Merge pull request #10 from RockChinQ/doc/update-readme

Doc: update readme

README.md

@@ -1,5 +1,7 @@
 <div align="center">
 
+<img width="150" alt="image" src="web/src/assets/logo.png">
+
 # free-one-api
 
 [中文文档](README.md) | [English](README_en.md)
@@ -10,8 +12,6 @@
   </a>
 ![Wakapi Count](https://wakapi.dev/api/badge/RockChinQ/interval:any/project:free-one-api)
 
-<img width="500" alt="image" src="assets/feature.png">
-
 </div>
 <hr>
 
@@ -24,6 +24,24 @@
 - 支持自动负载均衡。
 - 支持 Web UI。
 - 支持流模式。
+- 支持多个 LLM 逆向库。
+
+<details>
+<summary>截图展示</summary>
+
+**渠道页面:**
+
+<img width="400" alt="image" src="assets/channels.png">
+
+**添加渠道:**
+
+<img width="400" alt="image" src="assets/add_channel.png">
+
+**Curl:**
+
+<img width="400" alt="image" src="assets/feature.png">
+
+</details>
 
 ### 支持的 LLM 库
 
@@ -70,7 +88,7 @@ python main.py
 
 1. 创建一个 channel，按照说明填写配置，然后创建一个新的 key。
 
-<img width="500" alt="image" src="assets/add_channel.png">
+<img width="400" alt="image" src="assets/add_channel.png">
 
 2. 将 url (e.g. http://localhost:3000/v1 ) 设置为 OpenAI 的 api_base ，将生成的 key 设置为 OpenAI api key。
 3. 现在你可以使用 OpenAI API 来访问逆向工程的 LLM 库了。

README_en.md

@@ -1,5 +1,7 @@
 <div align="center">
 
+<img width="150" alt="image" src="web/src/assets/logo.png">
+
 # free-one-api
 
 [中文文档](README.md) | [English](README_en.md)
@@ -10,8 +12,6 @@
   </a>
 ![Wakapi Count](https://wakapi.dev/api/badge/RockChinQ/interval:any/project:free-one-api)
 
-<img width="500" alt="image" src="assets/feature.png">
-
 </div>
 <hr>
 
@@ -24,6 +24,24 @@ So other application supports OpenAI GPT API can use reverse engineered LLM libs
 - Automatically load balance.
 - Web UI.
 - Stream mode supported.
+- Multi lib supported.
+
+<details>
+<summary>Screenshots</summary>
+
+**Channel Page:**
+
+<img width="400" alt="image" src="assets/channels.png">
+
+**Add Channel:**
+
+<img width="400" alt="image" src="assets/add_channel.png">
+
+**Curl:**
+
+<img width="400" alt="image" src="assets/feature.png">
+
+</details>
 
 ### Supported LLM libs
 
@@ -70,7 +88,7 @@ then you can open the admin page at `http://localhost:3000/`.
 
 1. Create channel on the admin page, create a new key.
 
-<img width="500" alt="image" src="assets/add_channel.png">
+<img width="400" alt="image" src="assets/add_channel.png">
 
 2. Set the url (e.g. http://localhost:3000/v1 ) as OpenAI endpoint, and set the generated key as OpenAI api key.  
 3. Then you can use the OpenAI API to access the reverse engineered LLM lib.