[![][docker-release-shield]][docker-release-link]
@@ -70,13 +70,13 @@ The script supports the following deployment modes; please choose the appropriat
After the script finishes running, you need to check the configuration generation report, which includes the accounts and initial login passwords for the Casdoor administrator and user.
- Please log in to LobeChat using the user account; the administrator account is only for managing
+ Please log in to LobeHub using the user account; the administrator account is only for managing
Casdoor.
```log
The results of the secure key generation are as follows:
- LobeChat:
+ LobeHub:
- URL: http://localhost:3210
- Username: user
- Password: c66f8c
@@ -118,7 +118,7 @@ The script supports the following deployment modes; please choose the appropriat
### Access Application
- Visit your LobeChat service at [http://localhost:3210](http://localhost:3210). The account credentials for the application can be found in the report from step `2`.
+ Visit your LobeHub service at [http://localhost:3210](http://localhost:3210). The account credentials for the application can be found in the report from step `2`.
### Port Mode
@@ -136,13 +136,13 @@ The script supports the following deployment modes; please choose the appropriat
After the script finishes running, please check the configuration generation report for the Casdoor administrator account, user account, and their initial login passwords.
- Please log in to LobeChat using the user account; the administrator account is only for managing
+ Please log in to LobeHub using the user account; the administrator account is only for managing
Casdoor.
```log
The results of the secure key generation are as follows:
- LobeChat:
+ LobeHub:
- URL: http://your_server_ip:3210
- Username: user
- Password: 837e26
@@ -183,7 +183,7 @@ The script supports the following deployment modes; please choose the appropriat
### Access Application
- You can access your LobeChat service at `http://your_server_ip:3210`. The account credentials for the application can be found in the report from step `2`.
+ You can access your LobeHub service at `http://your_server_ip:3210`. The account credentials for the application can be found in the report from step `2`.
If your service can accessed via the public network,
@@ -231,7 +231,7 @@ The script supports the following deployment modes; please choose the appropriat
In domain mode, you need to complete the following configurations based on script prompts:
- - Domain setup for the LobeChat service: `lobe.example.com`
+ - Domain setup for the LobeHub service: `lobe.example.com`
- Domain setup for the Minio service: `minio.example.com`
- Domain setup for the Casdoor service: `auth.example.com`
- Choose the access protocol: `http` or `https`
@@ -252,13 +252,13 @@ The script supports the following deployment modes; please choose the appropriat
After the script finishes running, you need to check the configuration generation report, which includes the initial login password for the Casdoor administrator.
- Please log in to LobeChat using the user account; the administrator account is only for managing
+ Please log in to LobeHub using the user account; the administrator account is only for managing
Casdoor.
```log
The results of the secure key generation are as follows:
- LobeChat:
+ LobeHub:
- URL: https://lobe.example.com
- Username: user
- Password: 837e26
@@ -299,7 +299,7 @@ The script supports the following deployment modes; please choose the appropriat
### Access Application
- You can access your LobeChat service via `https://lobe.example.com`. The account credentials for the application can be found in the report from step `3`.
+ You can access your LobeHub service via `https://lobe.example.com`. The account credentials for the application can be found in the report from step `3`.
If your service can accessed via the public network,
@@ -311,7 +311,7 @@ The script supports the following deployment modes; please choose the appropriat
## Custom Deployment
-This section mainly introduces the configurations that need to be modified to customize the deployment of the LobeChat service in different network environments. Before starting, you can download the [Docker Compose configuration file](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml) and the [environment variable configuration file](https://raw.githubusercontent.com/lobehub/lobe-chat/refs/heads/main/docker-compose/local/.env.example).
+This section mainly introduces the configurations that need to be modified to customize the deployment of the LobeHub service in different network environments. Before starting, you can download the [Docker Compose configuration file](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml) and the [environment variable configuration file](https://raw.githubusercontent.com/lobehub/lobe-chat/refs/heads/main/docker-compose/local/.env.example).
```sh
curl -O https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml
@@ -326,14 +326,14 @@ mv .env.example .env
### Prerequisites
-Generally, to fully run the LobeChat database version, you will need at least the following four services:
+Generally, to fully run the LobeHub database version, you will need at least the following four services:
-- The LobeChat database version itself
+- The LobeHub database version itself
- PostgreSQL database with PGVector plugin
- Object storage service that supports S3 protocol
-- An SSO authentication service supported by LobeChat
+- An SSO authentication service supported by LobeHub
-These services can be combined through self-hosting or online cloud services to meet various deployment needs. In this article, we provide a Docker Compose configuration entirely based on open-source self-hosted services, which can be used directly to start the LobeChat database version or modified to suit your requirements.
+These services can be combined through self-hosting or online cloud services to meet various deployment needs. In this article, we provide a Docker Compose configuration entirely based on open-source self-hosted services, which can be used directly to start the LobeHub database version or modified to suit your requirements.
We use [MinIO](https://github.com/minio/minio) as the local S3 object storage service and [Casdoor](https://github.com/casdoor/casdoor) as the local authentication service by default.
@@ -348,15 +348,15 @@ Now, we will introduce the necessary configurations for running these services:
1. Casdoor
-- LobeChat requires communication with Casdoor, so you need to configure Casdoor's Issuer.
+- LobeHub requires communication with Casdoor, so you need to configure Casdoor's Issuer.
```env
AUTH_CASDOOR_ISSUER=https://auth.example.com
```
-This configuration will affect LobeChat's login authentication service, and you need to ensure that the URL of the Casdoor service is correct. You can find common manifestations and solutions for errors in this configuration in the [FAQ](#faq).
+This configuration will affect LobeHub's login authentication service, and you need to ensure that the URL of the Casdoor service is correct. You can find common manifestations and solutions for errors in this configuration in the [FAQ](#faq).
-- Additionally, you need to allow the callback URL in Casdoor to point to the LobeChat address:
+- Additionally, you need to allow the callback URL in Casdoor to point to the LobeHub address:
Please add a line in the `Authentication -> Application` -> `` -> `Redirect URI` in Casdoor's web panel:
@@ -372,7 +372,7 @@ origin=https://auth.example.com
2. MinIO
-- LobeChat needs to provide a public access URL for object files for the LLM service provider, hence you need to configure MinIO's Endpoint.
+- LobeHub needs to provide a public access URL for object files for the LLM service provider, hence you need to configure MinIO's Endpoint.
```env
S3_PUBLIC_DOMAIN=https://minio.example.com
@@ -423,13 +423,13 @@ Solutions:
lobe-chat | [auth][error] TypeError: fetch failed
```
-Cause: LobeChat cannot access the authentication service.
+Cause: LobeHub cannot access the authentication service.
Solutions:
-- Check whether your authentication service is running properly and whether LobeChat's network can reach the authentication service.
+- Check whether your authentication service is running properly and whether LobeHub's network can reach the authentication service.
-- A straightforward troubleshooting method is to use the `curl` command in the LobeChat container terminal to access your authentication service at `https://auth.example.com/.well-known/openid-configuration`. If JSON format data is returned, it indicates your authentication service is functioning correctly.
+- A straightforward troubleshooting method is to use the `curl` command in the LobeHub container terminal to access your authentication service at `https://auth.example.com/.well-known/openid-configuration`. If JSON format data is returned, it indicates your authentication service is functioning correctly.
#### OAuth Token Exchange Failures with Reverse Proxy
@@ -445,7 +445,7 @@ docker compose up -d
````markdown
## Extended Configuration
-To enhance your LobeChat service, you can perform the following extended configurations according to your needs.
+To enhance your LobeHub service, you can perform the following extended configurations according to your needs.
### Use MinIO to Store Casdoor Avatars
@@ -495,7 +495,7 @@ Allow users to change their avatars in Casdoor.
3. In Casdoor's `Authentication -> Providers`, associate the MinIO S3 service. Below is an example configuration:
- 
+ 
Here, the client ID and client secret correspond to the `Access Key` and `Secret Key` from the previous step; replace `192.168.31.251` with `your_server_ip`.
@@ -520,7 +520,7 @@ In the following, it is assumed that in addition to the above services, you are
The domain and corresponding service port descriptions are as follows:
-- `lobe.example.com`: This is your LobeChat service domain, which needs to reverse proxy to the LobeChat service port, default is `3210`.
+- `lobe.example.com`: This is your LobeHub service domain, which needs to reverse proxy to the LobeHub service port, default is `3210`.
- `auth.example.com`: This is your Logto UI domain, which needs to reverse proxy to the Logto WebUI service port, default is `8000`.
- `minio.example.com`: This is your MinIO API domain, which needs to reverse proxy to the MinIO API service port, default is `9000`.
- `minio-ui.example.com`: Optional, this is your MinIO UI domain, which needs to reverse proxy to the MinIO WebUI service port, default is `9001`.
@@ -633,7 +633,7 @@ After logging in, perform the following actions:
1. In `User Management -> Organizations`, add a new organization with the name and display name `Lobe Users`. Keep the rest as default.
2. In `Authentication -> Apps`, add a new application.
-- Name and display name should be `LobeChat`.
+- Name and display name should be `LobeHub`.
- Organization should be `Lobe Users`.
- Add a line in Redirect URLs as `https://lobe.example.com/api/auth/callback/casdoor`.
- Disable all login methods except password.
@@ -651,7 +651,7 @@ After logging in, perform the following actions:
This article uses MinIO as an example to explain the configuration process. If you are using another S3 service provider, please refer to their documentation for configuration.
- Please remember to configure the corresponding S3 service provider's CORS settings to ensure that LobeChat can access the S3 service correctly.
+ Please remember to configure the corresponding S3 service provider's CORS settings to ensure that LobeHub can access the S3 service correctly.
In this document, you need to allow cross-origin requests from `https://lobe.example.com`. This can either be configured in MinIO WebUI under `Configuration - API - Cors Allow Origin`, or in the Docker Compose configuration under `minio - environment - MINIO_API_CORS_ALLOW_ORIGIN`.
@@ -667,20 +667,20 @@ You first need to access the WebUI for configuration:
2. In the left panel under User / Access Keys, click `Create New Access Key`, no additional modifications needed, and fill the generated `Access Key` and `Secret Key` into your `.env` file under `S3_ACCESS_KEY_ID` and `S3_SECRET_ACCESS_KEY`.
-
- If you are deploying LobeChat behind a CDN (like Cloudflare) or reverse proxy, you may want to configure internal server-to-server communication to bypass the CDN/proxy layer for better performance.
+ If you are deploying LobeHub behind a CDN (like Cloudflare) or reverse proxy, you may want to configure internal server-to-server communication to bypass the CDN/proxy layer for better performance.
You can configure the `INTERNAL_APP_URL` environment variable:
@@ -733,7 +733,7 @@ CASDOOR_PORT=8000
MINIO_PORT=9000
# Postgres related, which are the necessary environment variables for DB
-LOBE_DB_NAME=lobechat
+LOBE_DB_NAME=LobeHub
POSTGRES_PASSWORD=uWNZugjBqixf8dxC
# Casdoor secret
@@ -762,7 +762,7 @@ services:
- '${MINIO_PORT}:${MINIO_PORT}' # MinIO API
- '9001:9001' # MinIO Console
- '${CASDOOR_PORT}:${CASDOOR_PORT}' # Casdoor
- - '${LOBE_PORT}:3210' # LobeChat
+ - '${LOBE_PORT}:3210' # LobeHub
command: tail -f /dev/null
networks:
- lobe-network
diff --git a/docs/self-hosting/server-database/docker-compose.zh-CN.mdx b/docs/self-hosting/server-database/docker-compose.zh-CN.mdx
index e187c034c5..10b269462b 100644
--- a/docs/self-hosting/server-database/docker-compose.zh-CN.mdx
+++ b/docs/self-hosting/server-database/docker-compose.zh-CN.mdx
@@ -1,14 +1,14 @@
---
-title: 通过 Docker Compose 部署 LobeChat
-description: 学习如何使用 Docker Compose 部署 LobeChat 服务，包括各种服务的配置教程。
+title: 通过 Docker Compose 部署 LobeHub
+description: 学习如何使用 Docker Compose 部署 LobeHub 服务，包括各种服务的配置教程。
tags:
- Docker Compose
- - LobeChat
+ - LobeHub
- Docker 容器
- 部署指引
---
-# 使用 Docker Compose 部署 LobeChat 服务端数据库版本
+# 使用 Docker Compose 部署 LobeHub 服务端数据库版本
- 本文已经假定你了解了 LobeChat 服务端数据库版本（下简称 DB
- 版）的部署基本原理和流程，因此只包含核心环境变量配置的内容。如果你还不了解 LobeChat DB
+ 本文已经假定你了解了 LobeHub 服务端数据库版本（下简称 DB
+ 版）的部署基本原理和流程，因此只包含核心环境变量配置的内容。如果你还不了解 LobeHub DB
版的部署原理，请先查阅 [使用服务端数据库部署](/zh/docs/self-hosting/server-database) 。
此外，针对国内的腾讯云储存桶用户，可查询[配置腾讯云 COS
存储服务](/zh/docs/self-hosting/advanced/s3/tencent-cloud)。
+
+ 由于无法使用 Docker 环境变量暴露 `NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY`，使用 Docker / Docker Compose
+ 部署 LobeHub 时，你不能使用 Clerk 作为登录鉴权服务。
+
+ 如果你确实需要 Clerk 作为登录鉴权服务，你可以考虑使用 Vercel 部署或者自行构建镜像。
+
## 在 Linux 服务器上部署
-以下是在 Linux 服务器上部署 LobeChat DB 版的流程：
+以下是在 Linux 服务器上部署 LobeHub DB 版的流程：
### 创建 Postgres 数据库实例
@@ -45,7 +51,7 @@ tags:
上述指令会创建一个名为 `my-postgres`，并且网络为 `pg` 的 PG 实例，其中 `pgvector/pgvector:pg16` 是一个 Postgres 16 的镜像，且默认安装了 pgvector 插件。
- pgvector 插件为 Postgres 提供了向量搜索的能力，是 LobeChat 实现 RAG 的重要构件之一。
+ pgvector 插件为 Postgres 提供了向量搜索的能力，是 LobeHub 实现 RAG 的重要构件之一。
@@ -77,9 +83,9 @@ tags:
S3_SECRET_ACCESS_KEY=xxxxxxxxxx
# 用于 S3 API 访问的域名
S3_ENDPOINT=https://xxxxxxxxxx.r2.cloudflarestorage.com
- S3_BUCKET=lobechat
+ S3_BUCKET=LobeHub
# 用于外网访问 S3 的公共域名，需配置 CORS
- S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com
+ S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com
# S3_REGION=ap-chengdu # 如果需要指定地域
```
@@ -120,7 +126,7 @@ tags:
## 在本地（Mac / Windows） 上使用
-LobeChat 的 DB 版也支持直接在本地的 Mac/Windows 本地使用。
+LobeHub 的 DB 版也支持直接在本地的 Mac/Windows 本地使用。
在此我们已假设你的本地有一个 5432 端口可用，账号为 `postgres` ，密码是 `mysecretpassword` 的 pg 实例，它在 `localhost:5432` 可用。
@@ -136,8 +142,8 @@ $ docker run -it -d --name lobe-chat-database -p 3210:3210 \
-e S3_ACCESS_KEY_ID=xxxxxxxxxx \
-e S3_SECRET_ACCESS_KEY=xxxxxxxxxx \
-e S3_ENDPOINT=https://xxxxxxxxxx.r2.cloudflarestorage.com \
- -e S3_BUCKET=lobechat \
- -e S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com \
+ -e S3_BUCKET=LobeHub \
+ -e S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com \
lobehub/lobe-chat-database
```
diff --git a/docs/self-hosting/server-database/dokploy.mdx b/docs/self-hosting/server-database/dokploy.mdx
index 15d534713d..9cb8dd5441 100644
--- a/docs/self-hosting/server-database/dokploy.mdx
+++ b/docs/self-hosting/server-database/dokploy.mdx
@@ -1,18 +1,18 @@
---
-title: Deploy LobeChat with database on Dokploy
+title: Deploy LobeHub with database on Dokploy
description: >-
- Learn how to deploy LobeChat with database on Dokploy with ease, including:
+ Learn how to deploy LobeHub with database on Dokploy with ease, including:
database, authentication and S3 storage service.
tags:
- - Deploy LobeChat
- - Dokploy Deployment
- - Better Auth
- - S3 Storage
+ - Deploy LobeHub
+ - Vercel Deployment
+ - OpenAI API Key
+ - Custom Domain Binding
---
# Deploying Server Database Version on Dokploy.
-This article will detail how to deploy the server database version of LobeChat.
+This article will detail how to deploy the server database version of LobeHub.
## 1. Preparation Work
@@ -24,11 +24,11 @@ curl -sSL https://dokploy.com/install.sh | sh
1. Connect your GitHub to Dokploy in the Settings / Git section according to the prompt.
-
+
2. Enter the Projects interface to create a Project.
-
+
### Configure S3 Storage Service
@@ -69,9 +69,9 @@ You also need to configure the `JWKS_KEY` environment variable for signing and v
Enter the previously created Project, click on Create Service, and select Database. In the Database interface, choose PostgreSQL, then set the database name, user, and password. In the Docker image field, enter `pgvector/pgvector:pg17`, and finally click Create to create the database.
-
+
-Enter the created database and set an unused port in External Credentials to allow external access; otherwise, LobeChat will not be able to connect to the database. You can view the Postgres database connection URL in External Host, as shown below:
+Enter the created database and set an unused port in External Credentials to allow external access; otherwise, LobeHub will not be able to connect to the database. You can view the Postgres database connection URL in External Host, as shown below:
```shell
postgresql://postgres:wAbLxfXSwkxxxxxx@45.577.281.48:5432/postgres
@@ -79,21 +79,21 @@ postgresql://postgres:wAbLxfXSwkxxxxxx@45.577.281.48:5432/postgres
Finally, click Deploy to deploy the database.
-
+
-## Deploy LobeChat on Dokploy.
+## Deploy LobeHub on Dokploy.
-Click "Create Service", select "Application", and create the LobeChat application.
+Click "Create Service", select "Application", and create the LobeHub application.
-
+
-Enter the created LobeChat application, select the forked lobe-chat project and branch, and click Save to save.
+Enter the created LobeHub application, select the forked lobe-chat project and branch, and click Save to save.
-
+
Switch to the Environment section, fill in the environment variables, and click Save.
-
+
```shell
# Environment variables required for building
@@ -125,14 +125,14 @@ S3_ENABLE_PATH_STYLE=
After adding the environment variables and saving, click Deploy to initiate the deployment. You can check the deployment progress and log information under Deployments.
-
+
-After a successful deployment, bind your own domain to your LobeChat application and request a certificate on the Domains page.
+After a successful deployment, bind your own domain to your LobeHub application and request a certificate on the Domains page.
-
+
-## Check if LobeChat is working properly.
+## Check if LobeHub is working properly.
-Go to your LobeChat website, and if you click on the login button in the upper left corner and the login pop-up appears normally, it means you have configured it successfully. Enjoy it to the fullest!
+Go to your LobeHub website, and if you click on the login button in the upper left corner and the login pop-up appears normally, it means you have configured it successfully. Enjoy it to the fullest!
-
+
diff --git a/docs/self-hosting/server-database/dokploy.zh-CN.mdx b/docs/self-hosting/server-database/dokploy.zh-CN.mdx
index 11464ab967..3c33ec2067 100644
--- a/docs/self-hosting/server-database/dokploy.zh-CN.mdx
+++ b/docs/self-hosting/server-database/dokploy.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 Dokploy 上部署 LobeChat 的服务端数据库版本
-description: 本文详细介绍如何在 Dokploy 中部署服务端数据库版 LobeChat，包括数据库配置、身份验证服务配置的设置步骤。
+title: 在 Dokploy 上部署 LobeHub 的服务端数据库版本
+description: 本文详细介绍如何在 Dokploy 中部署服务端数据库版 LobeHub，包括数据库配置、身份验证服务配置的设置步骤。
tags:
- 服务端数据库
- Postgres
@@ -13,7 +13,7 @@ tags:
# 在 Dokploy 上部署服务端数据库版
-本文将详细介绍如何在 Dokploy 中部署服务端数据库版 LobeChat。
+本文将详细介绍如何在 Dokploy 中部署服务端数据库版 LobeHub。
## 一、准备工作
@@ -25,11 +25,11 @@ curl -sSL https://dokploy.com/install.sh | sh
1. 在 Dokploy 的 Settings / Git 处根据提示将 Github 绑定到 Dokploy
-
+
2. 进入 Projects 界面创建一个 Project
-
+
### 配置 S3 存储服务
@@ -70,9 +70,9 @@ S3_ENABLE_PATH_STYLE=
进入前面创建的 Project，点击 Create Service 选择 Database，在 Database 界面选择 PostgreSQL ，然后设置数据库名、用户、密码，在 Docker image 中填入 `pgvector/pgvector:pg17` 最后点击 Create 创建数据库。
-
+
-进入创建的数据库，在 External Credentials 设置一个未被占用的端口，使其能能通过外部访问，否则 LobeChat 将无法连接到该数据库。你可以在 External Host 查看 Postgres 数据库连接 URL ，如下：
+进入创建的数据库，在 External Credentials 设置一个未被占用的端口，使其能能通过外部访问，否则 LobeHub 将无法连接到该数据库。你可以在 External Host 查看 Postgres 数据库连接 URL ，如下：
```shell
postgresql://postgres:wAbLxfXSwkxxxxxx@45.577.281.48:5432/postgres
@@ -80,21 +80,21 @@ postgresql://postgres:wAbLxfXSwkxxxxxx@45.577.281.48:5432/postgres
最后点击 Deploy 部署数据库
-
+
-## 在 Dokploy 上部署 LobeChat
+## 在 Dokploy 上部署 LobeHub
-点击 Create Service 选择 Application，创建 LobeChat 应用
+点击 Create Service 选择 Application，创建 LobeHub 应用
-
+
-进入创建的 LobeChat 应用，选择你 fork 的 lobe-chat 项目及分支，点击 Save 保存
+进入创建的 LobeHub 应用，选择你 fork 的 lobe-chat 项目及分支，点击 Save 保存
-
+
切换到 Environment ，在其中填入环境变量，点击保存。
-
+
```shell
# 构建所必需的环境变量
@@ -126,14 +126,14 @@ S3_ENABLE_PATH_STYLE=
添加完环境变量并保存后，点击 Deploy 进行部署，你可以在 Deployments 处查看部署进程及日志信息
-
+
-部署成功后在 Domains 页面，为你的 LobeChat 应用绑定自己的域名并申请证书。
+部署成功后在 Domains 页面，为你的 LobeHub 应用绑定自己的域名并申请证书。
-
+
-## 验证 LobeChat 是否正常工作
+## 验证 LobeHub 是否正常工作
-进入你的 LobeChat 网址，如果你点击左上角登录，可以正常显示登录弹窗，那么说明你已经配置成功了，尽情享用吧～
+进入你的 LobeHub 网址，如果你点击左上角登录，可以正常显示登录弹窗，那么说明你已经配置成功了，尽情享用吧～
-
+
diff --git a/docs/self-hosting/server-database/netlify.mdx b/docs/self-hosting/server-database/netlify.mdx
index bcc0e0fd82..0213750662 100644
--- a/docs/self-hosting/server-database/netlify.mdx
+++ b/docs/self-hosting/server-database/netlify.mdx
@@ -1,13 +1,13 @@
---
-title: Deploy LobeChat with Database on Netlify
+title: Deploy LobeHub with Database on Netlify
description: >-
- Learn how to deploy LobeChat on Netlify with ease, including: database,
+ Learn how to deploy LobeHub on Netlify with ease, including: database,
authentication and S3 storage service.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- Netlify Deployment
---
-# Deploy LobeChat with Database on Netlify
+# Deploy LobeHub with Database on Netlify
TODO
diff --git a/docs/self-hosting/server-database/netlify.zh-CN.mdx b/docs/self-hosting/server-database/netlify.zh-CN.mdx
index c71f604fa2..61dc3b92ce 100644
--- a/docs/self-hosting/server-database/netlify.zh-CN.mdx
+++ b/docs/self-hosting/server-database/netlify.zh-CN.mdx
@@ -1,16 +1,16 @@
---
-title: 在 Netlify 上部署 LobeChat 服务端数据库版
+title: 在 Netlify 上部署 LobeHub 服务端数据库版
description: >-
- 学习如何在 Netlify 上部署 LobeChat，包括 Fork 仓库、准备 OpenAI API Key、导入到 Netlify
+ 学习如何在 Netlify 上部署 LobeHub，包括 Fork 仓库、准备 OpenAI API Key、导入到 Netlify
工作台、配置站点名称与环境变量等步骤。
tags:
- Netlify
- - LobeChat
+ - LobeHub
- 部署教程
- OpenAI API Key
- 环境配置
---
-# 使用 Netlify 部署 LobeChat 数据库版
+# 使用 Netlify 部署 LobeHub 数据库版
TODO
diff --git a/docs/self-hosting/server-database/railway.mdx b/docs/self-hosting/server-database/railway.mdx
index d59f1243dd..cd6c5bb95a 100644
--- a/docs/self-hosting/server-database/railway.mdx
+++ b/docs/self-hosting/server-database/railway.mdx
@@ -1,13 +1,13 @@
---
-title: Deploy LobeChat with Database on Railway
+title: Deploy LobeHub with Database on Railway
description: >-
- Learn how to deploy LobeChat on Railway with ease, including: database,
+ Learn how to deploy LobeHub on Railway with ease, including: database,
authentication and S3 storage service.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- Railway Deployment
---
-# Deploy LobeChat with Database on Railway
+# Deploy LobeHub with Database on Railway
TODO
diff --git a/docs/self-hosting/server-database/railway.zh-CN.mdx b/docs/self-hosting/server-database/railway.zh-CN.mdx
index c51def9a1b..6347cf6e64 100644
--- a/docs/self-hosting/server-database/railway.zh-CN.mdx
+++ b/docs/self-hosting/server-database/railway.zh-CN.mdx
@@ -1,15 +1,15 @@
---
-title: 在 Railway 上部署 LobeChat 数据库版
-description: 学习如何在 Railway 上部署 LobeChat 应用，包括准备 OpenAI API Key、点击按钮进行部署、绑定自定义域名等步骤。
+title: 在 Railway 上部署 LobeHub 数据库版
+description: 学习如何在 Railway 上部署 LobeHub 应用，包括准备 OpenAI API Key、点击按钮进行部署、绑定自定义域名等步骤。
tags:
- Railway
- 部署
- - LobeChat
+ - LobeHub
- OpenAI
- API Key
- 自定义域名
---
-# 使用 Railway 部署 LobeChat 数据库版
+# 使用 Railway 部署 LobeHub 数据库版
TODO
diff --git a/docs/self-hosting/server-database/repocloud.mdx b/docs/self-hosting/server-database/repocloud.mdx
index ee95f9601f..7d7b745b53 100644
--- a/docs/self-hosting/server-database/repocloud.mdx
+++ b/docs/self-hosting/server-database/repocloud.mdx
@@ -1,18 +1,18 @@
---
-title: Deploy LobeChat with Database on RepoCloud
+title: Deploy LobeHub with Database on RepoCloud
description: >-
- Learn how to deploy LobeChat on RepoCloud with ease, including database,
+ Learn how to deploy LobeHub on RepoCloud with ease, including database,
authentication and S3 storage service.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- RepoCloud Deployment
- OpenAI API Key
- Custom Domain Binding
---
-# Deploying LobeChat Database Edition with RepoCloud
+# Deploying LobeHub Database Edition with RepoCloud
-If you want to deploy LobeChat Database Edition on RepoCloud, you can follow the steps below:
+If you want to deploy LobeHub Database Edition on RepoCloud, you can follow the steps below:
## RepoCloud Deployment Process
diff --git a/docs/self-hosting/server-database/repocloud.zh-CN.mdx b/docs/self-hosting/server-database/repocloud.zh-CN.mdx
index dd9bfbc730..e2a23c5efc 100644
--- a/docs/self-hosting/server-database/repocloud.zh-CN.mdx
+++ b/docs/self-hosting/server-database/repocloud.zh-CN.mdx
@@ -1,17 +1,17 @@
---
-title: 在 RepoCloud 上部署 LobeChat 数据库版
-description: 学习如何在 RepoCloud 上部署 LobeChat 应用，包括准备 OpenAI API Key、点击部署按钮、绑定自定义域名等操作。
+title: 在 RepoCloud 上部署 LobeHub 数据库版
+description: 学习如何在 RepoCloud 上部署 LobeHub 应用，包括准备 OpenAI API Key、点击部署按钮、绑定自定义域名等操作。
tags:
- RepoCloud
- - LobeChat
+ - LobeHub
- 部署流程
- OpenAI API Key
- 自定义域名
---
-# 在 RepoCloud 上部署 LobeChat 数据库版
+# 在 RepoCloud 上部署 LobeHub 数据库版
-如果您想在 RepoCloud 上部署 LobeChat 数据库版，可以按照以下步骤进行操作：
+如果您想在 RepoCloud 上部署 LobeHub 数据库版，可以按照以下步骤进行操作：
## RepoCloud 部署流程
diff --git a/docs/self-hosting/server-database/sealos.mdx b/docs/self-hosting/server-database/sealos.mdx
index 3b58162377..5bf6e8a9ce 100644
--- a/docs/self-hosting/server-database/sealos.mdx
+++ b/docs/self-hosting/server-database/sealos.mdx
@@ -1,10 +1,10 @@
---
title: Deploy Lobe Chat Database Version on Sealos
description: >-
- Learn how to deploy LobeChat on Sealos with ease. Follow the provided steps to
- set up LobeChat and start using it efficiently.
+ Learn how to deploy LobeHub on Sealos with ease. Follow the provided steps to
+ set up LobeHub and start using it efficiently.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- Sealos Deployment
- OpenAI API Key
- Custom Domain Binding
@@ -14,8 +14,8 @@ tags:
This article assumes that you are familiar with the basic principles and processes of deploying
- the LobeChat server database version, so it only includes content related to core environment
- variable configuration. If you are not familiar with the deployment principles of the LobeChat
+ the LobeHub server database version, so it only includes content related to core environment
+ variable configuration. If you are not familiar with the deployment principles of the LobeHub
server database version, please refer to [Deploying Server
Database](/docs/self-hosting/server-database) first.
diff --git a/docs/self-hosting/server-database/sealos.zh-CN.mdx b/docs/self-hosting/server-database/sealos.zh-CN.mdx
index 5ee18d91ef..95901922dc 100644
--- a/docs/self-hosting/server-database/sealos.zh-CN.mdx
+++ b/docs/self-hosting/server-database/sealos.zh-CN.mdx
@@ -1,15 +1,15 @@
---
-title: 在 Sealos 上部署 LobeChat 数据库版
-description: 学习如何在 Sealos 上部署 LobeChat，包括准备 OpenAI API Key、点击部署按钮、绑定自定义域名等操作。
+title: 在 Sealos 上部署 LobeHub 数据库版
+description: 学习如何在 Sealos 上部署 LobeHub，包括准备 OpenAI API Key、点击部署按钮、绑定自定义域名等操作。
tags:
- Sealos
- - LobeChat
+ - LobeHub
- OpenAI API Key
- 部署流程
- 自定义域名
---
-# 使用 Sealos 部署 LobeChat 数据库版
+# 使用 Sealos 部署 LobeHub 数据库版
本文假设你已经熟悉 Lobe Chat
@@ -22,7 +22,7 @@ tags:
- Logto 提供身份校验（需额外部署）
- 带有 Vector 插件的 PostgreSQL 来做数据存储和向量化
- 一个对象存储 Bucket
-- LobeChat Database 的实例
+- LobeHub Database 的实例
这里是在 Sealos 上部署 Lobe Chat 服务器数据库版的流程：
diff --git a/docs/self-hosting/server-database/vercel.mdx b/docs/self-hosting/server-database/vercel.mdx
index 971a04832c..ac6f6d30db 100644
--- a/docs/self-hosting/server-database/vercel.mdx
+++ b/docs/self-hosting/server-database/vercel.mdx
@@ -1,10 +1,10 @@
---
-title: Deploy LobeChat with database on Vercel
+title: Deploy LobeHub with database on Vercel
description: >-
- Learn how to deploy LobeChat with database on Vercel with ease, including:
+ Learn how to deploy LobeHub with database on Vercel with ease, including:
database, authentication and S3 storage service.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- Vercel Deployment
- Better Auth
- S3 Storage
@@ -12,7 +12,7 @@ tags:
# Deploying Server Database Version on Vercel
-This article will detail how to deploy the server database version of LobeChat on Vercel, including: 1) database configuration; 2) identity authentication service configuration; 3) steps for setting up the S3 storage service.
+This article will detail how to deploy the server database version of LobeHub on Vercel, including: 1) database configuration; 2) identity authentication service configuration; 3) steps for setting up the S3 storage service.
Before proceeding, please make sure of the following:
@@ -53,7 +53,7 @@ This article will detail how to deploy the server database version of LobeChat o
An example of filling in Vercel is as follows:
-
@@ -69,7 +69,7 @@ This article will detail how to deploy the server database version of LobeChat o
An example of filling in Vercel is as follows:
-
@@ -89,7 +89,7 @@ This article will detail how to deploy the server database version of LobeChat o
### Add the `APP_URL` Environment Variable
- Finally, you need to add the `APP_URL` environment variable, which specifies the URL address of the LobeChat application.
+ Finally, you need to add the `APP_URL` environment variable, which specifies the URL address of the LobeHub application.
## 2. Configure Authentication Service
@@ -114,6 +114,55 @@ The server-side database needs to be paired with a user authentication service t
For advanced features like SSO providers, magic link login, and email verification, see [Authentication Service](/docs/self-hosting/advanced/auth).
+
+ ### Add Public and Private Key Environment Variables in Vercel
+
+ In Vercel's deployment environment variables, add the `NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY` and `CLERK_SECRET_KEY` environment variables. You can click on "API Keys" in the menu, then copy the corresponding values and paste them into Vercel's environment variables.
+
+
+ The `https://` in the URL is essential to maintain the integrity of the URL.
+
+
+
@@ -164,21 +213,21 @@ In the server-side database, we need to configure the S3 storage service to stor
### Obtain S3 Key Environment Variables
- You need to obtain the access key for S3 so that the LobeChat server has permission to access the S3 storage service. In R2, you can configure the access key in the account details:
+ You need to obtain the access key for S3 so that the LobeHub server has permission to access the S3 storage service. In R2, you can configure the access key in the account details:
-
### Redeploy the latest commit
After configuring the environment variables, you need to redeploy the latest commit and wait for the deployment to complete.
-
## Appendix
@@ -285,11 +334,11 @@ S3_ACCESS_KEY_ID=9998d6757e276cf9f1edbd325b7083a6
S3_SECRET_ACCESS_KEY=55af75d8eb6b99f189f6a35f855336ea62cd9c4751a5cf4337c53c1d3f497ac2
# Bucket name
-S3_BUCKET=lobechat
+S3_BUCKET=LobeHub
# Bucket request endpoint
S3_ENDPOINT=https://0b33a03b5c993fd2f453379dc36558e5.r2.cloudflarestorage.com
# Public access domain for the bucket
-S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com
+S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com
# Bucket region, such as us-west-1, generally not needed to add, but some service providers may require configuration
# S3_REGION=us-west-1
```
diff --git a/docs/self-hosting/server-database/vercel.zh-CN.mdx b/docs/self-hosting/server-database/vercel.zh-CN.mdx
index b5d74a3c66..455172fdaf 100644
--- a/docs/self-hosting/server-database/vercel.zh-CN.mdx
+++ b/docs/self-hosting/server-database/vercel.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 Vercel 上部署 LobeChat 的服务端数据库版本
-description: 本文详细介绍如何在 Vercel 中部署服务端数据库版 LobeChat，包括数据库配置、身份验证服务配置和 S3 存储服务的设置步骤。
+title: 在 Vercel 上部署 LobeHub 的服务端数据库版本
+description: 本文详细介绍如何在 Vercel 中部署服务端数据库版 LobeHub，包括数据库配置、身份验证服务配置和 S3 存储服务的设置步骤。
tags:
- 服务端数据库
- Postgres
@@ -14,7 +14,7 @@ tags:
# 在 Vercel 上部署服务端数据库版
-本文将详细介绍如何在 Vercel 中部署服务端数据库版 LobeChat，包括： 1）数据库配置；2）身份验证服务配置；3） S3 存储服务的设置步骤。
+本文将详细介绍如何在 Vercel 中部署服务端数据库版 LobeHub，包括： 1）数据库配置；2）身份验证服务配置；3） S3 存储服务的设置步骤。
进行后续操作前，请务必确认以下事项：
@@ -54,7 +54,7 @@ tags:
在 Vercel 中填写的示例如下：
-
@@ -70,7 +70,7 @@ tags:
在 Vercel 中填写的示例如下：
-
@@ -89,7 +89,7 @@ tags:
### 添加 `APP_URL` 环境变量
- 该部分最后需要添加 `APP_URL` 环境变量，用于指定 LobeChat 应用的 URL 地址。
+ 该部分最后需要添加 `APP_URL` 环境变量，用于指定 LobeHub 应用的 URL 地址。
## 二、 配置身份验证服务
@@ -114,6 +114,53 @@ tags:
如需 SSO 登录、魔法链接登录、邮箱验证等高级功能，请参阅 [身份验证服务](/zh/docs/self-hosting/advanced/auth)。
+
+ ### 在 Vercel 中添加公、私钥环境变量
+
+ 在 Vercel 的部署环境变量中，添加 `NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY` 和 `CLERK_SECRET_KEY` 环境变量。你可以在菜单中点击「API Keys」，然后复制对应的值填入 Vercel 的环境变量中。
+
+ URL 的`https://`不可缺失，须保持 URL 的完整性
+
+ `S3_ENDPOINT`必须删除其路径，否则会无法访问所上传文件
### 获取 S3 密钥环境变量
- 你需要获取 S3 的访问密钥，以便 LobeChat 的服务端有权限访问 S3 存储服务。在 R2 中，你可以在账户详情中配置访问密钥：
+ 你需要获取 S3 的访问密钥，以便 LobeHub 的服务端有权限访问 S3 存储服务。在 R2 中，你可以在账户详情中配置访问密钥：
-
### 重新部署最新的 commit
配置好环境变量后，你需要重新部署最新的 commit，并等待部署完成。
-
## 附录
@@ -280,11 +327,11 @@ S3_ACCESS_KEY_ID=9998d6757e276cf9f1edbd325b7083a6
S3_SECRET_ACCESS_KEY=55af75d8eb6b99f189f6a35f855336ea62cd9c4751a5cf4337c53c1d3f497ac2
# 存储桶的名称
-S3_BUCKET=lobechat
+S3_BUCKET=LobeHub
# 存储桶的请求端点
S3_ENDPOINT=https://0b33a03b5c993fd2f453379dc36558e5.r2.cloudflarestorage.com
# 存储桶对外的访问域名
-S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com
+S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com
# 桶的区域，如 us-west-1，一般来说不需要添加，但某些服务商则需要配置
# S3_REGION=us-west-1
```
diff --git a/docs/self-hosting/server-database/zeabur.mdx b/docs/self-hosting/server-database/zeabur.mdx
index 5f9dc5503c..99e52fb37f 100644
--- a/docs/self-hosting/server-database/zeabur.mdx
+++ b/docs/self-hosting/server-database/zeabur.mdx
@@ -1,21 +1,21 @@
---
-title: Deploying LobeChat Database on Zeabur
+title: Deploying LobeHub Database on Zeabur
description: >-
- Learn how to deploy LobeChat on Zeabur with ease. Follow the provided steps to
+ Learn how to deploy LobeHub on Zeabur with ease. Follow the provided steps to
set up your chat application seamlessly.
tags:
- - Deploy LobeChat
+ - Deploy LobeHub
- Zeabur Deployment
- OpenAI API Key
- Custom Domain Binding
---
-# Deploying LobeChat Database on Zeabur
+# Deploying LobeHub Database on Zeabur
This article assumes that you are familiar with the basic principles and processes of deploying
- the LobeChat server database version, so it only includes content related to core environment
- variable configuration. If you are not familiar with the deployment principles of the LobeChat
+ the LobeHub server database version, so it only includes content related to core environment
+ variable configuration. If you are not familiar with the deployment principles of the LobeHub
server database version, please refer to [Deploying Server
Database](/docs/self-hosting/server-database) first.
@@ -25,16 +25,16 @@ The template on Zeabur includes 4 services:
- Logto for authrization.
- PostgreSQL with Vector plugin for data storage and indexing.
- MinIO for image storage.
-- LobeChat database version.
+- LobeHub database version.
## Deploying on Zeabur
-Here is the process for deploying the LobeChat server database version on Zeabur:
+Here is the process for deploying the LobeHub server database version on Zeabur:
### Go to the template page on Zeabur
- Go to the [LobeChat Database template page](https://zeabur.com/templates/RRSPSD) on Zeabur and click on the "Deploy" button.
+ Go to the [LobeHub Database template page](https://zeabur.com/templates/RRSPSD) on Zeabur and click on the "Deploy" button.
### Fill in the required environment variables
@@ -44,7 +44,7 @@ Here is the process for deploying the LobeChat server database version on Zeabur
- OpenAI API key: Your OpenAI API key to get responses from OpenAI.
- - LobeChat Domain: A free subdomain with `.zeabur.app` suffix.
+ - LobeHub Domain: A free subdomain with `.zeabur.app` suffix.
- MinIO Public Domain: A free subdomain with `.zeabur.app` suffix for yout MinIO web port to enable public access for the uploaded files.
@@ -54,7 +54,7 @@ Here is the process for deploying the LobeChat server database version on Zeabur
### Select a region and deploy
- After you fill all the required environment variables, select a region where you want to deploy your LobeChat Database and click on the "Deploy" button.
+ After you fill all the required environment variables, select a region where you want to deploy your LobeHub Database and click on the "Deploy" button.
You will see another modal pop-up where you can see the deployment progress.
@@ -64,13 +64,13 @@ Here is the process for deploying the LobeChat server database version on Zeabur
Access your Logto console with the console domain you just binded, and then create a `Next.js 14(App router)` application to get the client ID and client secret, and fill in the cors and callback URLs. You can check [this document](../advanced/auth.mdx) for a more detailed guide.
- Fill in those variables into your LobeChat service on Zeabur, here is a more detailed guide for [editing environment variables on Zeabur](https://zeabur.com/docs/deploy/variables).
+ Fill in those variables into your LobeHub service on Zeabur, here is a more detailed guide for [editing environment variables on Zeabur](https://zeabur.com/docs/deploy/variables).
For detailed configuration of Logto, refer to [this document](/docs/self-hosting/advanced/auth/next-auth/logto).
- ### Access your LobeChat Instance
+ ### Access your LobeHub Instance
- Press on the `LobeChat-Database` and you can see the public domain you just created, click on it to access your LobeChat Database.
+ Press on the `LobeHub-Database` and you can see the public domain you just created, click on it to access your LobeHub Database.
You can also bind a custom domain for your services if you want, here is a guide on how to [bind a custom domain on Zeabur](https://zeabur.com/docs/deploy/domain-binding).
diff --git a/docs/self-hosting/server-database/zeabur.zh-CN.mdx b/docs/self-hosting/server-database/zeabur.zh-CN.mdx
index a1d7fab2ae..16561609de 100644
--- a/docs/self-hosting/server-database/zeabur.zh-CN.mdx
+++ b/docs/self-hosting/server-database/zeabur.zh-CN.mdx
@@ -1,19 +1,19 @@
---
-title: 在 Zeabur 上部署 LobeChat
-description: 按照指南准备 OpenAI API Key 并点击按钮进行部署。在部署完成后，即可开始使用 LobeChat 并选择是否绑定自定义域名。
+title: 在 Zeabur 上部署 LobeHub
+description: 按照指南准备 OpenAI API Key 并点击按钮进行部署。在部署完成后，即可开始使用 LobeHub 并选择是否绑定自定义域名。
tags:
- Zeabur
- - LobeChat
+ - LobeHub
- OpenAI API Key
- 部署流程
- 自定义域名
---
-# 使用 Zeabur 部署 LobeChat 数据库版
+# 使用 Zeabur 部署 LobeHub 数据库版
- 本文假设你已经熟悉 LobeChat
- 服务器数据库版的部署基本原理和流程，因此只包含与核心环境变量配置相关的内容。如果你对 LobeChat
+ 本文假设你已经熟悉 LobeHub
+ 服务器数据库版的部署基本原理和流程，因此只包含与核心环境变量配置相关的内容。如果你对 LobeHub
服务器数据库版的部署原理不熟悉，请先参考[部署服务器数据库](/zh/docs/self-hosting/server-database)。
@@ -22,16 +22,16 @@ tags:
- Logto 提供身份校验
- 带有 Vector 插件的 PostgreSQL 来做数据存储和向量化
- MinIO 作为对象存储
-- LobeChat Database 的实例
+- LobeHub Database 的实例
## 在 Zeabur 上部署
-这里是在 Zeabur 上部署 LobeChat 服务器数据库版的流程：
+这里是在 Zeabur 上部署 LobeHub 服务器数据库版的流程：
### 前往 Zeabur 上的模板页面
- 前往 [Zeabur 上的 LobeChat 数据库模板页面](https://zeabur.com/templates/RRSPSD) 并点击 "Deploy" 按钮。
+ 前往 [Zeabur 上的 LobeHub 数据库模板页面](https://zeabur.com/templates/RRSPSD) 并点击 "Deploy" 按钮。
### 填写必要的环境变量
@@ -40,14 +40,14 @@ tags:
以下是你需要填写的环境变量：
- OpenAI API key: 你的 OpenAI API key 用于获取模型的访问权限。
- - LobeChat Domain: 一个免费的 `.zeabur.app` 后缀的域名。
+ - LobeHub Domain: 一个免费的 `.zeabur.app` 后缀的域名。
- MinIO Public Domain: 一个免费的 `.zeabur.app` 后缀的域名为了暴露 MinIO 服务以公开访问资源。
- Logto Console Domain: 一个免费的 `.zeabur.app` 后缀的域名来访问 Logto 的控制台。
- Logto API Domain: 一个免费的 `.zeabur.app` 后缀的域名来访问 Logto 的 API。
### 选择一个区域并部署
- 在你填写完所有必要的环境变量后，选择一个你想要部署 LobeChat 数据库的区域并点击 “部署” 按钮。
+ 在你填写完所有必要的环境变量后，选择一个你想要部署 LobeHub 数据库的区域并点击 “部署” 按钮。
你会看到另一个模态弹窗，你可以在这里看到部署的进度。
@@ -55,13 +55,13 @@ tags:
当部署完成后，你会被自动导航到你在 Zeabur 控制台上刚刚创建的项目。你需要再进一步配置你的 Logto 服务。
- 使用你刚绑定的域名来访问你的 Logto 控制台，创建一个新项目以获得对应的客户端 ID 与密钥，将它们填入你的 LobeChat 服务的变量中。关于如何填入变量，可以参照 [Zeabur 的官方文档](https://zeabur.com/docs/deploy/variables)。
+ 使用你刚绑定的域名来访问你的 Logto 控制台，创建一个新项目以获得对应的客户端 ID 与密钥，将它们填入你的 LobeHub 服务的变量中。关于如何填入变量，可以参照 [Zeabur 的官方文档](https://zeabur.com/docs/deploy/variables)。
Logto 的详细配置可以参考[这篇文档](/zh/docs/self-hosting/advanced/auth/next-auth/logto)。
- ### 访问你的 LobeChat
+ ### 访问你的 LobeHub
- 按下 `LobeChat-Database` 你会看到你刚刚创建的公共域名，点击它以访问你的 LobeChat 数据库。
+ 按下 `LobeHub-Database` 你会看到你刚刚创建的公共域名，点击它以访问你的 LobeHub 数据库。
你可以选择绑定一个自定义域名，这里有一个关于如何在 Zeabur 上[绑定自定义域名](https://zeabur.com/docs/deploy/domain-binding)的指南。
diff --git a/docs/self-hosting/start.mdx b/docs/self-hosting/start.mdx
index 4f5aa21e8a..7d2305f731 100644
--- a/docs/self-hosting/start.mdx
+++ b/docs/self-hosting/start.mdx
@@ -1,8 +1,8 @@
---
-title: Build Your Own LobeChat - Choose Your Deployment Platform
+title: Build Your Own LobeHub - Choose Your Deployment Platform
description: >-
Explore multiple deployment platforms like Vercel, Docker, Docker Compose, and
- more to deploy LobeChat. Choose the platform that best suits your needs.
