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<div align="center">
<a href="https://demo.ragflow.io/">
<img src="web/src/assets/logo-with-text.png" width="520" alt="ragflow logo">
</a>
</div>
<p align="center">
<a href="./README.md">English</a> |
<a href="./README_zh.md">็ฎไฝไธญๆ</a> |
<a href="./README_ja.md">ๆฅๆฌ่ช</a> |
<a href="./README_ko.md">ํ๊ตญ์ด</a>
</p>
<p align="center">
<a href="https://github.com/infiniflow/ragflow/releases/latest">
<img src="https://img.shields.io/github/v/release/infiniflow/ragflow?color=blue&label=Latest%20Release" alt="Latest Release">
</a>
<a href="https://demo.ragflow.io" target="_blank">
<img alt="Static Badge" src="https://img.shields.io/badge/Online-Demo-4e6b99"></a>
<a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
<img src="https://img.shields.io/badge/docker_pull-ragflow:v0.11.0-brightgreen" alt="docker pull infiniflow/ragflow:v0.11.0"></a>
<a href="https://github.com/infiniflow/ragflow/blob/main/LICENSE">
<img height="21" src="https://img.shields.io/badge/License-Apache--2.0-ffffff?labelColor=d4eaf7&color=2e6cc4" alt="license">
</a>
</p>
<h4 align="center">
<a href="https://ragflow.io/docs/dev/">Document</a> |
<a href="https://github.com/infiniflow/ragflow/issues/162">Roadmap</a> |
<a href="https://twitter.com/infiniflowai">Twitter</a> |
<a href="https://discord.gg/4XxujFgUN7">Discord</a> |
<a href="https://demo.ragflow.io">Demo</a>
</h4>
<details open>
<summary></b>๐ Table of Contents</b></summary>
- ๐ก [What is RAGFlow?](#-what-is-ragflow)
- ๐ฎ [Demo](#-demo)
- ๐ [Latest Updates](#-latest-updates)
- ๐ [Key Features](#-key-features)
- ๐ [System Architecture](#-system-architecture)
- ๐ฌ [Get Started](#-get-started)
- ๐ง [Configurations](#-configurations)
- ๐ [Documentation](#-documentation)
- ๐ [Roadmap](#-roadmap)
- ๐ [Community](#-community)
- ๐ [Contributing](#-contributing)
</details>
## ๐ก What is RAGFlow?
[RAGFlow](https://ragflow.io/) is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding. It offers a streamlined RAG workflow for businesses of any scale, combining LLM (Large Language Models) to provide truthful question-answering capabilities, backed by well-founded citations from various complex formatted data.
## ๐ฎ Demo
Try our demo at [https://demo.ragflow.io](https://demo.ragflow.io).
<div align="center" style="margin-top:20px;margin-bottom:20px;">
<img src="https://github.com/infiniflow/ragflow/assets/7248/2f6baa3e-1092-4f11-866d-36f6a9d075e5" width="1200"/>
<img src="https://github.com/infiniflow/ragflow/assets/12318111/b083d173-dadc-4ea9-bdeb-180d7df514eb" width="1200"/>
</div>
## ๐ฅ Latest Updates
- 2024-09-13 Adds search mode for knowledge base Q&A.
- 2024-09-09 Adds a medical consultant agent template.
- 2024-08-22 Support text to SQL statements through RAG.
- 2024-08-02 Supports GraphRAG inspired by [graphrag](https://github.com/microsoft/graphrag) and mind map.
- 2024-07-23 Supports audio file parsing.
- 2024-07-08 Supports workflow based on [Graph](./agent/README.md).
- 2024-06-27 Supports Markdown and Docx in the Q&A parsing method, extracting images from Docx files, extracting tables from Markdown files.
- 2024-05-23 Supports [RAPTOR](https://arxiv.org/html/2401.18059v1) for better text retrieval.
## ๐ Key Features
### ๐ญ **"Quality in, quality out"**
- [Deep document understanding](./deepdoc/README.md)-based knowledge extraction from unstructured data with complicated formats.
- Finds "needle in a data haystack" of literally unlimited tokens.
### ๐ฑ **Template-based chunking**
- Intelligent and explainable.
- Plenty of template options to choose from.
### ๐ฑ **Grounded citations with reduced hallucinations**
- Visualization of text chunking to allow human intervention.
- Quick view of the key references and traceable citations to support grounded answers.
### ๐ **Compatibility with heterogeneous data sources**
- Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.
### ๐ **Automated and effortless RAG workflow**
- Streamlined RAG orchestration catered to both personal and large businesses.
- Configurable LLMs as well as embedding models.
- Multiple recall paired with fused re-ranking.
- Intuitive APIs for seamless integration with business.
