| @@ -20,15 +20,13 @@ | |||
| <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. | |||
| ## 💡 What is RAGFlow? | |||
| <div align="center" style="margin-top:20px;margin-bottom:20px;"> | |||
| <img src="https://github.com/infiniflow/ragflow/assets/12318111/b24a7a5f-4d1d-4a30-90b1-7b0ec558b79d" width="1000"/> | |||
| </div> | |||
| [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 | |||
| - 🍭**Custom-build document understanding engine.** Our deep learning engine is made according to the needs of analyzing and searching various type of documents in different domain. | |||
| - For documents from different domain for different purpose, the engine applies different analyzing and search strategy. | |||
| - Easily intervene and manipulate the data proccessing procedure when things goes beyond expectation. | |||
| @@ -57,56 +55,41 @@ | |||
| - CPU >= 2 cores | |||
| - RAM >= 8 GB | |||
| - Docker | |||
| - `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 | |||
| > ``` | |||
| ### Start up the RagFlow server | |||
| 1. Clone the repo: | |||
| - 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 | |||
| ``` | |||
| 2. **Recommended**: In **docker/service_conf.yaml**, select the desired LLM factory in `user_default_llm` and update the `API_KEY` field with your own. | |||
| > - You can still continue with the default settings, but it is highly recommended that you use your own API key the next time you log into the system. | |||
| > - RagFlow now supports the flowing LLM factories: OpenAI, Tongyi-Qianwen, ZHIPU-AI, and Moonshot. | |||
| 3. Build the pre-built Docker images and start up the server: | |||
| 3. You now presented with two options for building the system: Using the pre-built images or building the images from source: | |||
| ```bash | |||
| # To use the pre-built images: | |||
| $ cd ragflow/docker | |||
| $ docker compose up -d | |||
| ``` | |||
| ```bash | |||
| # To build the images from source: | |||
| $ cd ragflow/ | |||
| $ docker build -t infiniflow/ragflow:v1.0 . | |||
| $ cd ragflow/docker | |||
| $ docker compose up -d | |||
| ``` | |||
| @@ -115,7 +98,7 @@ | |||
| 4. Check the server status after pulling all images and having Docker up and running: | |||
| ```bash | |||
| $ docker logs -f ragflow-server | |||
| $ docker logs -f ragflow-server | |||
| ``` | |||
| *The following output confirms a successful launch of the system:* | |||
| @@ -133,7 +116,8 @@ | |||
| INFO:werkzeug:Press CTRL+C to quit | |||
| ``` | |||
| 5. In your browser, enter the IP address of your server and now you can try it out. | |||
| 5. In your web browser, enter the IP address of your server as prompted. | |||
| *The show is on!* | |||
| ## 🔧 Configurations | |||
| @@ -148,16 +132,27 @@ Updates to system configurations require a system reboot to take effect *docker- | |||
| > If you change anything in [.env](./docker/.env), please check [service_conf.yaml](./docker/service_conf.yaml) which is a configuration of the back-end service and should be consistent with [.env](./docker/.env). | |||
| ## 🛠️ 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) | |||
| See the [RAGFlow Roadmap 2024](https://github.com/infiniflow/ragflow/issues/162) | |||
| ## 🏄 Community | |||
| - [Discord](https://discord.gg/uqQ4YMDf) | |||
| - [Twitter](https://twitter.com/infiniflowai) | |||
| - GitHub Discussions | |||
| ## 🙌 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. | |||
| 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. | |||