+ more to deploy LobeHub. Choose the platform that best suits your needs.
tags:
- Lobe Chat
- Deployment Platform
@@ -14,13 +14,13 @@ tags:
# Build Your Own Lobe Chat
-LobeChat supports various deployment platforms, including Vercel, Docker, and Docker Compose. You can choose a deployment platform that suits you to build your own Lobe Chat.
+LobeHub supports various deployment platforms, including Vercel, Docker, and Docker Compose. You can choose a deployment platform that suits you to build your own Lobe Chat.
## Quick Deployment
-For users who are new to LobeChat, we recommend using the client-side database mode for quick deployment. The advantage of this mode is that deployment can be quickly completed with just one command/button, making it easy for you to quickly get started and experience LobeChat.
+For users who are new to LobeHub, we recommend using the client-side database mode for quick deployment. The advantage of this mode is that deployment can be quickly completed with just one command/button, making it easy for you to quickly get started and experience LobeHub.
-You can follow the guide below for quick deployment of LobeChat:
+You can follow the guide below for quick deployment of LobeHub:
-
-
-
- **Quick Setup Tip**: You can conveniently modify the Prompt through the quick edit button in the
- sidebar.
-
-
-
-
-
-If you want to understand Prompt writing tips and common model parameter settings, you can continue to view:
-
-
-
diff --git a/docs/usage/agents/custom-agent.zh-CN.mdx b/docs/usage/agents/custom-agent.zh-CN.mdx
deleted file mode 100644
index 9f11f29198..0000000000
--- a/docs/usage/agents/custom-agent.zh-CN.mdx
+++ /dev/null
@@ -1,53 +0,0 @@
----
-title: LobeChat 自定义助手指南 - 添加和配置助手的最佳方法
-description: 了解如何通过角色市场或新建自定义助手将助手添加到你的常用列表中。快捷设置技巧和常见的模型参数设置也包括在内。
-tags:
- - 自定义助手
- - LobeChat
- - 添加助手
- - 配置助手
- - 角色市场
- - 快捷设置
- - 模型参数设置
----
-
-# 自定义助手指南
-
-作为 LobeChat 的基础职能单位，助手的添加和迭代是非常重要的。现在你可以通过两种方式将助手添加到你的常用列表中
-
-## `A` 通过角色市场添加
-
-如果你是一个 Prompt 编写的新手，不妨先浏览一下 LobeChat 的助手市场。在这里，你可以找到其他人提交的常用助手，并且只需一键添加到你的列表中，非常方便。
-
-
-
-
-**快捷设置技巧**: 可以通过侧边栏的快捷编辑按钮进行 Prompt 的便捷修改
-
-
-
-
-如果你希望理解 Prompt 编写技巧和常见的模型参数设置，可以继续查看：
-
-
-
diff --git a/docs/usage/agents/model.mdx b/docs/usage/agents/model.mdx
deleted file mode 100644
index 61afd6cd68..0000000000
--- a/docs/usage/agents/model.mdx
+++ /dev/null
@@ -1,95 +0,0 @@
----
-title: LobeChat Model Config Guide
-description: >-
- Explore the capabilities of ChatGPT models from gpt-3.5-turbo to gpt-4-32k, understanding their speed, context limits, and cost. Learn about model parameters like temperature and top-p for better output.
-
-tags:
- - ChatGPT Models
- - Model Parameters
- - Neural Networks
- - Language Understanding
- - Generation Capabilities
----
-
-# Model Guide
-
-## ChatGPT
-
-- **gpt-3.5-turbo**: Currently the fastest generating ChatGPT model, it is faster but may sacrifice some text quality, with a context length of 4k.
-- **gpt-4**: ChatGPT 4.0 has improved language understanding and generation capabilities compared to 3.5. It can better understand context and generate more accurate and natural responses. This is thanks to improvements in the GPT-4 model, including better language modeling and deeper semantic understanding, but it may be slower than other models, with a context length of 8k.
-- **gpt-4-32k**: Similar to gpt-4, the context limit is increased to 32k tokens, with a higher cost.
-
-## Concept of Model Parameters
-
-LLM seems magical, but it is essentially a probability problem. The neural network generates a bunch of candidate words from the pre-trained model based on the input text and selects the high-probability ones as output. Most of the related parameters are associated with sampling (i.e., how to select the output from the candidate words).
-
-### `temperature`
-
-This parameter controls the randomness of the model's output. The higher the value, the greater the randomness. Generally, when the same prompt is input multiple times, the model's output varies each time.
-
-- Set to 0: Generates a fixed output for each prompt
-- Lower values: More concentrated and deterministic output
-- Higher values: More random output (more creative)
-
-
- Generally, the longer and clearer the prompt, the better the quality and confidence of the model's
- output. In such cases, the temperature value can be adjusted appropriately. Conversely, if the
- prompt is short and ambiguous, setting a relatively high temperature value will result in unstable
- model output.
-
-
-
- -### `top_p` - -`top_p` is also a sampling parameter, but it differs from temperature in its sampling method. Before outputting, the model generates a bunch of tokens, and these tokens are ranked based on their quality. In the top-p sampling mode, the candidate word list is dynamic, and tokens are selected from the tokens based on a percentage. Top\_p introduces randomness in token selection, allowing other high-scoring tokens to have a chance of being selected, rather than always choosing the highest-scoring one. - -
- `top_p` is similar to randomness, and it is generally not recommended to change it together with
- the randomness of temperature.
-
-
-
- -### `presence_penalty` - -The presence penalty parameter can be seen as a punishment for repetitive content in the generated text. When this parameter is set high, the generation model will try to avoid producing repeated words, phrases, or sentences. Conversely, if the presence penalty parameter is set low, the generated text may contain more repetitive content. By adjusting the value of the presence penalty parameter, control over the originality and diversity of the generated text can be achieved. The importance of this parameter is mainly reflected in the following aspects: - -- Enhancing the originality and diversity of the generated text: In certain applications, such as creative writing or generating news headlines, it is necessary for the generated text to have high originality and diversity. By increasing the value of the presence penalty parameter, the amount of repeated content in the generated text can be effectively reduced, thereby enhancing its originality and diversity. -- Preventing the generation of loops and meaningless content: In some cases, the generation model may produce repetitive or meaningless text that usually fails to convey useful information. By appropriately increasing the value of the presence penalty parameter, the probability of generating such meaningless content can be reduced, thereby improving the readability and practicality of the generated text. - -
- It is worth noting that the presence penalty parameter, in conjunction with other parameters such
- as temperature and top-p, collectively influences the quality of the generated text. Compared to
- other parameters, the presence penalty parameter primarily focuses on the originality and
- repetitiveness of the text, while the temperature and top-p parameters more significantly affect
- the randomness and determinism of the generated text. By adjusting these parameters reasonably,
- comprehensive control over the quality of the generated text can be achieved.
-
-
-### `frequency_penalty`
-
-It is a mechanism that penalizes frequently occurring new vocabulary in the text to reduce the likelihood of the model repeating the same word. The larger the value, the more likely it is to reduce repeated words.
-
-- `-2.0` When the morning news started broadcasting, I found that my TV now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now now **(The highest frequency word is "now", accounting for 44.79%)**
-- `-1.0` He always watches the news in the early morning, in front of the TV watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch watch **(The highest frequency word is "watch", accounting for 57.69%)**
-- `0.0` When the morning sun poured into the small diner, a tired postman appeared at the door, carrying a bag of letters in his hands. The owner warmly prepared a breakfast for him, and he started sorting the mail while enjoying his breakfast. **(The highest frequency word is "of", accounting for 8.45%)**
-- `1.0` A girl in deep sleep was woken up by a warm ray of sunshine, she saw the first ray of morning light, surrounded by birdsong and flowers, everything was full of vitality. (The highest frequency word is "of", accounting for 5.45%)
-- `2.0` Every morning, he would sit on the balcony to have breakfast. Under the soft setting sun, everything looked very peaceful. However, one day, when he was about to pick up his breakfast, an optimistic little bird flew by, bringing him a good mood for the day. (The highest frequency word is "of", accounting for 4.94%)
-
-
- -### `reasoning_effort` - -The `reasoning_effort` parameter controls the strength of the reasoning process. This setting affects the depth of reasoning the model performs when generating a response. The available values are **`low`**, **`medium`**, and **`high`**, with the following meanings: - -- **low**: Lower reasoning effort, resulting in faster response times. Suitable for scenarios where quick responses are needed, but it may sacrifice some reasoning accuracy. -- **medium** (default): Balances reasoning accuracy and response speed, suitable for most scenarios. -- **high**: Higher reasoning effort, producing more detailed and complex responses, but slower response times and greater token consumption. - -By adjusting the `reasoning_effort` parameter, you can find an appropriate balance between response speed and reasoning depth based on your needs. For example, in conversational scenarios, if fast responses are a priority, you can choose low reasoning effort; if more complex analysis or reasoning is needed, you can opt for high reasoning effort. - -
- This parameter is only applicable to reasoning models, such as OpenAI's `o1`, `o1-mini`,
- `o3-mini`, etc.
-
diff --git a/docs/usage/agents/model.zh-CN.mdx b/docs/usage/agents/model.zh-CN.mdx
deleted file mode 100644
index 8ec1dc1afc..0000000000
--- a/docs/usage/agents/model.zh-CN.mdx
+++ /dev/null
@@ -1,88 +0,0 @@
----
-title: ChatGPT 模型指南：参数概念与应用
-description: >-
- 了解 ChatGPT 模型的不同版本及参数概念，包括 temperature、top_p、presence_penalty 和 frequency_penalty。
-
-tags:
- - ChatGPT
- - 模型指南
- - 参数概念
- - LLM
- - 生成模型
----
-
-# 模型指南
-
-## ChatGPT
-
-- **gpt-3.5-turbo**：目前最生成速度最快的 chatgpt 模型更快，但可能会牺牲一些生成文本的质量，上下文长度为 4k。
-- **gpt-4**：ChatGPT 4.0 在语言理解和生成能力方面相对于 3.5 有所提升。它可以更好地理解上下文和语境，并生成更准确、自然的回答。这得益于 GPT-4 模型的改进，包括更好的语言建模和更深入的语义理解，但它的速度可能比其他模型慢，上下文长度为 8k。
-- **gpt-4-32k**：同 gpt-4，上下文限制增加到 32k token，同时费率更高。
-
-## 模型参数概念
-
-LLM 看似很神奇，但本质还是一个概率问题，神经网络根据输入的文本，从预训练的模型里面生成一堆候选词，选择概率高的作为输出，相关的参数，大多都是跟采样有关（也就是要如何从候选词里选择输出）。
-
-### `temperature`
-
-用于控制模型输出的结果的随机性，这个值越大随机性越大。一般我们多次输入相同的 prompt 之后，模型的每次输出都不一样。
-
-- 设置为 0，对每个 prompt 都生成固定的输出
-- 较低的值，输出更集中，更有确定性
-- 较高的值，输出更随机（更有创意 ）
-
-
- 一般来说，prompt 越长，描述得越清楚，模型生成的输出质量就越好，置信度越高，这时可以适当调高
- temperature 的值；反过来，如果 prompt 很短，很含糊，这时再设置一个比较高的 temperature
- 值，模型的输出就很不稳定了。
-
-
-
- -### `top_p` - -核采样 `top_p` 也是采样参数，跟 temperature 不一样的采样方式。模型在输出之前，会生成一堆 token，这些 token 根据质量高低排名，核采样模式中候选词列表是动态的，从 tokens 里按百分比选择候选词。 top\_p 为选择 token 引入了随机性，让其他高分的 token 有被选择的机会，不会总是选最高分的。 - -`top_p` 与随机性类似，一般来说不建议和随机性 temperature 一起更改
-
-
- -### `presence_penalty` - -Presence Penalty 参数可以看作是对生成文本中重复内容的一种惩罚。当该参数设置较高时，生成模型会尽量避免产生重复的词语、短语或句子。相反，如果 Presence Penalty 参数较低，则生成的文本可能会包含更多重复的内容。通过调整 Presence Penalty 参数的值，可以实现对生成文本的原创性和多样性的控制。参数的重要性主要体现在以下几个方面： - -- 提高生成文本的独创性和多样性：在某些应用场景下，如创意写作、生成新闻标题等，需要生成的文本具有较高的独创性和多样性。通过增加 Presence Penalty 参数的值，可以有效减少生成文本中的重复内容，从而提高文本的独创性和多样性。 -- 防止生成循环和无意义的内容：在某些情况下，生成模型可能会产生循环、重复的文本，这些文本通常无法传达有效的信息。通过适当增加 Presence Penalty 参数的值，可以降低生成这类无意义内容的概率，提高生成文本的可读性和实用性。 - -
- 值得注意的是，Presence Penalty 参数与其他参数（如 Temperature 和
- top-p）共同影响着生成文本的质量。对比其他参数，Presence Penalty
- 参数主要关注文本的独创性和重复性，而 Temperature 和 top-p
- 参数则更多地影响着生成文本的随机性和确定性。通过合理地调整这些参数，可以实现对生成文本质量的综合控制
-
-
-
- -### `frequency_penalty` - -是一种机制，通过对文本中频繁出现的新词汇施加惩罚，以减少模型重复同一词语的可能性，值越大，越有可能降低重复字词。 - -- `-2.0` 当早间新闻开始播出，我发现我家电视现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在 *（频率最高的词是 “现在”，占比 44.79%）* -- `-1.0` 他总是在清晨看新闻，在电视前看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看 *（频率最高的词是 “看”，占比 57.69%）* -- `0.0` 当清晨的阳光洒进小餐馆时，一名疲倦的邮递员出现在门口，他的手中提着一袋信件。店主热情地为他准备了一份早餐，他在享用早餐的同时开始整理邮件。**（频率最高的词是 “的”，占比 8.45%）** -- `1.0` 一个深度睡眠的女孩被一阵温暖的阳光唤醒，她看到了早晨的第一缕阳光，周围是鸟语花香，一切都充满了生机。*（频率最高的词是 “的”，占比 5.45%）* -- `2.0` 每天早上，他都会在阳台上坐着吃早餐。在柔和的夕阳照耀下，一切看起来都非常宁静。然而有一天，当他准备端起早餐的时候，一只乐观的小鸟飞过，给他带来了一天的好心情。 *（频率最高的词是 “的”，占比 4.94%）* - -
- -### `reasoning_effort` - -`reasoning_effort` 参数用于控制推理过程的强度。此参数的设置会影响模型在生成回答时的推理深度。可选值包括 **`low`**、**`medium`** 和 **`high`**，具体含义如下： - -- **low（低）**：推理强度较低，生成速度较快，适用于需要快速响应的场景，但可能牺牲一定的推理精度。 -- **medium（中，默认值）**：平衡推理精度与响应速度，适用于大多数场景。 -- **high（高）**：推理强度较高，生成更为详细和复杂的回答，但响应时间较长，且消耗更多的 Token。 - -通过调整 `reasoning_effort` 参数，可以根据需求在生成速度与推理深度之间找到适合的平衡。例如，在对话场景中，如果更关注快速响应，可以选择低推理强度；如果需要更复杂的分析或推理，可以选择高推理强度。 - -该参数仅适用于推理模型，如 OpenAI 的 `o1`、`o1-mini`、`o3-mini` 等。
diff --git a/docs/usage/agents/prompt.mdx b/docs/usage/agents/prompt.mdx
deleted file mode 100644
index bce297d49b..0000000000
--- a/docs/usage/agents/prompt.mdx
+++ /dev/null
@@ -1,108 +0,0 @@
----
-title: >-
- Guide to Using Prompts in LobeChat - How to Write Effective Instructions for Generative AI
-
-description: >-
- Learn the basic concepts of prompts and how to write well-structured and effective instructions for generative AI. Improve the quality and effectiveness of prompts to guide AI models accurately.
-
-tags:
- - Generative AI
- - Prompts
- - Writing Instructions
- - Structured Prompts
- - Improving AI Output
----
-
-# Guide to Using Prompts
-
-## Basic Concepts of Prompts
-
-Generative AI is very useful, but it requires human guidance. In most cases, generative AI can be as capable as a new intern at a company, but it needs clear instructions to perform well. The ability to guide generative AI correctly is a very powerful skill. You can guide generative AI by sending a prompt, which is usually a text instruction. A prompt is the input provided to the assistant, and it will affect the output. A good prompt should be structured, clear, concise, and directive.
-
-## How to Write a Well-Structured Prompt
-
-
- A structured prompt refers to the construction of the prompt having a clear logic and structure.
- For example, if you want the model to generate an article, your prompt may need to include the
- article's topic, outline, and style.
-
-
-Let's look at a basic discussion prompt example:
-
-> *"What are the most urgent environmental issues facing our planet, and what actions can individuals take to help address these issues?"*
-
-We can convert it into a simple prompt for the assistant to answer the following questions: placed at the front.
-
-```prompt
-Answer the following questions:
-What are the most urgent environmental issues facing our planet, and what actions can individuals take to help address these issues?
-```
-
-Since the results generated by this prompt are not consistent, some are only one or two sentences. A typical discussion response should have multiple paragraphs, so these results are not ideal. A good prompt should provide **specific formatting and content instructions**. You need to eliminate ambiguity in the language to improve consistency and quality. Here is a better prompt.
-
-```prompt
-Write a highly detailed paper, including an introduction, body, and conclusion, to answer the following questions:
-What are the most urgent environmental issues facing our planet,
-and what actions can individuals take to help address these issues?
-```
-
-The second prompt generates longer output and better structure. The use of the term "paper" in the prompt is intentional, as the assistant can understand the definition of a paper, making it more likely to generate coherent, structured responses.
-
-## How to Improve Quality and Effectiveness
-
-
- There are several ways to improve the quality and effectiveness of prompts:
-
- - **Be Clear About Your Needs:** The model's output will strive to meet your needs, so if your needs are not clear, the output may not meet expectations.
- - **Use Correct Grammar and Spelling:** The model will try to mimic your language style, so if your language style is problematic, the output may also be problematic.
- - **Provide Sufficient Contextual Information:** The model will generate output based on the contextual information you provide, so if the information is insufficient, it may not produce the desired results.
-
-
-After formulating effective prompts for discussing issues, you now need to refine the generated results. This may involve adjusting the output to fit constraints such as word count or combining concepts from different generated results.
-
-A simple method of iteration is to generate multiple outputs and review them to understand the concepts and structures being used. Once the outputs have been evaluated, you can select the most suitable ones and combine them into a coherent response. Another iterative method is to start small and **gradually expand**. This requires more than one prompt: an initial prompt for drafting the initial one or two paragraphs, followed by additional prompts to expand on the content already written. Here is a potential philosophical discussion prompt:
-
-> *"Is mathematics an invention or a discovery? Use careful reasoning to explain your answer."*
-
-Add it to a simple prompt as follows:
-
-```prompt
-Write an opening paragraph to answer the following question:
-Is mathematics an invention or a discovery? Use careful reasoning to explain your answer.
-```
-
-After generating some responses, we found one that we like:
-
-```prompt
-Philosophers and mathematicians have long debated whether mathematics is an invention or a discovery.
-Some argue that the concepts and principles of mathematics exist independently of human thought, and therefore can be considered discovered rather than invented.
-For example, the concepts of numbers, ratios, and geometric shapes are observed in the natural world and can be abstracted and systematically studied.
-```
-
-It's a good start. Then, use another prompt to expand:
-
-```prompt
-I am writing a detailed essay to answer the following prompt:
-Is mathematics an invention or a discovery? Use careful reasoning to explain your answer. Here is my current situation: Philosophers and mathematicians have long debated whether mathematics is an invention or a discovery.
-Some argue that the concepts and principles of mathematics exist independently of human thought, and therefore can be considered discovered rather than invented.
-For example, the concepts of numbers, ratios, and geometric shapes are observed in the natural world and can be abstracted and systematically studied. Write the next paragraph of my essay.
-```
-
-I used this prompt to generate several extensions and selected one that I liked, resulting in the following:
-
-```prompt
-Philosophers and mathematicians have long debated whether mathematics is invented or discovered.
-Some argue that the concepts and principles of mathematics exist independently of human thought, and therefore can be considered to be discovered rather than invented.
-For example, the concepts of numbers, ratios, and geometric shapes are observed in the natural world and can be abstracted and systematically studied.
-On the other hand, some believe that mathematics is largely an invention of human thought.
-Mathematical principles are based on logical reasoning, which is a characteristic of human thought.
-For instance, Euclidean geometry is based on abstract axioms and premises, accepted as true without the need for proof.
-Therefore, geometry can be considered an invention of human thought rather than a discovery.
-Similarly, mathematical formulas and equations are used to model and predict physical phenomena, which are the result of human reasoning.
-```
-
-Using the prompt extensions, we can iteratively write and iterate at each step. This is very useful for situations that require **generating higher quality output and incremental modifications**.
-
-## Further Reading
-
-- **Learn Prompting**: [https://learnprompting.org/en-US/docs/intro](https://learnprompting.org/en-US/docs/intro)
diff --git a/docs/usage/agents/prompt.zh-CN.mdx b/docs/usage/agents/prompt.zh-CN.mdx
deleted file mode 100644
index 5c2e7de6cf..0000000000
--- a/docs/usage/agents/prompt.zh-CN.mdx
+++ /dev/null
@@ -1,105 +0,0 @@
----
-title: 如何通过 LobeChat 写好结构化 Prompt - 提高生成式 AI 输出质量的关键
-description: 学习如何撰写结构化 Prompt 可以提高生成式 AI 输出的质量和效果。本文介绍了撰写有效 Prompt 的方法和技巧，以及如何逐步扩展和优化生成的结果。
-tags:
- - 结构化 Prompt
- - 生成式AI
- - 提高输出质量
- - 撰写技巧
- - 逐步扩展
----
-
-# Prompt 使用指南
-
-## Prompt 基本概念
-
-生成式 AI 非常有用，但它需要人类指导。通常情况下，生成式 AI 能就像公司新来的实习生一样，非常有能力，但需要清晰的指示才能做得好。能够正确地指导生成式 AI 是一项非常强大的技能。你可以通过发送一个 prompt 来指导生成式 AI，这通常是一个文本指令。Prompt 是向助手提供的输入，它会影响输出结果。一个好的 Prompt 应该是结构化的，清晰的，简洁的，并且具有指向性。
-
-## 如何写好一个结构化 prompt
-
-
- 结构化 prompt 是指 prompt 的构造应该有明确的逻辑和结构。例如，如果你想让模型生成一篇文章，你的
- prompt 可能需要包括文章的主题，文章的大纲，文章的风格等信息。
-
-
-让我们看一个基本的讨论问题的例子:
-
-> *"我们星球面临的最紧迫的环境问题是什么，个人可以采取哪些措施来帮助解决这些问题？"*
-
-我们可以将其转化为简单的助手提示，将回答以下问题：放在前面。
-
-```prompt
-回答以下问题:
-我们星球面临的最紧迫的环境问题是什么，个人可以采取哪些措施来帮助解决这些问题？
-```
-
-由于这个提示生成的结果并不一致，有些只有一两个句子。一个典型的讨论回答应该有多个段落，因此这些结果并不理想。一个好的提示应该给出**具体的格式和内容指令**。您需要消除语言中的歧义以提高一致性和质量。这是一个更好的提示。
-
-```prompt
-写一篇高度详细的论文，包括引言、正文和结论段，回答以下问题:
-我们星球面临的最紧迫的环境问题是什么，
-个人可以采取哪些措施来帮助解决这些问题？
-```
-
-第二个提示生成了更长的输出和更好的结构。提示中使用 “论文” 一词是有意的，因为助手可以理解论文的定义，因此更有可能生成连贯的、结构化的回答。
-
-
- -## 如何提升其质量和效果 - -
- 提升 prompt 质量和效果的方法主要有以下几点：
-
- - **尽量明确你的需求：** 模型的输出会尽可能满足你的需求，所以如果你的需求不明确，输出可能会不如预期。
- - **使用正确的语法和拼写：** 模型会尽可能模仿你的语言风格，所以如果你的语言风格有问题，输出可能也会有问题。
- - **提供足够的上下文信息：** 模型会根据你提供的上下文信息生成输出，所以如果你提供的上下文信息不足，可能无法生成你想要的结果。
-
-
-在为讨论问题制定有效的提示后，您现在需要细化生成的结果。这可能涉及到调整输出以符合诸如字数等限制，或将不同生成的结果的概念组合在一起。
-
-迭代的一个简单方法是生成多个输出并查看它们，以了解正在使用的概念和结构。一旦评估了输出，您就可以选择最合适的输出并将它们组合成一个连贯的回答。另一种迭代的方法是逐步开始，然后**逐步扩展**。这需要不止一个提示：一个起始提示，用于撰写最初的一两段，然后是其他提示，以扩展已经写过的内容。以下是一个潜在的哲学讨论问题:
-
-> *"数学是发明还是发现？用仔细的推理来解释你的答案。"*
-
-将其添加到一个简单的提示中，如下所示:
-
-```prompt
-写一个起始段回答以下问题:
-数学是发明还是发现？用仔细的推理来解释你的答案。
-```
-
-生成了一些回答，找到了一个我们喜欢的：
-
-```prompt
-哲学家和数学家之间争论不休，数学是发明还是发现。
-一些人认为，数学的概念和原则独立于人类思维存在，因此可以被认为是被发现而不是被发明的。
-例如，数字、比率和几何形状的概念在自然界中被观察到，可以被抽象化和系统化地研究。
-```
-
-是一个不错的开端。然后使用另一个提示来扩展：
-
-```prompt
-我正在撰写一篇详细的短文，回答以下提示:
-数学是发明还是发现？用仔细的推理来解释你的答案。这是我目前的情况: 哲学家和数学家之间争论不休，数学是发明还是发现。
-一些人认为，数学的概念和原则独立于人类思维存在，因此可以被认为是被发现而不是被发明的。
-例如，数字、比率和几何形状的概念在自然界中被观察到，可以被抽象化和系统化地研究。写下我文章的下一段。
-```
-
-使用此提示生成了几个扩展，并选择了一个我喜欢的，最终得到了以下结果：
-
-```prompt
-哲学家和数学家之间争论不休，数学是发明还是发现。
-一些人认为，数学的概念和原则独立于人类思维存在，因此可以被认为是被发现而不是被发明的。
-例如，数字、比率和几何形状的概念在自然界中被观察到，可以被抽象化和系统化地研究。
-另一方面，有人认为数学在很大程度上是人类思维的发明。
-数学原理基于逻辑推理，这是人类思维的一个特征。
-例如，欧几里德几何基于抽象的公理和前提，被接受为真实而无需证明。
-因此，可以认为几何是人类思维的发明，而不是一种发现。
-同样，数学公式和方程用于模拟和预测物理现象，这又是人类推理的结果。
-```
-
-使用扩展提示，我们可以逐步地写作并在每个步骤上进行迭代。这对于需要**生成更高质量的输出并希望逐步修改**的情况非常有用。
-
-## 扩展阅读
-
-- **Learn Prompting**: [https://learnprompting.org/zh-Hans/docs/intro](https://learnprompting.org/zh-Hans/docs/intro)
diff --git a/docs/usage/agents/topics.mdx b/docs/usage/agents/topics.mdx
deleted file mode 100644
index 0f7bb762c5..0000000000
--- a/docs/usage/agents/topics.mdx
+++ /dev/null
@@ -1,26 +0,0 @@
----
-title: LobeChat Topic Usage Guide
-description: >-
- Learn how to save and manage topics during conversations in LobeChat, including saving topics, accessing the topic list, and pinning favorite topics.
-
-tags:
- - Topic Usage
- - Conversation Management
- - Save Topic
- - Topic List
- - Favorite Topics
----
-
-# Topic Usage Guide
-
-
+
+
+## Developing Custom Plugins
+
+If you're interested in developing your own LobeHub plugin, check out the [Plugin Development Guide](/en/docs/usage/plugins/development) to push the boundaries of what's possible with your AI assistant!
diff --git a/docs/usage/community/custom-plugin.zh-CN.mdx b/docs/usage/community/custom-plugin.zh-CN.mdx
new file mode 100644
index 0000000000..6ca41bdbed
--- /dev/null
+++ b/docs/usage/community/custom-plugin.zh-CN.mdx
@@ -0,0 +1,35 @@
+---
+title: 自定义插件
+description: 学习如何安装自定义插件和开发 LobeHub 插件，扩展你的 AI 智能助手的功能。
+tags:
+ - 自定义插件
+ - LobeHub
+ - 插件安装
+ - 插件开发
+ - AI 智能助手
+---
+
+# 自定义插件
+
+## 安装自定义插件
+
+如果你希望安装一个不在 LobeHub 插件商店中的插件，例如自己开发的 LobeHub，你可以点击「自定义插件」进行安装：
+
+
+
+此外，LobeHub 的插件机制兼容了 ChatGPT 的插件，因此你可以一键安装相应的 ChatGPT 插件。
+
+如果你希望尝试自行安装自定义插件，你可以使用以下链接来尝试：
+
+- `自定义 Lobe 插件` Mock Credit Card：[https://lobe-plugin-mock-credit-card.vercel.app/manifest.json](https://lobe-plugin-mock-credit-card.vercel.app/manifest.json)
+- `ChatGPT 插件` Access Links：[https://www.accesslinks.ai/.well-known/ai-plugin.json](https://www.accesslinks.ai/.well-known/ai-plugin.json)
+
+
+
+
+## 开发自定义插件
+
+如果你希望自行开发一个 LobeHub 的插件，欢迎查阅 [插件开发指南](/zh/docs/usage/plugins/development) 以扩展你的 AI 智能助手的可能性边界！
diff --git a/docs/usage/community/mcp-market.mdx b/docs/usage/community/mcp-market.mdx
new file mode 100644
index 0000000000..a1b4f07fcd
--- /dev/null
+++ b/docs/usage/community/mcp-market.mdx
@@ -0,0 +1,32 @@
+---
+title: MCP Marketplace
+description: >-
+ The MCP Marketplace is LobeHub's official hub, featuring a wide range of
+ meticulously crafted MCPs designed to enhance productivity in both work and
+ learning environments. You're welcome to submit your own MCP creations and
+ help build a more innovative, practical, and engaging ecosystem.
+tags:
+ - LobeHub
+ - MCP Marketplace
+ - Innovation Community
+ - Collaborative Space
+ - MCP Creations
+ - Automated Internationalization
+ - Multilingual Support
+---
+
+# MCP Marketplace
+
+The MCP Marketplace by LobeHub brings together high-quality MCPs from creators around the world.
+
+## Explore the MCP Marketplace
+
+Click on "Community" → "MCP" in the left sidebar to access the MCP Marketplace homepage.
+
+
+
+The assistant marketplace is organized by category, making it easy to quickly find the type of assistant you need.
+
+## Installing an MCP
+
+Please exercise caution when using MCPs from unknown sources. LobeHub cannot guarantee the safety of all MCPs.
diff --git a/docs/usage/community/mcp-market.zh-CN.mdx b/docs/usage/community/mcp-market.zh-CN.mdx
new file mode 100644
index 0000000000..335d6bcf59
--- /dev/null
+++ b/docs/usage/community/mcp-market.zh-CN.mdx
@@ -0,0 +1,30 @@
+---
+title: MCP 市场
+description: >-
+ MCP 市场是 LobeHub 的官方市场，汇聚了众多精心设计的 MCP，为工作场景和学习提供便利。欢迎提交你的 MCP
+ 作品，共同创造更多有趣、实用且具有创新性的 MCP。
+tags:
+ - LobeHub
+ - MCP 市场
+ - 创新社区
+ - 协作空间
+ - MCP 作品
+ - 自动化国际化
+ - 多语言版本
+---
+
+# MCP 市场
+
+LobeHub 的 MCP 市场汇聚了来自全球创作者的优质 MCP。
+
+## 浏览 MCP 市场
+
+点击左侧边栏的「社区」→「MCP」，进入 MCP 市场主页。
+
+
+
+助理市场按类别组织，方便你快速找到所需的助理类型。
+
+## 安装 MCP
+
+请谨慎使用来路不明的 MCP，LobeHub 无法确保所有 MCP 的安全性。
diff --git a/docs/usage/community/publish-agent.mdx b/docs/usage/community/publish-agent.mdx
new file mode 100644
index 0000000000..b9cea33fd4
--- /dev/null
+++ b/docs/usage/community/publish-agent.mdx
@@ -0,0 +1,30 @@
+---
+title: Publish Your Agent on the Marketplace
+description: >-
+ The LobeHub Assistant Marketplace is a vibrant and innovative community that
+ brings together a wide range of thoughtfully designed assistants to enhance
+ productivity and learning. You're welcome to submit your own assistant and
+ contribute to a growing collection of creative, practical, and cutting-edge
+ tools.
+tags:
+ - LobeHub
+ - LobeHub
+ - Assistant Marketplace
+ - Innovation Community
+ - Collaborative Space
+ - Assistant Creations
+ - Automated Internationalization
+ - Multilingual Support
+---
+
+# Submit Your Agent
+
+If you've created a high-quality Agent, you can submit it to the marketplace and share it with users around the world.
+
+If this is your first time submitting an Agent, you'll need to [create a community profile](/docs/usage/community/become-a-creator) first. This allows you to manage your submissions and published content within the community.
+
+Once you're a registered creator, go to the Agent you want to publish, open its "Agent Profile," and click "Share Assistant to Community."
+
+
+
+After your submission is reviewed and approved, your Agent will appear in the marketplace, available to users worldwide. LobeHub welcomes all users to join this ever-growing ecosystem and take part in the continuous improvement and evolution of assistants. Together, we can build a diverse, practical, and innovative collection of tools that enrich the assistant experience for everyone.
diff --git a/docs/usage/community/publish-agent.zh-CN.mdx b/docs/usage/community/publish-agent.zh-CN.mdx
new file mode 100644
index 0000000000..5584dfe832
--- /dev/null
+++ b/docs/usage/community/publish-agent.zh-CN.mdx
@@ -0,0 +1,27 @@
+---
+title: 在市场发布 Agent
+description: >-
+ LobeHub
+ 助手市场是一个充满活力和创新的社区，汇聚了众多精心设计的助手，为工作场景和学习提供便利。欢迎提交你的助手作品，共同创造更多有趣、实用且具有创新性的助手。
+tags:
+ - LobeHub
+ - LobeHub
+ - 助手市场
+ - 创新社区
+ - 协作空间
+ - 助手作品
+ - 自动化国际化
+ - 多语言版本
+---
+
+# 提交你的 Agent
+
+如果你创建了优质的 Agent，可以提交到市场与全球用户分享。
+
+如果你是首次提交 Agent，需要先[创建社区个人档案](/docs/usage/community/become-a-creator)，以便在社区上提交和管理上架信息。
+
+当你已成为创作者，选择需要发布的 Agent 进入「Agent 档案」，点击「分享助理到社区」即可。
+
+
+
+通过审核后，你的 Agent 会出现在市场中，供全球用户使用。LobeHub 欢迎所有用户加入这个不断成长的生态系统，共同参与到助理的迭代与优化中来。共同创造出更多有趣、实用且具有创新性的助理，进一步丰富助理的多样性和实用性。
diff --git a/docs/usage/community/pulgin-development.mdx b/docs/usage/community/pulgin-development.mdx
new file mode 100644
index 0000000000..273b910804
--- /dev/null
+++ b/docs/usage/community/pulgin-development.mdx
@@ -0,0 +1,281 @@
+---
+title: Plugin Development
+description: >-
+ Learn how to add and use custom plugins in LobeHub, including creating a
+ plugin project, adding local plugins in role settings, testing plugin
+ functionality, and understanding the development and deployment process.
+tags:
+ - LobeHub
+ - LobeHub
+ - Plugin Development
+ - Custom Plugins
+ - Plugin Deployment
+ - Plugin Publishing
+ - Plugin UI
+ - Plugin SDK
+---
+
+# Plugin Development
+
+## Plugin Structure
+
+A LobeHub plugin consists of the following components:
+
+1. **Plugin Index**: Displays basic plugin information, including name, description, author, version, and a link to the plugin manifest. The official plugin index is hosted at [lobe-chat-plugins](https://github.com/lobehub/lobe-chat-plugins). To publish your plugin to the official marketplace, you need to [submit a PR](https://github.com/lobehub/lobe-chat-plugins/pulls) to this repository.
+2. **Plugin Manifest**: Describes the plugin's functionality, including backend services, frontend UI, version, and more. For a detailed explanation, see \[manifest]\[manifest-docs-url].
+3. **Plugin Services**: Implements the backend and optional frontend modules described in the manifest:
+ - **Backend**: Implements the `api` section defined in the manifest.
+ - **Frontend UI** (optional): Implements the `ui` section, allowing for richer message displays beyond plain text.
+
+## Custom Plugin Workflow
+
+This section walks you through how to add and use a custom plugin in LobeHub.
+
+
+ ### Create and Start a Plugin Project
+
+ First, create a local plugin project using our template: \[lobe-chat-plugin-template]\[lobe-chat-plugin-template-url]
+
+ ```bash
+ $ git clone https://github.com/lobehub/chat-plugin-template.git
+ $ cd chat-plugin-template
+ $ npm i
+ $ npm run dev
+ ```
+
+ Once you see `ready started server on 0.0.0.0:3400, url: http://localhost:3400`, your plugin service is running locally.
+
+
+
+## Local Plugin Development
+
+Now that you know how to add and use a plugin, let’s dive into the development process.
+
+### Manifest
+
+The `manifest` defines how the plugin works. The key fields are `api` and `ui`, which describe the backend API and frontend UI respectively.
+
+Here’s an example from the template:
+
+```json
+{
+ "api": [
+ {
+ "url": "http://localhost:3400/api/clothes",
+ "name": "recommendClothes",
+ "description": "Recommend clothes based on the user's mood",
+ "parameters": {
+ "properties": {
+ "mood": {
+ "description": "User's current mood. Options: happy, sad, anger, fear, surprise, disgust",
+ "enums": ["happy", "sad", "anger", "fear", "surprise", "disgust"],
+ "type": "string"
+ },
+ "gender": {
+ "type": "string",
+ "enum": ["man", "woman"],
+ "description": "User's gender, must be asked before calling the API"
+ }
+ },
+ "required": ["mood", "gender"],
+ "type": "object"
+ }
+ }
+ ],
+ "gateway": "http://localhost:3400/api/gateway",
+ "identifier": "chat-plugin-template",
+ "ui": {
+ "url": "http://localhost:3400",
+ "height": 200
+ },
+ "version": "1"
+}
+```
+
+Key fields:
+
+1. `identifier`: Unique plugin ID. Must be globally unique.
+2. `api`: Array of API definitions. Each includes `url`, `name`, `description`, and `parameters`. The `description` and `parameters` are used in GPT’s [Function Call](https://sspai.com/post/81986) and must follow [JSON Schema](https://json-schema.org/).
+3. `ui`: Defines the plugin’s frontend interface, loaded via iframe. You can specify height and width.
+4. `gateway`: Specifies the API gateway. LobeHub’s default is a cloud service, but for local plugins, this should point to your local server.
+5. `version`: Plugin version (currently unused).
+
+For a full breakdown of manifest fields, see: \[manifest]\[manifest-docs-url].
+
+### Project Structure
+
+The \[lobe-chat-plugin-template]\[lobe-chat-plugin-template-url] uses Next.js. Its structure:
+
+```
+➜ chat-plugin-template
+├── public
+│ └── manifest-dev.json # Manifest file
+├── src
+│ └── pages
+│ │ ├── api # Next.js API routes
+│ │ │ ├── clothes.ts # recommendClothes API
+│ │ │ └── gateway.ts # Local plugin gateway
+│ │ └── index.tsx # Frontend UI
+```
+
+You can use any framework or language, as long as it implements the manifest functionality.
+
+We also welcome contributions of templates in other frameworks and languages.
+
+### Backend
+
+The backend implements the APIs defined in the manifest. The template uses Vercel’s [Edge Runtime](https://nextjs.org/docs/pages/api-reference/edge) for serverless deployment.
+
+#### API Implementation
+
+We provide a `createErrorResponse` method in `@lobehub/chat-plugin-sdk` for handling errors. See \[PluginErrorType]\[plugin-error-type-url] for available types.
+
+Example implementation of the clothes API:
+
+```ts
+export default async (req: Request) => {
+ if (req.method !== 'POST') return createErrorResponse(PluginErrorType.MethodNotAllowed);
+
+ const { gender, mood } = (await req.json()) as RequestData;
+
+ const clothes = gender === 'man' ? manClothes : womanClothes;
+
+ const result: ResponseData = {
+ clothes: clothes[mood] || [],
+ mood,
+ today: Date.now(),
+ };
+
+ return new Response(JSON.stringify(result));
+};
+```
+
+`manClothes` and `womanClothes` are mock data. Replace with real data sources as needed.
+
+#### Plugin Gateway
+
+LobeHub’s default plugin gateway is `/api/plugins`, which sends requests to the `api.url` in the manifest.
+
+For local plugins, set the `gateway` to a local address (e.g., `http://localhost:3400/api/gateway`). Then implement the gateway:
+
+```ts
+import { createLobeHubPluginGateway } from '@lobehub/chat-plugins-gateway';
+
+export const config = {
+ runtime: 'edge',
+};
+
+export default createLobeHubPluginGateway();
+```
+
+[`@lobehub/chat-plugins-gateway`](https://github.com/lobehub/chat-plugins-gateway) provides the gateway implementation used in LobeHub. Use it to route requests to your local plugin service.
+
+### Plugin UI
+
+The UI is optional. For example, the official plugin [🧩 / 🕸 Web Content Extractor](https://github.com/lobehub/chat-plugin-web-crawler) has no UI.
+
+();
+
+ useEffect(() => {
+ fetchPluginMessage().then((e: ResponseData) => {
+ setData(e);
+ });
+ }, []);
+
+ return <>...;
+});
+
+export default Render;
+```
+
+## Plugin Deployment & Publishing
+
+Once your plugin is ready, deploy it using your preferred method—Vercel, Docker, etc.
+
+To share your plugin with others, consider [submitting it](https://github.com/lobehub/lobe-chat-plugins) to the official plugin marketplace.
