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- <div align="center">
- <a href="https://demo.ragflow.io/">
- <img src="https://github.com/infiniflow/ragflow/assets/12318111/f034fb27-b3bf-401b-b213-e1dfa7448d2a" width="320" alt="ragflow logo">
- </a>
- </div>
-
-
- <p align="center">
- <a href="./README.md">English</a> |
- <a href="./README_zh.md">简体中文</a>
- </p>
-
- <p align="center">
- <a href="https://demo.ragflow.io" target="_blank">
- <img alt="Static Badge" src="https://img.shields.io/badge/RAGFLOW-LLM-white?&labelColor=dd0af7"></a>
- <a href="https://hub.docker.com/r/infiniflow/ragflow" target="_blank">
- <img src="https://img.shields.io/badge/docker_pull-ragflow:v1.0-brightgreen"
- alt="docker pull ragflow:v1.0"></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?style=flat-square&labelColor=d4eaf7&color=7d09f1" alt="license">
- </a>
- </p>
-
- ## 💡 What is RAGFlow?
-
- [RAGFlow](http://demo.ragflow.io) is a knowledge management platform built on custom-build document understanding engine and LLM, with reasoned and well-founded answers to your question. Clone this repository, you can deploy your own knowledge management platform to empower your business with AI.
-
- ## 🌟 Key Features
-
- - 🍭 **"Quality in, quality out"**
- - Deep document understanding-based knowledge extraction from unstructured data with complicated formats.
- - Finds "needle in a data haystack" of literally unlimited tokens.
- - 🍱 **Template-based chunking**
- - Intelligent and explainable.
- - Plenty of template options to choose from.
- - 🌱 **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.
- - 🍔 **Compatibility with heterogeneous data sources**
- - Supports Word, slides, excel, txt, images, scanned copies, structured data, web pages, and more.
- - 🛀 **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.
-
- ## 🔎 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>
-
- ## 🎬 Get Started
-
- ### 📝 Prerequisites
-
- - CPU >= 2 cores
- - RAM >= 8 GB
- - Docker
- > If you have not installed Docker on your local machine (Windows, Mac, or Linux), see [Install Docker Engine](https://docs.docker.com/engine/install/).
-
- ### Start up the server
-
- 1. Ensure `vm.max_map_count` > 65535:
-
- > To check the value of `vm.max_map_count`:
- >
- > ```bash
- > $ sysctl vm.max_map_count
- > ```
- >
- > Reset `vm.max_map_count` to a value greater than 65535 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:
-
- ```bash
- $ cd ragflow/docker
- $ docker compose up -d
- ```
-
- > The core image is about 15 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://172.22.0.5:9380
- INFO:werkzeug:Press CTRL+C to quit
- ```
-
- 5. In your web browser, enter the IP address of your server as prompted and log in to RAGFlow.
-
- *The show is now on!*
-
-
- ## 🔧 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 it is IMPORTANT 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 change the default serving port (80), go to [docker-compose.yml](./docker/docker-compose.yml) and change `80:80` to `<YOUR_SERVING_PORT>:80`.
-
- > Updates to all system configurations require a system reboot to take effect:
- >
- > ```bash
- > $ docker-compose up -d
- > ```
-
- ## 🛠️ Build from source
-
- To build the Docker images from source:
-
- ```bash
- $ git clone https://github.com/infiniflow/ragflow.git
- $ cd ragflow/
- $ docker build -t infiniflow/ragflow:v1.0 .
- $ cd ragflow/docker
- $ docker compose up -d
- ```
-
- ## 📜 Roadmap
-
- See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162)
-
- ## 🏄 Community
-
- - [Discord](https://discord.gg/uqQ4YMDf)
- - [Twitter](https://twitter.com/infiniflowai)
-
- ## 🙌 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](https://github.com/infiniflow/ragflow/blob/main/CONTRIBUTING.md) first.
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