## ๐ System Architecture
<div align="center" style="margin-top:20px;margin-bottom:20px;">
<img src="https://github.com/infiniflow/ragflow/assets/12318111/d6ac5664-c237-4200-a7c2-a4a00691b485" width="1000"/>
</div>
## ๐ฌ Get Started
### ๐ Prerequisites
- CPU >= 4 cores
- RAM >= 16 GB
- Disk >= 50 GB
- Docker >= 24.0.0 & Docker Compose >= v2.26.1
> If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
### ๐ Start up the server
1. Ensure `vm.max_map_count` >= 262144:
> To check the value of `vm.max_map_count`:
>
> ```bash
> $ sysctl vm.max_map_count
> ```
>
> Reset `vm.max_map_count` to a value at least 262144 if it is not.
>
> ```bash
> # In this case, we set it to 262144:
> $ sudo sysctl -w vm.max_map_count=262144
> ```
>
> This change will be reset after a system reboot. To ensure your change remains permanent, add or update the `vm.max_map_count` value in **/etc/sysctl.conf** accordingly:
>
> ```bash
> vm.max_map_count=262144
> ```
2. Clone the repo:
```bash
$ git clone https://github.com/infiniflow/ragflow.git
```
3. Build the pre-built Docker images and start up the server:
> Running the following commands automatically downloads the *dev* version RAGFlow Docker image. To download and run a specified Docker version, update `RAGFLOW_VERSION` in **docker/.env** to the intended version, for example `RAGFLOW_VERSION=v0.11.0`, before running the following commands.
```bash
$ cd ragflow/docker
$ docker compose up -d
```
> The core image is about 9 GB in size and may take a while to load.
4. Check the server status after having the server up and running:
```bash
$ docker logs -f ragflow-server
```
_The following output confirms a successful launch of the system:_
```bash
____ ______ __
/ __ \ ____ _ ____ _ / ____// /____ _ __
/ /_/ // __ `// __ `// /_ / // __ \| | /| / /
/ _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ /
/_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/
/____/
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:9380
* Running on http://x.x.x.x:9380
INFO:werkzeug:Press CTRL+C to quit
```
> If you skip this confirmation step and directly log in to RAGFlow, your browser may prompt a `network abnormal` error because, at that moment, your RAGFlow may not be fully initialized.
5. In your web browser, enter the IP address of your server and log in to RAGFlow.
> With the default settings, you only need to enter `http://IP_OF_YOUR_MACHINE` (**sans** port number) as the default HTTP serving port `80` can be omitted when using the default configurations.
6. In [service_conf.yaml](./docker/service_conf.yaml), select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with the corresponding API key.
> See [llm_api_key_setup](https://ragflow.io/docs/dev/llm_api_key_setup) for more information.
_The show is on!_
## ๐ง Configurations
When it comes to system configurations, you will need to manage the following files:
- [.env](./docker/.env): Keeps the fundamental setups for the system, such as `SVR_HTTP_PORT`, `MYSQL_PASSWORD`, and `MINIO_PASSWORD`.
- [service_conf.yaml](./docker/service_conf.yaml): Configures the back-end services.
- [docker-compose.yml](./docker/docker-compose.yml): The system relies on [docker-compose.yml](./docker/docker-compose.yml) to start up.
You must ensure that changes to the [.env](./docker/.env) file are in line with what are in the [service_conf.yaml](./docker/service_conf.yaml) file.
> The [./docker/README](./docker/README.md) file provides a detailed description of the environment settings and service configurations, and you are REQUIRED to ensure that all environment settings listed in the [./docker/README](./docker/README.md) file are aligned with the corresponding configurations in the [service_conf.yaml](./docker/service_conf.yaml) file.
To update the default HTTP serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80` to `<YOUR_SERVING_PORT>:80`.
Updates to the above configurations require a reboot of all containers to take effect:
> ```bash
> $ docker-compose -f docker/docker-compose.yml up -d
> ```
## ๐ Documentation
- [Quickstart](https://ragflow.io/docs/dev/)
- [User guide](https://ragflow.io/docs/dev/category/user-guides)
- [References](https://ragflow.io/docs/dev/category/references)
- [FAQ](https://ragflow.io/docs/dev/faq)
## ๐ Roadmap
See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162)
## ๐ Community
- [Discord](https://discord.gg/4XxujFgUN7)
- [Twitter](https://twitter.com/infiniflowai)
- [GitHub Discussions](https://github.com/orgs/infiniflow/discussions)
## ๐ Contributing
RAGFlow flourishes via open-source collaboration. In this spirit, we embrace diverse contributions from the community. If you would like to be a part, review our [Contribution Guidelines](./CONTRIBUTING.md) first.
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