+
+\[!\[]\[submit-plugin-shield]]\[submit-plugin-url]
+
+### Plugin Shield
+
+[](https://github.com/lobehub/lobe-chat-plugins)
+
+```markdown
+[](https://github.com/lobehub/lobe-chat-plugins)
+```
+
+## Links
+
+- **📘 Plugin SDK Docs**: [https://chat-plugin-sdk.lobehub.com](https://chat-plugin-sdk.lobehub.com)
+- **🚀 chat-plugin-template**: [https://github.com/lobehub/chat-plugin-template](https://github.com/lobehub/chat-plugin-template)
+- **🧩 chat-plugin-sdk**: [https://github.com/lobehub/chat-plugin-sdk](https://github.com/lobehub/chat-plugin-sdk)
+- **🚪 chat-plugin-gateway**: [https://github.com/lobehub/chat-plugins-gateway](https://github.com/lobehub/chat-plugins-gateway)
+- **🏪 lobe-chat-plugins**: [https://github.com/lobehub/lobe-chat-plugins](https://github.com/lobehub/lobe-chat-plugins)
+
+```
+
+[fetch-plugin-message-url]: https://github.com/lobehub/chat-plugin-template
+[lobe-chat-plugin-template-url]: https://github.com/lobehub/chat-plugin-template
+[manifest-docs-url]: https://chat-plugin-sdk.lobehub.com/guides/plugin-manifest
+[plugin-error-type-url]: https://github.com/lobehub/chat-plugin-template
+[submit-plugin-shield]: https://img.shields.io/badge/🧩/🏪_submit_plugin-%E2%86%92-95f3d9?labelColor=black&style=for-the-badge
+[submit-plugin-url]: https://github.com/lobehub/lobe-chat-plugins
+```
diff --git a/docs/usage/plugins/development.zh-CN.mdx b/docs/usage/community/pulgin-development.zh-CN.mdx
similarity index 78%
rename from docs/usage/plugins/development.zh-CN.mdx
rename to docs/usage/community/pulgin-development.zh-CN.mdx
index 7ac82ce7bd..2c7b99e265 100644
--- a/docs/usage/plugins/development.zh-CN.mdx
+++ b/docs/usage/community/pulgin-development.zh-CN.mdx
@@ -1,8 +1,9 @@
---
-title: LobeChat 插件开发指南
-description: 学习如何在 LobeChat 中添加和使用自定义插件，包括创建插件项目、在角色设置中添加本地插件、测试插件功能以及插件开发流程和部署。
+title: 插件开发
+description: 学习如何在 LobeHub 中添加和使用自定义插件，包括创建插件项目、在角色设置中添加本地插件、测试插件功能以及插件开发流程和部署。
tags:
- - LobeChat
+ - LobeHub
+ - LobeHub
- 插件开发
- 自定义插件
- 插件部署
@@ -11,11 +12,11 @@ tags:
- 插件SDK
---
-# 插件开发指南
+# 插件开发
## 插件构成
-一个 LobeChat 的插件由以下几个部分组成：
+一个 LobeHub 的插件由以下几个部分组成：
1. **插件索引**：用于展示插件的基本信息，包括插件名称、描述、作者、版本、插件描述清单的链接，官方的插件索引地址：[lobe-chat-plugins](https://github.com/lobehub/lobe-chat-plugins)。若想上架插件到官方插件市场，需要 [提交 PR](https://github.com/lobehub/lobe-chat-plugins/pulls) 到该仓库；
2. **插件描述清单 (manifest)**：用于描述插件的功能实现，包含了插件的服务端描述、前端展示信息、版本号等。关于 manifest 的详细介绍，详见 [manifest][manifest-docs-url]；
@@ -25,7 +26,7 @@ tags:
## 自定义插件流程
-本节将会介绍如何在 LobeChat 中添加和使用一个自定义插件。
+本节将会介绍如何在 LobeHub 中添加和使用一个自定义插件。
### 创建并启动插件项目
@@ -43,25 +44,25 @@ tags:
## 本地插件开发
@@ -127,8 +128,8 @@ tags:
1. `identifier`：这是插件的唯一标识符，用来区分不同的插件，这个字段需要全局唯一。
2. `api`：这是一个数组，包含了插件的所有 API 接口信息。每个接口都包含了 url、name、description 和 parameters 字段，均为必填项。其中 `description` 和 `parameters` 两个字段，将会作为 [Function Call](https://sspai.com/post/81986) 的 `functions` 参数发送给 gpt， parameters 需要符合 [JSON Schema](https://json-schema.org/) 规范。 在这个例子中，api 接口名为 `recommendClothes` ，这个接口的功能是根据用户的心情和性别来推荐衣服。接口的参数包括用户的心情和性别，这两个参数都是必填项。
-3. `ui`：这个字段包含了插件的用户界面信息，指明了 LobeChat 从哪个地址加载插件的前端界面。由于 LobeChat 插件界面加载是基于 iframe 实现的，因此可以按需指定插件界面的高度、宽度。
-4. `gateway`：这个字段指定了 LobeChat 查询 api 接口的网关。LobeChat 默认的插件网关是云端服务，而自定义插件的请求需要发给本地启动的服务，远端调用本地地址，一般调用不通。gateway 字段解决了该问题。通过在 manifest 中指定 gateway，LobeChat 将会向该地址发送插件请求，本地的网关地址将会调度请求到本地的插件服务。发布到线上的插件可以不用指定该字段。
+3. `ui`：这个字段包含了插件的用户界面信息，指明了 LobeHub 从哪个地址加载插件的前端界面。由于 LobeHub 插件界面加载是基于 iframe 实现的，因此可以按需指定插件界面的高度、宽度。
+4. `gateway`：这个字段指定了 LobeHub 查询 api 接口的网关。LobeHub 默认的插件网关是云端服务，而自定义插件的请求需要发给本地启动的服务，远端调用本地地址，一般调用不通。gateway 字段解决了该问题。通过在 manifest 中指定 gateway，LobeHub 将会向该地址发送插件请求，本地的网关地址将会调度请求到本地的插件服务。发布到线上的插件可以不用指定该字段。
5. `version`：这是插件的版本号，现阶段暂时没有作用；
在实际开发中，你可以根据自己的需求，修改插件的描述清单，声明想要实现的功能。 关于 manifest 各个字段的完整介绍，参见：[manifest][manifest-docs-url]。
@@ -185,21 +186,21 @@ export default async (req: Request) => {
#### Plugin Gateway
-由于 LobeChat 默认的插件网关是云端服务 `/api/plugins`，云端服务通过 manifest 上的 `api.url` 地址发送请求，以解决跨域问题。
+由于 LobeHub 默认的插件网关是云端服务 `/api/plugins`，云端服务通过 manifest 上的 `api.url` 地址发送请求，以解决跨域问题。
-针对自定义插件，插件请求需要发送给本地服务， 因此通过在 manifest 中指定网关 ([http://localhost:3400/api/gateway)，LobeChat](http://localhost:3400/api/gateway\)，LobeChat) 将会直接请求该地址，然后只需要在该地址下创建对应的网关即可。
+针对自定义插件，插件请求需要发送给本地服务， 因此通过在 manifest 中指定网关 ([http://localhost:3400/api/gateway)，LobeHub](http://localhost:3400/api/gateway\)，LobeHub) 将会直接请求该地址，然后只需要在该地址下创建对应的网关即可。
```ts
-import { createLobeChatPluginGateway } from '@lobehub/chat-plugins-gateway';
+import { createLobeHubPluginGateway } from '@lobehub/chat-plugins-gateway';
export const config = {
runtime: 'edge',
};
-export default createLobeChatPluginGateway();
+export default createLobeHubPluginGateway();
```
-[`@lobehub/chat-plugins-gateway`](https://github.com/lobehub/chat-plugins-gateway) 包含了 LobeChat 中插件网关的[实现](https://github.com/lobehub/lobe-chat/blob/main/src/pages/api/plugins.api.ts)，你可以直接使用该包创建网关，进而让 LobeChat 访问到本地的插件服务。
+[`@lobehub/chat-plugins-gateway`](https://github.com/lobehub/chat-plugins-gateway) 包含了 LobeHub 中插件网关的[实现](https://github.com/lobehub/lobe-chat/blob/main/src/pages/api/plugins.api.ts)，你可以直接使用该包创建网关，进而让 LobeHub 访问到本地的插件服务。
### 插件 UI 界面
@@ -213,13 +214,13 @@ export default createLobeChatPluginGateway();
#### 插件 UI 界面实现
-LobeChat 通过 `iframe` 实现插件 ui 的加载，使用 `postMessage` 实现主体与插件的通信。因此， 插件 UI 的实现方式与普通的网页开发一致，你可以使用任何你熟悉的前端框架与开发语言。
+LobeHub 通过 `iframe` 实现插件 ui 的加载，使用 `postMessage` 实现主体与插件的通信。因此， 插件 UI 的实现方式与普通的网页开发一致，你可以使用任何你熟悉的前端框架与开发语言。
();
useEffect(() => {
- // 从 LobeChat 获取当前插件的消息
+ // 从 LobeHub 获取当前插件的消息
fetchPluginMessage().then((e: ResponseData) => {
setData(e);
});
diff --git a/docs/usage/features/agent-market.mdx b/docs/usage/features/agent-market.mdx
deleted file mode 100644
index eb445f4e0a..0000000000
--- a/docs/usage/features/agent-market.mdx
+++ /dev/null
@@ -1,32 +0,0 @@
----
-title: Find best Assistants in LobeChat Assistant Market
-description: >-
- Explore a vibrant community of carefully designed assistants in LobeChat's Assistant Market. Contribute your wisdom and share your personally developed assistants in this collaborative space.
-
-tags:
- - LobeChat
- - Assistant Market
- - Community
- - Collaboration
- - Assistants
----
-
-# Assistant Market
-
-
- By [🤖/🏪 submitting agents](https://github.com/lobehub/lobe-chat-agents), you can easily submit
- your assistant works to our platform. We particularly emphasize that LobeChat has established a
- sophisticated automated internationalization (i18n) workflow, which excels in seamlessly
- converting your assistants into multiple language versions. This means that regardless of the
- language your users are using, they can seamlessly experience your assistant.
-
-
-
- We welcome all users to join this ever-growing ecosystem and participate in the iteration and
- optimization of assistants. Together, let's create more interesting, practical, and innovative
- assistants, further enriching the diversity and practicality of assistants.
-
diff --git a/docs/usage/features/agent-market.zh-CN.mdx b/docs/usage/features/agent-market.zh-CN.mdx
deleted file mode 100644
index a9d26d158a..0000000000
--- a/docs/usage/features/agent-market.zh-CN.mdx
+++ /dev/null
@@ -1,31 +0,0 @@
----
-title: 在 LobeChat 助手市场找到创新 AI 助手
-description: >-
- LobeChat助手市场是一个充满活力和创新的社区，汇聚了众多精心设计的助手，为工作场景和学习提供便利。欢迎提交你的助手作品，共同创造更多有趣、实用且具有创新性的助手。
-
-tags:
- - LobeChat
- - 助手市场
- - 创新社区
- - 协作空间
- - 助手作品
- - 自动化国际化
- - 多语言版本
----
-
-# 助手市场
-
-
- 通过 [🤖/🏪 提交助手](https://github.com/lobehub/lobe-chat-agents)
- ，你可以轻松地将你的助手作品提交到我们的平台。我们特别强调的是，LobeChat
- 建立了一套精密的自动化国际化（i18n）工作流程，
- 它的强大之处在于能够无缝地将你的助手转化为多种语言版本。这意味着，不论你的用户使用何种语言，他们都能无障碍地体验到你的助手。
-
-
-
- 我们欢迎所有用户加入这个不断成长的生态系统，共同参与到助手的迭代与优化中来。共同创造出更多有趣、实用且具有创新性的助手，进一步丰富助手的多样性和实用性。
-
diff --git a/docs/usage/features/agent-team.mdx b/docs/usage/features/agent-team.mdx
deleted file mode 100644
index dfb22668a0..0000000000
--- a/docs/usage/features/agent-team.mdx
+++ /dev/null
@@ -1,52 +0,0 @@
----
-title: Agent Team
-description: Turn any conversation into a team effort. Multiple AI agents collaborate naturally to give you richer, more insightful responses.
-tags:
- - Agent Team
- - Multi-Agent
- - AI Orchestration
- - Agent Coordination
----
-
-# Agent Team
-
-
- After submission, there is a **72-hour cooling-off period** during which you can cancel at any time. Once the period ends:
-
- - Your account data will be permanently deleted
- - Unpaid invoices will be canceled immediately
- - Paid fees will not be refunded
- - Your registration and deletion records will be retained for compliance purposes
-
-
-
- For self-hosting deployment, please refer to [Authentication Services](/docs/self-hosting/advanced/auth) for configuration details.
-
diff --git a/docs/usage/features/auth.zh-CN.mdx b/docs/usage/features/auth.zh-CN.mdx
deleted file mode 100644
index e078858ac0..0000000000
--- a/docs/usage/features/auth.zh-CN.mdx
+++ /dev/null
@@ -1,74 +0,0 @@
----
-title: 用户认证与账号管理
-description: 了解 LobeChat 基于 Better Auth 的用户认证方案，支持邮箱密码、魔法链接、SSO 登录及账号注销等功能。
-tags:
- - 用户认证
- - Better Auth
- - SSO
- - 账号管理
- - 会话管理
----
-
-# 用户认证与账号管理
-
-
- 提交后将进入 **72 小时冷静期**，期间可随时取消。冷静期结束后：
-
- - 您的账号数据将被永久删除
- - 未支付的账单将立即取消
- - 已支付的费用不予退还
- - 您的注册和注销记录将被保留以满足合规要求
-
-
-
- 如需自托管部署，请参阅 [身份验证服务](/zh/docs/self-hosting/advanced/auth) 了解配置详情。
-
diff --git a/docs/usage/features/branching-conversations.mdx b/docs/usage/features/branching-conversations.mdx
deleted file mode 100644
index 1cc5d4f135..0000000000
--- a/docs/usage/features/branching-conversations.mdx
+++ /dev/null
@@ -1,21 +0,0 @@
----
-title: Branching Conversations
-description: Explore dynamic AI chats with Branching Conversations for deeper interactions.
-tags:
- - Branching Conversations
- - AI Chat
- - Dynamic Conversations
----
-
-# Branching Conversations
-
-
- LobeChat defaults to the local database solution to reduce the onboarding cost for new users.
-
-
-Furthermore, we have attempted to introduce CRDT technology to achieve cross-device synchronization based on the local database. This experimental feature aims to provide users with greater autonomy and data security.
-
-## Server-Side Database: Convenient and Efficient User Experience
-
-For users who seek a convenient user experience, LobeChat supports PostgreSQL as the server-side database. By managing data with Dirzzle ORM and combining it with Clerk for authentication, LobeChat can offer users an efficient and reliable server-side data management solution.
-
-### Server-Side Database Technology Stack
-
-- **DB**: PostgreSQL (Neon is the default)
-- **ORM**: Dirzzle ORM
-- **Auth**: Clerk
-- **Server Router**: tRPC
-
-## Deployment Solution Selection Guide
-
-### 1. Local Database
-
-The local database solution is suitable for users who wish to have strict control over their data. With LobeChat's support for local databases, you can securely store and manage data without relying on external servers. This solution is particularly suitable for users with high requirements for data privacy.
-
-### 2. Server-Side Database
-
-The server-side database solution is ideal for users who want to simplify data management processes and enjoy a convenient user experience. Through server-side databases and user authentication, LobeChat can ensure the security and efficiency of data. If you want to learn how to configure a server-side database, please refer to our [detailed documentation](/docs/self-hosting/advanced/server-database).
-
-Whether you choose a local database or a server-side database, LobeChat can provide you with an excellent user experience.
diff --git a/docs/usage/features/database.zh-CN.mdx b/docs/usage/features/database.zh-CN.mdx
deleted file mode 100644
index 68b7dc4734..0000000000
--- a/docs/usage/features/database.zh-CN.mdx
+++ /dev/null
@@ -1,50 +0,0 @@
----
-title: LobeChat 支持本地 / 云端数据库存储
-description: LobeChat 支持本地 / 云端数据存储，既能实现 Local First，同时支持数据云同步。
-tags:
- - LobeChat
- - IndexedDB
- - Postgres
- - Local First
- - 数据云同步
- - 数据库
----
-
-# 本地 / 云端数据存储
-
-LobeChat 默认采取本地数据库方案，以降低新用户的上手成本。
-
-此外，我们尝试引入了 CRDT（Conflict-Free Replicated Data Type）技术，在本地数据库基础上实现了跨端同步。这一实验性功能旨在为用户提供更高的自主性和数据安全性。
-
-## 服务端数据库：便捷与高效的使用体验
-
-对于追求便捷使用体验的用户，LobeChat 支持 PostgreSQL 作为服务端数据库。通过 Drizzle ORM 管理数据，结合 Clerk 进行身份验证，LobeChat 能够为用户提供高效、可靠的服务端数据管理方案。
-
-### 服务端数据库技术栈
-
-- **DB**: PostgreSQL（默认使用 Neon）
-- **ORM**: Drizzle ORM
-- **Auth**: Clerk
-- **Server Router**: tRPC
-
-## 部署方案选择指南
-
-### 1. 本地数据库
-
-本地数据库方案适用于那些希望对数据进行严格控制的用户。通过 LobeChat 的本地数据库支持，您可以在不依赖外部服务器的情况下，安全地存储和管理数据。这一方案特别适合对数据隐私有高要求的用户。
-
-### 2. 服务端数据库
-
-服务端数据库方案则适合那些希望简化数据管理流程，享受便捷使用体验的用户。通过服务端数据库与用户身份验证，LobeChat 能够确保数据的安全性与高效性。如果您希望了解如何配置服务端数据库，请参考我们的[详细文档](/zh/docs/self-hosting/advanced/server-database)。
-
-无论选择本地数据库还是服务端数据库，LobeChat 都能为你提供卓越的用户体验。
diff --git a/docs/usage/features/desktop.mdx b/docs/usage/features/desktop.mdx
deleted file mode 100644
index 9a048c7662..0000000000
--- a/docs/usage/features/desktop.mdx
+++ /dev/null
@@ -1,53 +0,0 @@
----
-title: LobeChat Desktop Application
-description: >-
- Experience the full power of LobeChat without browser limitations. A
- lightweight, focused, and always-ready desktop app offering a dedicated
- environment and optimal performance.
-tags:
- - Desktop Application
- - Native App
- - Performance Optimization
- - Dedicated Environment
- - Offline Use
- - System Integration
- - User Experience
----
-
-# Desktop Application
-
-
-The desktop app delivers faster response times and a smoother user experience compared to the browser version.
-
-
-- **Dedicated Process**: Runs independently, free from browser limitations
-- **Memory Optimization**: More efficient memory management and resource allocation
-- **GPU Acceleration**: Fully leverages hardware acceleration capabilities
-- **Low Latency**: Reduces network delays and page load times
-
-### 🎯 Focused Experience
-
-- **Distraction-Free Environment**: Eliminates interruptions from browser tabs, bookmarks bar, and more
-- **Full-Screen Mode**: Supports immersive, full-screen usage
-- **Quick Launch**: Auto-start on boot, ready whenever you are
-- **Keyboard Shortcuts**: Extensive shortcut support to boost productivity
-
-### 🔒 Secure and Reliable
-
-- **Local Storage**: Data securely stored locally for enhanced privacy
-- **Offline Capability**: Partial functionality available offline
-- **Automatic Updates**: Always up to date without manual intervention
-- **Data Backup**: Comprehensive data backup and recovery features
-
diff --git a/docs/usage/features/desktop.zh-CN.mdx b/docs/usage/features/desktop.zh-CN.mdx
deleted file mode 100644
index 7058ac80ab..0000000000
--- a/docs/usage/features/desktop.zh-CN.mdx
+++ /dev/null
@@ -1,49 +0,0 @@
----
-title: LobeChat 桌面应用
-description: 获得完整的 LobeChat 体验，摆脱浏览器限制。轻量级、专注且随时就绪的桌面应用，提供专用环境和最佳性能。
-tags:
- - 桌面应用
- - 原生应用
- - 性能优化
- - 专用环境
- - 离线使用
- - 系统集成
- - 用户体验
----
-
-# 桌面应用
-
-
- 桌面应用提供比浏览器版本更快的响应速度和更流畅的用户体验。
-
-
-- **专用进程**：独立运行，不受浏览器限制
-- **内存优化**：更高效的内存管理和资源分配
-- **GPU 加速**：充分利用硬件加速能力
-- **低延迟**：减少网络延迟和页面加载时间
-
-### 🎯 专注体验
-
-- **无干扰环境**：摆脱浏览器标签页、书签栏等干扰
-- **全屏模式**：支持全屏和沉浸式体验
-- **快速启动**：开机自启动，随时可用
-- **键盘快捷键**：丰富的快捷键支持，提高操作效率
-
-### 🔒 安全可靠
-
-- **本地存储**：数据安全存储在本地，隐私保护更好
-- **离线能力**：部分功能支持离线使用
-- **自动更新**：无需手动更新，始终保持最新版本
-- **数据备份**：完整的数据备份和恢复功能
diff --git a/docs/usage/features/knowledge-base.mdx b/docs/usage/features/knowledge-base.mdx
deleted file mode 100644
index d9534756d9..0000000000
--- a/docs/usage/features/knowledge-base.mdx
+++ /dev/null
@@ -1,25 +0,0 @@
----
-title: File Upload / Knowledge Base
-description: >-
- Discover LobeChat's file upload and knowledge base features for enhanced user experience.
-
-tags:
- - File Upload
- - Knowledge Base
- - LobeChat
- - User Management
- - File Management
----
-
-# File Upload / Knowledge Base
-
-
- Learn more on [📘 LobeChat Knowledge Base Launch — From Now On, Every Step
- Counts](https://lobehub.com/blog/knowledge-base)
-
diff --git a/docs/usage/features/knowledge-base.zh-CN.mdx b/docs/usage/features/knowledge-base.zh-CN.mdx
deleted file mode 100644
index 115706674a..0000000000
--- a/docs/usage/features/knowledge-base.zh-CN.mdx
+++ /dev/null
@@ -1,22 +0,0 @@
----
-title: 文件上传 / 知识库
-description: 了解LobeChat的文件上传与知识库功能，提升对话体验。
-tags:
- - 文件上传
- - 知识库
- - LobeChat
- - 对话体验
----
-
-# 文件上传 / 知识库
-
-
- 查阅 [📘 LobeChat 知识库上线 —— 此刻起，跬步千里](https://lobehub.com/zh/blog/knowledge-base)
- 了解详情。
-
diff --git a/docs/usage/features/local-llm.mdx b/docs/usage/features/local-llm.mdx
deleted file mode 100644
index 5d93da2292..0000000000
--- a/docs/usage/features/local-llm.mdx
+++ /dev/null
@@ -1,51 +0,0 @@
----
-title: Using Local LLM in LobeChat
-description: >-
- Experience groundbreaking AI support with a local LLM in LobeChat powered by Ollama AI. Start conversations effortlessly and enjoy unprecedented interaction speed!
-
-tags:
- - Local Large Language Model
- - Ollama AI
- - LobeChat
- - AI communication
- - Natural Language Processing
- - Docker deployment
----
-
-# Local Large Language Model (LLM) Support
-
-Available in >=0.127.0, currently only supports Docker deployment
-
-With the release of LobeChat v0.127.0, we are excited to introduce a groundbreaking feature - Ollama AI support! 🤯 With the powerful infrastructure of [Ollama AI](https://ollama.ai/) and the [community's collaborative efforts](https://github.com/lobehub/lobe-chat/pull/1265), you can now engage in conversations with a local LLM (Large Language Model) in LobeChat! 🤩
-
-We are thrilled to introduce this revolutionary feature to all LobeChat users at this special moment. The integration of Ollama AI not only signifies a significant technological leap for us but also reaffirms our commitment to continuously pursue more efficient and intelligent communication.
-
-### How to Start a Conversation with Local LLM?
-
-The startup process is exceptionally simple! By running the following Docker command, you can experience conversations with a local LLM in LobeChat:
-
-```bash
-docker run -d -p 3210:3210 -e OLLAMA_PROXY_URL=http://host.docker.internal:11434/v1 lobehub/lobe-chat
-```
-
-Yes, it's that simple! 🤩 You don't need to go through complicated configurations or worry about a complex installation process. We have prepared everything for you. With just one command, you can engage in deep conversations with a local AI.
-
-### Experience Unprecedented Interaction Speed
-
-With the powerful capabilities of Ollama AI, LobeChat has greatly improved its efficiency in natural language processing. Both processing speed and response time have reached new heights. This means that your conversational experience will be smoother, without any waiting, and with instant responses.
-
-### Why Choose a Local LLM?
-
-Compared to cloud-based solutions, a local LLM provides higher privacy and security. All your conversations are processed locally, without passing through any external servers, ensuring the security of your data. Additionally, local processing can reduce network latency, providing you with a more immediate communication experience.
-
-### Embark on Your LobeChat & Ollama AI Journey
-
-Now, let's embark on this exciting journey together! Through the collaboration of LobeChat and Ollama AI, explore the endless possibilities brought by AI. Whether you are a tech enthusiast or simply curious about AI communication, LobeChat will offer you an unprecedented experience.
-
-
-
diff --git a/docs/usage/features/local-llm.zh-CN.mdx b/docs/usage/features/local-llm.zh-CN.mdx
deleted file mode 100644
index b4c044e0b8..0000000000
--- a/docs/usage/features/local-llm.zh-CN.mdx
+++ /dev/null
@@ -1,44 +0,0 @@
----
-title: 在 LobeChat 中使用本地大语言模型（LLM）
-description: LobeChat 支持本地 LLM，使用 Ollama AI集成带来高效智能沟通。体验本地大语言模型的隐私性、安全性和即时交流
-tags:
- - '本地大语言模型,LLM,LobeChat v0.127.0,Ollama AI,Docker 部署'
----
-
-# 支持本地大语言模型（LLM）
-
-在 >=v0.127.0 版本中可用，目前仅支持 Docker 部署
-
-随着 LobeChat v0.127.0 的发布，我们迎来了一个激动人心的特性 —— Ollama AI 支持！🤯 在 [Ollama AI](https://ollama.ai/) 强大的基础设施和 [社区的共同努力](https://github.com/lobehub/lobe-chat/pull/1265) 下，现在您可以在 LobeChat 中与本地 LLM (Large Language Model) 进行交流了！🤩
-
-我们非常高兴能在这个特别的时刻，向所有 LobeChat 用户介绍这项革命性的特性。Ollama AI 的集成不仅标志着我们技术上的一个巨大飞跃，更是向用户承诺，我们将不断追求更高效、更智能的沟通方式。
-
-### 如何启动与本地 LLM 的对话？
-
-启动过程异常简单！您只需运行以下 Docker 命令行，就可以在 LobeChat 中体验与本地 LLM 的对话了：
-
-```bash
-docker run -d -p 3210:3210 -e OLLAMA_PROXY_URL=http://host.docker.internal:11434/v1 lobehub/lobe-chat
-```
-
-是的，就是这么简单！🤩 您不需要进行繁杂的配置，也不必担心复杂的安装过程。我们已经为您准备好了一切，只需一行命令，即可开启与本地 AI 的深度对话。
-
-### 体验前所未有的交互速度
-
-借助 Ollama AI 的强大能力，LobeChat 在进行自然语言处理方面的效率得到了极大的提升。无论是处理速度还是响应时间，都达到了新的高度。这意味着您的对话体验将更加流畅，无需等待，即时得到回应。
-
-### 为什么选择本地 LLM？
-
-与基于云的解决方案相比，本地 LLM 提供了更高的隐私性和安全性。您的所有对话都在本地处理，不经过任何外部服务器，确保了您的数据安全性。此外，本地处理还能减少网络延迟，为您带来更加即时的交流体验。
-
-### 开启您的 LobeChat & Ollama AI 之旅
-
-现在，就让我们一起开启这段激动人心的旅程吧！通过 LobeChat 与 Ollama AI 的协作，探索 AI 带来的无限可能。无论您是技术爱好者，还是对 AI 交流充满好奇，LobeChat 都将为您提供一场前所未有的体验。
-
-
-
diff --git a/docs/usage/features/mcp-market.mdx b/docs/usage/features/mcp-market.mdx
deleted file mode 100644
index ccf125671c..0000000000
--- a/docs/usage/features/mcp-market.mdx
+++ /dev/null
@@ -1,26 +0,0 @@
----
-title: 'MCP Marketplace - Discover, Connect, Expand'
-description: >-
- Browse the ever-growing MCP plugin library to effortlessly enhance your AI
- capabilities and streamline workflows. Explore the MCP Marketplace to find
- curated collections of integrations.
-tags:
- - MCP Marketplace
- - Plugin Library
- - Integrations
- - Extensions
- - Workflows
- - Community
- - Developers
----
-
-# MCP Marketplace
-
- />
-
-**Seamlessly Connect Your AI with the World**
-
-Unlock the full potential of your AI by enabling smooth, secure, and dynamic interactions with external tools, data sources, and services. The MCP (Model Context Protocol)-based plugin system breaks down barriers between AI and the digital ecosystem, delivering unprecedented connectivity and functionality.
-
-Transform conversations into powerful workflows by connecting databases, APIs, file systems, and more. Experience an AI Agent that truly understands and interacts with your world.
-
-## What is MCP (Model Context Protocol)?
-
-MCP (Model Context Protocol) is an open protocol standard that provides AI models with a standardized way to access and interact with external resources. Through MCP, AI assistants can:
-
-- 🔗 **Secure Connections**: Establish secure links with various tools and services
-- 🔄 **Dynamic Interaction**: Retrieve and update external data in real time
-- 🛡️ **Permission Control**: Manage access rights with fine-grained precision
-- 📊 **Context Awareness**: Maintain rich conversational context information
-
-## Key Features
-
-### 🚀 One-Click Installation Experience
-
-
-No complicated setup required—installing and configuring MCP plugins takes just a few clicks.
-
-
-- **Rapid Deployment**: From discovery to use in under one minute
-- **Automatic Configuration**: The system handles connection and permission settings automatically
-- **Instant Activation**: Ready to use in conversations immediately after installation
-
-### 🔌 Extensive Connectivity
-
-MCP plugins support connections to a wide variety of external resources:
-
-- **Databases**: MySQL, PostgreSQL, MongoDB, and more
-- **API Services**: REST APIs, GraphQL, WebSocket
-- **File Systems**: Local files, cloud storage, version control
-- **Development Tools**: GitHub, GitLab, Jira, Slack
-- **Office Suites**: Google Workspace, Microsoft 365
-- **Professional Tools**: Docker, Kubernetes, Jenkins
-
diff --git a/docs/usage/features/mcp.zh-CN.mdx b/docs/usage/features/mcp.zh-CN.mdx
deleted file mode 100644
index 51ad1acbe7..0000000000
--- a/docs/usage/features/mcp.zh-CN.mdx
+++ /dev/null
@@ -1,54 +0,0 @@
----
-title: MCP 插件一键安装 - 无缝连接 AI 与世界
-description: 通过 MCP（模型上下文协议）插件系统，释放 AI 的全部潜力，实现与外部工具、数据源和服务的平滑、安全和动态交互。
-tags:
- - MCP
- - 模型上下文协议
- - 插件系统
- - 一键安装
- - 工具集成
- - 工作流程
- - 外部服务
----
-
-# MCP 插件一键安装
-
-
- 无需复杂的配置过程，只需几次点击即可完成 MCP 插件的安装和配置。
-
-
-- **快速部署**：从发现到使用，整个过程不超过 1 分钟
-- **自动配置**：系统自动处理连接和权限设置
-- **即时生效**：安装完成后立即可在对话中使用
-
-### 🔌 广泛的连接能力
-
-MCP 插件支持连接各种类型的外部资源：
-
-- **数据库**：MySQL、PostgreSQL、MongoDB 等
-- **API 服务**：REST API、GraphQL、WebSocket
-- **文件系统**：本地文件、云存储、版本控制
-- **开发工具**：GitHub、GitLab、Jira、Slack
-- **办公软件**：Google Workspace、Microsoft 365
-- **专业工具**：Docker、Kubernetes、Jenkins
diff --git a/docs/usage/features/mobile.mdx b/docs/usage/features/mobile.mdx
deleted file mode 100644
index d7a02ae41e..0000000000
--- a/docs/usage/features/mobile.mdx
+++ /dev/null
@@ -1,20 +0,0 @@
----
-title: LobeChat with Mobile Device Adaptation
-description: >-
- Explore the enhanced mobile user experience at LobeChat with optimized designs for smoother interactions. Share your feedback on GitHub!
-
-tags:
- - Mobile Device Adaptation
- - User Experience
- - Optimized Designs
- - Feedback
- - GitHub
----
-
-# Mobile Device Adaptation
-
-
- You can find our upcoming [Roadmap][github-project-link] plans in the Projects section.
-
-
-[github-project-link]: https://github.com/lobehub/lobe-chat/projects
diff --git a/docs/usage/features/more.zh-CN.mdx b/docs/usage/features/more.zh-CN.mdx
deleted file mode 100644
index 735db7628e..0000000000
--- a/docs/usage/features/more.zh-CN.mdx
+++ /dev/null
@@ -1,28 +0,0 @@
----
-title: 更多 LobeChat 特性 - 提供精致 UI 设计和流畅的对话体验
-description: 了解更多产品特性，包括精致 UI 设计、流畅的对话体验和快速部署功能，为用户带来更好的体验。
-tags:
- - 精致 UI 设计
- - 流畅对话体验
- - 快速部署
- - 隐私安全
- - 自定义域名
----
-
-# 更多特性
-
-除了上述功能特性以外，我们的所具有的设计和技术能力将为你带来了更多使用保障：
-
-- [x] 💎 **精致 UI 设计**：经过精心设计的界面，具有优雅的外观和流畅的交互效果，支持亮暗色主题，适配移动端。支持 PWA，提供更加接近原生应用的体验。
-- [x] 🗣️ **流畅的对话体验**：流式响应带来流畅的对话体验，并且支持完整的 Markdown 渲染，包括代码高亮、LaTex 公式、Mermaid 流程图等。
-- [x] 💨 **快速部署**：使用 Vercel 平台或者我们的 Docker 镜像，只需点击一键部署按钮，即可在 1 分钟内完成部署，无需复杂的配置过程。
-- [x] 🔒 **隐私安全**：所有数据保存在用户浏览器本地，保证用户的隐私安全。
-- [x] 🌐 **自定义域名**：如果用户拥有自己的域名，可以将其绑定到平台上，方便在任何地方快速访问对话助手。
-
-> ✨ 随着产品迭代持续更新，我们将会带来更多更多令人激动的功能！
-
----
-
-你可以在 Projects 中找到我们后续的 [Roadmap][github-project-link] 计划
-
-[github-project-link]: https://github.com/lobehub/lobe-chat/projects
diff --git a/docs/usage/features/multi-ai-providers.mdx b/docs/usage/features/multi-ai-providers.mdx
deleted file mode 100644
index 0431ba4414..0000000000
--- a/docs/usage/features/multi-ai-providers.mdx
+++ /dev/null
@@ -1,57 +0,0 @@
----
-title: LobeChat with Multi AI Providers
-description: >-
- Discover how LobeChat offers diverse model service provider support, including AWS Bedrock, Google AI Gemini series, ChatGLM, and Moonshot AI, to cater to various user needs. Explore local model support with Ollama integration.
-
-tags:
- - LobeChat
- - model service providers
- - AWS Bedrock
- - Google AI Gemini
- - ChatGLM
- - Moonshot AI
- - Together AI
- - local model support
- - Ollama
----
-
-# Multi-Model Service Provider Support
-
-Available in version 0.123.0 and later
-
-In the continuous development of LobeChat, we deeply understand the importance of diversity in model service providers for meeting the needs of the community when providing AI conversation services. Therefore, we have expanded our support to multiple model service providers, rather than being limited to a single one, in order to offer users a more diverse and rich selection of conversations.
-
-In this way, LobeChat can more flexibly adapt to the needs of different users, while also providing developers with a wider range of choices.
-
-## Supported Model Service Providers
-
-We have implemented support for the following model service providers:
-
-- **AWS Bedrock**: Integrated with AWS Bedrock service, supporting models such as **Claude / LLama2**, providing powerful natural language processing capabilities. [Learn more](https://aws.amazon.com/cn/bedrock)
-- **Anthropic (Claude)**: Accessed Anthropic's **Claude** series models, including Claude 3 and Claude 2, with breakthroughs in multi-modal capabilities and extended context, setting a new industry benchmark. [Learn more](https://www.anthropic.com/claude)
-- **Google AI (Gemini Pro, Gemini Vision)**: Access to Google's **Gemini** series models, including Gemini and Gemini Pro, to support advanced language understanding and generation. [Learn more](https://deepmind.google/technologies/gemini/)
-- **ChatGLM**: Added the **ChatGLM** series models from Zhipuai (GLM-4/GLM-4-vision/GLM-3-turbo), providing users with another efficient conversation model choice. [Learn more](https://www.zhipuai.cn/)
-- **Moonshot AI (Dark Side of the Moon)**: Integrated with the Moonshot series models, an innovative AI startup from China, aiming to provide deeper conversation understanding. [Learn more](https://www.moonshot.cn/)
-- **Groq**: Accessed Groq's AI models, efficiently processing message sequences and generating responses, capable of multi-turn dialogues and single-interaction tasks. [Learn more](https://groq.com/)
-- **OpenRouter**: Supports routing of models including **Claude 3**, **Gemma**, **Mistral**, **Llama2** and **Cohere**, with intelligent routing optimization to improve usage efficiency, open and flexible. [Learn more](https://openrouter.ai/)
-- **01.AI (Yi Model)**: Integrated the 01.AI models, with series of APIs featuring fast inference speed, which not only shortened the processing time, but also maintained excellent model performance. [Learn more](https://01.ai/)
-- **Together.ai**: Over 100 leading open-source Chat, Language, Image, Code, and Embedding models are available through the Together Inference API. For these models you pay just for what you use. [Learn more](https://www.together.ai/)
-- **Minimax**: Integrated the Minimax models, including the MoE model **abab6**, offers a broader range of choices. [Learn more](https://www.minimaxi.com/)
-- **DeepSeek**: Integrated with the DeepSeek series models, an innovative AI startup from China, The product has been designed to provide a model that balances performance with price. [Learn more](https://www.deepseek.com/)
-- **Qwen**: Integrated with the Qwen series models, including the latest **qwen-turbo**, **qwen-plus** and **qwen-max**. [Learn more](https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction)
-
-At the same time, we are also planning to support more model service providers, such as Replicate and Perplexity, to further enrich our service provider library. If you would like LobeChat to support your favorite service provider, feel free to join our [community discussion](https://github.com/lobehub/lobe-chat/discussions/6157).
-
-## Local Model Support
-
-
-
diff --git a/docs/usage/features/multi-ai-providers.zh-CN.mdx b/docs/usage/features/multi-ai-providers.zh-CN.mdx
deleted file mode 100644
index 8d490d402e..0000000000
--- a/docs/usage/features/multi-ai-providers.zh-CN.mdx
+++ /dev/null
@@ -1,58 +0,0 @@
----
-title: LobeChat 支持多模型服务商
-description: 了解 LobeChat 在多模型服务商支持方面的最新进展，包括已支持的模型服务商和计划中的扩展，以及本地模型支持的使用方式。
-tags:
- - LobeChat
- - AI 会话服务
- - 模型服务商
- - 多模型支持
- - 本地模型支持
- - AWS Bedrock
- - Google AI
- - ChatGLM
- - Moonshot AI
- - 01 AI
- - Together AI
- - Ollama
----
-
-# 多模型服务商支持
-
-在 0.123.0 及以后版本中可用
-
-在 LobeChat 的不断发展过程中，我们深刻理解到在提供 AI 会话服务时模型服务商的多样性对于满足社区需求的重要性。因此，我们不再局限于单一的模型服务商，而是拓展了对多种模型服务商的支持，以便为用户提供更为丰富和多样化的会话选择。
-
-通过这种方式，LobeChat 能够更灵活地适应不同用户的需求，同时也为开发者提供了更为广泛的选择空间。
-
-## 已支持的模型服务商
-
-我们已经实现了对以下模型服务商的支持：
-
-- **AWS Bedrock**：集成了 AWS Bedrock 服务，支持了 **Claude / LLama2** 等模型，提供了强大的自然语言处理能力。[了解更多](https://aws.amazon.com/cn/bedrock)
-- **Google AI (Gemini Pro、Gemini Vision)**：接入了 Google 的 **Gemini** 系列模型，包括 Gemini 和 Gemini Pro，以支持更高级的语言理解和生成。[了解更多](https://deepmind.google/technologies/gemini/)
-- **Anthropic (Claude)**：接入了 Anthropic 的 **Claude** 系列模型，包括 Claude 3 和 Claude 2，多模态突破，超长上下文，树立行业新基准。[了解更多](https://www.anthropic.com/claude)
-- **ChatGLM**：加入了智谱的 **ChatGLM** 系列模型（GLM-4/GLM-4-vision/GLM-3-turbo），为用户提供了另一种高效的会话模型选择。[了解更多](https://www.zhipuai.cn/)
-- **Moonshot AI (月之暗面)**：集成了 Moonshot 系列模型，这是一家来自中国的创新性 AI 创业公司，旨在提供更深层次的会话理解。[了解更多](https://www.moonshot.cn/)
-- **Together.ai**：集成部署了数百种开源模型和向量模型，无需本地部署即可随时访问这些模型。[了解更多](https://www.together.ai/)
-- **01.AI (零一万物)**：集成了零一万物模型，系列 API 具备较快的推理速度，这不仅缩短了处理时间，同时也保持了出色的模型效果。[了解更多](https://www.lingyiwanwu.com/)
-- **Groq**：接入了 Groq 的 AI 模型，高效处理消息序列，生成回应，胜任多轮对话及单次交互任务。[了解更多](https://groq.com/)
-- **OpenRouter**：其支持包括 **Claude 3**，**Gemma**，**Mistral**，**Llama2**和**Cohere**等模型路由，支持智能路由优化，提升使用效率，开放且灵活。[了解更多](https://openrouter.ai/)
-- **Minimax**: 接入了 Minimax 的 AI 模型，包括 MoE 模型 **abab6**，提供了更多的选择空间。[了解更多](https://www.minimaxi.com/)
-- **DeepSeek**: 接入了 DeepSeek 的 AI 模型，包括最新的 **DeepSeek-V2**，提供兼顾性能与价格的模型。[了解更多](https://www.deepseek.com/)
-- **Qwen (通义千问)**: 接入了 Qwen 的 AI 模型，包括最新的 **qwen-turbo**，**qwen-plus** 和 **qwen-max** 等模型。[了解更多](https://help.aliyun.com/zh/dashscope/developer-reference/model-introduction)
-
-同时，我们也在计划支持更多的模型服务商，如 Replicate 和 Perplexity 等，以进一步丰富我们的服务商库。如果你希望让 LobeChat 支持你喜爱的服务商，欢迎加入我们的[社区讨论](https://github.com/lobehub/lobe-chat/discussions/6157)。
-
-## 本地模型支持
-
-
-
diff --git a/docs/usage/features/plugin-system.mdx b/docs/usage/features/plugin-system.mdx
deleted file mode 100644
index a6f5166160..0000000000
--- a/docs/usage/features/plugin-system.mdx
+++ /dev/null
@@ -1,80 +0,0 @@
----
-title: Plugin System in LobeChat
-description: >-
- Explore the diverse plugin ecosystem of LobeChat, extending its capabilities to provide real-time information, interact with various platforms, and simplify user interactions.
-
-tags:
- - LobeChat
- - Plugin Ecosystem
- - Assistant Functionality
- - Plugin Development
- - SDK
- - Chat Application
----
-
-# Plugin System
-
-
- To help developers better participate in this ecosystem, we provide comprehensive development
- resources. This includes detailed component development documentation, a fully-featured software
- development kit (SDK), and template examples, all aimed at simplifying the development process and
- lowering the entry barrier for developers.
-
-
-
- We welcome developers to utilize these resources, unleash their creativity, and write
- feature-rich, user-friendly plugins. Through collective efforts, we can continuously expand the
- functional boundaries of the chat application and explore a more intelligent and efficient
- creativity platform.
-
-
-## Plugin Ecosystem
-
-
- If you are interested in plugin development, please refer to our [📘 Plugin Development
- Guide](/docs/usage/plugins/development) in the Wiki.
-
-
-- [lobe-chat-plugins][lobe-chat-plugins]: This is the plugin index for LobeChat. It retrieves the list of plugins from the index.json of this repository and displays them to the users.
-- [chat-plugin-template][chat-plugin-template]: Chat Plugin plugin development template, you can quickly create a new plugin project through the project template.
-- [@lobehub/chat-plugin-sdk][chat-plugin-sdk]: The LobeChat plugin SDK can help you create excellent Lobe Chat plugins.
-- [@lobehub/chat-plugins-gateway][chat-plugins-gateway]: The LobeChat plugin gateway is a backend service that serves as the gateway for LobeChat plugins. We deploy this service using Vercel.
-
-### Roadmap Progress
-
-The plugin system of LobeChat has now entered a stable stage, and we have basically completed most of the functionality required by the plugin system. However, we are still planning and considering the new possibilities that plugins can bring to us. You can learn more in the following Issues:
-
-
- ### ✅ Phase One of Plugins
-
- Implementing the separation of plugins from the main body, splitting the plugins into independent repositories for maintenance, and implementing dynamic loading of plugins. [**#73**](https://github.com/lobehub/lobe-chat/issues/73)
-
- ### ✅ Phase Two of Plugins
-
- The security and stability of plugin usage, more accurate presentation of abnormal states, maintainability and developer-friendliness of the plugin architecture. [**#97**](https://github.com/lobehub/lobe-chat/issues/97)
-
- ### ✅ Phase Three of Plugins
-
- Higher-level and improved customization capabilities, support for OpenAPI schema invocation, compatibility with ChatGPT plugins, and the addition of Midjourney plugins. [**#411**](https://github.com/lobehub/lobe-chat/discussions/#411)
-
- ### 💭 Phase Four of Plugins
-
- Comprehensive authentication, visual configuration of plugin definitions, Plugin SDK CLI, Python language development template, any other ideas? Join the discussion: [**#1310**](https://github.com/lobehub/lobe-chat/discussions/#1310)
-
-
-[chat-plugin-sdk]: https://github.com/lobehub/chat-plugin-sdk
-[chat-plugin-template]: https://github.com/lobehub/chat-plugin-template
-[chat-plugins-gateway]: https://github.com/lobehub/chat-plugins-gateway
-[lobe-chat-plugins]: https://github.com/lobehub/lobe-chat-plugins
diff --git a/docs/usage/features/plugin-system.zh-CN.mdx b/docs/usage/features/plugin-system.zh-CN.mdx
deleted file mode 100644
index 627349102d..0000000000
--- a/docs/usage/features/plugin-system.zh-CN.mdx
+++ /dev/null
@@ -1,70 +0,0 @@
----
-title: LobeChat 插件生态系统 - 功能扩展与开发资源
-description: 了解 LobeChat 插件生态系统如何增强 LobeChat 助手的实用性和灵活性，以及提供的开发资源和插件开发指南。
-tags:
- - LobeChat
- - 插件生态系统
- - 开发资源
- - 插件开发指南
----
-
-# 插件系统
-
-
- 为了帮助开发者更好地参与到这个生态中来，我们在提供了全面的开发资源。这包括详尽的组件开发文档、功能齐全的软件开发工具包（SDK），以及样板示例，这些都是为了简化开发过程，降低开发者的入门门槛。
-
-
-
- 我们欢迎开发者利用这些资源，发挥创造力，编写出功能丰富、用户友好的插件。通过共同的努力，我们可以不断扩展聊天应用的功能界限，探索一个更加智能、高效的创造力平台。
-
-
-## 插件生态体系
-
-
- 如果你对插件开发感兴趣，请在 Wiki 中查阅我们的 [📘
- 插件开发指南](/zh/docs/usage/plugins/development)。
-
-
-- [lobe-chat-plugins][lobe-chat-plugins]：这是 LobeChat 的插件索引。它从该仓库的 index.json 中获取插件列表并显示给用户。
-- [chat-plugin-template][chat-plugin-template]: Chat Plugin 插件开发模版，你可以通过项目模版快速新建插件项目。
-- [@lobehub/chat-plugin-sdk][chat-plugin-sdk]：LobeChat 插件 SDK 可帮助您创建出色的 Lobe Chat 插件。
-- [@lobehub/chat-plugins-gateway][chat-plugins-gateway]：LobeChat 插件网关是一个后端服务，作为 LobeChat 插件的网关。我们使用 Vercel 部署此服务。
-
-### 路线进展
-
-LobeChat 的插件系统目前已初步进入一个稳定阶段，我们已基本完成大部分插件系统所需的功能，但我们仍然在规划与思考插件能为我们带来的全新可能性。您可以在以下 Issues 中了解更多信息:
-
-
- ### ✅ 插件一期
-
- 实现插件与主体分离，将插件拆分为独立仓库维护，并实现插件的动态加载。 [**#73**](https://github.com/lobehub/lobe-chat/issues/73)
-
- ### ✅ 插件二期
-
- 插件的安全性与使用的稳定性，更加精准地呈现异常状态，插件架构的可维护性与开发者友好。[**#97**](https://github.com/lobehub/lobe-chat/issues/97)
-
- ### ✅ 插件三期
-
- 更高阶与完善的自定义能力，支持 OpenAPI schema 调用、兼容 ChatGPT 插件、新增 Midjourney 插件。 [**#411**](https://github.com/lobehub/lobe-chat/discussions/#411)
-
- ### 💭 插件四期
-
- 完善的鉴权、可视化配置插件定义、 Plugin SDK CLI 、 Python 语言研发模板、还有什么想法？欢迎参与讨论： [**#1310**](https://github.com/lobehub/lobe-chat/discussions/#1310)
-
-
-[chat-plugin-sdk]: https://github.com/lobehub/chat-plugin-sdk
-[chat-plugin-template]: https://github.com/lobehub/chat-plugin-template
-[chat-plugins-gateway]: https://github.com/lobehub/chat-plugins-gateway
-[lobe-chat-plugins]: https://github.com/lobehub/lobe-chat-plugins
diff --git a/docs/usage/features/pwa.mdx b/docs/usage/features/pwa.mdx
deleted file mode 100644
index d5664feb85..0000000000
--- a/docs/usage/features/pwa.mdx
+++ /dev/null
@@ -1,60 +0,0 @@
----
-title: LobeChat support Progressive Web Apps (PWA)
-description: >-
- Discover how LobeChat utilizes Progressive Web App (PWA) technology to provide a seamless and near-native app experience on both desktop and mobile devices. Learn how to install LobeChat as a desktop app for enhanced convenience.
