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  1. English | [简体中文](./README_zh.md)
  2. ## System Environment Preparation
  3. ### Install docker
  4. If your machine doesn't have *Docker* installed, please refer to [Install Docker Engine](https://docs.docker.com/engine/install/)
  5. ### OS Setups
  6. Firstly, you need to check the following command:
  7. ```bash
  8. 121:/ragflow# sysctl vm.max_map_count
  9. vm.max_map_count = 262144
  10. ```
  11. If **vm.max_map_count** is not larger than 65535, please run the following commands:
  12. ```bash
  13. 121:/ragflow# sudo sysctl -w vm.max_map_count=262144
  14. ```
  15. However, this change is not persistent and will be reset after a system reboot.
  16. To make the change permanent, you need to update the **/etc/sysctl.conf file**.
  17. Add or update the following line in the file:
  18. ```bash
  19. vm.max_map_count=262144
  20. ```
  21. ## Here we go!
  22. > If you want to change the basic setups, like port, password .etc., please refer to [.env](./docker/.env) before starting the system.
  23. > If you change anything in [.env](./docker/.env), please check [service_conf.yaml](./docker/service_conf.yaml) which is a
  24. > configuration of the back-end service and should be consistent with [.env](./docker/.env).
  25. > - In [service_conf.yaml](./docker/service_conf.yaml), configuration of *LLM* in **user_default_llm** is strongly recommended.
  26. > In **user_default_llm** of [service_conf.yaml](./docker/service_conf.yaml), you need to specify LLM factory and your own _API_KEY_.
  27. > It's O.K if you don't have _API_KEY_ at the moment, you can specify it later at the setting part after starting and logging in the system.
  28. > - We have supported the flowing LLM factory, and the others is coming soon:
  29. > [OpenAI](https://platform.openai.com/login?launch), [通义千问/QWen](https://dashscope.console.aliyun.com/model),
  30. > [智谱AI/ZhipuAI](https://open.bigmodel.cn/)
  31. ```bash
  32. 121:/ragflow# cd docker
  33. 121:/ragflow/docker# docker compose up -d
  34. ```
  35. If after about a half of minutes, use the following command to check the server status. If you can have the following outputs,
  36. _**Hallelujah!**_ You have successfully launched the system.
  37. ```bash
  38. 121:/ragflow# docker logs -f ragflow-server
  39. ____ ______ __
  40. / __ \ ____ _ ____ _ / ____// /____ _ __
  41. / /_/ // __ `// __ `// /_ / // __ \| | /| / /
  42. / _, _// /_/ // /_/ // __/ / // /_/ /| |/ |/ /
  43. /_/ |_| \__,_/ \__, //_/ /_/ \____/ |__/|__/
  44. /____/
  45. * Running on all addresses (0.0.0.0)
  46. * Running on http://127.0.0.1:9380
  47. * Running on http://172.22.0.5:9380
  48. INFO:werkzeug:Press CTRL+C to quit
  49. ```
  50. Open your browser, after entering the IP address of your server, if you see the flowing in your browser, _**Hallelujah**_ again!
  51. > The default serving port is 80, if you want to change that, please refer to [ragflow.conf](./nginx/ragflow.conf),
  52. > and change the *listen* value.
  53. <div align="center" style="margin-top:20px;margin-bottom:20px;">
  54. <img src="https://github.com/infiniflow/ragflow/assets/12318111/b24a7a5f-4d1d-4a30-90b1-7b0ec558b79d" width="1000"/>
  55. </div>