From d9e6b103d49e6b1133e4ebd3dc52dd3a1370dea2 Mon Sep 17 00:00:00 2001
From: writinwaters <93570324+writinwaters@users.noreply.github.com>
Date: Sun, 31 Mar 2024 15:07:12 +0800
Subject: [PATCH] 0331 config (#176)
* Updated steps
* Miscellaneous updates
---
README.md | 99 ++++++++++++++++++++++++++-----------------------------
1 file changed, 47 insertions(+), 52 deletions(-)
diff --git a/README.md b/README.md
index 94fd6c3..fc3af1e 100644
--- a/README.md
+++ b/README.md
@@ -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>
-## đź’ˇ 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.
+## đź’ˇ 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
+
- đźŤ**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
+```
+
## đź“ś 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.
--
GitLab