-
-tags:
- - Progressive Web App
- - PWA
- - LobeChat
- - Web Applications
- - User Experience
----
-
-# Progressive Web App (PWA)
-
-
- On macOS, when using a Chrome-installed PWA, it is required that Chrome be open, otherwise Chrome
- will automatically open and then launch the PWA app.
-
-
-
- ### Run Chrome or Edge browser on your computer
-
- ### Visit the LobeChat webpage
-
- ### In the top right corner of the address bar, click the Install icon
-
- ### Follow the on-screen instructions to complete the PWA installation
-
-
-## Running on Safari
-
-Safari PWA requires macOS Ventura or later. The PWA installed by Safari does not require Safari to be open; you can directly open the PWA app.
-
-
- ### Run Safari browser on your computer
-
- ### Visit the LobeChat webpage
-
- ### In the top right corner of the address bar, click the Share icon
-
- ### Click Add to Dock
-
- ### Follow the on-screen instructions to complete the PWA installation
-
-
-
- The default installed LobeChat PWA icon has a black background, you can use cmd +{' '}
- i to paste the following image to replace it with a white background.
-
-
-
- macOS 下，使用 Chrome 安装的 PWA 时，必须要求 Chrome 是打开状态，否则会自动打开 Chrome 再打开 PWA
- 应用。
-
-
-
- ### 在电脑上运行 Chrome 或 Edge 浏览器
-
- ### 访问 LobeChat 网页
-
- ### 在地址栏的右上角，单击 安装 图标
-
- ### 根据屏幕上的指示完成 PWA 的安装
-
-
-## Safari 浏览器上运行
-
-Safari PWA 需要 macOS Ventura 或更高版本。Safari 安装的 PWA 并不要求 Safari 是打开状态，可以直接打开 PWA 应用。
-
-
- ### 在电脑上运行 Safari 浏览器
-
- ### 访问 LobeChat 网页
-
- ### 在地址栏的右上角，单击 分享 图标
-
- ### 点选 添加到程序坞
-
- ### 根据屏幕上的指示完成 PWA 的安装
-
-
-
- 默认安装的 LobeChat PWA 图标是黑色背景的，您可以在自行使用 cmd + i{' '}
- 粘贴如下图片替换为白色背景的。
-
-
- />
-
-**Online Knowledge, On Demand**
-
-Stay in sync with the world through real-time online access — news, data, trends, and more. Keep your information up to date and access the latest available data, enabling your AI to provide accurate and current responses.
-
-Access real-time information, verify facts, and explore ongoing events without leaving the conversation. Your AI becomes a gateway to the world’s knowledge, always up-to-date and comprehensive.
-
-## Features Overview
-
-### 🌐 Real-Time Information Access
-
-
-Intelligent Connected Search empowers AI to access the latest internet information, ensuring accuracy and timeliness in responses.
-
-
-- **Breaking News**: Get the latest news reports and event updates
-- **Market Data**: Real-time stock prices, exchange rates, cryptocurrency values
-- **Weather Information**: Global weather forecasts and meteorological data
-- **Traffic Conditions**: Live traffic updates and road status
-- **Sports Events**: Match results, schedules, and statistics
-
-### 🔍 Multi-Source Search Engines
-
-Supports multiple search engines to ensure comprehensive and accurate information:
-
-- **Google**: The world’s largest search engine
-- **Bing**: Microsoft’s search engine
-- **DuckDuckGo**: Privacy-focused search engine
-
-### 📊 Structured Data Retrieval
-
-- **Academic Papers**: Access academic databases and journals
-- **Technical Documentation**: Obtain the latest technical documents and API references
-- **Statistical Data**: Government statistics, survey reports, market research
-- **Product Information**: Product details and reviews from e-commerce platforms
-- **Laws and Regulations**: Latest legal texts and policy interpretations
-
diff --git a/docs/usage/features/search.zh-CN.mdx b/docs/usage/features/search.zh-CN.mdx
deleted file mode 100644
index 51fad75f37..0000000000
--- a/docs/usage/features/search.zh-CN.mdx
+++ /dev/null
@@ -1,52 +0,0 @@
----
-title: 智能联网搜索 - 在线知识，按需获取
-description: 通过实时联网访问，你的 AI 与世界保持同步。获取最新信息，验证事实，探索当前事件，无需离开对话。
-tags:
- - 联网搜索
- - 实时信息
- - 搜索引擎
- - 信息获取
- - 事实验证
- - 实时数据
- - 知识更新
----
-
-# 智能联网搜索
-
-
- 智能联网搜索让 AI 能够访问最新的互联网信息，确保回答的准确性和时效性。
-
-
-- **实时新闻**：获取最新的新闻报道和事件动态
-- **市场数据**：实时股价、汇率、加密货币价格
-- **天气信息**：全球天气预报和气象数据
-- **交通状况**：实时路况和交通信息
-- **体育赛事**：比赛结果、赛程和统计数据
-
-### 🔍 多源搜索引擎
-
-支持多个搜索引擎，确保信息的全面性和准确性：
-
-- **Google**：全球最大的搜索引擎
-- **Bing**：Microsoft 搜索引擎
-- **DuckDuckGo**：注重隐私的搜索引擎
-
-### 📊 结构化数据获取
-
-- **学术论文**：访问学术数据库和期刊
-- **技术文档**：获取最新的技术文档和 API 资料
-- **统计数据**：政府统计、调查报告、市场研究
-- **产品信息**：电商平台的产品详情和评价
-- **法律法规**：最新的法律条文和政策解读
diff --git a/docs/usage/features/text-to-image.mdx b/docs/usage/features/text-to-image.mdx
deleted file mode 100644
index ff9064cb57..0000000000
--- a/docs/usage/features/text-to-image.mdx
+++ /dev/null
@@ -1,18 +0,0 @@
----
-title: Text to Image in LobeChat
-description: >-
- Transform your ideas into images with the latest text-to-image generation technology integrated into LobeChat AI Assistant. Experience a private and immersive creative process.
-
-tags:
- - Text to Image Generation
- - LobeChat AI Assistant
- - DALL-E 3
- - MidJourney
- - Pollinations
----
-
-# Text to Image Generation
-
-
- The default configuration can intelligently identify the user's system color mode and
- automatically switch themes to ensure a consistent visual experience with the operating system.
-
-
-For users who prefer to manually adjust details, LobeChat also provides intuitive setting options and offers a choice between conversation bubble mode and document mode for chat scenes.
diff --git a/docs/usage/features/theme.zh-CN.mdx b/docs/usage/features/theme.zh-CN.mdx
deleted file mode 100644
index 1a392352ed..0000000000
--- a/docs/usage/features/theme.zh-CN.mdx
+++ /dev/null
@@ -1,25 +0,0 @@
----
-title: LobeChat 自定义主题 - 个性化体验
-description: 了解 LobeChat 的灵活多变主题模式，包括日间亮色模式和夜间深色模式，以及颜色定制选项，让用户根据喜好调整应用主题色彩。
-tags:
- - LobeChat
- - 自定义主题
- - 主题模式
- - 颜色定制
- - 界面设计
- - 个性化体验
----
-
-# 自定义主题
-
-
- 默认配置能够智能地识别用户系统的颜色模式，自动进行主题切换，以确保应用界面与操作系统保持一致的视觉体验。
-
-
-对于喜欢手动调控细节的用户，LobeChat 同样提供了直观的设置选项，针对聊天场景也提供了对话气泡模式和文档模式的选择。
diff --git a/docs/usage/features/tts.mdx b/docs/usage/features/tts.mdx
deleted file mode 100644
index 6141ef4e70..0000000000
--- a/docs/usage/features/tts.mdx
+++ /dev/null
@@ -1,40 +0,0 @@
----
-title: LobeChat support Speech Synthesis and Recognition (TTS & STT)
-description: >-
- Experience seamless Text-to-Speech (TTS) and Speech-to-Text (STT) technologies in LobeChat. Choose from a variety of high-quality voices for personalized communication. Learn more about Lobe TTS toolkit @lobehub/tts.
-
-tags:
- - LobeChat
- - TTS
- - STT
- - Voice Conversation
- - Lobe TTS
- - Text-to-Speech
- - Speech-to-Text
- - Voice Options
----
-
-# TTS & STT Voice Conversation
-
-
- During the implementation of the TTS feature in LobeChat, we found that there was no good frontend
- TTS library on the market, which resulted in a lot of effort being spent on implementation,
- including data conversion, audio progress management, and speech visualization. Adhering to the
- "Community First" concept, we have polished and open-sourced this implementation, hoping to help
- community developers who want to implement TTS.
-
diff --git a/docs/usage/features/tts.zh-CN.mdx b/docs/usage/features/tts.zh-CN.mdx
deleted file mode 100644
index 1639520b69..0000000000
--- a/docs/usage/features/tts.zh-CN.mdx
+++ /dev/null
@@ -1,35 +0,0 @@
----
-title: LobeChat 支持 TTS & STT 语音会话
-description: LobeChat 支持文字转语音（TTS）和语音转文字（STT）技术，提供高品质声音选项，个性化交流体验。了解更多关于 Lobe TTS 工具包。
-tags:
- - TTS
- - STT
- - 语音会话
- - LobeChat
- - Lobe TTS
- - 文字转语音
- - 语音转文字
----
-
-# TTS & STT 语音会话
-
-
- 我们在实现 LobeChat 的 TTS 功能过程中，发现市面上并没有一款很好的 TTS
- 前端库，导致在实现上耗费了很多精力，包括数据转换、音频进度管理、语音可视化等。秉承「 Community
- First 」 的理念，我们把这套实现打磨并开源了出来，希望能帮助到想要实现 TTS 的社区开发者们。
-
diff --git a/docs/usage/features/vision.mdx b/docs/usage/features/vision.mdx
deleted file mode 100644
index 968d2c8580..0000000000
--- a/docs/usage/features/vision.mdx
+++ /dev/null
@@ -1,20 +0,0 @@
----
-title: LobeChat support Vision Recognition
-description: >-
- Discover how LobeChat integrates visual recognition capabilities like OpenAI's gpt-4-vision and Google Gemini Pro vision for intelligent conversations based on uploaded images.
-
-tags:
- - LobeChat
- - Model Vision Recognition
- - Multimodal Interaction
- - Visual Elements
- - Intelligent Conversations
----
-
-# Model Vision Recognition
-
-
- - **Send Shortcut**: Set a shortcut to send messages and line breaks using the Enter key or ⌘ +
- Enter key. - **Add an AI Message**: Manually add and edit a message input by an AI character in
- the conversation context, which will not trigger a model response. - **Add a User Message**: Add
- the current input content as a message input by the user character to the conversation context,
- which will not trigger a model response.
-
diff --git a/docs/usage/foundation/basic.zh-CN.mdx b/docs/usage/foundation/basic.zh-CN.mdx
deleted file mode 100644
index 5c858e7a9a..0000000000
--- a/docs/usage/foundation/basic.zh-CN.mdx
+++ /dev/null
@@ -1,46 +0,0 @@
----
-title: 会话基本使用指南 - 大型语言模型交互指南
-description: 了解如何使用大型语言模型进行基本交互，包括模型选择、文件/图片上传、温度设置、历史记录设置等。
-tags:
- - 大型语言模型
- - LLM
- - 模型选择
- - 文件上传
- - 温度设置
- - 历史记录设置
- - 语音输入
- - 插件设置
- - Token 用量
- - 新建话题
- - 发送按钮
----
-
-# 会话基本使用指南
-
-
- - **发送快捷键**：设置使用 Enter 键或 ⌘ + Enter 键发送消息和换行的快捷方式。 -
- **添加一条 AI 消息**：在对话上下文中手动添加并编辑一条由 AI 角色输入的消息，该操作不会触发模型响应。
- -
-
- **添加一条用户消息**：将当前输入内容作为用户角色输入的消息添加到对话上下文中，该操作不会触发模型响应。
-
diff --git a/docs/usage/foundation/share.mdx b/docs/usage/foundation/share.mdx
deleted file mode 100644
index 12e9de3ff1..0000000000
--- a/docs/usage/foundation/share.mdx
+++ /dev/null
@@ -1,35 +0,0 @@
----
-title: Share Conversation Records - Screenshot Sharing & ShareGPT
-description: >-
- Learn how to share conversation records in LobeChat using Screenshot Sharing and ShareGPT methods. Capture conversation details in images or generate permanent links effortlessly.
-
-tags:
- - Share Conversation Records
- - Screenshot Sharing
- - ShareGPT
- - Conversation Sharing
- - AI Conversation Sharing
----
-
-# Share Conversation Records
-
-
- info For plugin installation, please refer to [Plugin Usage](/docs/usage/plugins/basic-usage)
-
-
-When using the Midjourney plugin for the first time, you will need to fill in your Midjourney API key in the plugin settings.
-
-插件安装请参考[插件使用](/zh/docs/usage/plugins/basic-usage)
-
-首次使用 Midjourney 插件时，您需要在插件设置中填写您的 Midjourney API 密钥。
-
-
+ For more on using knowledge bases, see [Knowledge Base](./docs/usage/getting-started/resource).
+
+
+## Manage Agents
+
+When you have many assistants and group chats, organizing them into groups is the most intuitive way to manage them. It keeps your assistant list clean and makes switching between them easier.
+
+### Create a Group
+
+On the LobeHub homepage, open the assistant list menu and select "Add New Group" to create a new group.
+
+
+
+### Move to a Group
+
+Select an existing assistant or group chat, then click "Move to Group" to organize it. You can also create new assistants or group chats directly within a group.
+
+### Manage Groups
+
+If you have multiple groups, go to the assistant list or group menu and select "Manage Groups" to easily rename or reorder them.
+
+### Pin Frequently Used Assistants
+
+You can pin frequently used assistants to the top of the list for quicker access. Select the assistant and choose "Pin" from the menu. Pinned assistants will stay at the top of the list for easy access.
+
+## Create a Copy
+
+You can duplicate an assistant to create a copy. Select the assistant and choose "Create Copy" from the menu. The system will generate an identical assistant, which is useful for creating variants with different configurations.
+
+## Delete an Assistant
+
+If you no longer need an assistant, you can delete it. Select the assistant, choose "Delete" from the menu, and confirm the deletion to remove it.
diff --git a/docs/usage/getting-started/agent.zh-CN.mdx b/docs/usage/getting-started/agent.zh-CN.mdx
new file mode 100644
index 0000000000..94c036fa64
--- /dev/null
+++ b/docs/usage/getting-started/agent.zh-CN.mdx
@@ -0,0 +1,103 @@
+---
+title: Agent
+description: 简单的集中配置，例如提示词，选择模型，知识库，插件等。
+tags:
+ - LobeHub
+ - LobeHub
+ - AI 助手
+ - 助手组织
+ - 分组设置
+ - 助手搜索
+ - 助手固定
+---
+
+# Agent
+
+在 LobeHub，你可以自由创建和定制 AI 助理 —— 翻译助理记得你的术语偏好，编程助理熟悉你的代码风格，写作助理了解你的表达习惯。通过配置提示词、选择模型、添加插件和关联资源库，你能打造真正符合需求的专属助理。
+
+本篇指南将详细介绍如何创建和配置你的 AI 助理。
+
+## 新建 AI 助理
+
+新建助理有三种方式：使用 Agent Builder 智能创建、从零开始打造专属助理，或从社区快速添加。无论哪种方式，都能让助理精准匹配你的工作需求。
+
+### 使用 Agent builder 智能创建
+
+Agent Builder 是 LobeHub 的内置助理，可以帮助你完成 AI 助理的创建。只需与 Agent Builder 对话，描述你的需求，它就能理解并自动生成完整的助理配置 —— 包括角色设定、系统提示词、插件配置。
+
+- 在首页左侧边栏找到创建助理按键，或选择对话框下方 「创建 Agent」 开始创建。
+- 在助理档案页面右侧，你可以和 Agent builder 对话，描述需求，完成智能创建。
+- 完成智能创建后，你也可以手动进行调整。
+
+
+
+### 创建自定义助理
+
+自定义助理能最大程度地贴合你的习惯。你可以自行定制助理的头像、名称、提示词，设置想使用的 AI 模型、插件，从而打造个人专属 AI 助理。在助理档案页面手动完成定制即可。
+
+### 从社区添加
+
+如果想快速获取配置完整的助理，可以选择从社区直接添加 AI 助理。社区有大量种类丰富的优质助理 —— 设计专家、代码助理、文案策划师、学术导师…… 添加即用。
+
+- 首页左侧边栏找到 「社区」→「助理」，或直接下滑主界面，找到「社区助理」。
+- 选择想添加的助理，点击进入详情界面了解具体信息，点击 「添加助理并会话」 即可完成添加。
+
+
+
+### 配置 AI 助理
+
+助理创建完成后，你可以通过添加插件和链接外部工作流来增强它的能力。插件让助理获得各种扩展功能，链接外部工作流让助理能直接读取或操作你的更多常用工具。强化 AI 助理能够极大程度优化你的工作流程。
+
+### 编辑助理信息
+
+你可以随时编辑助理的任何信息，让它持续跟随你的脚步。选择助理进入会话，选择左侧边栏「助理档案」即可编辑。
+
+### 添加插件和链接工具
+
+为助理添加插件，链接其他工具，能够让你们的配合更加高效。
+
+选择助理进入会话，选择左侧边栏「助理档案」→「+ 集成插件」。
+
+
+
+### 关联资源库
+
+在会话中为助理关联资源库后，助手能基于你的资源库提供更精准、更个性化的回答。
+
+进入会话页面，找到相应按键即可选择资源库进行关联。
+
+
+
+
+ 关于资源库的使用，请参阅[资源库](./docs/usage/getting-started/resource)。
+
+
+## 管理 Agent
+
+助手和群聊数量过多时，分组是最直观的管理方式，能够让助手列表更加简洁清晰，切换助手更加轻松。
+
+### 创建分组
+
+在 LobeHub 首页助手列表菜单选择「添加新分组」以创建新的分组。
+
+
+
+### 移入分组
+
+选择已有助手和群聊菜单，点击「移动到分组」进行移入。也可以直接在分组内创建助手和群聊。\[Image]
+
+### 管理分组
+
+存在多个分组时，在助手列表或分组菜单选择「分组管理」，可以便捷修改分组显示顺序、分组命名。\[Image]
+
+### 置顶常用助手
+
+你可以把频繁使用的助手置顶在列表最上方，以节省查找和滚动的时间。选中助手，在菜单中选择「置顶」即可。置顶的助手会固定在列表顶部，方便快速访问。\[Image]
+
+## 创建副本
+
+你可以复制一个助手，创建副本。选中助手，在菜单中选择「创建副本」，系统会创建一个完全相同的助手副本。适合在原助手基础上创建不同配置的变体。
+
+## 删除助手
+
+不需要的助手可以删除。选中助手，在菜单中选择「删除」，确认删除后助手将被移除。
diff --git a/docs/usage/getting-started/get-lobehub.mdx b/docs/usage/getting-started/get-lobehub.mdx
new file mode 100644
index 0000000000..15a94dc994
--- /dev/null
+++ b/docs/usage/getting-started/get-lobehub.mdx
@@ -0,0 +1,41 @@
+---
+title: Getting LobeHub
+description: >-
+ Learn how to get started with LobeHub, including downloading and installing
+ the app, signing up and logging in, and creating your assistant.
+tags:
+ - LobeHub
+ - LobeHub
+ - Getting LobeHub
+ - Download and Install
+ - Sign Up and Log In
+ - Create Assistant
+---
+
+# Getting LobeHub
+
+## Use LobeHub in Your Browser
+
+You can access LobeHub directly in your browser by visiting [app.lobehub.com](https://app.lobehub.com).
+
+## Install the macOS App
+
+Visit the [Download Page](https://lobehub.com/download) to get the macOS app.
+
+Currently, the app is not available on the Mac App Store.
+
+## Install the Windows App
+
+Visit the [Download Page](https://lobehub.com/download) to get the Windows app.
+
+Currently, the app is not available on the Microsoft Store.
+
+## Install the Android App
+
+Download the Android app from [Google Play](https://play.google.com/store/apps/details?id=com.lobehub.app).
+
+Alternatively, you can download the APK file from the [Download Page](https://lobehub.com/download) and install it manually.
+
+## Install the iOS App
+
+Download the iOS app from the [App Store](https://apps.apple.com/app/id6471212236).
diff --git a/docs/usage/getting-started/get-lobehub.zh-CN.mdx b/docs/usage/getting-started/get-lobehub.zh-CN.mdx
new file mode 100644
index 0000000000..45e45d3bba
--- /dev/null
+++ b/docs/usage/getting-started/get-lobehub.zh-CN.mdx
@@ -0,0 +1,39 @@
+---
+title: 获取 LobeHub
+description: 了解如何获取 LobeHub，包括下载安装、注册登录、创建助理等。
+tags:
+ - LobeHub
+ - LobeHub
+ - 获取 LobeHub
+ - 下载安装
+ - 注册登录
+ - 创建助理
+---
+
+# 获取 LobeHub
+
+## 在浏览器中使用 LobeHub
+
+你可以访问 [app.lobehub.com](https://app.lobehub.com) 在浏览器中使用 LobeHub。
+
+## 安装 macOS App
+
+前往[下载页](https://lobehub.com/download)即可下载 macOS App。
+
+目前不支持在 App Store 下载。
+
+## 安装 Windows App
+
+前往[下载页](https://lobehub.com/download)即可下载 Windows App。
+
+目前不支持在 Windows Store 下载。
+
+## 安装 Android App
+
+前往[Google Play](https://play.google.com/store/apps/details?id=com.lobehub.app)即可下载 Android App。
+
+或者，前往[下载页](https://lobehub.com/download)下载 APK 文件，然后手动安装。
+
+## 安装 iOS App
+
+前往[App Store](https://apps.apple.com/app/id6471212236)即可下载 iOS App。
diff --git a/docs/usage/getting-started/image-generation.mdx b/docs/usage/getting-started/image-generation.mdx
new file mode 100644
index 0000000000..f5049d3331
--- /dev/null
+++ b/docs/usage/getting-started/image-generation.mdx
@@ -0,0 +1,54 @@
+---
+title: Image Generation
+description: >-
+ A simple centralized configuration for prompts, model selection, knowledge
+ base, plugins, and more.
+tags:
+ - LobeHub
+ - LobeHub
+ - AI Assistant
+ - Assistant Organization
+ - Group Settings
+ - Assistant Search
+ - Assistant Pinning
+---
+
+# Image Generation
+
+LobeHub offers an AI-powered image generation feature that allows you to create visuals from text descriptions. Whether you're working on product prototypes, design inspiration, illustrations, or creative exploration, AI image generation helps bring your ideas to life quickly and effortlessly. Simply enter a description, choose a model and parameters, and receive high-quality images within seconds. All generated images are automatically saved to your LobeHub asset library for easy access, download, and reuse. From concept to creation, the entire process is streamlined and efficient.
+
+## Get Started with Drawing
+
+Click on the "Drawing" section on the LobeHub main interface to access the AI image generation page.
+
+## Enter a Prompt
+
+Describe the image you want in the input box. The more detailed your description, the more accurate the generated image will be.
+
+## Choose an AI Model
+
+LobeHub offers multiple AI image generation models. Select the one that best fits your needs.
+
+
+
+## Select Reference Images
+
+If you have reference images, you can upload them to guide the generation process. Click the upload button or drag and drop your reference images directly. You can upload multiple reference images.
+
+
+
+## Choose Image Aspect Ratio
+
+Select an appropriate aspect ratio based on your intended use case.
+
+## Set Number of Images to Generate
+
+You can choose how many images to generate in one go.
+
+## View and Manage Images
+
+Once the images are generated, they will appear on the drawing page. You can preview them, click to view in full size, select your favorites, and download them.
+
+All generated images are automatically saved to your LobeHub asset library.
+
+
diff --git a/docs/usage/getting-started/image-generation.zh-CN.mdx b/docs/usage/getting-started/image-generation.zh-CN.mdx
new file mode 100644
index 0000000000..de9591a35e
--- /dev/null
+++ b/docs/usage/getting-started/image-generation.zh-CN.mdx
@@ -0,0 +1,52 @@
+---
+title: 图像生成
+description: 简单的集中配置，例如提示词，选择模型，知识库，插件等。
+tags:
+ - LobeHub
+ - LobeHub
+ - AI 助手
+ - 助手组织
+ - 分组设置
+ - 助手搜索
+ - 助手固定
+---
+
+# 图像生成
+
+LobeHub 提供 AI 画图功能，让你通过文字描述生成图像。无论是产品原型、设计灵感、插图配图，还是创意探索，AI 画图都能快速将你的想法可视化。输入描述，选择模型和参数，几秒钟内就能获得高质量的图像。生成的图片会自动保存到你的 LobeHub 资源库，方便随时查看、下载和使用。从创意构思到图像生成，整个过程简单高效。
+
+## 开始画图
+
+在 LobeHub 主界面点击「绘画」板块，进入 AI 画图页面。
+
+## 输入提示词
+
+在输入框中描述你想要的图像。描述越详细，生成的图像越符合预期。
+
+## 选择 AI 模型
+
+LobeHub 提供多个 AI 画图模型，选择最符合需求的模型即可。
+
+
+
+## 选择参考图片
+
+选择参考图片如果你有参考图片，可以上传作为生成的参考。点击上传参考图片按钮或直接把参考图片拖入即可。参考图片可以上传多张。
+
+
+
+## 选择图片比例
+
+选择图片比例你可以根据使用场景选择合适的图片比例。
+
+## 设置生成图片数量
+
+你可以选择一次生成多少张图片。
+
+## 查看和管理图片
+
+图像生成完成后，会显示在画图页面。你可以查看生成的图像、点击图像查看大图、选择满意的图像并下载。
+
+生成的图片会自动保存到你的 LobeHub 资源库。
+
+
diff --git a/docs/usage/getting-started/lobe-ai.mdx b/docs/usage/getting-started/lobe-ai.mdx
new file mode 100644
index 0000000000..9156b96d49
--- /dev/null
+++ b/docs/usage/getting-started/lobe-ai.mdx
@@ -0,0 +1,34 @@
+---
+title: Lobe AI
+description: >-
+ Use Lobe AI to handle your daily tasks, including checking the weather,
+ setting reminders, reading news, managing emails, and more.
+tags:
+ - LobeHub
+ - Lobe AI
+ - Daily Tasks
+---
+
+# Lobe AI
+
+Lobe AI is the official assistant from LobeHub, designed to help you accomplish a wide range of tasks efficiently.
+
+## Use Cases
+
+Lobe AI can assist you with various everyday tasks, such as:
+
+- Software Development: View code snippets, generate code, debug programs, and more.
+- Learning Support: Answer questions, provide study materials, generate practice exercises, etc.
+- Personal Assistant: Check the weather, set reminders, read the news, manage emails, and more.
+- Creative Writing: Generate story ideas, polish your writing, offer writing suggestions, etc.
+- Data Analysis: Create data reports, visualize data, provide analytical insights, and more.
+
+If you have specific needs, you can create a [custom assistant](/docs/usage/getting-started/agent) tailored to your personal requirements.
+
+## Built-in Tools
+
+Lobe AI comes with a variety of built-in tools to help you complete tasks more efficiently:
+
+- [GTD](/docs/usage/agents/gtd)
+- [Plan](/docs/usage/agents/plan)
+- [Notebook](/docs/usage/agents/notebook)
diff --git a/docs/usage/getting-started/lobe-ai.zh-CN.mdx b/docs/usage/getting-started/lobe-ai.zh-CN.mdx
new file mode 100644
index 0000000000..07ddafb15f
--- /dev/null
+++ b/docs/usage/getting-started/lobe-ai.zh-CN.mdx
@@ -0,0 +1,32 @@
+---
+title: Lobe AI
+description: 使用 Lobe AI 完成每日任务，包括查看天气、设置提醒、查看新闻、查看邮件等。
+tags:
+ - LobeHub
+ - Lobe AI
+ - 每日任务
+---
+
+# Lobe AI
+
+Lobe AI 是 LobeHub 的官方助手，可以帮助你完成各种任务。
+
+## 场景
+
+Lobe AI 可以帮助你完成多种日常任务，例如：
+
+- 软件开发：查看代码片段、生成代码、调试代码等。
+- 学习辅助：解答问题、提供学习资料、生成练习题等。
+- 生活助手：查看天气、设置提醒、查看新闻、查看邮件等。
+- 创意写作：生成故事情节、润色文章、提供写作建议等。
+- 数据分析：生成数据报告、可视化数据、提供分析建议等。
+
+如果你有特殊的需求，可以创建[自定义助手](/docs/usage/getting-started/agent)，满足你的个性化需求。
+
+## 内置工具
+
+Lobe AI 集成了多种内置工具，帮助你更高效地完成任务：
+
+- [GTD](/docs/usage/agents/gtd)
+- [Plan](/docs/usage/agents/plan)
+- [Notebook](/docs/usage/agents/notebook)
diff --git a/docs/usage/getting-started/memory.mdx b/docs/usage/getting-started/memory.mdx
new file mode 100644
index 0000000000..2b7a213984
--- /dev/null
+++ b/docs/usage/getting-started/memory.mdx
@@ -0,0 +1,72 @@
+---
+title: Memory
+description: >-
+ Learn about LobeHub's memory feature, including types of memory, memory
+ sources, memory search, and more.
+tags:
+ - LobeHub
+ - LobeHub
+ - Memory
+ - Types of Memory
+ - Memory Sources
+ - Memory Search
+---
+
+# Memory
+
+Traditional AI treats every conversation like the first time—you have to repeat the same information over and over. With the Agent Memory feature, your assistant truly gets to know you. It automatically identifies and remembers key information from your conversations, making each interaction more efficient and personalized.
+
+This isn’t just a simple chat history—it’s intelligent knowledge extraction and organization. The assistant recognizes your identity, work context, personal preferences, and practical experience, and stores them in a structured format. In future conversations, it can proactively recall this memory to provide responses tailored to your needs—just like a colleague who really understands you.
+
+## Understanding Agent Memory
+
+Agent Memory is a built-in plugin in LobeHub. It automatically identifies and extracts key information from your conversations with the assistant, forming a structured memory base. These memories are proactively used in future interactions, making communication more personalized and efficient. Instead of merely recording dialogue, the assistant understands and extracts actionable memory instructions. In later conversations, it references relevant memories to provide more personalized responses, avoid asking for known information again, and tailor its output based on your preferences.
+
+
+
+## Enabling Agent Memory
+
+Memory is a built-in plugin in LobeHub and must be enabled for each assistant. You can enable the memory plugin from the "Assistant Profile" page under the "Add Plugin" section, or directly within a conversation by selecting the plugin in the chat interface.
+
+### Enable from Assistant Profile
+
+Go to the Assistant Profile page, click "+ Add Plugin", and check the "Memory" plugin to enable it.
+
+
+
+### Enable in a Conversation
+
+Open a conversation, click the plugin icon below the chat box, and check the "Memory" plugin to activate it.
+
+
+
+## Managing Memory
+
+### Viewing Memory
+
+Click the "Memory" icon at the bottom of the left sidebar on the LobeHub homepage to open the memory management panel. This panel displays all memories extracted from your conversations. Memories are organized by type for easy browsing and management. Each memory includes the following details:
+
+- Memory Title: A concise summary of the memory’s core content, such as "Dislikes coffee".
+- Preference Weight: Indicates the importance of the memory. The higher the weight, the more the assistant prioritizes it in conversations.
+- Created Time: Shows when the memory was extracted from a conversation.
+- Memory Instruction: The behavioral rule derived from the conversation, which the assistant follows in future interactions. For example: "Avoid recommending coffee or coffee-based drinks unless the user explicitly asks for them; suggest non-coffee alternatives instead."
+- Possible Assistant Actions: Describes how the assistant might apply this memory, such as: "Offer tea, hot chocolate, juice, smoothies, or decaf/non-coffee options depending on context."
+- Tags: Tags related to the memory for easier categorization and search.
+
+
+
+### Searching Memory
+
+When you have many memories, use the search function to quickly locate specific ones. You can also open the command menu at any time to search for memories.
+
+### Editing Memory
+
+You can modify the memory instructions generated from conversations to better reflect your actual needs and preferences.
+
+
+
+### Deleting Memory
+
+Select the memory you want to delete and click the delete button.
+
+
diff --git a/docs/usage/getting-started/memory.zh-CN.mdx b/docs/usage/getting-started/memory.zh-CN.mdx
new file mode 100644
index 0000000000..d7aa2662a8
--- /dev/null
+++ b/docs/usage/getting-started/memory.zh-CN.mdx
@@ -0,0 +1,68 @@
+---
+title: 记忆
+description: 了解 LobeHub 的记忆功能，包括记忆的类型、记忆的来源、记忆的搜索等。
+tags:
+ - LobeHub
+ - LobeHub
+ - 记忆
+ - 记忆的类型
+ - 记忆的来源
+ - 记忆的搜索
+---
+
+# 记忆
+
+传统的 AI 每次对话都像第一次见面，你需要反复说明相同的信息。Agent 记忆功能让助手真正了解你，从对话中自动识别和记住关键信息，让每次交流都更高效、更个性化。
+
+这不是简单的对话历史记录，而是智能的知识提取和组织。助手会识别你的身份信息、工作情景、个人偏好、实践经验，并将它们结构化存储。下次对话时，助手能主动调用这些记忆，提供更贴合你需求的回答，就像一个真正了解你的工作伙伴。
+
+## 理解 Agent 记忆
+
+Agent 记忆是 LobeHub 的内置插件。它能从你与助手的对话中自动识别和提取关键信息，形成结构化的记忆库。这些记忆会在后续对话中被助手主动调用，让交流更加个性化和高效。助理不会简单记录对话内容，而是理解并提取关键信息，形成可执行的记忆指令。在后续对话中，助理会根据问题调用相关记忆，提供更个性化的回答，避免重复询问已知信息，基于你的偏好调整输出。
+
+
+
+## 启用 Agent 记忆
+
+记忆是 LobeHub 的内置插件，需要为助理启用后才能使用。你可以在「助手档案」页面添加插件处启用记忆插件，也可以进入会话，在对话框勾选插件处启用记忆插件。在助理档案中启用
+
+进入助理档案页面，点击「+ 集成插件」，勾选「记忆」插件即可开启。
+
+
+
+### 在会话中启用
+
+进入会话页面，点击对话框下方插件图标，勾选「记忆」插件即可。
+
+
+
+## 管理记忆
+
+### 查看记忆
+
+在 LobeHub 首页左侧边栏下方点击「记忆」图标，进入记忆管理面板。这里展示了助手从对话中提取的所有记忆。记忆面板按类型组织，方便查看和管理。每条记忆包含以下信息：
+
+- 记忆标题标题简洁概括了记忆的核心内容，如 "Dislikes coffee"。
+- 偏好权重显示该记忆的重要程度，权重越高，助理在对话中越会优先考虑这条记忆。
+- 创建时间显示记忆是何时从对话中提取的。
+- 记忆指令助理基于对话内容形成的行为指令，这是助理在后续对话中实际遵循的规则。例如："Avoid recommending coffee or coffee-based drinks unless the user explicitly asks for them; suggest non-coffee alternatives instead."
+- 助理可能采取的行动展示助理如何应用这条记忆，例如："Offer tea, hot chocolate, juice, smoothies, or decaf/non-coffee options depending on context.
+- 标签记忆相关的标签，方便分类和搜索。
+
+
+
+### 搜索记忆
+
+当记忆数量较多时，可以使用搜索功能快速定位。你也可以随时呼出命令菜单来查找记忆。
+
+### 编辑记忆
+
+你可以调整助手基于对话形成的记忆指令，让记忆更准确地反映你的真实需求。
+
+
+
+### 删除记忆
+
+选中想删除的记忆，点击删除即可。
+
+
diff --git a/docs/usage/getting-started/page.mdx b/docs/usage/getting-started/page.mdx
new file mode 100644
index 0000000000..b4c79781bc
--- /dev/null
+++ b/docs/usage/getting-started/page.mdx
@@ -0,0 +1,62 @@
+---
+title: Create and Configure Your AI Assistant
+description: >-
+ A simple centralized configuration for prompts, model selection, knowledge
+ base, plugins, and more.
+tags:
+ - LobeHub
+ - LobeHub
+ - AI Assistant
+ - Assistant Organization
+ - Group Settings
+ - Assistant Search
+ - Assistant Pinning
+---
+
+# Docs
+
+LobeHub offers a professional writing space designed to help you focus on long-form content creation. Whether you're working on technical documentation, study notes, project proposals, or blog posts, the Docs feature has you covered. It supports Markdown formatting, provides real-time preview, and automatically saves every edit.
+
+You can summon the AI assistant at any time to help with writing. The assistant does more than just offer suggestions—it can directly edit your content, polish your writing, add paragraphs, improve structure, and insert examples.
+
+## Understanding the Docs Feature
+
+Docs is LobeHub’s built-in writing environment, tailored for long-form writing and editing. Unlike the chat feature, Docs provides:
+
+- A persistent writing space: Each document exists independently, allowing you to return and continue editing at any time. Your content is saved permanently.
+- Structured content organization: Full Markdown support lets you organize your content with headings, lists, code blocks, quotes, and more—perfect for creating professional documents.
+- Flexible file management: Create, import, rename, duplicate—comprehensive file management tools help you efficiently organize all your documents.
+
+### Creating and Importing Docs
+
+## Create a New Document
+
+From the LobeHub main interface, go to “Docs” and click “New Document,” or use the dropdown menu from the new file icon on the homepage to quickly create one. Once created, you can start writing immediately. Your work is auto-saved, so you can close it anytime and pick up where you left off later.
+
+### Import a Markdown File
+
+If you already have a Markdown document, you can import it directly. In the Docs section, click “Upload Markdown File,” select your file, and it will be loaded into a new document for immediate editing.
+
+### Editing Documents
+
+Docs are edited using Markdown. Markdown is a lightweight markup language that uses simple symbols to format text, allowing you to focus on content. You can also add an icon to your document, which will appear before the title.
+
+
+
+### Command Palette
+
+While editing, press the / key to open the command palette. This is a quick-access tool that lets you insert various formatting elements with ease.
+
+
+
+### Collaborate with Lobe AI
+
+While editing a document, click the AI assistant icon on the right side of the editor to open the assistant panel. The panel slides in from the right and displays alongside your document, allowing you to chat with the assistant while continuing to write.
+
+By default, the “Docs Assistant” is used—an AI assistant optimized specifically for document writing. If you need help in a specific domain, you can switch to a custom assistant you’ve created via the top-left corner of the assistant panel.
+
+The assistant can directly edit the content within your document.
+
+### Managing Documents
+
+In the document list, you can rename documents, create duplicates, copy the full content, or delete them.
diff --git a/docs/usage/getting-started/page.zh-CN.mdx b/docs/usage/getting-started/page.zh-CN.mdx
new file mode 100644
index 0000000000..dea954fe0a
--- /dev/null
+++ b/docs/usage/getting-started/page.zh-CN.mdx
@@ -0,0 +1,60 @@
+---
+title: 创建和配置你的 AI 助理
+description: 简单的集中配置，例如提示词，选择模型，知识库，插件等。
+tags:
+ - LobeHub
+ - LobeHub
+ - AI 助手
+ - 助手组织
+ - 分组设置
+ - 助手搜索
+ - 助手固定
+---
+
+# 文稿
+
+LobeHub 提供专业的文稿编辑空间，让你能专注于长文本创作。无论是技术文档、学习笔记、项目方案，还是博客文章，文稿功能都能满足你的需求。支持 Markdown 格式，提供实时预览，自动保存每次编辑。
+
+你可以随时呼出 AI 助手参与编写。助手不只是提供建议，还能直接在文稿中编辑内容 —— 润色文字、补充段落、优化结构、添加示例。
+
+## 理解文稿功能
+
+文稿是 LobeHub 的内置写作空间，专为长文本创作和编辑设计。与对话功能不同，文稿提供了：
+
+- 持久的创作空间：文稿独立存在，你可以随时回到文稿继续编辑，内容永久保存。
+- 结构化的内容组织：支持完整的 Markdown 语法，让你能用标题、列表、代码块、引用等元素组织内容，呈现专业的文档效果。
+- 灵活的文件管理：创建、导入、重命名、复制 —— 完整的文件管理功能，让你高效组织所有文稿。
+
+### 创建和导入文稿
+
+## 新建文稿
+
+在 LobeHub 主界面进入「文稿」，点击「新建文稿」，或在主界面新建图标的下拉菜单处选择「创建文稿」快速创建。创建完成后，即可开始编写。文稿会自动保存，你可以随时关闭，下次继续编辑。
+
+### 导入 Markdown 文件
+
+如果你已经有现成的 Markdown 文档，可以直接导入。在文稿板块点击「上传 Markdown 文件」，选择并上传，文件内容会自动加载到新文稿中，你可以立即开始编辑。
+
+### 编辑文稿
+
+文稿使用 Markdown 格式编辑。Markdown 是一种轻量级标记语言，用简单的符号表示格式，让你专注于内容。在文稿标题上方，可以为文稿添加 icon。icon 会显示在文稿标题前。
+
+
+
+### 命令面板
+
+在编辑时按下 / 键，会呼出命令面板。这是一个快捷工具，让你能快速插入各种格式元素。
+
+
+
+### 与 Lobe AI 合作编辑
+
+在编辑文稿时，点击编辑器右侧的 AI 助手图标按钮，助手面板会从右侧滑出。面板与文稿并排显示，你可以一边编辑文稿，一边与助手对话。
+
+呼出助手面板后，默认使用「文稿助理」。这是专门为文稿编写优化的助手，如果需要特定领域的专业帮助，可以在助手面板左上方切换到自己创建的助手。
+
+助手可以直接在文稿中编辑内容。
+
+### 管理文稿
+
+在文稿列表，可以重命名文稿、创建副本、复制全文、删除文稿。
diff --git a/docs/usage/getting-started/resource.mdx b/docs/usage/getting-started/resource.mdx
new file mode 100644
index 0000000000..4439628241
--- /dev/null
+++ b/docs/usage/getting-started/resource.mdx
@@ -0,0 +1,67 @@
+---
+title: Resource Library
+description: >-
+ A simple centralized configuration for prompts, model selection, knowledge
+ bases, plugins, and more.
+tags:
+ - LobeHub
+ - LobeHub
+ - AI Assistant
+ - Assistant Organization
+ - Group Settings
+ - Assistant Search
+ - Assistant Pinning
+---
+
+# Resource Library
+
+The Resource Library in LobeHub is your personal knowledge hub. Documents uploaded during conversations, AI-generated images, and created drafts are all collected here. It strengthens your collaboration with AI by centralizing your knowledge, making it easier to manage and access anytime.
+
+## Sources of Resources
+
+- Conversation Uploads: Files uploaded during chats with assistants are automatically saved to the Resource Library. For example, if you upload a PDF for summarization, the file will be stored and available for future use.
+- AI-Generated Content: Images created in the drawing module are automatically saved to the Resource Library. You can view, download, and reuse them in conversations or drafts at any time.
+- Manual Uploads: You can directly upload files or folders to the Resource Library to actively build your knowledge base. Supported formats include documents, images, videos, audio, and more.
+- Draft Creation: Drafts created in the writing module are also stored in the Resource Library for unified management alongside other resources.
+- Notion Import: You can import content from Notion into the LobeHub Resource Library, enabling seamless knowledge management across platforms.
+- Accessing the Resource Library: Click the "Resources" icon at the bottom of the left sidebar on the LobeHub main interface to enter the Resource Library.
+
+## Creating a Resource Library
+
+You can organize your Resource Library by theme, project, type, and more. Creating separate libraries helps keep your resources well-structured.
+
+Click "New Library" in the left panel of the Resource Library page, enter a name, add an optional description, and click "Create" to get started.
+
+
+
+### Uploading Folders
+
+Choose to upload a folder to batch upload all files within it.
+
+### Connecting Notion
+
+Select and export documents from Notion, then import the Notion ZIP file via the "Connect Notion" page. Once imported, you can continue editing these documents within LobeHub.
+
+
+
+## Managing the Resource Library
+
+File Chunking: This process splits long documents into smaller text segments and vectorizes each one. It enables the AI assistant to better understand and retrieve relevant content.
+
+After chunking:
+
+- When you ask a question, the AI can quickly locate the relevant parts of a document instead of processing the entire file.
+- Vectorization allows the AI to grasp the semantic meaning of the text, not just match keywords.
+- The AI only processes relevant chunks, resulting in faster and more accurate responses.
+
+### Batch Operations
+
+Select multiple files and open the menu in the top-right corner to perform batch operations, including moving files to a library, chunking, or deleting them in bulk.
+
+
+
+### Cross-Feature Collaboration
+
+- Chat + Resource Library: Reference resources during conversations so the assistant can provide answers based on your knowledge.
+- Drafts + Resource Library: Use materials from the Resource Library while writing to enhance content creation efficiency.
