
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```
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4. If you cannot access HuggingFace, set the `HF_ENDPOINT` environment variable to use a mirror site:
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4. If you cannot access HuggingFace, please set the `HF_ENDPOINT` environment variable to use a mirror site:
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```bash
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export HF_ENDPOINT=https://hf-mirror.com
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npm run dev
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```
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_The following output confirms a successful launch of the system:_
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🎉 _The following output confirms a successful launch of the system:_ 🎉
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9. Stop RAGFlow front-end and back-end service after development is complete:
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- [Quickstart](https://ragflow.io/docs/dev/)
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- [Configuration](https://ragflow.io/docs/dev/configurations)
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- [Release notes](https://ragflow.io/docs/dev/release_notes)
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- [User guides](https://ragflow.io/docs/dev/category/guides)
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- [Developer guides](https://ragflow.io/docs/dev/category/developers)
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- [Release Notes](https://ragflow.io/docs/dev/release_notes)
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- [User Guides](https://ragflow.io/docs/dev/category/guides)
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- [Developer Guides](https://ragflow.io/docs/dev/category/developers)
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- [References](https://ragflow.io/docs/dev/category/references)
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- [FAQs](https://ragflow.io/docs/dev/faq)
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## 📜 Roadmap
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See the [RAGFlow Roadmap 2025](https://github.com/infiniflow/ragflow/issues/4214)
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Please see the [RAGFlow Roadmap 2025](https://github.com/infiniflow/ragflow/issues/4214)
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## 🏄 Community
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@ -396,5 +399,4 @@ See the [RAGFlow Roadmap 2025](https://github.com/infiniflow/ragflow/issues/4214
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## 🙌 Contributing
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RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community.
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If you would like to be a part, review our [Contribution Guidelines](https://ragflow.io/docs/dev/contributing) first.
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RAGFlow flourishes via open-source collaboration, and in this spirit, we welcome diverse contributions from the community. If you would like to be a part, please review our [Contribution Guidelines](https://ragflow.io/docs/dev/contributing) first.
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