+- Drawing + Resource Library: Save generated images to the Resource Library for centralized management of all visual assets.
diff --git a/docs/usage/getting-started/resource.zh-CN.mdx b/docs/usage/getting-started/resource.zh-CN.mdx
new file mode 100644
index 0000000000..638adb3024
--- /dev/null
+++ b/docs/usage/getting-started/resource.zh-CN.mdx
@@ -0,0 +1,65 @@
+---
+title: 资源库
+description: 简单的集中配置，例如提示词，选择模型，知识库，插件等。
+tags:
+ - LobeHub
+ - LobeHub
+ - AI 助手
+ - 助手组织
+ - 分组设置
+ - 助手搜索
+ - 助手固定
+---
+
+# 资源库
+
+LobeHub 的资源库是你的个人知识中心。对话中上传的文档、AI 生成的图片、创建的文稿，都会汇聚在这里。资源库让你和 AI 的协作更紧密，知识积累不再分散在各处，而是统一管理、随时可用。
+
+## 资源的来源
+
+- 对话上传：在与助手对话时上传的文件会自动保存到资源库。例如你上传一份 PDF 让助手总结，这份文件会保留在资源库中，下次可以继续使用。
+- AI 生成：在画图板块生成的图片会自动保存到资源库。你可以随时查看、下载、在对话和文稿中使用这些图片。
+- 主动上传：你可以在资源库直接上传文件或文件夹，主动构建知识库。支持文档、图片、视频、音频等多种格式。
+- 文稿创建：在文稿板块创建的文稿也会出现在资源库中，与其他资源统一管理。
+- Notion 导入：你可以将 Notion 中的内容导入到 LobeHub 资源库，打通两个平台的知识管理。
+- 创建资源库：在 LobeHub 主界面左侧边栏下方点击「资源」图标，进入资源库页面。
+
+## 创建资源库
+
+资源库可以按主题、项目、类型等方式组织。创建不同的资源库，让资源管理更有条理。
+
+在资源库页面左侧面板点击「新建资源库」，输入资源库名称，添加简介（可选），点击新建即可。
+
+
+
+### 上传文件夹
+
+选择上传文件夹，可以批量上传整个文件夹的文件。
+
+### 连接 Notion
+
+在 Notion 选择文档并导出，再在「连接 Notion 」页面选择导入 Notion ZIP 即可。导入后，你可以在 LobeHub 中再编辑这些文档。
+
+
+
+## 管理资源库
+
+文件分块：文件分块是将长文档拆分成多个较小的文本片段，并对每个片段进行向量化处理。这让 AI 助手能更精准地理解和检索文件内容。
+
+进行文件分块后：
+
+- 当你提问时，AI 能快速定位到文档中相关的部分，而不是处理整个文档。
+- 向量化让 AI 能理解文本的语义含义，而不只是关键词匹配。
+- AI 只需要处理相关的文本块，响应更快、更准确。
+
+### 批量操作
+
+勾选多个文件，展开右上角菜单可以进行批量操作，包括将多个文件批量移入资源库、批量分块和批量删除文件。
+
+
+
+### 跨功能协作
+
+- 对话 + 资源库：在对话中引用资源库，让助手基于你的知识提供回答。
+- 文稿 + 资源库：编写文稿时使用资源库中的素材，内容创作更高效。
+- 画图 + 资源库：将生成的图片保存到资源库，统一管理所有视觉素材。
diff --git a/docs/usage/help.mdx b/docs/usage/help.mdx
new file mode 100644
index 0000000000..3e72601c92
--- /dev/null
+++ b/docs/usage/help.mdx
@@ -0,0 +1,38 @@
+---
+title: Help & Support - LobeHub User Guide
+description: >-
+ Learn about help and support options for LobeHub, including community support
+ and how to contact us.
+tags:
+ - LobeHub
+ - LobeHub
+ - Help & Support
+ - Community Support
+ - Contact Us
+---
+
+# Help & Support
+
+If you encounter any issues while using LobeHub, please refer to the following resources.
+
+## Common Guides
+
+- [Migrate from v1.x Local Database to v2.x (Cloud / Self-hosted)](/docs/usage/migrate-from-local-database)
+
+## Report an Issue
+
+- [GitHub Issues](https://github.com/lobehub/lobe-chat/issues/new/choose)
+
+## Community Support
+
+You're welcome to ask questions or help others in the following communities:
+
+- [Discord](https://discord.com/invite/AYFPHvv2jT)
+- [Reddit](https://www.reddit.com/r/LobeHub/)
+
+## Contact Us
+
+You can reach us through the following channels:
+
+- [hi@lobehub.com](mailto:hi@lobehub.com)
+- [X (formerly Twitter)](https://x.com/lobehub)
diff --git a/docs/usage/help.zh-CN.mdx b/docs/usage/help.zh-CN.mdx
new file mode 100644
index 0000000000..6327a3d6b0
--- /dev/null
+++ b/docs/usage/help.zh-CN.mdx
@@ -0,0 +1,36 @@
+---
+title: 帮助与支持 - LobeHub 用户指南
+description: 了解 LobeHub 的帮助与支持，包括社区支持、联系我们等。
+tags:
+ - LobeHub
+ - LobeHub
+ - 帮助与支持
+ - 社区支持
+ - 联系我们
+---
+
+# 帮助与支持
+
+如果你在使用 LobeHub 的过程中遇到任何问题，请参考以下内容。
+
+## 常用指南
+
+- [从 v1.x 本地数据库迁移到 v2.x（云端 / 自部署）](/docs/usage/migrate-from-local-database)
+
+## 反馈问题
+
+- [GitHub Issues](https://github.com/lobehub/lobe-chat/issues/new/choose)
+
+## 社区支持
+
+欢迎你在以下社区中提出问题或帮助他人。
+
+- [Discord](https://discord.com/invite/AYFPHvv2jT)
+- [Reddit](https://www.reddit.com/r/LobeHub/)
+
+## 联系我们
+
+你可以通过以下方式联系我们：
+
+- [hi@lobehub.com](mailto:hi@lobehub.com)
+- [X (Twitter)](https://x.com/lobehub)
diff --git a/docs/usage/migrate-from-local-database.mdx b/docs/usage/migrate-from-local-database.mdx
new file mode 100644
index 0000000000..771c5b982a
--- /dev/null
+++ b/docs/usage/migrate-from-local-database.mdx
@@ -0,0 +1,118 @@
+---
+title: Migrate from Local Database (v1.x) to Cloud (v2.x)
+description: >-
+ Export your data from the v1.x local database and import it into LobeHub v2.x
+ Cloud.
+tags:
+ - LobeHub
+ - Migration
+ - Cloud
+ - Desktop
+ - Local Database
+---
+
+# Migrate from Local Database (v1.x) to Cloud (v2.x)
+
+LobeHub v1.x Desktop supported a **local database** mode, which stored your data on this device. Starting from v2.x, we have moved to a **cloud-first architecture** and removed the local database so we can iterate faster and deliver a more consistent experience across platforms.
+
+
+ Why the change? The v1.x local database typically consumed more system resources, and only a small
+ portion of users relied on it. By simplifying the client and focusing on the cloud-first
+ experience, we can improve overall performance and ship new features faster.
+
+
+This guide explains how to **export your data from v1.x** and **import it into v2.x**.
+
+## Before you start
+
+- Keep your **v1.x client installed** until you confirm the migration is successful.
+- Prepare a **stable network connection** (importing may take time, especially for large histories).
+- Sign in to **LobeHub v2.x** (Cloud or your self-hosted instance).
+
+If you prefer self-hosting, you can follow the [Self-Hosting Guide](/docs/self-hosting/start) first, then import into your self-hosted v2.x instance.
+
+## If you already upgraded to v2.x by accident
+
+You can still migrate your data:
+
+1. Download and install a **v1.x build** from [GitHub Releases](https://github.com/lobehub/lobe-chat/releases).
+2. Use v1.x to export your data (`Settings -> Data Storage -> Export Data`), then import it in v2.x.
+
+Don’t worry: **upgrading to v2.x does not delete your local database files**. As long as the local database files are still there, your data is still there.
+
+### Local database location
+
+By default, the local database is stored at:
+
+- `${appData}/lobehub-storage/lobehub-local-db`
+
+## What will be migrated
+
+The exact items depend on the export format and your v1.x build, but typically include:
+
+- Your assistants/agents
+- Conversations / topics and messages
+- Prompt templates (if used in your v1.x build)
+- Basic preferences and settings (when supported)
+
+## What will NOT be migrated (common cases)
+
+- Provider API keys and secrets (recommended to re-enter them in v2.x)
+- Local-only files or cached data
+- Some device-specific settings
+
+
+ If your v1.x data contains sensitive content, keep the export file in a safe location. Do not
+ share it publicly.
+
+
+## Step 1: Export data from LobeHub v1.x
+
+In the v1.x Desktop app:
+
+1. Go to **Settings** → **Data Storage** → **Export Data**.
+2. You will get a JSON export file (for example: `2026-01-22-10-02_LobeHub-data.json`).
+3. Save the file to a location you can easily find (for example, Desktop).
+
+
+
+### Export tips
+
+- If you have a very large message history, consider exporting during idle time.
+
+## Step 2: Import data into LobeHub v2.x
+
+In any v2.x app (Desktop / Web / self-hosted):
+
+1. Sign in to your LobeHub account.
+2. Go to **Settings** → **Data Storage** → **Import Data**.
+3. Upload the export JSON file from Step 1.
+4. Wait for the import to complete, then refresh the page/app if needed.
+
+
+
+## Verify your migration
+
+After importing, check:
+
+- Agents/assistants are present and their prompts look correct
+- Recent conversations appear as expected
+- Key settings (language, theme, shortcuts, etc.) are set the way you want
+
+If anything is missing, keep the v1.x export file and retry the import after updating to the latest v2.x.
+
+## Troubleshooting
+
+### Import fails or gets stuck
+
+- Confirm your network is stable and try again.
+- Update to the latest v2.x and re-import.
+
+### Some data is missing after import
+
+- Different v1.x builds may store data slightly differently.
+- If you used multiple profiles/workspaces in v1.x, export and import them separately (when supported).
+
+## Getting help
+
+If you run into issues, please check [Help & Support](/docs/usage/help) or report an issue via [GitHub Issues](https://github.com/lobehub/lobe-chat/issues/new/choose).
diff --git a/docs/usage/migrate-from-local-database.zh-CN.mdx b/docs/usage/migrate-from-local-database.zh-CN.mdx
new file mode 100644
index 0000000000..d2d2d541d8
--- /dev/null
+++ b/docs/usage/migrate-from-local-database.zh-CN.mdx
@@ -0,0 +1,115 @@
+---
+title: 从本地数据库（v1.x）迁移到云端（v2.x）
+description: 在 v1.x 客户端导出本地数据库数据，并导入到 LobeHub v2.x 云端版本。
+tags:
+ - LobeHub
+ - 迁移
+ - Cloud
+ - 桌面端
+ - 本地数据库
+---
+
+# 从本地数据库（v1.x）迁移到云端（v2.x）
+
+在 LobeHub v1.x Desktop 中，我们曾提供 **本地数据库** 模式，将数据保存在当前设备上。自 v2.x 起，我们转向 **Cloud-first 架构** 并移除了本地数据库能力，以便后续更好、更快地迭代，并在不同平台上提供更一致的体验。
+
+
+ 为什么要这样做？v1.x
+ 的本地数据库通常会带来更高的资源占用，而实际使用它的用户占比较小。砍掉这条分支能力后，我们可以让客户端更轻量、更稳定，同时把更多精力投入到
+ Cloud-first 体验与新功能交付上。
+
+
+本文会引导你完成：**在 v1.x 导出数据** → **在 v2.x 导入数据**。
+
+## 开始前准备
+
+- 建议在迁移确认完成之前，**不要卸载 v1.x**。
+- 准备 **稳定的网络连接**（如果对话记录较多，导入可能需要更久）。
+- 登录 **LobeHub v2.x**（云端或你的自部署实例）。
+
+如果你希望把 Cloud 部署在自己的服务器上，也可以先参考 [私有化部署指南](/docs/self-hosting/start) 完成部署，再把数据导入到自部署的 v2.x 实例中。
+
+## 如果你已经不小心升级到了 v2.x
+
+你依然可以完成迁移：
+
+1. 前往 [GitHub Releases](https://github.com/lobehub/lobe-chat/releases) 下载并安装一个 **v1.x 版本**。
+2. 使用 v1.x 按照本文的导出流程导出数据（`Settings -> Data Storage -> Export Data`），再在 v2.x 中导入。
+
+请放心：**升级到 v2.x 的过程不会删除你的本地数据库文件**。只要本地数据库文件仍然存在，你的数据就依然存在。
+
+### 本地数据库文件位置
+
+本地数据库默认位于：
+
+- `${appData}/lobehub-storage/lobehub-local-db`
+
+## 通常可以迁移的内容
+
+可迁移内容会受导出格式与 v1.x 构建版本影响，但一般包括：
+
+- 助手 / Agents
+- 会话 / Topics 与消息记录
+- 提示词模板（如你的 v1.x 版本支持）
+- 部分基础偏好设置（如版本支持）
+
+## 通常不会迁移的内容（常见情况）
+
+- 各模型服务商的 API Key / Secret（更推荐在 v2.x 重新填写）
+- 仅存在于本地的临时文件、缓存数据
+- 一些与设备强绑定的设置项
+
+
+ 如果你的 v1.x 数据包含敏感内容，请妥善保管导出的迁移文件，避免在公共渠道分享。
+
+
+## 第一步：在 LobeHub v1.x 导出数据
+
+在 v1.x Desktop 客户端中：
+
+1. 进入 **Settings** → **Data Storage** → **Export Data**。
+2. 你会得到一个 JSON 导出文件（例如：`2026-01-22-10-02_LobeHub-data.json`）。
+3. 将导出的文件保存到你容易找到的位置（例如桌面）。
+
+
+
+### 导出建议
+
+- 如果你的历史记录非常多，建议在设备空闲时导出。
+
+## 第二步：在 LobeHub v2.x 导入数据
+
+在任意 v2.x 应用中（Desktop / Web / 自部署 WebApp）：
+
+1. 登录你的 LobeHub 账号。
+2. 进入 **Settings** → **Data Storage** → **Import Data**。
+3. 上传你在第一步导出的 JSON 文件。
+4. 等待导入完成；必要时刷新页面 / 重启应用。
+
+
+
+## 迁移完成后如何验收
+
+导入完成后，建议你检查：
+
+- 助手是否齐全，提示词 / 配置是否正确
+- 最近的会话是否能正常打开、消息是否完整
+- 常用设置（语言、主题、快捷键等）是否符合预期
+
+如发现缺失，建议先升级到最新 v2.x 后再重试导入，同时保留 v1.x 的导出文件用于排查。
+
+## 常见问题排查
+
+### 导入失败或长时间卡住
+
+- 确认网络稳定后重试。
+- 升级到最新 v2.x 再导入一次。
+
+### 导入后部分数据缺失
+
+- 不同 v1.x 构建版本的数据结构可能略有差异。
+- 如果你在 v1.x 使用过多个配置 / 空间（若支持），可尝试分别导出并逐个导入（如版本支持）。
+
+## 获取帮助
+
+如果你遇到迁移问题，可以查看 [帮助与支持](/docs/usage/help) 或通过 [GitHub Issues](https://github.com/lobehub/lobe-chat/issues/new/choose) 反馈。
diff --git a/docs/usage/plugins/basic-usage.mdx b/docs/usage/plugins/basic-usage.mdx
deleted file mode 100644
index 3cd09a073d..0000000000
--- a/docs/usage/plugins/basic-usage.mdx
+++ /dev/null
@@ -1,45 +0,0 @@
----
-title: Enhance Your LobeChat Assistant with Plugins
-description: >-
- Learn how to expand your LobeChat assistant's capabilities by enabling and using various plugins. Access the Plugin Store, install plugins, and configure them to enhance your assistant's functionality.
-
-tags:
- - LobeChat plugins
- - Plugin Store
- - Using Plugins
- - Plugin Configuration
----
-
-# Plugin Usage
-
-The plugin system is a key element in expanding the capabilities of assistants in LobeChat. You can enhance the assistant's abilities by enabling a variety of plugins.
-
-Watch the following video to quickly get started with using LobeChat plugins:
-
-
-
-## Plugin Store
-
-You can access the Plugin Store by navigating to "Extension Tools" -> "Plugin Store" in the session toolbar.
-
-
-
-
-## Developing Custom Plugins
-
-If you wish to develop a LobeChat plugin on your own, feel free to refer to the [Plugin Development Guide](/docs/usage/plugins/development) to expand the possibilities of your AI assistant!
diff --git a/docs/usage/plugins/custom-plugin.zh-CN.mdx b/docs/usage/plugins/custom-plugin.zh-CN.mdx
deleted file mode 100644
index 8693557821..0000000000
--- a/docs/usage/plugins/custom-plugin.zh-CN.mdx
+++ /dev/null
@@ -1,35 +0,0 @@
----
-title: 自定义插件 - LobeChat 插件安装与开发指南
-description: 学习如何安装自定义插件和开发 LobeChat 插件，扩展你的 AI 智能助手的功能。
-tags:
- - 自定义插件
- - LobeChat
- - 插件安装
- - 插件开发
- - AI 智能助手
----
-
-# 自定义插件
-
-## 安装自定义插件
-
-如果你希望安装一个不在 LobeChat 插件商店中的插件，例如自己开发的 LobeChat，你可以点击「自定义插件」进行安装：
-
-
-
-此外，LobeChat 的插件机制兼容了 ChatGPT 的插件，因此你可以一键安装相应的 ChatGPT 插件。
-
-如果你希望尝试自行安装自定义插件，你可以使用以下链接来尝试：
-
-- `自定义 Lobe 插件` Mock Credit Card：[https://lobe-plugin-mock-credit-card.vercel.app/manifest.json](https://lobe-plugin-mock-credit-card.vercel.app/manifest.json)
-- `ChatGPT 插件` Access Links：[https://www.accesslinks.ai/.well-known/ai-plugin.json](https://www.accesslinks.ai/.well-known/ai-plugin.json)
-
-
-
-
-## 开发自定义插件
-
-如果你希望自行开发一个 LobeChat 的插件，欢迎查阅 [插件开发指南](/zh/docs/usage/plugins/development) 以扩展你的 AI 智能助手的可能性边界！
diff --git a/docs/usage/plugins/development.mdx b/docs/usage/plugins/development.mdx
deleted file mode 100644
index 4be3246341..0000000000
--- a/docs/usage/plugins/development.mdx
+++ /dev/null
@@ -1,279 +0,0 @@
----
-title: LobeChat Plugin Development Guide
-description: >-
- Learn how to create and integrate custom plugins in LobeChat, including plugin composition, custom plugin workflow, local plugin development, manifest structure, project structure, server-side implementation, plugin UI interface, deployment, and release.
-
-tags:
- - Plugin Development
- - LobeChat
- - Custom Plugins
- - Plugin Workflow
- - Manifest Structure
- - Server-side Implementation
- - Plugin UI Interface
- - Deployment
- - Release
----
-
-# Plugin Development Guide
-
-## Plugin Composition
-
-A LobeChat plugin consists of the following components:
-
-1. **Plugin Index**: Used to display basic information about the plugin, including the plugin name, description, author, version, and a link to the plugin manifest. The official plugin index can be found at [lobe-chat-plugins](https://github.com/lobehub/lobe-chat-plugins). If you want to publish a plugin to the official plugin marketplace, you need to [submit a PR](https://github.com/lobehub/lobe-chat-plugins/pulls) to this repository.
-2. **Plugin Manifest**: Used to describe the functionality of the plugin, including the server-side description, frontend display information, and version number. For a detailed introduction to the manifest, see [manifest][manifest-docs-url].
-3. **Plugin Services**: Used to implement the server-side and frontend modules described in the plugin manifest, as follows:
- - **Server-side**: Needs to implement the interface capabilities described in the `api` section of the manifest.
- - **Frontend UI** (optional): Needs to implement the interface described in the `ui` section of the manifest. This interface will be displayed in plugin messages, allowing for a richer display of information than plain text.
-
-## Custom Plugin Workflow
-
-This section will introduce how to add and use a custom plugin in LobeChat.
-
-
- ### Create and Launch Plugin Project
-
- You need to first create a plugin project locally, you can use the template we have prepared [lobe-chat-plugin-template][lobe-chat-plugin-template-url]
-
- ```bash
- $ git clone https://github.com/lobehub/chat-plugin-template.git
- $ cd chat-plugin-template
- $ npm i
- $ npm run dev
- ```
-
- When you see `ready started server on 0.0.0.0:3400, url: http://localhost:3400`, it means the plugin service has been successfully launched locally.
-
-
-
-## Local Plugin Development
-
-In the above process, we have learned how to add and use plugins. Next, we will focus on the process of developing custom plugins.
-
-### Manifest
-
-The `manifest` aggregates information on how the plugin's functionality is implemented. The core fields are `api` and `ui`, which respectively describe the server-side interface capabilities and the front-end rendering interface address of the plugin.
-
-Taking the `manifest` in the template we provided as an example:
-
-```json
-{
- "api": [
- {
- "url": "http://localhost:3400/api/clothes",
- "name": "recommendClothes",
- "description": "Recommend clothes to the user based on their mood",
- "parameters": {
- "properties": {
- "mood": {
- "description": "The user's current mood, with optional values: happy, sad, anger, fear, surprise, disgust",
- "enums": ["happy", "sad", "anger", "fear", "surprise", "disgust"],
- "type": "string"
- },
- "gender": {
- "type": "string",
- "enum": ["man", "woman"],
- "description": "The user's gender, which needs to be asked for from the user to obtain this information"
- }
- },
- "required": ["mood", "gender"],
- "type": "object"
- }
- }
- ],
- "gateway": "http://localhost:3400/api/gateway",
- "identifier": "chat-plugin-template",
- "ui": {
- "url": "http://localhost:3400",
- "height": 200
- },
- "version": "1"
-}
-```
-
-In this manifest, it mainly includes the following parts:
-
-1. `identifier`: This is the unique identifier of the plugin, used to distinguish different plugins. This field needs to be globally unique.
-2. `api`: This is an array containing all the API interface information of the plugin. Each interface includes the url, name, description, and parameters fields, all of which are required. The `description` and `parameters` fields will be sent to GPT as the `functions` parameter of the [Function Call](https://sspai.com/post/81986), and the parameters need to comply with the [JSON Schema](https://json-schema.org/) specification. In this example, the API interface is named `recommendClothes`, and its function is to recommend clothes based on the user's mood and gender. The interface parameters include the user's mood and gender, both of which are required.
-3. `ui`: This field contains information about the plugin's user interface, indicating from which address LobeChat loads the plugin's front-end interface. Since LobeChat plugin interface loading is implemented based on iframes, the height and width of the plugin interface can be specified as needed.
-4. `gateway`: This field specifies the gateway for LobeChat to query the plugin's API interface. LobeChat's default plugin gateway is a cloud-based service, and requests for custom plugins need to be sent to a locally launched service. Remote calls to a local address are generally not feasible. The `gateway` field solves this problem. By specifying the gateway in the manifest, LobeChat will send plugin requests to this address, and the local gateway address will dispatch requests to the local plugin service. Published online plugins do not need to specify this field.
-5. `version`: This is the version number of the plugin, which currently has no effect.
-
-In actual development, you can modify the plugin's description list according to your own needs to declare the functionality you want to implement. For a complete introduction to each field in the manifest, see: [manifest][manifest-docs-url].
-
-### Project Structure
-
-The [lobe-chat-plugin-template][lobe-chat-plugin-template-url] template project uses Next.js as the development framework, and its core directory structure is as follows:
-
-```
-➜ chat-plugin-template
-├── public
-│ └── manifest-dev.json # Manifest file
-├── src
-│ └── pages
-│ │ ├── api # Next.js server-side folder
-│ │ │ ├── clothes.ts # Implementation of the recommendClothes interface
-│ │ │ └── gateway.ts # Local plugin proxy gateway
-│ │ └── index.tsx # Front-end display interface
-```
-
-This template uses Next.js as the development framework. You can use any development framework and language you are familiar with, as long as it can implement the functionality described in the manifest.
-
-Contributions of more plugin templates using different frameworks and languages are also welcome.
-
-### Server-Side
-
-The server-side needs to implement the API interfaces described in the manifest. In the template, we use Vercel's [Edge Runtime](https://nextjs.org/docs/pages/api-reference/edge) to eliminate the need for maintenance.
-
-#### API Implementation
-
-For the Edge Runtime, we provide the `createErrorResponse` method in `@lobehub/chat-plugin-sdk` to quickly return error responses. Currently, the provided error types are detailed in: [PluginErrorType][plugin-error-type-url].
-
-The implementation of the clothes interface in the template is as follows:
-
-```ts
-export default async (req: Request) => {
- if (req.method !== 'POST') return createErrorResponse(PluginErrorType.MethodNotAllowed);
-
- const { gender, mood } = (await req.json()) as RequestData;
-
- const clothes = gender === 'man' ? manClothes : womanClothes;
-
- const result: ResponseData = {
- clothes: clothes[mood] || [],
- mood,
- today: Date.now(),
- };
-
- return new Response(JSON.stringify(result));
-};
-```
-
-Where `manClothes` and `womanClothes` are mock data and can be replaced with database queries in actual scenarios.
-
-#### Plugin Gateway
-
-Since the default plugin gateway for LobeChat is a cloud service `/api/plugins`, the cloud service sends requests to the address specified in the manifest's `api.url` to solve cross-origin issues.
-
-For custom plugins, plugin requests need to be sent to the local service. Therefore, by specifying the gateway in the manifest ([http://localhost:3400/api/gateway](http://localhost:3400/api/gateway)), LobeChat> will directly request this address, and then only the corresponding gateway needs to be created at that address.
-
-```ts
-import { createLobeChatPluginGateway } from '@lobehub/chat-plugins-gateway';
-
-export const config = {
- runtime: 'edge',
-};
-
-export default createLobeChatPluginGateway();
-```
-
-[`@lobehub/chat-plugins-gateway`](https://github.com/lobehub/chat-plugins-gateway) contains the implementation of the plugin gateway in LobeChat [here](https://github.com/lobehub/lobe-chat/blob/main/src/pages/api/plugins.api.ts). You can use this package directly to create a gateway, allowing LobeChat to access the local plugin service.
-
-### Plugin UI Interface
-
-The custom UI interface for plugins is optional. For example, the official plugin [Web Content Extraction](https://github.com/lobehub/chat-plugin-web-crawler) does not have a corresponding user interface.
-
-();
-
- useEffect(() => {
- // Retrieve the current plugin message from LobeChat
- fetchPluginMessage().then((e: ResponseData) => {
- setData(e);
- });
- }, []);
-
- return <>...;
-});
-
-export default Render;
-```
-
-## Plugin Deployment and Release
-
-Once you have finished developing the plugin, you can deploy it using your preferred method, such as using Vercel or packaging it as a Docker container for release, and so on.
-
-If you want more people to use your plugin, feel free to [submit it for listing](https://github.com/lobehub/lobe-chat-plugins) on the plugin marketplace.
-
-[![][submit-plugin-shield]][submit-plugin-url]
-
-### Plugin Shield
-
-[](https://github.com/lobehub/lobe-chat-plugins)
-
-```md
-[](https://github.com/lobehub/lobe-chat-plugins)
-```
-
-## Links
-
-- **📘 Pluging SDK Documentation**: [https://chat-plugin-sdk.lobehub.com](https://chat-plugin-sdk.lobehub.com)
-- **🚀 chat-plugin-template**: [https://github.com/lobehub/chat-plugin-template](https://github.com/lobehub/chat-plugin-template)
-- **🧩 chat-plugin-sdk**: [https://github.com/lobehub/chat-plugin-sdk](https://github.com/lobehub/chat-plugin-sdk)
-- **🚪 chat-plugin-gateway**: [https://github.com/lobehub/chat-plugins-gateway](https://github.com/lobehub/chat-plugins-gateway)
-- **🏪 lobe-chat-plugins**: [https://github.com/lobehub/lobe-chat-plugins](https://github.com/lobehub/lobe-chat-plugins)
-
-[fetch-plugin-message-url]: https://github.com/lobehub/chat-plugin-template
-[lobe-chat-plugin-template-url]: https://github.com/lobehub/chat-plugin-template
-[manifest-docs-url]: https://chat-plugin-sdk.lobehub.com/guides/plugin-manifest
-[plugin-error-type-url]: https://github.com/lobehub/chat-plugin-template
-[submit-plugin-shield]: https://img.shields.io/badge/🧩/🏪_submit_plugin-%E2%86%92-95f3d9?labelColor=black&style=for-the-badge
-[submit-plugin-url]: https://github.com/lobehub/lobe-chat-plugins
diff --git a/docs/usage/plugins/store.mdx b/docs/usage/plugins/store.mdx
deleted file mode 100644
index 9f07d7b1f8..0000000000
--- a/docs/usage/plugins/store.mdx
+++ /dev/null
@@ -1,22 +0,0 @@
----
-title: LobeChat Plugin Store
-description: >-
- Learn how to access the Plugin Store in LobeChat to easily install and use various plugins for enhanced functionality.
-
-tags:
- - Plugin Store
- - LobeChat
- - Install Plugins
- - Extension Tools
- - Enhanced Functionality
----
-
-# Plugin Store
-
-You can access the plugin store by going to `Extension Tools` -> `Plugin Store` in the session toolbar.
-
-
- ### Step 1: Obtain the AI21 Labs API Key
+ ### Step 1: Obtain an API Key from AI21 Labs
- - Register and log in to [AI21 Studio](https://studio.ai21.com)
- - Click on the `User Avatar` menu, then select `API Key`
+ - Sign up and log in to [AI21 Studio](https://studio.ai21.com)
+ - Click on your `user avatar` and select `API Key`
- Copy and save the generated API key
-
- During use, you may need to pay the API service provider; please refer to the relevant fee policy
- of AI21 Labs.
+ You may need to pay for API usage depending on your usage level. Please refer to AI21 Labs' pricing policy for more details.
-Now you are ready to engage in conversations using the models provided by AI21 Labs in LobeChat.
+And that’s it! You’re now ready to use AI21 Labs models for conversations in LobeHub.
diff --git a/docs/usage/providers/ai21.zh-CN.mdx b/docs/usage/providers/ai21.zh-CN.mdx
index 1cae62a8f5..93a533528c 100644
--- a/docs/usage/providers/ai21.zh-CN.mdx
+++ b/docs/usage/providers/ai21.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 AI21 Labs
-description: 学习如何在 LobeChat 中配置和使用 AI21 Labs 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 AI21 Labs
+description: 学习如何在 LobeHub 中配置和使用 AI21 Labs 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- AI21 Labs
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 AI21 Labs
+# 在 LobeHub 中使用 AI21 Labs
-
### 步骤一：获得 AI21 Labs 的 API Key
@@ -23,23 +23,23 @@ tags:
- 点击 `用户头像` 菜单，点击 `API Key`
- 复制并保存生成的 API 密钥
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 AI21 Labs 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 AI21 Labs 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 AI21 Labs 提供的模型进行对话了。
diff --git a/docs/usage/providers/ai302.mdx b/docs/usage/providers/ai302.mdx
index c0fbc71461..daa88b7c57 100644
--- a/docs/usage/providers/ai302.mdx
+++ b/docs/usage/providers/ai302.mdx
@@ -1,45 +1,47 @@
---
-title: Using 302.AI in LobeChat
-description: Learn how to configure and use 302.AI's API Key in LobeChat to start conversations and interactions.
+title: Using 302.AI in LobeHub
+description: >-
+ Learn how to configure and use your 302.AI API Key in LobeHub to start
+ chatting and interacting.
tags:
- - LobeChat
+ - LobeHub
- 302.AI
- API Key
- Web UI
---
-# Using 302.AI in LobeChat
+# Using 302.AI in LobeHub
-
- ### Step 1: Obtain [302.AI](https://www.302.ai/) API Key
+ ### Step 1: Get Your [302.AI](https://www.302.ai/) API Key
- - Click `Get Started`, register and log in to [302.AI](https://www.302.ai/)
- - Click `API Keys` on the left side
- - Click `Add API KEY`, copy and save the generated API key
+ - Click on `Get Started` to register and log in to [302.AI](https://www.302.ai/)
+ - Navigate to the `API Keys` section on the left sidebar
+ - Click `Add API KEY`, then copy and save the generated API key
-
- During usage, you may need to pay the API service provider. Please refer to 302.AI's relevant pricing policy.
+ You may need to pay for API usage. Please refer to 302.AI’s pricing policy for more details.
-Now you can use 302.AI's models for conversations in LobeChat.
+And that’s it! You’re now ready to use 302.AI models within LobeHub for conversations and interactions.
diff --git a/docs/usage/providers/ai302.zh-CN.mdx b/docs/usage/providers/ai302.zh-CN.mdx
index aba052c591..7c80b2146b 100644
--- a/docs/usage/providers/ai302.zh-CN.mdx
+++ b/docs/usage/providers/ai302.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 302.AI
-description: 学习如何在 LobeChat 中配置和使用 302.AI 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 302.AI
+description: 学习如何在 LobeHub 中配置和使用 302.AI 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 302.AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 302.AI
+# 在 LobeHub 中使用 302.AI
### 步骤一：获得 [302.AI](https://www.302.ai/) 的 API Key
@@ -25,9 +25,9 @@ tags:
-至此你已经可以在 LobeChat 中使用 302.AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 302.AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/ai360.mdx b/docs/usage/providers/ai360.mdx
index 6964a09697..6fc8ea7f67 100644
--- a/docs/usage/providers/ai360.mdx
+++ b/docs/usage/providers/ai360.mdx
@@ -1,46 +1,47 @@
---
-title: Using the 360AI in LobeChat
-description: Learn how to integrate and utilize 360AI's language model APIs in LobeChat.
+title: Using 360 Zhinao in LobeHub
+description: >-
+ Learn how to configure and use the 360 Zhinao API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
- - 360AI
+ - LobeHub
+ - 360 Zhinao
- API Key
- Web UI
---
-# Using the 360AI in LobeChat
+# Using 360 Zhinao in LobeHub
-
- ### Step 1: Obtain the 360AI API Key
+ ### Step 1: Obtain a 360 Zhinao API Key
- - Register and log in to the [360AI API Open Platform](https://ai.360.com/platform/keys)
+ - Register and log in to the [360 Zhinao API Platform](https://ai.360.com/platform/keys)
- Click on the `API Keys` menu on the left
- - Create an API key and copy it
+ - Create a new API key and copy it
-
- Please note that you may need to pay the API service provider during use, refer to the relevant
- pricing policy of the 360AI.
+ You may need to pay for API usage depending on your usage level. Please refer to 360 Zhinao’s pricing policy for details.
-You can now use the models provided by the 360AI for conversations in LobeChat.
+That's it! You're now ready to use 360 Zhinao's models for conversations in LobeHub.
diff --git a/docs/usage/providers/ai360.zh-CN.mdx b/docs/usage/providers/ai360.zh-CN.mdx
index 47f45df27f..48bed81f6a 100644
--- a/docs/usage/providers/ai360.zh-CN.mdx
+++ b/docs/usage/providers/ai360.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用360智脑
-description: 学习如何在 LobeChat 中配置和使用360智脑的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用360智脑
+description: 学习如何在 LobeHub 中配置和使用360智脑的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 360智脑
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 360 智脑
+# 在 LobeHub 中使用 360 智脑
-
### 步骤一：获得 360 智脑的 API Key
@@ -23,23 +23,23 @@ tags:
- 点击左侧 `API Keys` 菜单
- 创建一个 API 密钥并复制
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 360 智脑的相关费用政策。
-至此你已经可以在 LobeChat 中使用 360 智脑提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 360 智脑提供的模型进行对话了。
diff --git a/docs/usage/providers/aihubmix.mdx b/docs/usage/providers/aihubmix.mdx
new file mode 100644
index 0000000000..8a2e6f0ac2
--- /dev/null
+++ b/docs/usage/providers/aihubmix.mdx
@@ -0,0 +1,98 @@
+---
+title: AiHubMix Provider Configuration
+description: Learn how to configure and use the AiHubMix provider in LobeHub
+tags:
+ - AiHubMix
+ - Provider Configuration
+ - Setup Guide
+---
+
+# AiHubMix Provider Configuration
+
+AiHubMix is an AI model aggregation platform that offers access to a variety of AI models through a unified OpenAI-compatible API. This guide will help you set up the AiHubMix provider in LobeHub.
+
+## Prerequisites
+
+Before using the AiHubMix API, you need to:
+
+1. **Create an AiHubMix Account**
+ - Visit [AiHubMix](https://lobe.li/MZmv94N)
+ - Sign up for an account
+
+2. **Obtain an API Key**
+ - Log in to your AiHubMix dashboard
+ - Navigate to the API settings
+ - Generate an API key for use with LobeHub
+
+## Configuration
+
+### Environment Variables
+
+Add the following environment variable to your `.env` file:
+
+```bash
+# AiHubMix API Key (required)
+AIHUBMIX_API_KEY=your_aihubmix_api_key
+```
+
+### Available Models
+
+AiHubMix provides access to a variety of popular AI models, including:
+
+- **GPT-4o Mini** – A cost-effective lightweight model from OpenAI
+- **GPT-4o** – OpenAI’s flagship multimodal model
+- **Claude 3.5 Sonnet** – Anthropic’s advanced reasoning model
+- **Claude 3.5 Haiku** – A fast and efficient Claude model
+- **Gemini Pro 1.5** – Google’s model with long-context support
+- **DeepSeek V3** – A model with strong reasoning capabilities
+
+## How to Use
+
+1. **Configure the API Key**
+ - Set your AiHubMix API key in the environment variables
+ - Restart your LobeHub instance
+
+2. **Select a Model**
+ - Go to LobeHub settings
+ - Navigate to the Language Model section
+ - Choose AiHubMix as your provider
+ - Select a model from the available options
+
+3. **Start a Conversation**
+ - Create a new conversation
+ - Select an AiHubMix model
+ - Begin chatting
+
+## Features
+
+- **Multi-Model Access**: Access a variety of AI models through a single API
+- **OpenAI-Compatible**: Uses the standard OpenAI API format
+- **Function Calling**: Supports function calling for compatible models
+- **Vision Capabilities**: Some models support image analysis
+- **Model Discovery**: Automatically fetches the list of available models
+
+## Troubleshooting
+
+### Common Issues
+
+1. **401 Unauthorized Error**
+ - Verify that your API key is correct
+ - Ensure the API key has the necessary permissions
+ - Check if your account has sufficient credits
+
+2. **Model Unavailable**
+ - Some models may have usage restrictions
+ - Refer to the AiHubMix documentation for model availability
+ - Confirm that your account tier supports the requested model
+
+3. **Rate Limiting**
+ - AiHubMix may enforce rate limits based on your subscription plan
+ - Consider upgrading your plan for higher limits
+
+## Support
+
+For additional help:
+
+- Visit the [AiHubMix Documentation](https://docs.aihubmix.com/)
+- Browse the [Model List](https://aihubmix.com/models)
+- Contact the AiHubMix support team for API-related issues
diff --git a/docs/usage/providers/aihubmix.zh-CN.mdx b/docs/usage/providers/aihubmix.zh-CN.mdx
index 586c082b2c..6817ee90ee 100644
--- a/docs/usage/providers/aihubmix.zh-CN.mdx
+++ b/docs/usage/providers/aihubmix.zh-CN.mdx
@@ -1,6 +1,6 @@
---
title: AiHubMix 提供商配置
-description: 学习如何在 LobeChat 中配置和使用 AiHubMix 提供商
+description: 学习如何在 LobeHub 中配置和使用 AiHubMix 提供商
tags:
- AiHubMix
- 提供商配置
@@ -9,7 +9,7 @@ tags:
# AiHubMix 提供商配置
-AiHubMix 是一个 AI 模型聚合平台，通过统一的 OpenAI 兼容 API 接口提供多种 AI 模型的访问服务。本指南将帮助您在 LobeChat 中设置 AiHubMix 提供商。
+AiHubMix 是一个 AI 模型聚合平台，通过统一的 OpenAI 兼容 API 接口提供多种 AI 模型的访问服务。本指南将帮助您在 LobeHub 中设置 AiHubMix 提供商。
## 前置条件
@@ -22,7 +22,7 @@ AiHubMix 是一个 AI 模型聚合平台，通过统一的 OpenAI 兼容 API 接
2. **获取 API 密钥**
- 登录您的 AiHubMix 控制台
- 导航到 API 设置
- - 生成用于 LobeChat 的 API 密钥
+ - 生成用于 LobeHub 的 API 密钥
## 配置
@@ -50,10 +50,10 @@ AiHubMix 提供多种热门 AI 模型的访问，包括：
1. **配置 API 密钥**
- 在环境变量中设置您的 AiHubMix API 密钥
- - 重启您的 LobeChat 实例
+ - 重启您的 LobeHub 实例
2. **选择模型**
- - 进入 LobeChat 设置
+ - 进入 LobeHub 设置
- 导航到语言模型
- 选择 AiHubMix 作为您的提供商
- 从可用模型中选择
diff --git a/docs/usage/providers/anthropic.mdx b/docs/usage/providers/anthropic.mdx
index 49a403e9d9..2472cc6f40 100644
--- a/docs/usage/providers/anthropic.mdx
+++ b/docs/usage/providers/anthropic.mdx
@@ -1,55 +1,52 @@
---
-title: Using Anthropic Claude API Key in LobeChat
+title: Using the Anthropic Claude API Key in LobeHub
description: >-
- Learn how to integrate Anthropic Claude API in LobeChat to enhance your AI assistant capabilities. Support Claude 3.5 sonnet / Claude 3 Opus / Claude 3 haiku
-
+ Learn how to configure and use the Anthropic Claude API in LobeHub, including
+ Claude 3.5 Sonnet, Claude 3 Opus, and Claude 3 Haiku.
tags:
- Anthropic Claude
- - API Key
- - AI assistant
- - Web UI
+ - API
+ - WebUI
+ - AI Assistant
---
-# Using Anthropic Claude in LobeChat
+# Using Anthropic Claude in LobeHub
-
- ### Step 1: Obtain Anthropic Claude API Key
+ ### Step 1: Get Your Anthropic Claude API Key
- - Create an [Anthropic Claude API](https://www.anthropic.com/api) account.
- - Get your [API key](https://console.anthropic.com/settings/keys).
+ - Create an [Anthropic Claude API](https://www.anthropic.com/api) account
+ - Retrieve your [API key](https://console.anthropic.com/settings/keys)
-
- The Claude API currently offers $5 of free credits, but it is only available in certain specific
- countries/regions. You can go to Dashboard > Claim to see if it is applicable to your
- country/region.
+ Claude API currently offers $5 in free credits. However, this is only available in select countries/regions. You can check your eligibility by visiting Dashboard > Claim.
- - Set up your billing for the API key to work on [https://console.anthropic.com/settings/plans](https://console.anthropic.com/settings/plans) (choose the "Build" plan so you can add credits and only pay for usage).
+ - Set up your billing to activate the API key at [https://console.anthropic.com/settings/plans](https://console.anthropic.com/settings/plans) (Choose the "Developer" plan to add credits and pay only for what you use)
-
- During usage, you may need to pay the API service provider. Please refer to Anthropic Claude's
- relevant pricing policies.
+ You may incur charges from the API provider during usage. Please refer to Anthropic Claude’s pricing policy for more details.
-You can now engage in conversations using the models provided by Anthropic Claude in LobeChat.
+That's it! You’re now ready to use Anthropic Claude models in LobeHub for conversations.
diff --git a/docs/usage/providers/anthropic.zh-CN.mdx b/docs/usage/providers/anthropic.zh-CN.mdx
index 34abda173f..34d817f20c 100644
--- a/docs/usage/providers/anthropic.zh-CN.mdx
+++ b/docs/usage/providers/anthropic.zh-CN.mdx
@@ -1,8 +1,8 @@
---
-title: 在 LobeChat 中使用 Anthropic Claude API Key
+title: 在 LobeHub 中使用 Anthropic Claude API Key
description: >-
- 学习如何在 LobeChat 中配置和使用 Anthropic Claude API， Claude 3.5 sonnet / Claude 3 Opus / Claude 3 haiku
-
+ 学习如何在 LobeHub 中配置和使用 Anthropic Claude API， Claude 3.5 sonnet / Claude 3 Opus /
+ Claude 3 haiku
tags:
- Anthropic Claude
- API
@@ -10,11 +10,11 @@ tags:
- AI助手
---
-# 在 LobeChat 中使用 Anthropic Claude
+# 在 LobeHub 中使用 Anthropic Claude
-
### 步骤一：获取 Anthropic Claude API 密钥
@@ -22,7 +22,7 @@ Anthropic Claude API 现在可供所有人使用，本文档将指导你如何
- 创建一个 [Anthropic Claude API](https://www.anthropic.com/api) 帐户
- 获取您的 [API 密钥](https://console.anthropic.com/settings/keys)
-
Claude API 现在提供 5 美元的免费积分，但是，它仅适用于某些特定国家 / 地区，您可以转到 Dashboard >
@@ -31,23 +31,23 @@ Anthropic Claude API 现在可供所有人使用，本文档将指导你如何
- 设置您的账单，让 API 密钥在 [https://console.anthropic.com/settings/plans](https://console.anthropic.com/settings/plans) 上工作（选择 “生成” 计划，以便您可以添加积分并仅为使用量付费）
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Anthropic Claude 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Anthropic Claude 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Anthropic Claude 提供的模型进行对话了。
diff --git a/docs/usage/providers/azure.mdx b/docs/usage/providers/azure.mdx
index 57a7316103..8091ccb099 100644
--- a/docs/usage/providers/azure.mdx
+++ b/docs/usage/providers/azure.mdx
@@ -1,57 +1,52 @@
---
-title: Using Azure OpenAI API Key in LobeChat
+title: Using Azure OpenAI API Key in LobeHub
description: >-
- Learn how to integrate and configure Azure OpenAI in LobeChat to enhance your AI assistant capabilities. Follow these steps to obtain the API key, configure the settings, and start engaging in conversations.
-
+ Learn how to configure and use Azure OpenAI models in LobeHub, including how
+ to obtain your API key and select a model.
tags:
- Azure OpenAI
- - AI assistant
- - API key
- - Configuration
- - Conversation models
+ - API Key
+ - Web UI
---
-# Using Azure OpenAI in LobeChat
+# Using Azure OpenAI in LobeHub
-
- ### Step 1: Obtain Azure OpenAI API Key
+ ### Step 1: Obtain Your Azure OpenAI API Key
- - If you haven't registered yet, you need to create an [Azure OpenAI account](https://oai.azure.com/).
+ - If you haven’t already, you’ll need to sign up for an [Azure OpenAI account](https://oai.azure.com/).
-
- During usage, you may need to pay the API service provider. Please refer to Azure OpenAI's
- relevant pricing policies.
+ You may incur charges from the API provider while using the service. Please refer to Azure OpenAI’s pricing policy for more details.
-Now you can engage in conversations using the models provided by Azure OpenAI in LobeChat.
+And that’s it! You’re now ready to start chatting with models powered by Azure OpenAI in LobeHub.
diff --git a/docs/usage/providers/azure.zh-CN.mdx b/docs/usage/providers/azure.zh-CN.mdx
index bbb65cd1b3..fc4d8cc5dd 100644
--- a/docs/usage/providers/azure.zh-CN.mdx
+++ b/docs/usage/providers/azure.zh-CN.mdx
@@ -1,50 +1,50 @@
---
-title: 在 LobeChat 中使用 Azure OpenAI API Key
-description: 学习如何在 LobeChat 中配置和使用 Azure OpenAI 模型进行对话，包括获取 API 密钥和选择模型。
+title: 在 LobeHub 中使用 Azure OpenAI API Key
+description: 学习如何在 LobeHub 中配置和使用 Azure OpenAI 模型进行对话，包括获取 API 密钥和选择模型。
tags:
- Azure OpenAI
- API Key
- Web UI
---
-# 在 LobeChat 中使用 Azure OpenAI
+# 在 LobeHub 中使用 Azure OpenAI
-
### 步骤一：获取 Azure OpenAI API 密钥
- 如果尚未注册，则必须注册 [Azure OpenAI 帐户](https://oai.azure.com/)。
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Azure OpenAI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Azure OpenAI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Azure OpenAI 提供的模型进行对话了。
diff --git a/docs/usage/providers/azureai.mdx b/docs/usage/providers/azureai.mdx
index 68df568071..c099d7d92b 100644
--- a/docs/usage/providers/azureai.mdx
+++ b/docs/usage/providers/azureai.mdx
@@ -1,71 +1,71 @@
---
-title: Using Azure AI API Key in LobeChat
-description: Learn how to configure and use Azure AI models in LobeChat, get the API key, and start a conversation.
+title: Using Azure AI API Key in LobeHub
+description: >-
+ Learn how to configure and use Azure AI models in LobeHub, obtain your API
+ key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Azure AI
- API Key
- Web UI
---
-# Using Azure AI in LobeChat
+# Using Azure AI in LobeHub
-
- ### Step 1: Deploy Azure AI Project and Model
+ ### Step 1: Deploy an Azure AI Project and Model
- - First, visit [Azure AI Foundry](https://ai.azure.com/) and complete the registration and login process.
- - After logging in, select `Browse models` on the homepage.
+ - First, visit [Azure AI Foundry](https://ai.azure.com/) and sign up or log in.
+ - Once logged in, go to the homepage and select `Browse Models`.
-
- For detailed configuration of Azure AI Foundry, please refer to the [official
- documentation](https://learn.microsoft.com/azure/ai-foundry/model-inference/).
+ For detailed configuration of Azure AI Foundry, please refer to the [official documentation](https://learn.microsoft.com/azure/ai-foundry/model-inference/).
- ### Step 2: Obtain the Model's API Key and Endpoint
+ ### Step 2: Retrieve the Model's API Key and Endpoint
- - In the details of the deployed model, you can find the Endpoint and API Key information.
- - Copy and save the obtained information.
+ - In the deployed model's details page, you can find the Endpoint and API Key.
+ - Copy and securely save this information.
-
- For the Endpoint, you only need to fill in the first part:
- `https://xxxxxx.services.ai.azure.com/models`.
+ Only enter the base part of the Endpoint, e.g., `https://xxxxxx.services.ai.azure.com/models`.
- - Choose an Azure AI model for your assistant and start the conversation.
+ - Select an Azure AI model for your assistant to start chatting.
-
- You may need to pay the API service provider for usage. Please refer to Azure AI's relevant pricing policies.
+ You may incur charges from the API service provider during usage. Please refer to Azure AI's pricing policy for more details.
-Now you can use the models provided by Azure AI in LobeChat for conversations.
+That's it! You're now ready to use Azure AI models for conversations in LobeHub.
diff --git a/docs/usage/providers/azureai.zh-CN.mdx b/docs/usage/providers/azureai.zh-CN.mdx
index e8ae2b9dee..52258cd059 100644
--- a/docs/usage/providers/azureai.zh-CN.mdx
+++ b/docs/usage/providers/azureai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Azure AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Azure AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 Azure AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Azure AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- Azure AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Azure AI
+# 在 LobeHub 中使用 Azure AI
-
### 步骤一：部署 Azure AI 项目以及模型
@@ -22,16 +22,16 @@ tags:
- 首先，访问[Azure AI Foundry](https://ai.azure.com/)并完成注册登录
- 登录后在首页选择`浏览模型`
-
Azure AI Foundry
@@ -43,14 +43,14 @@ tags:
- 在已部署的模型详情里，可以查询到 Endpoint 以及 API Key 信息
- 复制并保存好获取的信息
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Azure AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Azure AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Azure AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/baichuan.mdx b/docs/usage/providers/baichuan.mdx
index 2988404faa..20774d3801 100644
--- a/docs/usage/providers/baichuan.mdx
+++ b/docs/usage/providers/baichuan.mdx
@@ -1,45 +1,45 @@
---
-title: Using Baichuan API Key in LobeChat
+title: Using Baichuan API Key in LobeHub
description: >-
- Learn how to integrate Baichuan AI into LobeChat for enhanced conversational experiences. Follow the steps to configure Baichuan AI and start using its models.
-
+ Learn how to configure and use Baichuan's API key in LobeHub to start chatting
+ and interacting.
tags:
- - LobeChat
+ - LobeHub
- Baichuan
+ - Baichuan AI
- API Key
- Web UI
---
-# Using Baichuan in LobeChat
+# Using Baichuan in LobeHub
-
- ### Step 1: Obtain Baichuan Intelligent API Key
+ ### Step 1: Obtain a Baichuan AI API Key
- - Create a [Baichuan Intelligent](https://platform.baichuan-ai.com/homePage) account
- - Create and obtain an [API key](https://platform.baichuan-ai.com/console/apikey)
+ - Create a [Baichuan AI](https://platform.baichuan-ai.com/homePage) account
+ - Generate and retrieve your [API Key](https://platform.baichuan-ai.com/console/apikey)
-
- During usage, you may need to pay the API service provider, please refer to Baichuan's relevant
- pricing policies.
+ You may need to pay for API usage depending on your usage. Please refer to Baichuan's pricing policy for more details.
-You can now use the models provided by Baichuan for conversation in LobeChat.
+That's it! You're now ready to use Baichuan-powered models in LobeHub for conversations.
diff --git a/docs/usage/providers/baichuan.zh-CN.mdx b/docs/usage/providers/baichuan.zh-CN.mdx
index 5cb0c99646..abe1e8df8b 100644
--- a/docs/usage/providers/baichuan.zh-CN.mdx
+++ b/docs/usage/providers/baichuan.zh-CN.mdx
@@ -1,19 +1,19 @@
---
-title: 在 LobeChat 中使用百川 API Key
-description: 学习如何在 LobeChat 中配置和使用百川的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用百川 API Key
+description: 学习如何在 LobeHub 中配置和使用百川的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 百川
- 百川智能
- API密钥
- Web UI
---
-# 在 LobeChat 中使用百川
+# 在 LobeHub 中使用百川
-
### 步骤一：获取百川智能 API 密钥
@@ -21,23 +21,23 @@ tags:
- 创建一个[百川智能](https://platform.baichuan-ai.com/homePage)账户
- 创建并获取 [API 密钥](https://platform.baichuan-ai.com/console/apikey)
-
在使用过程中你可能需要向 API 服务提供商付费，请参考百川的相关费用政策。
-至此你已经可以在 LobeChat 中使用百川提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用百川提供的模型进行对话了。
diff --git a/docs/usage/providers/bedrock.mdx b/docs/usage/providers/bedrock.mdx
index f782149c5b..8643daf7fe 100644
--- a/docs/usage/providers/bedrock.mdx
+++ b/docs/usage/providers/bedrock.mdx
@@ -1,89 +1,89 @@
---
-title: Using Amazon Bedrock API Key in LobeChat
+title: Using Amazon Bedrock API Key in LobeHub
description: >-
- Learn how to integrate Amazon Bedrock models into LobeChat for AI-powered conversations. Follow these steps to grant access, obtain API keys, and configure Amazon Bedrock.
-
+ Learn how to configure and use Amazon Bedrock, a fully managed foundation
+ model API service, in LobeHub to start chatting.
tags:
- Amazon Bedrock
- - Claude 3.5 sonnect
+ - Claude 3.5 Sonnet
- API keys
- Claude 3 Opus
- Web UI
---
-# Using Amazon Bedrock in LobeChat
+# Using Amazon Bedrock in LobeHub
-
- ### Step 1: Grant Access to Amazon Bedrock Models in AWS
+ ### Step 1: Enable Access to Amazon Bedrock Models in AWS
- - Access and log in to the [AWS Console](https://console.aws.amazon.com/)
- - Search for `bedrock` and enter the `Amazon Bedrock` service
+ - Visit and log in to the [AWS Console](https://console.aws.amazon.com/)
+ - Search for "Bedrock" and navigate to the `Amazon Bedrock` service
- Some models may require additional information from you
+
+ Some models may require you to provide additional information.
+
### Step 2: Obtain API Access Keys
- - Continue searching for IAM in the AWS console and enter the IAM service
+ - In the AWS Console, search for IAM and go to the IAM service
-
- Please securely store the keys as they will only be shown once. If you lose them accidentally, you
- will need to create a new access key.
+ Store your keys securely, as they will only be shown once. If you lose them, you’ll need to generate new access keys.
- ### Step 3: Configure Amazon Bedrock in LobeChat
+ ### Step 3: Configure Amazon Bedrock in LobeHub
- - Access the `Settings` interface in LobeChat
- - Find the setting for `Amazon Bedrock` under `AI Service Provider` and open it
+ - Open the `Settings` panel in LobeHub
+ - Under `AI Providers`, find and enable the `Amazon Bedrock` option
-
- You may incur charges while using the API service, please refer to Amazon Bedrock's pricing
- policy.
+ You may incur charges while using the API. Please refer to Amazon Bedrock’s pricing policy for details.
-You can now engage in conversations using the models provided by Amazon Bedrock in LobeChat.
+You’re all set! You can now start chatting in LobeHub using models provided by Amazon Bedrock.
diff --git a/docs/usage/providers/bedrock.zh-CN.mdx b/docs/usage/providers/bedrock.zh-CN.mdx
index 3ea7a4df52..4b7b8c98f9 100644
--- a/docs/usage/providers/bedrock.zh-CN.mdx
+++ b/docs/usage/providers/bedrock.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 Amazon Bedrock API Key
-description: 学习如何在 LobeChat 中配置和使用 Amazon Bedrock，一个完全托管的基础模型API服务，以便开始对话。
+title: 在 LobeHub 中使用 Amazon Bedrock API Key
+description: 学习如何在 LobeHub 中配置和使用 Amazon Bedrock，一个完全托管的基础模型API服务，以便开始对话。
tags:
- Amazon Bedrock
- Claude 3.5 sonnect
@@ -9,13 +9,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Amazon Bedrock
+# 在 LobeHub 中使用 Amazon Bedrock
-
### 步骤一：在 AWS 中打开 Amazon Bedrock 模型的访问权限
@@ -23,15 +23,15 @@ Amazon Bedrock 是一个完全托管的基础模型 API 服务，允许用户通
- 访问并登录 [AWS Console](https://console.aws.amazon.com/)
- 搜索 beckrock 并进入 `Amazon Bedrock` 服务
- 某些模型可能需要你提供额外的信息
@@ -39,47 +39,47 @@ Amazon Bedrock 是一个完全托管的基础模型 API 服务，允许用户通
- 继续在 AWS console 中搜索 IAM，进入 IAM 服务
-
请安全地存储密钥，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新访问密钥。
- ### 步骤三：在 LobeChat 中配置 Amazon Bedrock
+ ### 步骤三：在 LobeHub 中配置 Amazon Bedrock
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到`Amazon Bedrock`的设置项并打开
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Amazon Bedrock 的费用政策。
-至此你已经可以在 LobeChat 中使用 Amazone Bedrock 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Amazone Bedrock 提供的模型进行对话了。
diff --git a/docs/usage/providers/bfl.mdx b/docs/usage/providers/bfl.mdx
index 1ecc1c417e..3f71a0dcb0 100644
--- a/docs/usage/providers/bfl.mdx
+++ b/docs/usage/providers/bfl.mdx
@@ -1,8 +1,8 @@
---
-title: Using Black Forest Labs API Key in LobeChat
+title: Using Black Forest Labs API Key in LobeHub
description: >-
- Learn how to integrate Black Forest Labs API Key in LobeChat for AI image generation using advanced models and high-quality output.
-
+ Learn how to configure and use the Black Forest Labs API Key in LobeHub to
+ generate high-quality AI images with advanced models.
tags:
- Black Forest Labs
- Image Generation
@@ -10,21 +10,21 @@ tags:
- Web UI
---
-# Using Black Forest Labs in LobeChat
+# Using Black Forest Labs in LobeHub
-
- ### Step 1: Obtain Black Forest Labs API Key
+ ### Step 1: Get Your Black Forest Labs API Key
- - Register for a [Black Forest Labs account](https://auth.bfl.ai/).
- - Navigate to the [API Keys dashboard](https://dashboard.bfl.ai/api/keys) and click **Add Key** to generate a new API key.
- - Copy the generated API key and keep it secure; it will only be shown once.
+ - Sign up for a [Black Forest Labs](https://auth.bfl.ai/) account;
+ - Go to the [API Keys Console](https://dashboard.bfl.ai/api/keys) and click **Add Key** to create a new API key;
+ - Copy and securely save the generated API key — it will only be shown once.
- During usage, you may incur charges according to Black Forest Labs's pricing policy. Please review Black Forest Labs's
- official pricing before heavy usage.
+ Please note that usage may incur charges from Black Forest Labs. Be sure to review their official pricing policy before making extensive API calls.
-You can now use Black Forest Labs's advanced image generation models directly within LobeChat to create stunning visual content.
+And that’s it! You’re now ready to create stunning visual content in LobeHub using the advanced image generation models provided by Black Forest Labs.
diff --git a/docs/usage/providers/bfl.zh-CN.mdx b/docs/usage/providers/bfl.zh-CN.mdx
index dd4b2398fc..73c70564a4 100644
--- a/docs/usage/providers/bfl.zh-CN.mdx
+++ b/docs/usage/providers/bfl.zh-CN.mdx
@@ -1,8 +1,6 @@
---
-title: 在 LobeChat 中使用 Black Forest Labs API Key
-description: >-
- 学习如何在 LobeChat 中配置和使用 Black Forest Labs API Key，使用先进模型进行高质量 AI 图像生成。
-
+title: 在 LobeHub 中使用 Black Forest Labs API Key
+description: 学习如何在 LobeHub 中配置和使用 Black Forest Labs API Key，使用先进模型进行高质量 AI 图像生成。
tags:
- Black Forest Labs
- 图像生成
@@ -10,11 +8,11 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Black Forest Labs
+# 在 LobeHub 中使用 Black Forest Labs
-
### 步骤一：获取 Black Forest Labs API Key
@@ -47,9 +45,9 @@ tags:
}
/>
- ### 步骤二：在 LobeChat 中配置 Black Forest Labs
+ ### 步骤二：在 LobeHub 中配置 Black Forest Labs
- - 访问 LobeChat 的 `设置` 页面；
+ - 访问 LobeHub 的 `设置` 页面；
- 在 `AI服务商` 下找到 `Black Forest Labs` 的设置项；
-至此，你已经可以在 LobeChat 中使用 Black Forest Labs 提供的先进图像生成模型来创作精美的视觉内容了。
+至此，你已经可以在 LobeHub 中使用 Black Forest Labs 提供的先进图像生成模型来创作精美的视觉内容了。
diff --git a/docs/usage/providers/cloudflare.mdx b/docs/usage/providers/cloudflare.mdx
index 7085c0e7f1..d7d4a79884 100644
--- a/docs/usage/providers/cloudflare.mdx
+++ b/docs/usage/providers/cloudflare.mdx
@@ -1,8 +1,10 @@
---
-title: Using Cloudflare Workers AI in LobeChat
-description: Learn how to integrate and utilize Cloudflare Workers AI Models in LobeChat.
+title: Using Cloudflare Workers AI in LobeHub
+description: >-
+ Learn how to configure and use the Cloudflare Workers AI API Key in LobeHub to
+ start chatting and interacting.
tags:
- - LobeChat
+ - LobeHub
- Cloudflare
- Workers AI
- Provider
@@ -10,51 +12,49 @@ tags:
- Web UI
---
-# Using Cloudflare Workers AI in LobeChat
+# Using Cloudflare Workers AI in LobeHub
-
- ### Step 1: Obtain Your Cloudflare Workers AI API Key
+ ### Step 1: Obtain a Cloudflare Workers AI API Key
- Visit the [Cloudflare website](https://www.cloudflare.com/) and sign up for an account.
- - Log in to the [Cloudflare dashboard](https://dash.cloudflare.com/).
- - In the left-hand menu, locate the `AI` > `Workers AI` option.
+ - Log in to the [Cloudflare Dashboard](https://dash.cloudflare.com/).
+ - In the left-hand menu, navigate to `AI` > `Workers AI`.
-
- - Please store your API token securely, as it will only be displayed once. If you accidentally
- lose it, you will need to create a new token.
+ - Be sure to store your API token securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure Cloudflare Workers AI in LobeChat
+ ### Step 2: Configure Cloudflare Workers AI in LobeHub
- - Go to the `Settings` interface in LobeChat.
- - Under `AI Service Provider`, find the `Cloudflare` settings.
+ - Open the `Settings` panel in LobeHub.
+ - Under `AI Providers`, locate the `Cloudflare` configuration section.
-
- You may incur charges while using the API service, please refer to Cloudflare's pricing policy for
- details.
+ You may incur charges from the API provider during usage. Please refer to Cloudflare’s pricing policy for details.
-At this point, you can start conversing with the model provided by Cloudflare Workers AI in LobeChat.
+You’re all set! You can now start using Cloudflare Workers AI models for conversations in LobeHub.
diff --git a/docs/usage/providers/cloudflare.zh-CN.mdx b/docs/usage/providers/cloudflare.zh-CN.mdx
index 73073a7cf6..c49ef36198 100644
--- a/docs/usage/providers/cloudflare.zh-CN.mdx
+++ b/docs/usage/providers/cloudflare.zh-CN.mdx
@@ -1,8 +1,8 @@
---
-title: 在 LobeChat 中使用 Cloudflare Workers AI
-description: 学习如何在 LobeChat 中配置和使用 Cloudflare Workers AI 的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 Cloudflare Workers AI
+description: 学习如何在 LobeHub 中配置和使用 Cloudflare Workers AI 的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- Cloudflare
- Workers AI
- 供应商
@@ -10,13 +10,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Cloudflare Workers AI
+# 在 LobeHub 中使用 Cloudflare Workers AI
-
### 步骤一：获取 Cloudflare Workers AI 的 API Key
@@ -25,34 +25,34 @@ tags:
- 登录 [Cloudflare 控制台](https://dash.cloudflare.com/).
- 在左侧的菜单中找到 `AI` > `Workers AI` 选项。
-
- 请安全地存储 API 令牌，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新令牌。
- ### 步骤二：在 LobeChat 中配置 Cloudflare Workers AI
+ ### 步骤二：在 LobeHub 中配置 Cloudflare Workers AI
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `Cloudflare` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Cloudflare 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Cloudflare Workers AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Cloudflare Workers AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/comfyui.mdx b/docs/usage/providers/comfyui.mdx
index 1825c25e85..309d156365 100644
--- a/docs/usage/providers/comfyui.mdx
+++ b/docs/usage/providers/comfyui.mdx
@@ -1,6 +1,20 @@
---
-title: Using ComfyUI for Image Generation in LobeChat
-description: Learn how to configure and use ComfyUI service in LobeChat, supporting FLUX series models for high-quality image generation and editing features
+title: ''
+description: >-
+ Learn to configure ComfyUI in LobeHub for high-quality image generation and
+ editing.
+tags:
+ - ComfyUI
+ - FLUX
+ - Image Generation
+ - AI Image Editing
+ - Text-to-Image
+---
+
+````markdown
+---
+title: Using ComfyUI in LobeHub for Image Generation
+description: Learn how to configure and use the ComfyUI service in LobeHub to support high-quality image generation and editing with the FLUX model series.
tags:
- ComfyUI
- FLUX
@@ -9,54 +23,54 @@ tags:
- AI Image Generation
---
-# Using ComfyUI in LobeChat
+# Using ComfyUI in LobeHub
-
- Image editing functionality requires uploading the original image first, then describing the modifications you want to make.
+ Image editing requires uploading the original image first, followed by a description of the desired changes.
## Authentication Configuration Guide
-ComfyUI supports four authentication methods. Choose the appropriate method based on your server configuration and security requirements:
+ComfyUI supports four authentication methods. Choose the one that best fits your server setup and security needs:
### No Authentication (none)
-**Use Cases**:
+**Best for**:
-- Local development environment (localhost)
-- Internal network with trusted users
-- Personal single-machine deployment
+- Local development (localhost)
+- Trusted internal networks
+- Personal single-machine setups
**Configuration**:
```yaml
Authentication Type: None
-Server Address: http://localhost:8188
+Server Address: http://localhost:8000
```
### Basic Authentication (basic)
-**Use Cases**:
+**Best for**:
-- Deployments using Nginx reverse proxy
-- Team internal use requiring basic access control
+- Deployments behind Nginx reverse proxy
+- Internal team use with basic access control
-**Configuration**:
+**Setup**:
-1. **Create User Password**:
+1. **Create Username and Password**:
```bash
# Install apache2-utils
@@ -124,21 +138,21 @@ sudo apt-get install apache2-utils
sudo htpasswd -c /etc/nginx/.htpasswd admin
```
-2. **LobeChat Configuration**:
+2. **LobeHub Configuration**:
```yaml
-Authentication Type: Basic Authentication
-Server Address: http://your-domain.com
+Authentication Type: Basic
+Server Address: https://your-domain.com
Username: admin
Password: your_secure_password
```
### Bearer Token (bearer)
-**Use Cases**:
+**Best for**:
-- API-driven application integration
-- Enterprise environments requiring Token authentication
+- API-driven integrations
+- Enterprise environments requiring token-based auth
**Generate Token**:
@@ -156,41 +170,41 @@ token = jwt.encode(payload, secret_key, algorithm='HS256')
print(f"Bearer Token: {token}")
```
-**LobeChat Configuration**:
+**LobeHub Configuration**:
```yaml
Authentication Type: Bearer Token
-Server Address: http://your-server:8188
-API Key: eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
+Server Address: https://your-domain.com
+API Key: example-eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...
```
### Custom Authentication (custom)
-**Use Cases**:
+**Best for**:
-- Integration with existing enterprise authentication systems
-- Systems requiring multiple authentication headers
+- Integrating with existing enterprise auth systems
+- Systems requiring multiple custom headers
-**LobeChat Configuration**:
+**LobeHub Configuration**:
```yaml
Authentication Type: Custom
-Server Address: http://your-server:8188
+Server Address: https://your-domain.com
Custom Headers:
{
"X-API-Key": "your_api_key",
- "X-Client-ID": "lobechat"
+ "X-Client-ID": "LobeHub"
}
```
-## Common Issues Resolution
+## Troubleshooting
### 1. How to Install Comfy-Manager
-Comfy-Manager is ComfyUI's extension manager that allows you to easily install and manage various nodes, models, and extensions.
+Comfy-Manager is an extension manager for ComfyUI that simplifies installing and managing nodes, models, and extensions.
- Please note during use:
-
- - FLUX Dev, Krea-dev, Kontext-dev models are for non-commercial use only
- - Generated content must comply with relevant laws and platform policies
- - Large model generation may take considerable time, please be patient
-
-
-## API Reference
-
-
- **智能模型选择**：LobeChat 会根据服务器上可用的模型文件自动选择最佳模型。您无需下载所有模型，系统会在可用模型中按优先级（官方 > 企业 > 社区）自动选择。
+ **智能模型选择**：LobeHub 会根据服务器上可用的模型文件自动选择最佳模型。您无需下载所有模型，系统会在可用模型中按优先级（官方 > 企业 > 社区）自动选择。
## 支持的模型
-LobeChat ComfyUI 集成采用配置驱动的架构，支持 **223 个模型**，提供从官方模型到社区优化版本的全覆盖。
+LobeHub ComfyUI 集成采用配置驱动的架构，支持 **223 个模型**，提供从官方模型到社区优化版本的全覆盖。
### FLUX 系列推荐参数
@@ -637,7 +637,7 @@ LobeChat ComfyUI 集成采用配置驱动的架构，支持 **223 个模型**，
-至此你已经可以在 LobeChat 中使用 ComfyUI 进行高质量的 AI 图像生成和编辑了。如果遇到问题，请参考故障排除部分或查阅 [ComfyUI 官方文档](https://github.com/comfyanonymous/ComfyUI)。
+至此你已经可以在 LobeHub 中使用 ComfyUI 进行高质量的 AI 图像生成和编辑了。如果遇到问题，请参考故障排除部分或查阅 [ComfyUI 官方文档](https://github.com/comfyanonymous/ComfyUI)。
diff --git a/docs/usage/providers/deepseek.mdx b/docs/usage/providers/deepseek.mdx
index 24f5f7f3b0..be33e6f7b8 100644
--- a/docs/usage/providers/deepseek.mdx
+++ b/docs/usage/providers/deepseek.mdx
@@ -1,64 +1,62 @@
---
-title: Using DeepSeek API Key in LobeChat
+title: Using DeepSeek API Key in LobeHub
description: >-
- Learn how to use DeepSeek-V2 in LobeChat, obtain API keys. Get started with DeepSeek integration now!
-
+ Learn how to configure and use the DeepSeek language model in LobeHub, obtain
+ your API key, and start chatting.
tags:
+ - LobeHub
- DeepSeek
- - LobeChat
- - DeepSeek-V2
+ - DeepSeek R1
- API Key
- Web UI
---
-# Using DeepSeek in LobeChat
+# Using DeepSeek in LobeHub
-
- ### Step 1: Obtain DeepSeek API Key
+ ### Step 1: Get Your DeepSeek API Key
- - First, you need to register and log in to the [DeepSeek](https://platform.deepseek.com/) open platform.
+ - First, sign up and log in to the [DeepSeek Open Platform](https://platform.deepseek.com/)
- New users will receive a free quota of 500M Tokens
+ New users currently receive 500M tokens for free.
- - Go to the `API keys` menu and click on `Create API Key`.
+ - Navigate to the `API keys` section and click `Create API Key`
-
- Please store the key securely as it will only appear once. If you accidentally lose it, you will
- need to create a new key.
+ Make sure to store your key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure DeepSeek in LobeChat
+ ### Step 2: Configure DeepSeek in LobeHub
- - Access the `App Settings` interface in LobeChat.
- - Find the setting for `DeepSeek` under `AI Service Provider`.
+ - Go to the `App Settings` page in LobeHub
+ - Under `AI Providers`, find the `DeepSeek` configuration section
-
- You may need to pay the API service provider during usage, please refer to DeepSeek's relevant
- pricing policies.
+ You may incur charges from the API provider during usage. Please refer to DeepSeek’s pricing policy for details.
-You can now engage in conversations using the models provided by Deepseek in LobeChat.
+And that’s it! You’re now ready to start chatting with DeepSeek-powered models in LobeHub.
diff --git a/docs/usage/providers/deepseek.zh-CN.mdx b/docs/usage/providers/deepseek.zh-CN.mdx
index 85f59698b7..653dc38fc1 100644
--- a/docs/usage/providers/deepseek.zh-CN.mdx
+++ b/docs/usage/providers/deepseek.zh-CN.mdx
@@ -1,21 +1,21 @@
---
-title: 在 LobeChat 中使用 DeepSeek API Key
-description: 学习如何在 LobeChat 中配置和使用 DeepSeek 语言模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 DeepSeek API Key
+description: 学习如何在 LobeHub 中配置和使用 DeepSeek 语言模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- DeepSeek
- DeepSeek R1
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 DeepSeek
+# 在 LobeHub 中使用 DeepSeek
-
### 步骤一：获取 DeepSeek API 密钥
@@ -26,35 +26,35 @@ tags:
- 进入 `API keys` 菜单，并点击 `创建 API Key`
-
请安全地存储密钥，因为它只会出现一次。如果你意外丢失它，您将需要创建一个新密钥。
- ### 步骤二：在 LobeChat 中配置 DeepSeek
+ ### 步骤二：在 LobeHub 中配置 DeepSeek
- - 访问 LobeChat 的 `应用设置`界面
+ - 访问 LobeHub 的 `应用设置`界面
- 在 `AI 服务商` 下找到 `DeepSeek` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 DeepSeek 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Deepseek 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Deepseek 提供的模型进行对话了。
diff --git a/docs/usage/providers/fal.mdx b/docs/usage/providers/fal.mdx
index 4087851bee..bd0893e8af 100644
--- a/docs/usage/providers/fal.mdx
+++ b/docs/usage/providers/fal.mdx
@@ -1,31 +1,31 @@
---
-title: Using Fal API Key in LobeChat
+title: Using Fal API Key in LobeHub
description: >-
- Learn how to integrate Fal API Key in LobeChat for AI image and video generation using cutting-edge models like FLUX, Kling, and more.
-
+ Learn how to configure and use the Fal API Key in LobeHub to generate
+ AI-powered images and videos with cutting-edge models like FLUX and Kling.
tags:
- - Fal AI
+ - Fal
- Image Generation
- Video Generation
- API Key
- Web UI
---
-# Using Fal in LobeChat
+# Using Fal in LobeHub
-
- ### Step 1: Obtain Fal API Key
+ ### Step 1: Obtain Your Fal API Key
- - Register for a [Fal.ai account](https://fal.ai/).
- - Navigate to [API Keys dashboard](https://fal.ai/dashboard/keys) and click **Add key** to create a new API key.
- - Copy the generated API key and keep it secure; it will only be shown once.
+ - Sign up for a [Fal.ai](https://fal.ai/) account;
+ - Go to the [API Keys Dashboard](https://fal.ai/dashboard/keys) and click **Add key** to create a new API key;
+ - Copy the generated API key and store it securely — it will only be shown once.
- During usage, you may incur charges according to Fal's pricing policy. Please review Fal's
- official pricing before heavy usage.
+ Please note that using Fal may incur charges. Be sure to review Fal’s official pricing policy before making extensive API calls.
-You can now use Fal's advanced image and video generation models directly within LobeChat to create stunning visual content.
+And that’s it! You’re now ready to create stunning visual content in LobeHub using Fal’s advanced image and video generation models.
diff --git a/docs/usage/providers/fal.zh-CN.mdx b/docs/usage/providers/fal.zh-CN.mdx
index 05155c42d2..ba4cea51cb 100644
--- a/docs/usage/providers/fal.zh-CN.mdx
+++ b/docs/usage/providers/fal.zh-CN.mdx
@@ -1,8 +1,6 @@
---
-title: 在 LobeChat 中使用 Fal API Key
-description: >-
- 学习如何在 LobeChat 中配置和使用 Fal API Key，使用 FLUX、Kling 等尖端模型进行 AI 图像和视频生成。
-
+title: 在 LobeHub 中使用 Fal API Key
+description: 学习如何在 LobeHub 中配置和使用 Fal API Key，使用 FLUX、Kling 等尖端模型进行 AI 图像和视频生成。
tags:
- Fal
- 图像生成
@@ -11,11 +9,11 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Fal
+# 在 LobeHub 中使用 Fal
-
### 步骤一：获取 Fal API Key
@@ -48,9 +46,9 @@ tags:
}
/>
- ### 步骤二：在 LobeChat 中配置 Fal
+ ### 步骤二：在 LobeHub 中配置 Fal
- - 访问 LobeChat 的 `设置` 页面；
+ - 访问 LobeHub 的 `设置` 页面；
- 在 `AI服务商` 下找到 `Fal` 的设置项；
-至此，你已经可以在 LobeChat 中使用 Fal 提供的先进图像和视频生成模型来创作精美的视觉内容了。
+至此，你已经可以在 LobeHub 中使用 Fal 提供的先进图像和视频生成模型来创作精美的视觉内容了。
diff --git a/docs/usage/providers/fireworksai.mdx b/docs/usage/providers/fireworksai.mdx
index 565fc25279..6ef8ac18fe 100644
--- a/docs/usage/providers/fireworksai.mdx
+++ b/docs/usage/providers/fireworksai.mdx
@@ -1,57 +1,55 @@
---
-title: Using Fireworks AI in LobeChat
+title: Using Fireworks AI in LobeHub
description: >-
- Learn how to integrate and utilize Fireworks AI's language model APIs in LobeChat.
-
+ Learn how to configure and use Fireworks AI's API Key in LobeHub to start
+ chatting and interacting.
tags:
- - LobeChat
+ - LobeHub
- Fireworks AI
- API Key
- Web UI
---
-# Using Fireworks AI in LobeChat
+# Using Fireworks AI in LobeHub
-
- ### Step 1: Obtain an API Key for Fireworks AI
+ ### Step 1: Obtain Your Fireworks AI API Key
- Log in to the [Fireworks.ai Console](https://fireworks.ai/account/api-keys)
- Navigate to the `User` page and click on `API Keys`
- Create a new API key
-
- Please store the key securely, as it will appear only once. If you accidentally lose it, you will
- need to create a new key.
+ Make sure to store your API key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure Fireworks AI in LobeChat
+ ### Step 2: Configure Fireworks AI in LobeHub
- - Access the `Settings` interface in LobeChat
- - Under `AI Service Provider`, locate the settings for `Fireworks AI`
+ - Go to the `Settings` page in LobeHub
+ - Under `AI Providers`, locate the settings for `Fireworks AI`
-
- Please note that you may need to pay fees to the API service provider during use; refer to
- Fireworks AI's pricing policy for details.
+ Please note that usage may incur charges from the API provider. Refer to Fireworks AI’s pricing policy for more details.
-You are now ready to use the models provided by Fireworks AI for conversations in LobeChat.
+And that’s it! You’re now ready to start using Fireworks AI models in LobeHub for conversations and interactions.
diff --git a/docs/usage/providers/fireworksai.zh-CN.mdx b/docs/usage/providers/fireworksai.zh-CN.mdx
index 647a51f0e9..e31a67104f 100644
--- a/docs/usage/providers/fireworksai.zh-CN.mdx
+++ b/docs/usage/providers/fireworksai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Fireworks AI
-description: 学习如何在 LobeChat 中配置和使用 Fireworks AI 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 Fireworks AI
+description: 学习如何在 LobeHub 中配置和使用 Fireworks AI 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- Fireworks AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Fireworks AI
+# 在 LobeHub 中使用 Fireworks AI
-
### 步骤一：获得 Fireworks AI 的 API Key
@@ -23,31 +23,31 @@ tags:
- 进入 `User` 页面，点击 `API Keys`
- 创建一个新的 API 密钥
-
请安全地存储密钥，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新密钥。
- ### 步骤二：在 LobeChat 中配置 Fireworks AI
+ ### 步骤二：在 LobeHub 中配置 Fireworks AI
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `Fireworks AI` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Fireworks AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Fireworks AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Fireworks AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/giteeai.mdx b/docs/usage/providers/giteeai.mdx
index 4d48cef369..ba5b14e103 100644
--- a/docs/usage/providers/giteeai.mdx
+++ b/docs/usage/providers/giteeai.mdx
@@ -1,58 +1,56 @@
---
-title: Using Gitee AI in LobeChat
+title: Using Gitee AI in LobeHub
description: >-
- Learn how to configure and use Gitee AI's API Key in LobeChat to start conversations and interactions.
-
+ Learn how to configure and use Gitee AI's API Key in LobeHub to start chatting
+ and interacting.
tags:
- - LobeChat
+ - LobeHub
- Gitee AI
- API Key
- Web UI
---
-# Using Gitee AI in LobeChat
+# Using Gitee AI in LobeHub
-
- ### Step 1: Obtain the Gitee AI API Key
+ ### Step 1: Obtain Your Gitee AI API Key
- Register and log in to the [Gitee AI official website](https://ai.gitee.com/)
- - Purchase and recharge `Serverless API` from your dashboard
+ - In the dashboard, purchase and top up the `Serverless API`
-
- Please keep the access token safe as it will only appear once. If you accidentally lose it, you
- will need to create a new one.
+ Make sure to save the access token shown in the pop-up window. It will only be displayed once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure Gitee AI in LobeChat
+ ### Step 2: Configure Gitee AI in LobeHub
- - Access the `Settings` page in LobeChat
- - Under `AI Service Provider`, find the settings for `Gitee AI`
+ - Go to the `Settings` page in LobeHub
+ - Under `AI Providers`, find the configuration section for `Gitee AI`
-
- During usage, you may need to make payments to the API service provider; please refer to Gitee
- AI's relevant pricing policy.
+ You may need to pay for API usage depending on your usage. Please refer to Gitee AI’s pricing policy for more details.
-Now you can start having conversations using the models provided by Gitee AI in LobeChat!
+And that’s it! You’re now ready to use Gitee AI models for conversations in LobeHub.
diff --git a/docs/usage/providers/giteeai.zh-CN.mdx b/docs/usage/providers/giteeai.zh-CN.mdx
index bf7d84fc70..5612358878 100644
--- a/docs/usage/providers/giteeai.zh-CN.mdx
+++ b/docs/usage/providers/giteeai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Gitee AI
-description: 学习如何在 LobeChat 中配置和使用 Gitee AI 的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 Gitee AI
+description: 学习如何在 LobeHub 中配置和使用 Gitee AI 的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- Gitee AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Gitee AI
+# 在 LobeHub 中使用 Gitee AI
-
### 步骤一：获取 Gitee AI 的 API 密钥
@@ -22,33 +22,33 @@ tags:
- 注册并登录 [Gitee AI 官网](https://ai.gitee.com/)
- 在工作台中购买并充值 `Serverless API`
-
妥善保存弹窗中的访问令牌，它只会出现一次，如果不小心丢失了，你需要重新创建一个访问令牌。
- ### 步骤二：在 LobeChat 中配置 Gitee AI
+ ### 步骤二：在 LobeHub 中配置 Gitee AI
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `Gitee AI` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Gitee AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Gitee AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Gitee AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/github.mdx b/docs/usage/providers/github.mdx
index 80877584a0..cf706be5b6 100644
--- a/docs/usage/providers/github.mdx
+++ b/docs/usage/providers/github.mdx
@@ -1,67 +1,69 @@
---
-title: Using GitHub Models in LobeChat
-description: Learn how to integrate and utilize GitHub Models in LobeChat.
+title: Using GitHub Models in LobeHub
+description: >-
+ Learn how to configure and use GitHub's API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
+ - LobeHub
- GitHub
- GitHub Models
- API Key
- Web UI
---
-# Using GitHub Models in LobeChat
+# Using GitHub Models in LobeHub
-
- These limits are subject to change at any time. For specific information, please refer to the
- [GitHub Official
- Documentation](https://docs.github.com/en/github-models/prototyping-with-ai-models#rate-limits).
+ These limits are subject to change. For the most up-to-date information, please refer to the [official GitHub documentation](https://docs.github.com/en/github-models/prototyping-with-ai-models#rate-limits).
---
-## Configuration Guide for GitHub Models
+## GitHub Models Configuration Guide
### Step 1: Obtain a GitHub Access Token
- - Log in to GitHub and open the [Access Tokens](https://github.com/settings/tokens) page.
+ - Log in to GitHub and navigate to the [Personal Access Tokens](https://github.com/settings/tokens) page.
- Create and configure a new access token.
-
- - During the testing phase of GitHub Models, users must apply to join the [waitlist](https://github.com/marketplace/models/waitlist/join) in order to gain access.
+ - During the GitHub Models testing phase, you must apply to join the [waitlist](https://github.com/marketplace/models/waitlist/join) to gain access.
- - Please store the access token securely, as it will only be displayed once. If you accidentally lose it, you will need to create a new token.
+ ```
+ - Be sure to store your access token securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
+ ```
- ### Step 2: Configure GitHub Models in LobeChat
+ ### Step 2: Configure GitHub Models in LobeHub
- - Navigate to the `Settings` interface in LobeChat.
- - Under `AI Service Provider`, find the GitHub settings.
+ - Open the `Settings` panel in LobeHub.
+ - Under `AI Providers`, locate the `GitHub` configuration section.
-
-You are now ready to use the models provided by GitHub for conversations within LobeChat.
+And that’s it! You’re now ready to start using GitHub-provided models in LobeHub for conversations and interactions.
diff --git a/docs/usage/providers/github.zh-CN.mdx b/docs/usage/providers/github.zh-CN.mdx
index 689a978007..04a11b9f14 100644
--- a/docs/usage/providers/github.zh-CN.mdx
+++ b/docs/usage/providers/github.zh-CN.mdx
@@ -1,27 +1,27 @@
---
-title: 在 LobeChat 中使用 GitHub Models
-description: 学习如何在 LobeChat 中配置和使用 GitHub 的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 GitHub Models
+description: 学习如何在 LobeHub 中配置和使用 GitHub 的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- GitHub
- GitHub Models
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 GitHub Models
+# 在 LobeHub 中使用 GitHub Models
-
这些限制可能随时更改，具体信息请参考 [GitHub
@@ -38,11 +38,11 @@ tags:
- 登录 GitHub 并打开 [访问令牌](https://github.com/settings/tokens) 页面
- 创建并设置一个新的访问令牌
-
- GitHub Models 测试期间，要使用 GitHub Models，用户需要申请加入[等待名单（waitlist）](https://github.com/marketplace/models/waitlist/join) 通过后才能获得访问权限。
@@ -50,17 +50,17 @@ tags:
- 请安全地存储访问令牌，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新令牌。
- ### 步骤二：在 LobeChat 中配置 GitHub Models
+ ### 步骤二：在 LobeHub 中配置 GitHub Models
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `GitHub` 的设置项
-
- ### Step 1: Obtain Google API Key
+ ### Step 1: Obtain a Google API Key
- - Visit and log in to [Google AI Studio](https://aistudio.google.com/)
- - Navigate to `Get API Key` in the menu and click on `Create API Key`
+ - Visit and sign in to [Google AI Studio](https://aistudio.google.com/)
+ - In the "Get API Key" menu, click on "Create API Key"
-
- During usage, you may need to pay the API service provider, please refer to Google Gemini's
- pricing policy.
+ You may incur charges from the API provider while using the service. Please refer to Google Gemini’s pricing policy for details.
-Congratulations! You can now use Google Gemini in LobeChat.
+And that’s it — you’re now ready to use Google Gemini in LobeHub!
diff --git a/docs/usage/providers/google.zh-CN.mdx b/docs/usage/providers/google.zh-CN.mdx
index bc38a3785a..1c57361c18 100644
--- a/docs/usage/providers/google.zh-CN.mdx
+++ b/docs/usage/providers/google.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 Google Gemini API Key
-description: 本文将指导你如何在 LobeChat 中配置并使用 Google Gemini，一个由 Google AI 创建的强大语言模型。
+title: 在 LobeHub 中使用 Google Gemini API Key
+description: 本文将指导你如何在 LobeHub 中配置并使用 Google Gemini，一个由 Google AI 创建的强大语言模型。
tags:
- Google Gemini
- Google AI
@@ -8,13 +8,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Google Gemini
+# 在 LobeHub 中使用 Google Gemini
-
### 步骤一：获取 Google 的 API 密钥
@@ -22,31 +22,31 @@ Gemini AI 是由 Google AI 创建的一组大型语言模型（LLM），以其
- 访问并登录 [Google AI Studio](https://aistudio.google.com/)
- 在 `获取 API 密钥` 菜单中 `创建 API 密钥`
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Google Gemini 的费用政策。
-至此，你已经可以在 LobeChat 中使用 Google Gemini 啦。
+至此，你已经可以在 LobeHub 中使用 Google Gemini 啦。
diff --git a/docs/usage/providers/groq.mdx b/docs/usage/providers/groq.mdx
index add4015330..63e84663dd 100644
--- a/docs/usage/providers/groq.mdx
+++ b/docs/usage/providers/groq.mdx
@@ -1,55 +1,50 @@
---
-title: Using Groq API Key in LobeChat
+title: Using the Groq API Key in LobeHub
description: >-
- Learn how to obtain GroqCloud API keys and configure Groq in LobeChat for optimal performance.
-
+ Learn how to obtain a GroqCloud API Key and configure Groq in LobeHub to
+ experience its powerful performance.
tags:
- - LPU Inference Engine
- - GroqCloud
- LLAMA3
- Qwen2
- API keys
- Web UI
+ - API Key
---
-# Using Groq in LobeChat
+# Using Groq in LobeHub
-
- Groq's LPU Inference Engine achieved a sustained speed of 300 tokens per second in internal
- benchmark tests, and according to benchmark tests by ArtificialAnalysis.ai, Groq outperformed
- other providers in terms of throughput (241 tokens per second) and total time to receive 100
- output tokens (0.8 seconds).
+ In internal benchmarks, Groq’s LPU Inference Engine consistently achieved speeds of 300 tokens per second. According to ArtificialAnalysis.ai, Groq outperforms other providers in both throughput (241 tokens per second) and total time to receive 100 output tokens (0.8 seconds).
-This document will guide you on how to use Groq in LobeChat:
+This guide will walk you through how to use Groq in LobeHub:
- ### Obtaining GroqCloud API Keys
+ ### Step 1: Get Your GroqCloud API Key
- First, you need to obtain an API Key from the [GroqCloud Console](https://console.groq.com/).
+ First, visit the [GroqCloud Console](https://console.groq.com/) to obtain your API Key.
-
- Safely store the key from the pop-up as it will only appear once. If you accidentally lose it, you
- will need to create a new key.
+ Make sure to save the key shown in the popup — it will only be displayed once. If you lose it, you’ll need to generate a new one.
- ### Configure Groq in LobeChat
+ ### Step 2: Configure Groq in LobeHub
- You can find the Groq configuration option in `Settings` -> `AI Service Provider`, where you can input the API Key you just obtained.
+ Go to `Settings` -> `AI Providers` in LobeHub, and find the configuration section for Groq. Paste the API Key you just obtained.
-
-Next, select a Groq-supported model in the assistant's model options, and you can experience the powerful performance of Groq in LobeChat.
+Next, in the assistant’s model selection menu, choose a model supported by Groq to start experiencing Groq’s powerful performance in LobeHub.
-
+
diff --git a/docs/usage/providers/groq.zh-CN.mdx b/docs/usage/providers/groq.zh-CN.mdx
index ad2bf43a05..09259776bf 100644
--- a/docs/usage/providers/groq.zh-CN.mdx
+++ b/docs/usage/providers/groq.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 Groq API Key
-description: 了解如何获取 GroqCloud API Key，并在 LobeChat 中配置 Groq，体验 Groq 强大的性能。
+title: 在 LobeHub 中使用 Groq API Key
+description: 了解如何获取 GroqCloud API Key，并在 LobeHub 中配置 Groq，体验 Groq 强大的性能。
tags:
- LLAMA3
- Qwen2
@@ -9,11 +9,11 @@ tags:
- API Key
---
-# 在 LobeChat 中使用 Groq
+# 在 LobeHub 中使用 Groq
-
Groq LPU 推理引擎在内部基准测试中连续达到每秒 300 个令牌的速度，据 ArtificialAnalysis.ai
@@ -21,30 +21,30 @@ Groq 的 [LPU 推理引擎](https://wow.groq.com/news_press/groq-lpu-inference-e
秒）方面优于其他提供商。
-本文档将指导你如何在 LobeChat 中使用 Groq：
+本文档将指导你如何在 LobeHub 中使用 Groq：
### 获取 GroqCloud API Key
首先，你需要到 [GroqCloud Console](https://console.groq.com/) 中获取一个 API Key。
-
妥善保存弹窗中的 key，它只会出现一次，如果不小心丢失了，你需要重新创建一个 key。
- ### 在 LobeChat 中配置 Groq
+ ### 在 LobeHub 中配置 Groq
你可以在 `设置` -> `AI 服务商` 中找到 Groq 的配置选项，将刚才获取的 API Key 填入。
-
-接下来，在助手的模型选项中，选中一个 Groq 支持的模型，就可以在 LobeChat 中体验 Groq 强大的性能了。
+接下来，在助手的模型选项中，选中一个 Groq 支持的模型，就可以在 LobeHub 中体验 Groq 强大的性能了。
-
+
diff --git a/docs/usage/providers/hunyuan.mdx b/docs/usage/providers/hunyuan.mdx
index 2922be251a..6130af23b9 100644
--- a/docs/usage/providers/hunyuan.mdx
+++ b/docs/usage/providers/hunyuan.mdx
@@ -1,52 +1,51 @@
---
-title: Using Tencent Hunyuan in LobeChat
+title: Using Tencent Hunyuan in LobeHub
description: >-
- Learn how to integrate and utilize Tencent Hunyuan's language model APIs in LobeChat.
-
+ Learn how to configure and use Tencent Hunyuan's API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
+ - LobeHub
- Tencent Hunyuan
- API Key
- Web UI
---
-# Using Tencent Hunyuan in LobeChat
+# Using Tencent Hunyuan in LobeHub
-
- ### Step 1: Obtain the Tencent Hunyuan API Key
+ ### Step 1: Obtain a Tencent Hunyuan API Key
- Register and log in to the [Tencent Cloud Console](https://console.cloud.tencent.com/hunyuan/api-key)
- Navigate to `Hunyuan Large Model` and click on `API KEY Management`
- - Create an API key
+ - Create a new API Key
-
- During usage, you may need to pay the API service provider, please refer to Tencent Hunyuan's
- relevant pricing policy.
+ You may incur charges from the API service provider during usage. Please refer to Tencent Hunyuan’s pricing policy for details.
-You can now engage in conversations using the models provided by Tencent Hunyuan in LobeChat.
+And that’s it! You’re now ready to use Tencent Hunyuan’s models for conversations in LobeHub.
diff --git a/docs/usage/providers/hunyuan.zh-CN.mdx b/docs/usage/providers/hunyuan.zh-CN.mdx
index 3b7fac59b3..3adadc80be 100644
--- a/docs/usage/providers/hunyuan.zh-CN.mdx
+++ b/docs/usage/providers/hunyuan.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用腾讯混元
-description: 学习如何在 LobeChat 中配置和使用腾讯混元的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用腾讯混元
+description: 学习如何在 LobeHub 中配置和使用腾讯混元的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 腾讯混元
- API密钥
- Web UI
---
-# 在 LobeChat 中使用腾讯混元
+# 在 LobeHub 中使用腾讯混元
-
### 步骤一：获得腾讯混元的 API Key
@@ -23,27 +23,27 @@ tags:
- 进入 `混元大模型` 并点击 `API KEY 管理`
- 创建一个 API 密钥
-
在使用过程中你可能需要向 API 服务提供商付费，请参考腾讯混元的相关费用政策。
-至此你已经可以在 LobeChat 中使用腾讯混元提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用腾讯混元提供的模型进行对话了。
diff --git a/docs/usage/providers/infiniai.mdx b/docs/usage/providers/infiniai.mdx
index d83f1c3996..b4700ac131 100644
--- a/docs/usage/providers/infiniai.mdx
+++ b/docs/usage/providers/infiniai.mdx
@@ -1,29 +1,36 @@
---
-title: Using Infini-AI in LobeChat
-description: Learn how to configure and utilize Infini-AI's model services in LobeChat.
+title: Using Infini-AI in LobeHub
+description: >-
+ Learn how to configure and use Infini-AI's API Key in LobeHub to enable
+ AI-powered conversations.
tags:
- - LobeChat
+ - LobeHub
- Infini-AI
- API Key
- - LLM Deployment
+ - Large Model Deployment
---
-# Using Infini-AI in LobeChat
+# Using Infini-AI in LobeHub
-[Infini-AI](https://cloud.infini-ai.com/) is a large model service platform optimized for multiple chip architectures, providing efficient and unified AGI infrastructure solutions.
+[Infini-AI](https://cloud.infini-ai.com/) is a large model service platform optimized for diverse chip architectures, offering a high-performance and unified AGI infrastructure solution.
-This guide will help you quickly integrate Infini-AI's AI capabilities into LobeChat.
+This guide will walk you through the steps to quickly integrate Infini-AI's capabilities into LobeHub.
+
+
+ Infini-AI enforces a whitelist mechanism for image URLs. Currently, image links from services like Alibaba Cloud OSS and AWS S3 are supported.\
+ If you encounter a 400 error when using image-based conversations, try [uploading images using base64 encoding](/docs/self-hosting/environment-variables/s3#llm-vision-image-use-base-64).
+
- ### Step 1: Obtain Infini-AI API Key
+ ### Step 1: Obtain an Infini-AI API Key
- Log in to the [Large Model Service Platform](https://cloud.infini-ai.com/genstudio/model)
- - Select "API KEY Management" in the left navigation bar
- - In the newly opened page, click the "Create API KEY" button, enter a name, and click "Create"
+ - In the left-hand navigation menu, select "API KEY Management"
+ - On the newly opened page, click the "Create API KEY" button, enter a name, and click "Create"
- ### Step 2: Configure LobeChat Model Service
+ ### Step 2: Configure the Model Service in LobeHub
- - Open LobeChat and go to the "Settings" interface
- - Select "Infini-AI" in the "Language Model" module
- - Paste the API key you obtained
+ - Open LobeHub and go to the "Settings" page
+ - In the "Language Model" section, select "Infini-AI"
+ - Paste the API Key you obtained earlier
diff --git a/docs/usage/providers/infiniai.zh-CN.mdx b/docs/usage/providers/infiniai.zh-CN.mdx
index e2a0ee90a1..c22c9cdf39 100644
--- a/docs/usage/providers/infiniai.zh-CN.mdx
+++ b/docs/usage/providers/infiniai.zh-CN.mdx
@@ -1,18 +1,18 @@
---
-title: 在 LobeChat 中使用无问芯穹
-description: 学习如何在 LobeChat 中配置和使用无问芯穹的 API Key，实现 AI 对话交互。
+title: 在 LobeHub 中使用无问芯穹
+description: 学习如何在 LobeHub 中配置和使用无问芯穹的 API Key，实现 AI 对话交互。
tags:
- - LobeChat
+ - LobeHub
- 无问芯穹
- API密钥
- 大模型部署
---
-# 在 LobeChat 中使用无问芯穹
+# 在 LobeHub 中使用无问芯穹
[无问芯穹](https://cloud.infini-ai.com/)是基于多元芯片优化的大模型服务平台，提供高效统一的 AGI 基础设施解决方案。
-本文将指导你如何在 LobeChat 中快速接入无问芯穹的 AI 能力。
+本文将指导你如何在 LobeHub 中快速接入无问芯穹的 AI 能力。
无问芯穹的图片链接输入有白名单机制，目前已知支持阿里云 OSS / AWS S3
@@ -27,9 +27,9 @@ tags:
- 在左侧导航栏选择「API KEY 管理」
- 在新打开的页面中，点击「创建 API KEY」按钮，填入名称，点击「创建」
- ### 步骤二：配置 LobeChat 模型服务
+ ### 步骤二：配置 LobeHub 模型服务
- - 打开 LobeChat 进入「设置」界面
+ - 打开 LobeHub 进入「设置」界面
- 在「语言模型」模块选择「Infini-AI」
- 粘贴已获取的 API 密钥
diff --git a/docs/usage/providers/internlm.mdx b/docs/usage/providers/internlm.mdx
index 8e2bb77a7d..ffef312e13 100644
--- a/docs/usage/providers/internlm.mdx
+++ b/docs/usage/providers/internlm.mdx
@@ -1,53 +1,51 @@
---
-title: Using InternLM in LobeChat
+title: Using InternLM in LobeHub
description: >-
- Learn how to configure and use SenseNova's API Key in LobeChat to start conversations and interactions.
-
+ Learn how to configure and use your InternLM API Key in LobeHub to start
+ chatting and interacting.
tags:
- - LobeChat
+ - LobeHub
- InternLM
- API Key
- Web UI
---
-# Using InternLM in LobeChat
+# Using InternLM in LobeHub
-
- ### Step 1: Obtain the InternLM API Key
+ ### Step 1: Obtain Your InternLM API Key
- - Register and log in to [InternLM API](https://InternLM.intern-ai.org.cn/api/tokens)
- - Create an API token
- - Save the API token in the pop-up window
+ - Register and log in to the [InternLM API Portal](https://internlm.intern-ai.org.cn/api/tokens)
+ - Create a new API token
+ - Save the token from the pop-up window
-
- Please store the API token shown in the pop-up securely; it will only appear once. If you lose it,
- you will need to create a new API token.
+ Make sure to save the API token shown in the pop-up window. It will only be displayed once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure InternLM in LobeChat
+ ### Step 2: Configure InternLM in LobeHub
- - Go to the `Settings` interface in LobeChat
- - Find the settings option for `InternLM` under `AI Service Provider`
+ - Go to the `Settings` page in LobeHub
+ - Under `AI Providers`, locate the configuration section for `InternLM`
-
- During usage, you may need to pay the API service provider; please refer to the pricing policy
- regarding InternLM.
+ Please note that usage may incur charges depending on the API provider’s pricing policy. Refer to InternLM’s official documentation for details.
-You are now ready to engage in conversations using the models provided by InternLM in LobeChat.
+You’re all set! You can now start using InternLM-powered models in LobeHub for conversations and interactions.
diff --git a/docs/usage/providers/internlm.zh-CN.mdx b/docs/usage/providers/internlm.zh-CN.mdx
index eba76cae46..9446f36ee4 100644
--- a/docs/usage/providers/internlm.zh-CN.mdx
+++ b/docs/usage/providers/internlm.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用书生浦语
-description: 学习如何在 LobeChat 中配置和使用书生浦语的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用书生浦语
+description: 学习如何在 LobeHub 中配置和使用书生浦语的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 书生浦语
- API密钥
- Web UI
---
-# 在 LobeChat 中使用书生浦语
+# 在 LobeHub 中使用书生浦语
-
### 步骤一：获取书生浦语的 API 密钥
@@ -23,27 +23,27 @@ tags:
- 创建一个 API 令牌
- 在弹出窗口中保存 API 令牌
-
妥善保存弹窗中的 API 令牌，它只会出现一次，如果不小心丢失了，你需要重新创建一个 API 令牌。
- ### 步骤二：在 LobeChat 中配置书生浦语
+ ### 步骤二：在 LobeHub 中配置书生浦语
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `书生` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考书生浦语的相关费用政策。
-至此你已经可以在 LobeChat 中使用书生浦语提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用书生浦语提供的模型进行对话了。
diff --git a/docs/usage/providers/jina.mdx b/docs/usage/providers/jina.mdx
index a39c62fe89..0e9de26d95 100644
--- a/docs/usage/providers/jina.mdx
+++ b/docs/usage/providers/jina.mdx
@@ -1,52 +1,53 @@
---
-title: Using Jina AI API Key in LobeChat
-description: Learn how to configure and use Jina AI models in LobeChat, obtain an API key, and start conversations.
+title: Using Jina AI API Key in LobeHub
+description: >-
+ Learn how to configure and use Jina AI models in LobeHub, obtain your API key,
+ and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Jina AI
- API Key
- Web UI
---
-# Using Jina AI in LobeChat
+# Using Jina AI in LobeHub
-
- ### Step 1: Obtain a Jina AI API Key
+ ### Step 1: Get Your Jina AI API Key
- - Visit the [Jina AI official website](https://jina.ai/) and click the `API` button on the homepage.
+ - Visit the [Jina AI official website](https://jina.ai/) and click the `API` button on the homepage
-
- * Jina AI provides each user with 1M free API Tokens, and the API can be used without
- registration. \* If you need to manage the API Key or recharge the API, you need to register and
- log in to the [Jina AI Console](https://jina.ai/api-dashboard/).
+ \* Jina AI provides each user with 1M free API tokens—no registration required to start using the API.\
+ \* To manage your API key or purchase additional tokens, you’ll need to sign up and log in to the [Jina AI Dashboard](https://jina.ai/api-dashboard/).
- ### Step 2: Configure Jina AI in LobeChat
+ ### Step 2: Configure Jina AI in LobeHub
- - Visit LobeChat's `Application Settings` interface.
- - Find the `Jina AI` setting under `AI Service Provider`.
+ - Go to the `App Settings` page in LobeHub
+ - Under `AI Providers`, locate the `Jina AI` configuration section
-
- You may need to pay the API service provider during use. Please refer to Jina AI's relevant fee policy.
+ You may incur charges when using the API. Please refer to Jina AI’s pricing policy for more details.
-Now you can use the models provided by Jina AI in LobeChat to have conversations.
+And that’s it! You’re now ready to start chatting with models powered by Jina AI in LobeHub.
diff --git a/docs/usage/providers/jina.zh-CN.mdx b/docs/usage/providers/jina.zh-CN.mdx
index 8aa2529e58..3f6a29f071 100644
--- a/docs/usage/providers/jina.zh-CN.mdx
+++ b/docs/usage/providers/jina.zh-CN.mdx
@@ -1,27 +1,27 @@
---
-title: 在 LobeChat 中使用 Jina AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Jina AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 Jina AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Jina AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- Jina AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Jina AI
+# 在 LobeHub 中使用 Jina AI
-
### 步骤一：获取 Jina AI API 密钥
- 访问 [Jina AI 官方网站](https://jina.ai/)，点击首页的 `API` 按钮
-
- ### 步骤二：在 LobeChat 中配置 Jina AI
+ ### 步骤二：在 LobeHub 中配置 Jina AI
- - 访问 LobeChat 的 `应用设置`界面
+ - 访问 LobeHub 的 `应用设置`界面
- 在 `AI 服务商` 下找到 `Jina AI` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Jina AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Jina AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Jina AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/lmstudio.mdx b/docs/usage/providers/lmstudio.mdx
index 488e010ea0..abb7b802a8 100644
--- a/docs/usage/providers/lmstudio.mdx
+++ b/docs/usage/providers/lmstudio.mdx
@@ -1,75 +1,77 @@
---
-title: Using LM Studio in LobeChat
-description: Learn how to configure and use LM Studio, and run AI models for conversations in LobeChat through LM Studio.
+title: Using LM Studio in LobeHub
+description: >-
+ Learn how to configure and use LM Studio to run AI models for conversations
+ within LobeHub.
tags:
- - LobeChat
+ - LobeHub
- LM Studio
- - Open Source Model
+ - Open Source Models
- Web UI
---
-# Using LM Studio in LobeChat
+# Using LM Studio in LobeHub
-
- ### Step 1: Obtain and Install LM Studio
+ ### Step 1: Download and Install LM Studio
- - Go to the [LM Studio official website](https://lmstudio.ai/)
- - Choose your platform and download the installation package. LM Studio currently supports MacOS, Windows, and Linux platforms.
- - Follow the prompts to complete the installation and run LM Studio.
+ - Visit the [official LM Studio website](https://lmstudio.ai/)
+ - Choose your operating system and download the installer. LM Studio currently supports macOS, Windows, and Linux
+ - Follow the installation instructions and launch LM Studio
-
- If your LM Studio is running locally, make sure to turn on `Client Request Mode`.
+ If LM Studio is running locally, make sure to enable the "Client Request Mode".
- - Add the model you are running in the model list below.
- - Select a Volcano Engine model for your assistant to start the conversation.
+ - Add the model you’re running to the model list below
+ - Choose a model for your assistant and start chatting
-
-Now you can use the model running in LM Studio in LobeChat for conversations.
+And that’s it! You’re now ready to use models running in LM Studio directly within LobeHub.
diff --git a/docs/usage/providers/lmstudio.zh-CN.mdx b/docs/usage/providers/lmstudio.zh-CN.mdx
index 23ac7af1a0..394f5488a7 100644
--- a/docs/usage/providers/lmstudio.zh-CN.mdx
+++ b/docs/usage/providers/lmstudio.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 LM Studio
-description: 学习如何配置和使用 LM Studio，并在 LobeChat 中 通过 LM Studio 运行 AI 模型进行对话。
+title: 在 LobeHub 中使用 LM Studio
+description: 学习如何配置和使用 LM Studio，并在 LobeHub 中 通过 LM Studio 运行 AI 模型进行对话。
tags:
- - LobeChat
+ - LobeHub
- LM Studio
- 开源模型
- Web UI
---
-# 在 LobeChat 中使用 LM Studio
+# 在 LobeHub 中使用 LM Studio
-
### 步骤一：获取并安装 LM Studio
@@ -23,7 +23,7 @@ tags:
- 选择你的平台并下载安装包，LM Studio 目前支持 MacOS、Windows 和 Linux 平台
- 按照提示完成安装，运行 LM Studio
-
-至此你已经可以在 LobeChat 中使用 LM Studio 运行的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 LM Studio 运行的模型进行对话了。
diff --git a/docs/usage/providers/minimax.mdx b/docs/usage/providers/minimax.mdx
index 34902e2d26..ed1dba583f 100644
--- a/docs/usage/providers/minimax.mdx
+++ b/docs/usage/providers/minimax.mdx
@@ -1,60 +1,59 @@
---
-title: Using Minimax API Key in LobeChat
+title: Using the Minimax API Key in LobeHub
description: >-
- Learn how to use MiniMax in LobeChat to enhance AI conversations. Obtain MiniMax API key, configure MiniMax in LobeChat settings, and select a model for your AI assistant.
-
+ Learn how to configure and use the MiniMax AI model in LobeHub. This guide
+ walks you through obtaining a MiniMax API key, detailed setup steps, and
+ starting conversations with the MiniMax model.
tags:
+ - LobeHub
- MiniMax
- - Web UI
- API Key
- - MiniMax Models
+ - Web UI
---
-# Using Minimax in LobeChat
+# Using Minimax in LobeHub
-
- ### Step 1: Obtain MiniMax API Key
+ ### Step 1: Obtain a MiniMax API Key
- - Register and log in to the [MiniMax Open Platform](https://www.minimaxi.com/platform)
- - In `Account Management`, locate the `API Key` menu and create a new key
+ - Register and log in to the [MiniMax Developer Platform](https://www.minimaxi.com/platform)
+ - Navigate to the `Account Management` section and find the `API Keys` menu to create a new key
-
- Please store the key securely as it will only appear once. If you accidentally lose it, you will
- need to create a new key.
+ Make sure to store your API key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure MiniMax in LobeChat
+ ### Step 2: Configure MiniMax in LobeHub
- - Go to the `Settings` interface of LobeChat
- - Find the setting for `MiniMax` under `AI Service Provider`
+ - Go to the `Settings` page in LobeHub
+ - Under `AI Providers`, locate the `MiniMax` configuration section
-
- During usage, you may need to pay the API service provider, please refer to MiniMax's relevant
- pricing policies.
+ Please note that usage may incur charges from the API provider. Refer to MiniMax’s pricing policy for more details.
-You can now use the models provided by MiniMax to have conversations in LobeChat.
+You're all set! You can now start chatting with models powered by MiniMax in LobeHub.
diff --git a/docs/usage/providers/minimax.zh-CN.mdx b/docs/usage/providers/minimax.zh-CN.mdx
index dea7a06f01..88749741c3 100644
--- a/docs/usage/providers/minimax.zh-CN.mdx
+++ b/docs/usage/providers/minimax.zh-CN.mdx
@@ -1,22 +1,22 @@
---
-title: 在 LobeChat 中使用 Minimax API Key
+title: 在 LobeHub 中使用 Minimax API Key
description: >-
- 学习如何在 LobeChat 中配置并使用 MiniMax 智能模型进行对话。获取 MiniMax API 密钥、配置步骤详解，开始与 MiniMax 模型交互。
-
+ 学习如何在 LobeHub 中配置并使用 MiniMax 智能模型进行对话。获取 MiniMax API 密钥、配置步骤详解，开始与 MiniMax
+ 模型交互。
tags:
- - LobeChat
+ - LobeHub
- MiniMax
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Minimax
+# 在 LobeHub 中使用 Minimax
-
### 步骤一：获取 MiniMax API 密钥
@@ -24,35 +24,35 @@ tags:
- 注册并登录 [MiniMax 开放平台](https://www.minimaxi.com/platform)
- 在 `账户管理` 中找到 `接口密钥` 菜单，并创建新的密钥
-
请安全地存储密钥，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新密钥。
- ### 步骤二：在 LobeChat 中配置 MiniMax
+ ### 步骤二：在 LobeHub 中配置 MiniMax
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到`MiniMax`的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 MiniMax 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 MiniMax 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 MiniMax 提供的模型进行对话了。
diff --git a/docs/usage/providers/mistral.mdx b/docs/usage/providers/mistral.mdx
index ab4ba1a30a..b46dd90940 100644
--- a/docs/usage/providers/mistral.mdx
+++ b/docs/usage/providers/mistral.mdx
@@ -1,50 +1,47 @@
---
-title: Using Mistral AI API Key in LobeChat
+title: Using Mistral AI API Key in LobeHub
description: >-
- Learn how to integrate Mistral AI into LobeChat for enhanced conversational experiences. Follow the steps to configure Mistral AI and start using its models.
-
+ Learn how to configure and use Mistral AI in LobeHub, including how to obtain
+ an API key and select the appropriate AI model for conversations.
tags:
- - Mistral AI
- Web UI
- - API key
+ - Mistral AI
+ - API Key
---
-# Using Mistral AI in LobeChat
+# Using Mistral AI in LobeHub
-
- ### Step 1: Obtain Mistral AI API Key
+ ### Step 1: Get Your Mistral AI API Key
- Create a [Mistral AI](https://mistral.ai/) account
- - Obtain your [API key](https://console.mistral.ai/user/api-keys/)
+ - Retrieve your [API key](https://console.mistral.ai/user/api-keys/)
-
- If you are using mistral.ai, your account must have a valid subscription for the API key to work
- properly. Newly created API keys may take 2-3 minutes to become active. If the "Test" button
- fails, please retry after 2-3 minutes.
+ If you're using mistral.ai, your account must have an active subscription for the API key to function properly. Newly created API keys may take 2–3 minutes to become active. If clicking the "Test" button fails, please try again after a few minutes.
- - Enter the obtained API key
- - Choose a Mistral AI model for your AI assistant to start the conversation
+ - Paste your API key into the input field
+ - Choose a Mistral AI model for your assistant to start chatting
-
- During usage, you may need to pay the API service provider, please refer to Mistral AI's relevant
- pricing policies.
+ You may incur charges from the API provider during usage. Please refer to Mistral AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Mistral AI in LobeChat.
+You're all set! You can now start chatting with models powered by Mistral AI in LobeHub.
diff --git a/docs/usage/providers/mistral.zh-CN.mdx b/docs/usage/providers/mistral.zh-CN.mdx
index 799637a8d8..605f6cb80f 100644
--- a/docs/usage/providers/mistral.zh-CN.mdx
+++ b/docs/usage/providers/mistral.zh-CN.mdx
@@ -1,17 +1,17 @@
---
-title: 在 LobeChat 中使用 Mistral AI API Key
-description: 学习如何在 LobeChat 中配置并使用 Mistral AI，包括获取 API 密钥和选择适合的 AI 模型进行对话。
+title: 在 LobeHub 中使用 Mistral AI API Key
+description: 学习如何在 LobeHub 中配置并使用 Mistral AI，包括获取 API 密钥和选择适合的 AI 模型进行对话。
tags:
- Web UI
- Mistral AI
- API Key
---
-# 在 LobeChat 中使用 Mistral AI
+# 在 LobeHub 中使用 Mistral AI
-
### 步骤一：获取 Mistral AI API 密钥
@@ -19,14 +19,14 @@ Mistral AI API 现在可供所有人使用，本文档将指导你如何在 Lobe
- 创建一个 [Mistral AI](https://mistral.ai/) 帐户
- 获取您的 [API 密钥](https://console.mistral.ai/user/api-keys/)
-
如果您使用的是 mistral.ai，则您的帐户必须具有有效的订阅才能使 API 密钥正常工作。新创建的 API
@@ -36,11 +36,11 @@ Mistral AI API 现在可供所有人使用，本文档将指导你如何在 Lobe
- 填入获得的 API 密钥
- 为你的 AI 助手选择一个 Mistral AI 的模型即可开始对话
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Mistral AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Mistral AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Mistral AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/modelscope.mdx b/docs/usage/providers/modelscope.mdx
index 665d0b5bd9..4cac01ee0b 100644
--- a/docs/usage/providers/modelscope.mdx
+++ b/docs/usage/providers/modelscope.mdx
@@ -1,33 +1,33 @@
---
-title: ModelScope Provider Setup
-description: Learn how to configure and use ModelScope provider in LobeChat
+title: ModelScope Provider Configuration
+description: Learn how to configure and use the ModelScope provider in LobeHub
tags:
- ModelScope
---
-# ModelScope Provider Setup
+# ModelScope Provider Configuration
-ModelScope (魔塔社区) is Alibaba's open-source model community that provides access to various AI models. This guide will help you set up the ModelScope provider in LobeChat.
+ModelScope is an open-source AI model community by Alibaba, offering access to a wide range of AI models. This guide will walk you through setting up the ModelScope provider in LobeHub.
## Prerequisites
-Before using ModelScope API, you need to:
+Before using the ModelScope API, you need to:
1. **Create a ModelScope Account**
- Visit [ModelScope](https://www.modelscope.cn/)
- - Register for an account
+ - Sign up for an account
-2. **Bind Alibaba Cloud Account**
+2. **Link Your Alibaba Cloud Account**
- - **Important**: ModelScope API requires binding with an Alibaba Cloud account
- - Visit your [ModelScope Access Token page](https://www.modelscope.cn/my/myaccesstoken)
- - Follow the instructions to bind your Alibaba Cloud account
+ - **Important**: Accessing the ModelScope API requires linking your Alibaba Cloud account
+ - Go to your [ModelScope Access Token Page](https://www.modelscope.cn/my/myaccesstoken)
+ - Follow the instructions to link your Alibaba Cloud account
- This step is mandatory for API access
-3. **Get API Token**
- - After binding your Alibaba Cloud account, generate an API token
- - Copy the token for use in LobeChat
+3. **Obtain an API Token**
+ - After linking your Alibaba Cloud account, generate an API token
+ - Copy the token for use in LobeHub
## Configuration
@@ -45,13 +45,13 @@ MODELSCOPE_API_KEY=your_modelscope_api_token
# Optional: Custom model list (comma-separated)
MODELSCOPE_MODEL_LIST=deepseek-ai/DeepSeek-V3-0324,Qwen/Qwen3-235B-A22B
-# Optional: Proxy URL if needed
+# Optional: Proxy URL (if needed)
MODELSCOPE_PROXY_URL=https://your-proxy-url
```
### Docker Configuration
-If using Docker, add the ModelScope environment variables to your `docker-compose.yml`:
+If you're using Docker, add the ModelScope environment variables to your `docker-compose.yml`:
```yaml
environment:
@@ -62,7 +62,7 @@ environment:
## Available Models
-ModelScope provides access to various models including:
+ModelScope provides access to a variety of models, including:
- **DeepSeek Models**: DeepSeek-V3, DeepSeek-R1 series
- **Qwen Models**: Qwen3 series, Qwen2.5 series
@@ -73,25 +73,25 @@ ModelScope provides access to various models including:
### Common Issues
-1. **"Please bind your Alibaba Cloud account before use" Error**
+1. **"Please link your Alibaba Cloud account first" error**
- - This means you haven't bound your Alibaba Cloud account to ModelScope
- - Visit [ModelScope Access Token page](https://www.modelscope.cn/my/myaccesstoken)
- - Complete the Alibaba Cloud account binding process
+ - This means your Alibaba Cloud account is not yet linked to ModelScope
+ - Visit the [ModelScope Access Token Page](https://www.modelscope.cn/my/myaccesstoken)
+ - Complete the account linking process
-2. **401 Authentication Error**
+2. **401 Unauthorized Error**
- Check if your API token is correct
- - Ensure the token hasn't expired
- - Verify that your Alibaba Cloud account is properly bound
+ - Ensure the token has not expired
+ - Verify that your Alibaba Cloud account is properly linked
-3. **Model Not Available**
+3. **Model Unavailable**
- Some models may require additional permissions
- Check the model's page on ModelScope for access requirements
### Debug Mode
-Enable debug mode to see detailed logs:
+Enable debug mode to view detailed logs:
```bash
DEBUG_MODELSCOPE_CHAT_COMPLETION=1
@@ -99,19 +99,39 @@ DEBUG_MODELSCOPE_CHAT_COMPLETION=1
## Notes
-- ModelScope API is compatible with OpenAI API format
-- The service is primarily designed for users in China
-- Some models may have usage limitations or require additional verification
-- API responses are in Chinese by default for some models
+- The ModelScope API is compatible with the OpenAI API format
+- This service is primarily designed for users in China
+- Some models may have usage restrictions or require additional verification
+- API responses for certain models may default to Chinese
## Support
For ModelScope-specific issues:
-- Visit [ModelScope Documentation](https://www.modelscope.cn/docs)
-- Check [ModelScope Community](https://www.modelscope.cn/community)
+- Visit the [ModelScope Documentation](https://www.modelscope.cn/docs)
+- Check out the [ModelScope Community](https://www.modelscope.cn/community)
-For LobeChat integration issues:
+For LobeHub integration issues:
-- Check our [GitHub Issues](https://github.com/lobehub/lobe-chat/issues)
+- Browse our [GitHub Issues](https://github.com/lobehub/lobe-chat/issues)
- Join our community discussions
+
+## Model ID Format
+
+ModelScope uses a namespace-prefixed format for model IDs, for example:
+
+```
+deepseek-ai/DeepSeek-V3-0324
+deepseek-ai/DeepSeek-R1-0528
+Qwen/Qwen3-235B-A22B
+Qwen/Qwen3-32B
+```
+
+When configuring the model list, be sure to use the full model ID format.
+
+## API Limitations
+
+- The ModelScope API is subject to rate limits
+- Some models may require special permissions
+- It's recommended to monitor API usage in production environments
+- Certain advanced models may require a paid subscription to access
diff --git a/docs/usage/providers/modelscope.zh-CN.mdx b/docs/usage/providers/modelscope.zh-CN.mdx
index e508f9195e..b55f3fc037 100644
--- a/docs/usage/providers/modelscope.zh-CN.mdx
+++ b/docs/usage/providers/modelscope.zh-CN.mdx
@@ -1,13 +1,13 @@
---
title: ModelScope 提供商配置
-description: 学习如何在 LobeChat 中配置和使用 ModelScope 提供商
+description: 学习如何在 LobeHub 中配置和使用 ModelScope 提供商
tags:
- ModelScope
---
# ModelScope 提供商配置
-ModelScope（魔塔社区）是阿里巴巴的开源模型社区，提供各种 AI 模型的访问服务。本指南将帮助您在 LobeChat 中设置 ModelScope 提供商。
+ModelScope（魔塔社区）是阿里巴巴的开源模型社区，提供各种 AI 模型的访问服务。本指南将帮助您在 LobeHub 中设置 ModelScope 提供商。
## 前置条件
@@ -27,7 +27,7 @@ ModelScope（魔塔社区）是阿里巴巴的开源模型社区，提供各种
3. **获取 API 令牌**
- 绑定阿里云账户后，生成 API 令牌
- - 复制令牌以在 LobeChat 中使用
+ - 复制令牌以在 LobeHub 中使用
## 配置
@@ -111,7 +111,7 @@ DEBUG_MODELSCOPE_CHAT_COMPLETION=1
- 访问 [ModelScope 文档](https://www.modelscope.cn/docs)
- 查看 [ModelScope 社区](https://www.modelscope.cn/community)
-对于 LobeChat 集成问题：
+对于 LobeHub 集成问题：
- 查看我们的 [GitHub Issues](https://github.com/lobehub/lobe-chat/issues)
- 加入我们的社区讨论
diff --git a/docs/usage/providers/moonshot.mdx b/docs/usage/providers/moonshot.mdx
index d9f95ff924..deda8c178c 100644
--- a/docs/usage/providers/moonshot.mdx
+++ b/docs/usage/providers/moonshot.mdx
@@ -1,49 +1,46 @@
---
-title: Using Moonshot AI API Key in LobeChat
+title: Using Moonshot AI API Key in LobeHub
description: >-
- Learn how to integrate Moonshot AI into LobeChat for AI-powered conversations. Follow the steps to get the API key, configure Moonshot AI, and start engaging with AI models.
-
+ Learn how to configure and use Moonshot AI in LobeHub, including how to obtain
+ an API key and select the appropriate AI model for conversations.
tags:
- Moonshot AI
- Web UI
- API Key
---
-# Using Moonshot AI in LobeChat
+# Using Moonshot AI in LobeHub
-
- ### Step 1: Get Moonshot AI API Key
+ ### Step 1: Get Your Moonshot AI API Key
- - Apply for your [API key](https://platform.moonshot.cn/console/api-keys)
+ - Apply for your [API Key](https://platform.moonshot.cn/console/api-keys)
-
- If you are using mistral.ai, your account must have a valid subscription for the API key to work
- properly. Newly created API keys may take 2-3 minutes to become active. If the "Test" button
- fails, please retry after 2-3 minutes.
+ If you're using mistral.ai, your account must have an active subscription for the API key to work properly. Newly created API keys may take 2–3 minutes to become active. If clicking the "Test" button fails, please try again after a few minutes.
- - Enter the API key you obtained
- - Choose a Moonshot AI model for your AI assistant to start the conversation
+ - Paste your API key into the input field
+ - Choose a Moonshot AI model for your assistant to start chatting
-
- During usage, you may need to pay the API service provider according to Moonshot AI's related
- pricing policies.
+ You may be required to pay for API usage. Please refer to Moonshot AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Moonshot AI in LobeChat.
+That's it! You're now ready to start chatting with models powered by Moonshot AI in LobeHub.
diff --git a/docs/usage/providers/moonshot.zh-CN.mdx b/docs/usage/providers/moonshot.zh-CN.mdx
index 30f3027634..8d1366be41 100644
--- a/docs/usage/providers/moonshot.zh-CN.mdx
+++ b/docs/usage/providers/moonshot.zh-CN.mdx
@@ -1,31 +1,31 @@
---
-title: 在 LobeChat 中使用 Moonshot（月之暗面） AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Moonshot AI，包括获取 API 密钥和选择适合的 AI 模型进行对话。
+title: 在 LobeHub 中使用 Moonshot（月之暗面） AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Moonshot AI，包括获取 API 密钥和选择适合的 AI 模型进行对话。
tags:
- Moonshot AI
- Web UI
- API Key
---
-# 在 LobeChat 中使用 Moonshot AI
+# 在 LobeHub 中使用 Moonshot AI
-
### 步骤一：获取 Moonshot AI API 密钥
- 申请您的 [API 密钥](https://platform.moonshot.cn/console/api-keys)
-
如果您使用的是 mistral.ai，则您的帐户必须具有有效的订阅才能使 API 密钥正常工作。新创建的 API
@@ -35,11 +35,11 @@ Moonshot AI API 现在可供所有人使用，本文档将指导你如何在 Lob
- 填入获得的 API 密钥
- 为你的 AI 助手选择一个 Moonshot AI 的模型即可开始对话
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Moonshot AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Moonshot AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Moonshot AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/novita.mdx b/docs/usage/providers/novita.mdx
index e8b3fbca47..6229fc1df5 100644
--- a/docs/usage/providers/novita.mdx
+++ b/docs/usage/providers/novita.mdx
@@ -1,8 +1,10 @@
---
-title: Using Novita AI API Key in LobeChat
+title: Using Novita AI API Key in LobeHub
description: >-
- Learn how to integrate Novita AI's language model APIs into LobeChat. Follow the steps to register, create an Novita AI API key, configure settings, and chat with our various AI models.
-
+ Learn how to integrate Novita AI's large language model API into LobeHub.
+ Follow the steps to register a Novita AI account, create an API key, add
+ credits, and configure it in LobeHub. Start chatting with a variety of AI
+ models.
tags:
- Novita AI
- Llama3
@@ -12,45 +14,44 @@ tags:
- Web UI
---
-# Using Novita AI in LobeChat
+# Using Novita AI in LobeHub
-
- ### Step 1: Register and Log in to Novita AI
+ ### Step 1: Sign Up and Log In to Novita AI
- Visit [Novita.ai](https://novita.ai/) and create an account
- - You can log in with your Google or Github account
- - Upon registration, Novita AI will provide a $0.5 credit.
+ - You can sign in using your Google or GitHub account
+ - Upon registration, Novita AI grants you $0.50 in free credits
-
- During usage, you may need to pay the API service provider, please refer to Novita AI's pricing
- policy.
+ You may need to pay for API usage. Please refer to Novita AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Novita AI in LobeChat.
+That’s it! You’re now ready to chat with Novita AI models directly in LobeHub.
diff --git a/docs/usage/providers/novita.zh-CN.mdx b/docs/usage/providers/novita.zh-CN.mdx
index 1112894d83..328602898c 100644
--- a/docs/usage/providers/novita.zh-CN.mdx
+++ b/docs/usage/providers/novita.zh-CN.mdx
@@ -1,8 +1,8 @@
---
-title: 在 LobeChat 中使用 Novita AI API Key
+title: 在 LobeHub 中使用 Novita AI API Key
description: >-
- 学习如何将 Novita AI 的大语言模型 API 集成到 LobeChat 中。跟随以下步骤注册 Novita AI 账号、创建 API Key、充值信用额度并在 LobeChat 中进行设置。并与我们的多种 AI 模型交谈。
-
+ 学习如何将 Novita AI 的大语言模型 API 集成到 LobeHub 中。跟随以下步骤注册 Novita AI 账号、创建 API
+ Key、充值信用额度并在 LobeHub 中进行设置。并与我们的多种 AI 模型交谈。
tags:
- Novita AI
- Llama3
@@ -12,13 +12,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 Novita AI
+# 在 LobeHub 中使用 Novita AI
-
### 步骤一：注册 Novita AI 账号并登录
@@ -27,29 +27,29 @@ tags:
- 你可以使用 Google 或者 Github 账号登录
- 注册后，Novita AI 会赠送 0.5 美元的使用额度
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Novita AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Novita AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Novita AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/nvidia.mdx b/docs/usage/providers/nvidia.mdx
index 06721b49ad..c92aa4cabc 100644
--- a/docs/usage/providers/nvidia.mdx
+++ b/docs/usage/providers/nvidia.mdx
@@ -1,56 +1,57 @@
---
-title: Using Nvidia NIM API Key in LobeChat
-description: Learn how to configure and use Nvidia NIM AI models in LobeChat, obtain an API key, and start a conversation.
+title: Using Nvidia NIM API Key in LobeHub
+description: >-
+ Learn how to configure and use Nvidia NIM AI models in LobeHub, obtain your
+ API key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Nvidia NIM
- API Key
- Web UI
---
-# Using Nvidia NIM in LobeChat
+# Using Nvidia NIM in LobeHub
-
- ### Step 1: Obtain Nvidia NIM API Key
+ ### Step 1: Obtain Your Nvidia NIM API Key
- - First, visit the [Nvidia NIM console](https://build.nvidia.com/explore/discover) and complete the registration and login.
- - On the `Models` page, select the model you need, such as Deepseek-R1.
+ - First, visit the [Nvidia NIM Console](https://build.nvidia.com/explore/discover) and complete the registration and login process.
+ - On the `Models` page, select the model you want to use, such as Deepseek-R1.
-
- Please store the key securely as it will only appear once. If you accidentally lose it, you will
- need to create a new key.
+ Make sure to store your API key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure Nvidia NIM in LobeChat
+ ### Step 2: Configure Nvidia NIM in LobeHub
- - Visit the `Application Settings` -> `AI Service Provider` interface in LobeChat.
- - Find the settings item for `Nvidia NIM` in the list of providers.
+ - Go to the `App Settings` section in LobeHub and navigate to `AI Service Providers`.
+ - Find the `Nvidia NIM` option in the list of providers.
-
- You may need to pay the API service provider during use, please refer to Nvidia NIM's related fee policies.
+ You may incur charges from the API service provider during usage. Please refer to Nvidia NIM’s pricing policy for details.
-Now you can use the models provided by Nvidia NIM to have conversations in LobeChat.
+That’s it! You’re now ready to use Nvidia NIM-powered models in LobeHub for your conversations.
diff --git a/docs/usage/providers/nvidia.zh-CN.mdx b/docs/usage/providers/nvidia.zh-CN.mdx
index ae6ab12caf..3de83fc828 100644
--- a/docs/usage/providers/nvidia.zh-CN.mdx
+++ b/docs/usage/providers/nvidia.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Nvidia NIM API Key
-description: 学习如何在 LobeChat 中配置和使用 Nvidia NIM AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 Nvidia NIM API Key
+description: 学习如何在 LobeHub 中配置和使用 Nvidia NIM AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- Nvidia NIM
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Nvidia NIM
+# 在 LobeHub 中使用 Nvidia NIM
-
### 步骤一：获取 Nvidia NIM API 密钥
@@ -22,12 +22,12 @@ tags:
- 首先，访问[Nvidia NIM 控制台](https://build.nvidia.com/explore/discover)并完成注册登录
- 在 `Models` 页面选择你需要的模型，例如 Deepseek-R1
-
- ### 步骤二：在 LobeChat 中配置 Nvidia NIM
+ ### 步骤二：在 LobeHub 中配置 Nvidia NIM
- - 访问 LobeChat 的 `应用设置` 的 `AI 服务供应商` 界面
+ - 访问 LobeHub 的 `应用设置` 的 `AI 服务供应商` 界面
- 在供应商列表中找到 ` Nvidia NIM` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Nvidia NIM 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Nvidia NIM 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Nvidia NIM 提供的模型进行对话了。
diff --git a/docs/usage/providers/ollama.mdx b/docs/usage/providers/ollama.mdx
index a1c9233388..5250c77e2d 100644
--- a/docs/usage/providers/ollama.mdx
+++ b/docs/usage/providers/ollama.mdx
@@ -1,98 +1,98 @@
---
-title: Using Ollama in LobeChat
+title: Using Ollama in LobeHub
description: >-
- Learn how to use Ollama in LobeChat, run LLM locally, and experience cutting-edge AI usage.
-
+ Learn how to use Ollama in LobeHub to run large language models locally and
+ experience cutting-edge AI capabilities.
tags:
- Ollama
- - Local LLM
- - Ollama WebUI
- Web UI
- API Key
+ - Local LLM
+ - Ollama WebUI
---
-# Using Ollama in LobeChat
+# Using Ollama in LobeHub
-
- ### Local Installation of Ollama
+ ### Install Ollama Locally
- [Download Ollama for macOS](https://ollama.com/download?utm_source=lobehub\&utm_medium=docs\&utm_campaign=download-macos) and unzip/install it.
+ [Download Ollama for macOS](https://ollama.com/download?utm_source=lobehub\&utm_medium=docs\&utm_campaign=download-macos), then unzip and install it.
### Configure Ollama for Cross-Origin Access
- Due to Ollama's default configuration, which restricts access to local only, additional environment variable setting `OLLAMA_ORIGINS` is required for cross-origin access and port listening. Use `launchctl` to set the environment variable:
+ By default, Ollama only allows local access. To enable cross-origin access and port listening, set the `OLLAMA_ORIGINS` environment variable using `launchctl`:
```bash
launchctl setenv OLLAMA_ORIGINS "*"
```
- After setting up, restart the Ollama application.
+ After setting the variable, restart the Ollama application.
- ### Conversing with Local Large Models in LobeChat
+ ### Chat with Local LLMs in LobeHub
- Now, you can start conversing with the local LLM in LobeChat.
+ You can now start chatting with local LLMs in LobeHub.
-
## Using Ollama on Windows
- ### Local Installation of Ollama
+ ### Install Ollama Locally
[Download Ollama for Windows](https://ollama.com/download?utm_source=lobehub\&utm_medium=docs\&utm_campaign=download-windows) and install it.
### Configure Ollama for Cross-Origin Access
- Since Ollama's default configuration allows local access only, additional environment variable setting `OLLAMA_ORIGINS` is needed for cross-origin access and port listening.
+ By default, Ollama only allows local access. To enable cross-origin access and port listening, set the `OLLAMA_ORIGINS` environment variable.
- On Windows, Ollama inherits your user and system environment variables.
+ On Windows, Ollama inherits your user and system environment variables:
- 1. First, exit the Ollama program by clicking on it in the Windows taskbar.
- 2. Edit system environment variables from the Control Panel.
- 3. Edit or create the Ollama environment variable `OLLAMA_ORIGINS` for your user account, setting the value to `*`.
- 4. Click `OK/Apply` to save and restart the system.
- 5. Run `Ollama` again.
+ 1. Exit Ollama from the system tray.
+ 2. Open the Control Panel and edit system environment variables.
+ 3. Add or edit the `OLLAMA_ORIGINS` variable for your user account and set its value to `*`.
+ 4. Click `OK/Apply` and restart your system.
+ 5. Relaunch Ollama.
- ### Conversing with Local Large Models in LobeChat
+ ### Chat with Local LLMs in LobeHub
- Now, you can start conversing with the local LLM in LobeChat.
+ You can now start chatting with local LLMs in LobeHub.
## Using Ollama on Linux
- ### Local Installation of Ollama
+ ### Install Ollama Locally
- Install using the following command:
+ Run the following command to install:
```bash
curl -fsSL https://ollama.com/install.sh | sh
```
- Alternatively, you can refer to the [Linux manual installation guide](https://github.com/ollama/ollama/blob/main/docs/linux.md).
+ Alternatively, refer to the [manual installation guide for Linux](https://github.com/ollama/ollama/blob/main/docs/linux.md).
### Configure Ollama for Cross-Origin Access
- Due to Ollama's default configuration, which allows local access only, additional environment variable setting `OLLAMA_ORIGINS` is required for cross-origin access and port listening. If Ollama runs as a systemd service, use `systemctl` to set the environment variable:
+ By default, Ollama only allows local access. To enable cross-origin access and port listening, set the `OLLAMA_ORIGINS` environment variable. If Ollama is running as a systemd service, use `systemctl` to configure it:
- 1. Edit the systemd service by calling `sudo systemctl edit ollama.service`:
+ 1. Edit the systemd service with:
```bash
sudo systemctl edit ollama.service
```
- 2. Add `Environment` under `[Service]` for each environment variable:
+ 2. Add the following under the `[Service]` section:
```bash
[Service]
@@ -101,24 +101,24 @@ This document will guide you on how to use Ollama in LobeChat:
```
3. Save and exit.
- 4. Reload `systemd` and restart Ollama:
+ 4. Reload systemd and restart Ollama:
```bash
sudo systemctl daemon-reload
sudo systemctl restart ollama
```
- ### Conversing with Local Large Models in LobeChat
+ ### Chat with Local LLMs in LobeHub
- Now, you can start conversing with the local LLM in LobeChat.
+ You can now start chatting with local LLMs in LobeHub.
-## Deploying Ollama using Docker
+## Using Ollama with Docker
- ### Pulling Ollama Image
+ ### Pull the Ollama Docker Image
- If you prefer using Docker, Ollama provides an official Docker image that you can pull using the following command:
+ If you prefer using Docker, Ollama provides an official image. Pull it with:
```bash
docker pull ollama/ollama
@@ -126,48 +126,48 @@ This document will guide you on how to use Ollama in LobeChat:
### Configure Ollama for Cross-Origin Access
- Since Ollama's default configuration allows local access only, additional environment variable setting `OLLAMA_ORIGINS` is needed for cross-origin access and port listening.
-
- If Ollama runs as a Docker container, you can add the environment variable to the `docker run` command.
+ By default, Ollama only allows local access. To enable cross-origin access and port listening, set the `OLLAMA_ORIGINS` environment variable in your `docker run` command:
```bash
docker run -d --gpus=all -v ollama:/root/.ollama -e OLLAMA_ORIGINS="*" -p 11434:11434 --name ollama ollama/ollama
```
- ### Conversing with Local Large Models in LobeChat
+ ### Chat with Local LLMs in LobeHub
- Now, you can start conversing with the local LLM in LobeChat.
+ You can now start chatting with local LLMs in LobeHub.
## Installing Ollama Models
-Ollama supports various models, which you can view in the [Ollama Library](https://ollama.com/library) and choose the appropriate model based on your needs.
+Ollama supports a wide range of models. You can browse the available models in the [Ollama Library](https://ollama.com/library) and choose the ones that best suit your needs.
-### Installation in LobeChat
+### Install via LobeHub
-In LobeChat, we have enabled some common large language models by default, such as llama3, Gemma, Mistral, etc. When you select a model for conversation, we will prompt you to download that model.
+LobeHub comes pre-configured with popular LLMs like llama3, Gemma, and Mistral. When you select a model for the first time, LobeHub will prompt you to download it.
-
- Visit [Integrating with Ollama](/docs/self-hosting/examples/ollama) to learn how to deploy
- LobeChat to meet integration needs with Ollama.
+ To learn how to deploy LobeHub with Ollama integration, visit [Integrating with Ollama](/en/docs/self-hosting/examples/ollama).
+
+```
+```
diff --git a/docs/usage/providers/ollama.zh-CN.mdx b/docs/usage/providers/ollama.zh-CN.mdx
index 3d560d00c2..3adf514b0b 100644
--- a/docs/usage/providers/ollama.zh-CN.mdx
+++ b/docs/usage/providers/ollama.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 Ollama
-description: 了解如何在 LobeChat 中使用 Ollama ，在你的本地运行大型语言模型，获得最前沿的 AI 使用体验。
+title: 在 LobeHub 中使用 Ollama
+description: 了解如何在 LobeHub 中使用 Ollama ，在你的本地运行大型语言模型，获得最前沿的 AI 使用体验。
tags:
- Ollama
- Web UI
@@ -9,15 +9,15 @@ tags:
- Ollama WebUI
---
-# 在 LobeChat 中使用 Ollama
+# 在 LobeHub 中使用 Ollama
-
- 你可以前往 [与 Ollama 集成](/zh/docs/self-hosting/examples/ollama) 了解如何部署 LobeChat
+ 你可以前往 [与 Ollama 集成](/zh/docs/self-hosting/examples/ollama) 了解如何部署 LobeHub
，以满足与 Ollama 的集成需求。
diff --git a/docs/usage/providers/ollama/gemma.mdx b/docs/usage/providers/ollama/gemma.mdx
index 79efe20ee2..650790620f 100644
--- a/docs/usage/providers/ollama/gemma.mdx
+++ b/docs/usage/providers/ollama/gemma.mdx
@@ -1,50 +1,49 @@
---
-title: Using Google Gemma Model in LobeChat
+title: Using the Google Gemma Model in LobeHub
description: >-
- Learn how to integrate and utilize Google Gemma in LobeChat, an open-source large language model, in LobeChat with the help of Ollama. Follow these steps to pull and select the Gemma model for natural language processing tasks.
-
+ Easily perform natural language processing tasks with the Google Gemma model
+ through LobeHub's integration with Ollama. Install Ollama, pull the Gemma
+ model, select it from the model panel, and start chatting.
tags:
- Google Gemma
- - LobeChat
+ - LobeHub
- Ollama
- Natural Language Processing
- - Language Model
+ - Model Selection
---
-# Using Google Gemma Model
+# Using the Google Gemma Model
-
- ### Install Ollama locally
+ ### Install Ollama Locally
- First, you need to install Ollama. For the installation process, please refer to the [Ollama usage documentation](/docs/usage/providers/ollama).
+ First, you’ll need to install Ollama. For installation instructions, refer to the [Ollama usage guide](/en/docs/usage/providers/ollama).
- ### Pull Google Gemma model to local using Ollama
+ ### Pull the Google Gemma Model Using Ollama
- After installing Ollama, you can install the Google Gemma model using the following command, using the 7b model as an example:
+ Once Ollama is installed, you can pull the Google Gemma model locally. For example, to pull the 7b model, run the following command:
```bash
ollama pull gemma
```
-
- If you do not see the Ollama provider in the model selection panel, please refer to [Integrating
- with Ollama](/docs/self-hosting/examples/ollama) to learn how to enable the Ollama provider in
- LobeChat.
+ If you don’t see the Ollama provider in the model selection panel, refer to the [Ollama Integration Guide](/en/docs/self-hosting/examples/ollama) to learn how to enable the Ollama provider in LobeHub.
-Now, you can start conversing with the local Gemma model using LobeChat.
+You’re all set! You can now start chatting with the local Gemma model directly in LobeHub.
diff --git a/docs/usage/providers/ollama/gemma.zh-CN.mdx b/docs/usage/providers/ollama/gemma.zh-CN.mdx
index 9fe774c0a9..e2d7ecb148 100644
--- a/docs/usage/providers/ollama/gemma.zh-CN.mdx
+++ b/docs/usage/providers/ollama/gemma.zh-CN.mdx
@@ -1,11 +1,11 @@
---
-title: 在 LobeChat 中使用 Google Gemma 模型
+title: 在 LobeHub 中使用 Google Gemma 模型
description: >-
- 通过 LobeChat 与 Ollama 的集成，轻松使用 Google Gemma 模型进行自然语言处理任务。安装 Ollama，拉取 Gemma 模型，选择模型面板中的 Gemma 模型，开始对话。
-
+ 通过 LobeHub 与 Ollama 的集成，轻松使用 Google Gemma 模型进行自然语言处理任务。安装 Ollama，拉取 Gemma
+ 模型，选择模型面板中的 Gemma 模型，开始对话。
tags:
- Google Gemma
- - LobeChat
+ - LobeHub
- Ollama
- 自然语言处理
- 模型选择
@@ -13,11 +13,11 @@ tags:
# 使用 Google Gemma 模型
-
### 本地安装 Ollama
@@ -32,18 +32,18 @@ tags:
ollama pull gemma
```
-
如果你没有在模型选择面板中看到 Ollama 服务商，请查阅 [与 Ollama
- 集成](/zh/docs/self-hosting/examples/ollama) 了解如何在 LobeChat 中开启 Ollama 服务商。
+ 集成](/zh/docs/self-hosting/examples/ollama) 了解如何在 LobeHub 中开启 Ollama 服务商。
-接下来，你就可以使用 LobeChat 与本地 Gemma 模型对话了。
+接下来，你就可以使用 LobeHub 与本地 Gemma 模型对话了。
diff --git a/docs/usage/providers/ollama/qwen.mdx b/docs/usage/providers/ollama/qwen.mdx
index 12df710767..44324e8893 100644
--- a/docs/usage/providers/ollama/qwen.mdx
+++ b/docs/usage/providers/ollama/qwen.mdx
@@ -1,54 +1,52 @@
---
-title: Using Local Qwen Model in LobeChat
-description: 通过LobeChat和Ollama的集成，您可以轻松在LobeChat中使用Qwen。本文将指导您如何在LobeChat中使用本地部署版本的Qwen。
+title: Using the Local Qwen Model in LobeHub
+description: >-
+ Easily chat with the locally deployed Qwen model through LobeHub's integration
+ with Ollama. Learn how to install and select the Qwen model.
tags:
- Qwen
- - LobeChat
+ - Qwen Model
+ - LobeHub Integration
- Ollama
- - 本地部署
- - AI大模型
+ - Local Deployment
---
# Using the Local Qwen Model
-
- ## Local Installation of Ollama
+ ### Install Ollama Locally
- First, you need to install Ollama. For the installation process, please refer to the [Ollama Usage Document](/docs/usage/providers/ollama).
+ First, you’ll need to install Ollama. For installation instructions, refer to the [Ollama usage guide](/en/docs/usage/providers/ollama).
- ## Pull the Qwen Model to Local with Ollama
+ ### Pull the Qwen Model Using Ollama
- After installing Ollama, you can install the Qwen model with the following command, taking the 14b model as an example:
+ Once Ollama is installed, you can pull the Qwen model locally. For example, to pull the 14b version of the model, run:
```bash
ollama pull qwen:14b
```
-
- The local version of Qwen provides different model sizes to choose from. Please refer to the
- [Qwen's Ollama integration page](https://ollama.com/library/qwen) to understand how to choose the
- model size.
-
-
-
- If you do not see the Ollama provider in the model selection panel, please refer to [Integration with Ollama](/docs/self-hosting/examples/ollama) to learn how to enable the Ollama provider in LobeChat.
+ If you don’t see the Ollama provider in the model selection panel, refer to the [Ollama Integration Guide](/en/docs/self-hosting/examples/ollama) to learn how to enable the Ollama provider in LobeHub.
-Next, you can have a conversation with the local Qwen model in LobeChat.
+You’re now ready to start chatting with the local Qwen model in LobeHub.
diff --git a/docs/usage/providers/ollama/qwen.zh-CN.mdx b/docs/usage/providers/ollama/qwen.zh-CN.mdx
index da13ad753c..149cb3b331 100644
--- a/docs/usage/providers/ollama/qwen.zh-CN.mdx
+++ b/docs/usage/providers/ollama/qwen.zh-CN.mdx
@@ -1,25 +1,25 @@
---
-title: 在 LobeChat 中使用本地通义千问 Qwen 模型
-description: 通过 LobeChat 与 Ollama 的集成，轻松在本地部署的通义千问 Qwen 模型中进行对话。学习如何安装和选择 Qwen 模型。
+title: 在 LobeHub 中使用本地通义千问 Qwen 模型
+description: 通过 LobeHub 与 Ollama 的集成，轻松在本地部署的通义千问 Qwen 模型中进行对话。学习如何安装和选择 Qwen 模型。
tags:
- 通义千问
- Qwen模型
- - LobeChat集成
+ - LobeHub集成
- Ollama
- 本地部署
---
# 使用本地通义千问 Qwen 模型
-
### 本地安装 Ollama
@@ -34,18 +34,18 @@ tags:
ollama pull qwen:14b
```
-
如果你没有在模型选择面板中看到 Ollama 服务商，请查阅 [与 Ollama
- 集成](/zh/docs/self-hosting/examples/ollama) 了解如何在 LobeChat 中开启 Ollama 服务商。
+ 集成](/zh/docs/self-hosting/examples/ollama) 了解如何在 LobeHub 中开启 Ollama 服务商。
-接下来，你就可以使用 LobeChat 与本地 Qwen 模型对话了。
+接下来，你就可以使用 LobeHub 与本地 Qwen 模型对话了。
diff --git a/docs/usage/providers/openai.mdx b/docs/usage/providers/openai.mdx
index 4bd8204644..6c457646e9 100644
--- a/docs/usage/providers/openai.mdx
+++ b/docs/usage/providers/openai.mdx
@@ -1,10 +1,9 @@
---
-title: Using OpenAI API Key in LobeChat
+title: Using OpenAI API Key in LobeHub
description: >-
- Learn how to integrate OpenAI API Key in LobeChat. Support GPT-4o / GPT-4-turbo / GPT-4-vision
-
+ Learn how to configure and use your OpenAI API Key in LobeHub, supporting
+ GPT-4o / GPT-4-turbo / GPT-4-vision
tags:
- - OpenAI
- ChatGPT
- GPT-4
- GPT-4o
@@ -12,43 +11,43 @@ tags:
- Web UI
---
-# Using OpenAI in LobeChat
+# Using OpenAI in LobeHub
-
- ### Step 1: Obtain OpenAI API Key
+ ### Step 1: Get Your OpenAI API Key
- - Register for an [OpenAI account](https://platform.openai.com/signup). You will need to register using an international phone number and a non-mainland email address.
+ - Sign up for an [OpenAI account](https://platform.openai.com/signup). You’ll need an international phone number and a non-mainland China email address.
- - After registration, go to the [API Keys](https://platform.openai.com/api-keys) page and click on `Create new secret key` to generate a new API Key.
+ - After signing up, go to the [API Keys](https://platform.openai.com/api-keys) page and click `Create new secret key` to generate a new API key:
- - Open the creation window
+ - Open the key creation window
- After registering, you generally have a free credit of $5, but it is only valid for three months.
+ New accounts typically receive $5 in free credits, valid for three months.
- ### Step 2: Configure OpenAI in LobeChat
+ ### Step 2: Configure OpenAI in LobeHub
- - Visit the `Settings` page in LobeChat
- - Find the setting for `OpenAI` under `AI Service Provider`
+ - Open the `Settings` panel in LobeHub
+ - Under `AI Providers`, locate the `OpenAI` section
-
- During usage, you may need to pay the API service provider. Please refer to OpenAI's relevant
- pricing policies.
+ You may incur charges while using the API. Please refer to OpenAI’s pricing policy for details.
-You can now engage in conversations using the models provided by OpenAI in LobeChat.
+That’s it! You’re now ready to use OpenAI models in LobeHub for conversations.
diff --git a/docs/usage/providers/openai.zh-CN.mdx b/docs/usage/providers/openai.zh-CN.mdx
index 1ffd2ce189..dfa7d3628a 100644
--- a/docs/usage/providers/openai.zh-CN.mdx
+++ b/docs/usage/providers/openai.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 OpenAI API Key
-description: 学习如何在 LobeChat 中配置和使用 OpenAI API Key，支持 GPT-4o / GPT-4-turbo / GPT-4-vision
+title: 在 LobeHub 中使用 OpenAI API Key
+description: 学习如何在 LobeHub 中配置和使用 OpenAI API Key，支持 GPT-4o / GPT-4-turbo / GPT-4-vision
tags:
- ChatGPT
- GPT-4
@@ -9,11 +9,11 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 OpenAI
+# 在 LobeHub 中使用 OpenAI
-
### 步骤一：获取 OpenAI API 密钥
@@ -54,21 +54,21 @@ tags:
账户注册后，一般有 5 美元的免费额度，但有效期只有三个月。
- ### 步骤二：在 LobeChat 中配置 OpenAI
+ ### 步骤二：在 LobeHub 中配置 OpenAI
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到`OpenAI`的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 OpenAI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 OpenAI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 OpenAI 提供的模型进行对话了。
diff --git a/docs/usage/providers/openrouter.mdx b/docs/usage/providers/openrouter.mdx
index 15e1e79963..d0c6ddb8c0 100644
--- a/docs/usage/providers/openrouter.mdx
+++ b/docs/usage/providers/openrouter.mdx
@@ -1,73 +1,70 @@
---
-title: Using OpenRouter API Key in LobeChat
+title: Using OpenRouter API Key in LobeHub
description: >-
- Learn how to integrate and utilize OpenRouter's language model APIs in LobeChat. Follow these steps to register, create an API key, recharge credit, and configure OpenRouter for seamless conversations.
-
+ Learn how to register, create an API key, add credit, and configure OpenRouter
+ in LobeHub to start using a variety of powerful large language model APIs.
tags:
- OpenRouter
- - LobeChat
- API Key
- Web UI
---
-# Using OpenRouter in LobeChat
+# Using OpenRouter in LobeHub
-
- ### Step 1: Register and Log in to OpenRouter
+ ### Step 1: Register and Log In to OpenRouter
- - Visit [OpenRouter.ai](https://openrouter.ai/) and create an account
- - You can log in using your Google account or MetaMask wallet
+ - Visit [OpenRouter.ai](https://openrouter.ai/) and create an account.
+ - You can log in using your Google account or MetaMask wallet.
-
- Please store the key securely as it will only appear once. If you lose it accidentally, you will
- need to create a new key.
+ Make sure to store your API key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 3: Recharge Credit
+ ### Step 3: Add Credit to Your Account
- - Go to the `Credit` menu or visit [OpenRouter Credit](https://openrouter.ai/credits) directly
- - Click on `Manage Credits` to recharge your credit, you can check model prices at [https://openrouter.ai/models](https://openrouter.ai/models)
- - OpenRouter provides some free models that can be used without recharging
+ - Go to the `Credit` section or visit [OpenRouter Credit](https://openrouter.ai/credits).
+ - Click `Manage Credits` to add funds. You can view model pricing at [https://openrouter.ai/models](https://openrouter.ai/models).
+ - OpenRouter also offers some free models that can be used without adding credit.
-
- You may need to pay the API service provider during usage, please refer to OpenRouter's relevant
- fee policies.
+ You may incur charges when using API services. Please refer to OpenRouter’s pricing policy for more details.
-You can now engage in conversations using the models provided by OpenRouter in LobeChat.
+You’re now ready to start using OpenRouter’s models in LobeHub for conversations.
diff --git a/docs/usage/providers/openrouter.zh-CN.mdx b/docs/usage/providers/openrouter.zh-CN.mdx
index bb0b368c1f..daadd5bbbe 100644
--- a/docs/usage/providers/openrouter.zh-CN.mdx
+++ b/docs/usage/providers/openrouter.zh-CN.mdx
@@ -1,19 +1,19 @@
---
-title: 在 LobeChat 中使用 OpenRouter API Key
-description: 学习如何在 LobeChat 中注册、创建 API Key、充值信用额度并配置 OpenRouter，以便开始使用多种优秀大语言模型 API。
+title: 在 LobeHub 中使用 OpenRouter API Key
+description: 学习如何在 LobeHub 中注册、创建 API Key、充值信用额度并配置 OpenRouter，以便开始使用多种优秀大语言模型 API。
tags:
- OpenRouter
- API Key
- Web UI
---
-# 在 LobeChat 中使用 OpenRouter
+# 在 LobeHub 中使用 OpenRouter
-
### 步骤一：注册 OpenRouter 账号并登录
@@ -21,20 +21,20 @@ tags:
- 访问 [OpenRouter.ai](https://openrouter.ai/) 并创建一个账号
- 你可以用 Google 账号或 MetaMask 钱包登录
-
请安全地存储密钥，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新密钥。
@@ -46,23 +46,23 @@ tags:
- 点击 `Manage Credits` 充值信用额度，在 [https://openrouter.ai/models](https://openrouter.ai/models) 中可以查看模型价格
- OpenRouter 提供了一些免费模型，未充值的情况下可以使用
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 OpenRouter 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 OpenRouter 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 OpenRouter 提供的模型进行对话了。
diff --git a/docs/usage/providers/perplexity.mdx b/docs/usage/providers/perplexity.mdx
index c4953135e1..1c31a382dd 100644
--- a/docs/usage/providers/perplexity.mdx
+++ b/docs/usage/providers/perplexity.mdx
@@ -1,44 +1,43 @@
---
-title: Using Perplexity AI API Key in LobeChat
+title: Using the Perplexity AI API Key in LobeHub
description: >-
- Learn how to integrate and use Perplexity AI in LobeChat to enhance your AI assistant's capabilities.
-
+ Learn how to configure and use Perplexity AI in LobeHub, obtain your API key,
+ and choose the right language model to start chatting.
tags:
- Perplexity AI
- API key
- Web UI
---
-# Using Perplexity AI in LobeChat
+# Using Perplexity AI in LobeHub
-
- ### Step 1: Obtain Perplexity AI API Key
+ ### Step 1: Get Your Perplexity AI API Key
- Create a [Perplexity AI](https://www.perplexity.ai/) account
- - Obtain your [API key](https://www.perplexity.ai/settings/api)
+ - Retrieve your [API key](https://www.perplexity.ai/settings/api)
-
- During usage, you may need to pay the API service provider. Please refer to Perplexity AI's
- relevant pricing policies.
+ You may incur charges from the API provider while using the service. Please refer to Perplexity AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Perplexity AI in LobeChat.
+And that’s it! You’re now ready to start chatting with models powered by Perplexity AI in LobeHub.
diff --git a/docs/usage/providers/perplexity.zh-CN.mdx b/docs/usage/providers/perplexity.zh-CN.mdx
index f14e4cf4c7..ac0faead63 100644
--- a/docs/usage/providers/perplexity.zh-CN.mdx
+++ b/docs/usage/providers/perplexity.zh-CN.mdx
@@ -1,17 +1,17 @@
---
-title: 在 LobeChat 中使用 Perplexity AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Perplexity AI，获取 API 密钥并选择适合的语言模型开始对话。
+title: 在 LobeHub 中使用 Perplexity AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Perplexity AI，获取 API 密钥并选择适合的语言模型开始对话。
tags:
- Perplexity AI
- API key
- Web UI
---
-# 在 LobeChat 中使用 Perplexity AI
+# 在 LobeHub 中使用 Perplexity AI
-
### 步骤一：获取 Perplexity AI API 密钥
@@ -19,23 +19,23 @@ Perplexity AI API 现在可供所有人使用，本文档将指导你如何在 L
- 创建一个 [Perplexity AI](https://www.perplexity.ai/) 帐户
- 获取您的 [API 密钥](https://www.perplexity.ai/settings/api)
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Perplexity AI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Perplexity AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Perplexity AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/ppio.mdx b/docs/usage/providers/ppio.mdx
index d2929b8cea..64e0b4e482 100644
--- a/docs/usage/providers/ppio.mdx
+++ b/docs/usage/providers/ppio.mdx
@@ -1,56 +1,55 @@
---
-title: Using PPIO API Key in LobeChat
+title: Using PPIO API Key in LobeHub
description: >-
- Learn how to integrate PPIO's language model APIs into LobeChat. Follow the steps to register, create an PPIO API key, configure settings, and chat with our various AI models.
-
+ Learn how to integrate PPIO's LLM API into LobeHub. Follow these steps to
+ register a PPIO account, create an API key, and configure it in LobeHub.
tags:
- PPIO
+ - PPInfra
- DeepSeek
- - Llama
- Qwen
- - uncensored
+ - Llama3
- API key
- Web UI
---
-# Using PPIO in LobeChat
+# Using PPIO in LobeHub
-
- ### Step 1: Register and Log in to PPIO
+ ### Step 1: Register and Log In to PPIO
- - Visit [PPIO](https://ppinfra.com/user/register?invited_by=RQIMOC\&utm_source=github_lobechat) and create an account
- - Upon registration, PPIO will provide a ￥5 credit (about 5M tokens).
+ - Visit [PPIO](https://ppinfra.com/user/register?invited_by=RQIMOC\&utm_source=github_LobeHub) and sign up for an account.
+ - Upon registration, PPIO will grant you a free credit of ¥5 (approximately 5 million tokens).
-
- During usage, you may need to pay the API service provider, please refer to PPIO's [pricing
- policy](https://ppinfra.com/llm-api?utm_source=github_lobe-chat\&utm_medium=github_readme\&utm_campaign=link).
+ You may incur charges when using the API services. For pricing details, refer to the official [PPIO pricing page](https://ppinfra.com/llm-api?utm_source=github_lobe-chat\&utm_medium=github_readme\&utm_campaign=link).
-You can now engage in conversations using the models provided by PPIO in LobeChat.
+That's it! You're now ready to use PPIO's models for conversations in LobeHub.
diff --git a/docs/usage/providers/ppio.zh-CN.mdx b/docs/usage/providers/ppio.zh-CN.mdx
index bafc0c2127..c248f86f61 100644
--- a/docs/usage/providers/ppio.zh-CN.mdx
+++ b/docs/usage/providers/ppio.zh-CN.mdx
@@ -1,8 +1,8 @@
---
-title: 在 LobeChat 中使用 PPIO 派欧云 API Key
+title: 在 LobeHub 中使用 PPIO 派欧云 API Key
description: >-
- 学习如何将 PPIO 派欧云的 LLM API 集成到 LobeChat 中。跟随以下步骤注册 PPIO 账号、创建 API Key、并在 LobeChat 中进行设置。
-
+ 学习如何将 PPIO 派欧云的 LLM API 集成到 LobeHub 中。跟随以下步骤注册 PPIO 账号、创建 API Key、并在 LobeHub
+ 中进行设置。
tags:
- PPIO
- PPInfra
@@ -13,43 +13,43 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用 PPIO 派欧云
+# 在 LobeHub 中使用 PPIO 派欧云
-
### 步骤一：注册 PPIO 派欧云账号并登录
- - 访问 [PPIO 派欧云](https://ppinfra.com/user/register?invited_by=RQIMOC\&utm_source=github_lobechat) 并注册账号
+ - 访问 [PPIO 派欧云](https://ppinfra.com/user/register?invited_by=RQIMOC\&utm_source=github_LobeHub) 并注册账号
- 注册后，PPIO 会赠送 5 元（约 500 万 tokens）的使用额度
-
在使用过程中你可能需要向 API 服务提供商付费，PPIO 的 API 费用参考[这里](https://ppinfra.com/llm-api?utm_source=github_lobe-chat\&utm_medium=github_readme\&utm_campaign=link)。
-至此你已经可以在 LobeChat 中使用 PPIO 派欧云提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 PPIO 派欧云提供的模型进行对话了。
diff --git a/docs/usage/providers/qiniu.mdx b/docs/usage/providers/qiniu.mdx
index 37f29a625d..c2e8591457 100644
--- a/docs/usage/providers/qiniu.mdx
+++ b/docs/usage/providers/qiniu.mdx
@@ -1,58 +1,57 @@
---
-title: Using Qiniu API Key in LobeChat
+title: Using Qiniu Cloud's Large Language Model API Key in LobeHub
description: >-
- Learn how to integrate and utilize powerful language models developed by Qiniu into LobeChat for various tasks. Follow the steps to obtain an API key and configure it for seamless interaction.
-
+ Learn how to configure and use Qiniu Cloud's large language models in LobeHub
+ to enable powerful natural language understanding and generation.
tags:
- API key
- Web UI
- - 七牛
- - 七牛云
- - 七牛智能
- Qiniu
+ - Qiniu Cloud
+ - Qiniu AI
- DeepSeek
---
-# Using Qiniu's AI Models in LobeChat
+# Using Qiniu Cloud's Large Language Model in LobeHub
-
- ### Step 1: [Obtain AI Model API Key](https://developer.qiniu.com/aitokenapi/12884/how-to-get-api-key)
+ ### Step 1: [Obtain Your AI Model API Key](https://developer.qiniu.com/aitokenapi/12884/how-to-get-api-key)
- - Method 1: Using Console
+ - Method 1: Get it via the Console
1. [Register a Qiniu account](https://s.qiniu.com/umqq6n?ref=developer.qiniu.com\&s_path=%2Faitokenapi%2F12884%2Fhow-to-get-api-key)
- 2. [Go to the console to obtain your API Key](https://portal.qiniu.com/ai-inference/api-key)
-
- During usage, you may need to pay the API service provider. Please refer to [Qiniu's relevant pricing policies](https://developer.qiniu.com/aitokenapi/12898/ai-token-api-pricing).
+ You may incur charges from the API service provider during usage. Please refer to [Qiniu Cloud's pricing policy](https://developer.qiniu.com/aitokenapi/12898/ai-token-api-pricing) for details.
-You can now engage in conversations using the models provided by Qiniu in LobeChat.
+That's it! You're now ready to use Qiniu Cloud's large language models in LobeHub for intelligent conversations.
diff --git a/docs/usage/providers/qiniu.zh-CN.mdx b/docs/usage/providers/qiniu.zh-CN.mdx
index 2bba25631f..04bd9d50c7 100644
--- a/docs/usage/providers/qiniu.zh-CN.mdx
+++ b/docs/usage/providers/qiniu.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用七牛云大模型 API Key
-description: 学习如何在 LobeChat 中配置和使用七牛云的大模型，提供强大的自然语言理解和生成能力。
+title: 在 LobeHub 中使用七牛云大模型 API Key
+description: 学习如何在 LobeHub 中配置和使用七牛云的大模型，提供强大的自然语言理解和生成能力。
tags:
- API key
- Web UI
@@ -11,13 +11,13 @@ tags:
- DeepSeek
---
-# 在 LobeChat 中使用七牛云大模型
+# 在 LobeHub 中使用七牛云大模型
-
### 步骤一：[获取 AI 大模型 API 密钥](https://developer.qiniu.com/aitokenapi/12884/how-to-get-api-key)
@@ -36,9 +36,9 @@ tags:
5. 进入【AI 推理】
6. 查看和复制你的 API 密钥
- ### 步骤二：在 LobeChat 中配置七牛云大模型服务
+ ### 步骤二：在 LobeHub 中配置七牛云大模型服务
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到`七牛云`的设置项
-至此你已经可以在 LobeChat 中使用七牛云提供的大模型进行对话了。
+至此你已经可以在 LobeHub 中使用七牛云提供的大模型进行对话了。
diff --git a/docs/usage/providers/qwen.mdx b/docs/usage/providers/qwen.mdx
index 6f946df8c5..2fffefa1ce 100644
--- a/docs/usage/providers/qwen.mdx
+++ b/docs/usage/providers/qwen.mdx
@@ -1,64 +1,63 @@
---
-title: Using Qwen2 API Key in LobeChat
+title: Using Tongyi Qianwen API Key in LobeHub
description: >-
- Learn how to integrate and utilize Tongyi Qianwen, a powerful language model by Alibaba Cloud, in LobeChat for various tasks. Follow the steps to activate the service, obtain the API key, and configure Tongyi Qianwen for seamless interaction.
-
+ Learn how to configure and use Alibaba Cloud's Tongyi Qianwen model in
+ LobeHub, offering powerful natural language understanding and generation
+ capabilities.
tags:
+ - LobeHub
- Tongyi Qianwen
- - Alibaba Cloud
- DashScope
- API key
- Web UI
---
-# Using Tongyi Qianwen in LobeChat
+# Using Tongyi Qianwen in LobeHub
-
- ### Step 1: Activate DashScope Model Service
+ ### Step 1: Enable the DashScope Model Service
- - Visit and log in to Alibaba Cloud's [DashScope](https://dashscope.console.aliyun.com/) platform.
- - If it is your first time, you need to activate the DashScope service.
- - If you have already activated it, you can skip this step.
+ - Visit and log in to the [DashScope](https://dashscope.console.aliyun.com/) platform by Alibaba Cloud.
+ - If this is your first time, you’ll need to activate the DashScope service.
+ - If you’ve already enabled it, you can skip this step.
-
- Please store the key securely as it will only appear once. If you accidentally lose it, you will
- need to create a new key.
+ Make sure to store your API key securely, as it will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 3: Configure Tongyi Qianwen in LobeChat
+ ### Step 3: Configure Tongyi Qianwen in LobeHub
- - Visit the `Settings` interface in LobeChat.
- - Find the setting for `Tongyi Qianwen` under `AI Service Provider`.
+ - Open the Settings panel in LobeHub.
+ - Under AI Providers, locate the configuration section for Tongyi Qianwen.
-
- During usage, you may need to pay the API service provider. Please refer to Tongyi Qianwen's
- relevant pricing policies.
+ Please note that usage may incur charges from the API provider. Refer to Tongyi Qianwen’s pricing policy for details.
-You can now engage in conversations using the models provided by Tongyi Qianwen in LobeChat.
+You’re all set! You can now start using Tongyi Qianwen’s models in LobeHub for intelligent conversations.
diff --git a/docs/usage/providers/qwen.zh-CN.mdx b/docs/usage/providers/qwen.zh-CN.mdx
index 7dd95be765..f32f9fbe69 100644
--- a/docs/usage/providers/qwen.zh-CN.mdx
+++ b/docs/usage/providers/qwen.zh-CN.mdx
@@ -1,8 +1,8 @@
---
-title: 在 LobeChat 中使用通义千问 API Key
-description: 学习如何在 LobeChat 中配置和使用阿里云的通义千问模型，提供强大的自然语言理解和生成能力。
+title: 在 LobeHub 中使用通义千问 API Key
+description: 学习如何在 LobeHub 中配置和使用阿里云的通义千问模型，提供强大的自然语言理解和生成能力。
tags:
- - LobeChat
+ - LobeHub
- 通义千问
- DashScope
- DashScope
@@ -10,13 +10,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用通义千问
+# 在 LobeHub 中使用通义千问
-
### 步骤一：开通 DashScope 模型服务
@@ -25,37 +25,37 @@ tags:
- 初次进入时需要开通 DashScope 服务
- 若你已开通，可跳过该步骤
-
请安全地存储密钥，因为它只会出现一次。如果您意外丢失它，您将需要创建一个新密钥。
- ### 步骤三：在 LobeChat 中配置通义千问
+ ### 步骤三：在 LobeHub 中配置通义千问
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到`通义千问`的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考通义千问的相关费用政策。
-至此你已经可以在 LobeChat 中使用通义千问提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用通义千问提供的模型进行对话了。
diff --git a/docs/usage/providers/sambanova.mdx b/docs/usage/providers/sambanova.mdx
index 50f2c48084..31f2479a0c 100644
--- a/docs/usage/providers/sambanova.mdx
+++ b/docs/usage/providers/sambanova.mdx
@@ -1,51 +1,52 @@
---
-title: Using SambaNova API Key in LobeChat
-description: Learn how to configure and use SambaNova models in LobeChat, obtain an API key, and start a conversation.
+title: Using the SambaNova API Key in LobeHub
+description: >-
+ Learn how to configure and use SambaNova models in LobeHub, obtain your API
+ key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- SambaNova
- API Key
- Web UI
---
-# Using SambaNova in LobeChat
+# Using SambaNova in LobeHub
-
### Step 1: Obtain a SambaNova API Key
- - First, you need to register and log in to [SambaNova Cloud](https://cloud.sambanova.ai/)
- - Create an API key in the `APIs` page
+ - First, sign up and log in to [SambaNova Cloud](https://cloud.sambanova.ai/)
+ - Navigate to the `APIs` page and create a new API key
-
- Please save the generated API Key securely, as it will only appear once. If you accidentally lose
- it, you will need to create a new API key.
+ Make sure to save your API key securely. It will only be shown once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure SambaNova in LobeChat
+ ### Step 2: Configure SambaNova in LobeHub
- - Access the `Application Settings` interface of LobeChat
- - Find the `SambaNova` setting item under `AI Service Provider`
+ - Go to the `App Settings` section in LobeHub
+ - Under `AI Providers`, locate the `SambaNova` configuration option
-
- You may need to pay the API service provider during use, please refer to SambaNova's related fee policies.
+ Please note that you may incur charges from the API provider. Refer to SambaNova’s pricing policy for more details.
-Now you can use the models provided by SambaNova in LobeChat to conduct conversations.
+You're now ready to start chatting with models powered by SambaNova in LobeHub.
diff --git a/docs/usage/providers/sambanova.zh-CN.mdx b/docs/usage/providers/sambanova.zh-CN.mdx
index 0412ab0cdb..75443ce7b3 100644
--- a/docs/usage/providers/sambanova.zh-CN.mdx
+++ b/docs/usage/providers/sambanova.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 SambaNova API Key
-description: 学习如何在 LobeChat 中配置和使用 SambaNova 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 SambaNova API Key
+description: 学习如何在 LobeHub 中配置和使用 SambaNova 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- SambaNova
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 SambaNova
+# 在 LobeHub 中使用 SambaNova
-
### 步骤一：获取 SambaNova API 密钥
@@ -22,7 +22,7 @@ tags:
- 首先，你需要注册并登录 [SambaNova Cloud](https://cloud.sambanova.ai/)
- 在 `APIs` 页面中创建一个 API 密钥
-
- ### 步骤二：在 LobeChat 中配置 SambaNova
+ ### 步骤二：在 LobeHub 中配置 SambaNova
- - 访问 LobeChat 的 `应用设置`界面
+ - 访问 LobeHub 的 `应用设置`界面
- 在 `AI 服务商` 下找到 `SambaNova` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 SambaNova 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 SambaNova 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 SambaNova 提供的模型进行对话了。
diff --git a/docs/usage/providers/sensenova.mdx b/docs/usage/providers/sensenova.mdx
index 22712e388e..1d09226654 100644
--- a/docs/usage/providers/sensenova.mdx
+++ b/docs/usage/providers/sensenova.mdx
@@ -1,58 +1,56 @@
---
-title: Using SenseNova in LobeChat
+title: Using SenseTime SenseNova in LobeHub
description: >-
- Learn how to configure and use SenseNova's API Key in LobeChat to start conversations and interactions.
-
+ Learn how to configure and use your SenseTime SenseNova API Key in LobeHub to
+ start chatting and interacting.
tags:
- - LobeChat
- - SenseNova
+ - LobeHub
+ - SenseTime SenseNova
- API Key
- Web UI
---
-# Using SenseNova in LobeChat
+# Using SenseTime SenseNova in LobeHub
-
- ### Step 1: Obtain the API Key for SenseNova
+ ### Step 1: Obtain Your SenseNova API Key
- - Register and log in to the [SenseCore Development Platform](https://www.sensecore.cn/product/aistudio).
- - Locate the `SenseNova Large Model` in the product menu and activate the service.
+ - Register and log in to the [SenseCore AI Studio](https://www.sensecore.cn/product/aistudio)
+ - In the product menu, locate and activate the `SenseNova Large Model` service
-
- Please keep the access key from the pop-up window secure, as it will only appear once. If you lose
- it, you will need to create a new access key.
+ Make sure to save the access key shown in the pop-up window. It will only be displayed once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure SenseNova in LobeChat
+ ### Step 2: Configure SenseNova in LobeHub
- - Access the `Settings` interface on LobeChat.
- - Find the setting for `SenseNova` under `AI Service Provider`.
+ - Open the `Settings` panel in LobeHub
+ - Under `AI Providers`, find the configuration section for `SenseTime SenseNova`
-
- During usage, you may need to pay the API service provider, please refer to the relevant fee
- policy for SenseNova.
+ You may incur charges when using the API services. Please refer to SenseNova’s pricing policy for more details.
-You can now have conversations using the models provided by SenseNova in LobeChat.
+And that’s it! You’re now ready to use SenseTime SenseNova models in LobeHub for intelligent conversations.
diff --git a/docs/usage/providers/sensenova.zh-CN.mdx b/docs/usage/providers/sensenova.zh-CN.mdx
index 7b96ed715e..133ab1f939 100644
--- a/docs/usage/providers/sensenova.zh-CN.mdx
+++ b/docs/usage/providers/sensenova.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用商汤日日新
-description: 学习如何在 LobeChat 中配置和使用商汤日日新的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用商汤日日新
+description: 学习如何在 LobeHub 中配置和使用商汤日日新的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 商汤日日新
- API密钥
- Web UI
---
-# 在 LobeChat 中使用商汤日日新
+# 在 LobeHub 中使用商汤日日新
-
### 步骤一：获取商汤日日新的 API 密钥
@@ -22,33 +22,33 @@ tags:
- 注册并登录 [万象模型开发平台](https://www.sensecore.cn/product/aistudio)
- 在产品菜单中找到 `日日新大模型` 并开通服务
-
妥善保存弹窗中的访问密钥，它只会出现一次，如果不小心丢失了，你需要重新创建一个访问密钥。
- ### 步骤二：在 LobeChat 中配置商汤日日新
+ ### 步骤二：在 LobeHub 中配置商汤日日新
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `商汤日日新` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考商汤日日新的相关费用政策。
-至此你已经可以在 LobeChat 中使用商汤日日新提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用商汤日日新提供的模型进行对话了。
diff --git a/docs/usage/providers/siliconcloud.mdx b/docs/usage/providers/siliconcloud.mdx
index f6a12644a3..5b62c2d50e 100644
--- a/docs/usage/providers/siliconcloud.mdx
+++ b/docs/usage/providers/siliconcloud.mdx
@@ -1,48 +1,47 @@
---
-title: Using SiliconCloud in LobeChat
+title: Using SiliconCloud in LobeHub
description: >-
- Learn how to integrate and utilize SiliconCloud's language model APIs in LobeChat.
-
+ Learn how to configure and use SiliconCloud's API Key in LobeHub to start
+ chatting and interacting.
tags:
- - LobeChat
+ - LobeHub
- SiliconCloud
- API Key
- Web UI
---
-# Using SiliconCloud in LobeChat
+# Using SiliconCloud in LobeHub
-
- ### Step 1: Obtain the API Key from SiliconCloud
+ ### Step 1: Obtain an API Key from SiliconCloud
- - Sign up and log in to [SiliconCloud](https://cloud.siliconflow.cn/account/ak)
- - Click on the `API Keys` menu on the left side
- - Create an API Key and copy it
+ - Register and log in to [SiliconCloud](https://cloud.siliconflow.cn/account/ak)
+ - Click on the `API Key` menu on the left sidebar
+ - Create a new API key and copy it
-
- During usage, you may need to pay the API service provider, so please refer to SiliconCloud's
- relevant pricing policy.
+ You may need to pay the API service provider during usage. Please refer to SiliconCloud’s pricing policy for details.
-At this point, you can start chatting using the models provided by SiliconCloud in LobeChat.
+That's it! You're now ready to use SiliconCloud's models for conversations in LobeHub.
diff --git a/docs/usage/providers/siliconcloud.zh-CN.mdx b/docs/usage/providers/siliconcloud.zh-CN.mdx
index 270a689ac4..911caf5ed3 100644
--- a/docs/usage/providers/siliconcloud.zh-CN.mdx
+++ b/docs/usage/providers/siliconcloud.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 SiliconCloud
-description: 学习如何在 LobeChat 中配置和使用 SiliconCloud 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 SiliconCloud
+description: 学习如何在 LobeHub 中配置和使用 SiliconCloud 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- SiliconCloud
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 SiliconCloud
+# 在 LobeHub 中使用 SiliconCloud
-
### 步骤一：获得 SiliconCloud 的 API Key
@@ -23,23 +23,23 @@ tags:
- 点击左侧 `API 密钥` 菜单
- 创建一个 API 密钥并复制
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 SiliconCloud 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 SiliconCloud 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 SiliconCloud 提供的模型进行对话了。
diff --git a/docs/usage/providers/spark.mdx b/docs/usage/providers/spark.mdx
index 948da8098a..676e3eba37 100644
--- a/docs/usage/providers/spark.mdx
+++ b/docs/usage/providers/spark.mdx
@@ -1,51 +1,51 @@
---
-title: Using iFLYTEK Spark in LobeChat
-description: Learn how to integrate and utilize iFLYTEK's Spark model APIs in LobeChat.
+title: Using iFLYTEK Spark in LobeHub
+description: >-
+ Learn how to configure and use the iFLYTEK Spark API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
- - iFLYTEK
- - Spark
+ - LobeHub
+ - iFLYTEK Spark
- API Key
- Web UI
---
-# Using iFLYTEK Spark in LobeChat
+# Using iFLYTEK Spark in LobeHub
-
- ### Step 1: Obtain the iFLYTEK Spark API Key
+ ### Step 1: Obtain an API Key for iFLYTEK Spark
- Register and log in to the [iFLYTEK Open Platform](https://console.xfyun.cn/)
- - Create an application
+ - Create a new application
-
- During usage, you may need to pay the API service provider, please refer to the relevant pricing
- policy of iFLYTEK Spark.
+ You may need to pay for API usage depending on your usage level. Please refer to iFLYTEK Spark's pricing policy for more details.
-Now you can use the models provided by iFLYTEK Spark for conversations in LobeChat.
+That's it! You're now ready to use iFLYTEK Spark's models for conversations in LobeHub.
diff --git a/docs/usage/providers/spark.zh-CN.mdx b/docs/usage/providers/spark.zh-CN.mdx
index 7498a78c59..ecd618d5e8 100644
--- a/docs/usage/providers/spark.zh-CN.mdx
+++ b/docs/usage/providers/spark.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用讯飞星火
-description: 学习如何在 LobeChat 中配置和使用讯飞星火的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用讯飞星火
+description: 学习如何在 LobeHub 中配置和使用讯飞星火的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 讯飞星火
- API密钥
- Web UI
---
-# 在 LobeChat 中使用讯飞星火
+# 在 LobeHub 中使用讯飞星火
-
### 步骤一：获得讯飞星火的 API Key
@@ -22,28 +22,28 @@ tags:
- 注册并登录 [讯飞开放平台](https://console.xfyun.cn/)
- 创建一个应用
-
在使用过程中你可能需要向 API 服务提供商付费，请参考讯飞星火的相关费用政策。
-至此你已经可以在 LobeChat 中使用讯飞星火提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用讯飞星火提供的模型进行对话了。
diff --git a/docs/usage/providers/stepfun.mdx b/docs/usage/providers/stepfun.mdx
index 83099426e2..28d18d4ebe 100644
--- a/docs/usage/providers/stepfun.mdx
+++ b/docs/usage/providers/stepfun.mdx
@@ -1,47 +1,46 @@
---
-title: Using Stepfun API Key in LobeChat
+title: Using the Stepfun API Key in LobeHub
description: >-
- Learn how to integrate Stepfun AI models into LobeChat for engaging conversations. Obtain Stepfun API key, configure Stepfun in LobeChat settings, and select a model to start chatting.
-
+ Learn how to configure and use Stepfun's AI models in LobeHub, including how
+ to obtain an API key and select a model to start chatting.
tags:
- Stepfun
- API key
- Web UI
---
-# Using Stepfun in LobeChat
+# Using Stepfun in LobeHub
-
- ### Step 1: Obtain Stepfun API Key
+ ### Step 1: Get Your Stepfun API Key
- - Visit and log in to the [Stepfun Open Platform](https://platform.stepfun.com/)
- - Go to the `API Key` menu, where the system has already created an API key for you
- - Copy the created API key
+ - Visit and log in to the [Stepfun Developer Platform](https://platform.stepfun.com/)
+ - Navigate to the `API Key` section — an API key will be automatically generated for you
+ - Copy the generated API key
-
- During usage, you may need to pay the API service provider, please refer to Stepfun's relevant
- pricing policies.
+ You may need to pay for API usage depending on your usage level. Please refer to Stepfun’s pricing policy for more details.
-You can now use the models provided by Stepfun to have conversations in LobeChat.
+And that’s it! You’re now ready to start chatting with AI models powered by Stepfun in LobeHub.
diff --git a/docs/usage/providers/stepfun.zh-CN.mdx b/docs/usage/providers/stepfun.zh-CN.mdx
index ad74a5d507..fea8cca8ad 100644
--- a/docs/usage/providers/stepfun.zh-CN.mdx
+++ b/docs/usage/providers/stepfun.zh-CN.mdx
@@ -1,19 +1,19 @@
---
-title: 在 LobeChat 中使用 Stepfun 阶跃星辰 API Key
-description: 学习如何在 LobeChat 中配置和使用 Stepfun 阶跃星辰的人工智能模型，包括获取 API Key 和选择模型开始对话。
+title: 在 LobeHub 中使用 Stepfun 阶跃星辰 API Key
+description: 学习如何在 LobeHub 中配置和使用 Stepfun 阶跃星辰的人工智能模型，包括获取 API Key 和选择模型开始对话。
tags:
- Stepfun 阶跃星辰
- API key
- Web UI
---
-# 在 LobeChat 中使用 Stepfun 阶跃星辰
+# 在 LobeHub 中使用 Stepfun 阶跃星辰
-
### 步骤一：获取 Stepfun 阶跃星辰 API 密钥
@@ -22,23 +22,23 @@ tags:
- 进入`接口密钥`菜单，系统已为你创建好 API 密钥
- 复制已创建的 API 密钥
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Stepfun 阶跃星辰的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Stepfun 阶跃星辰提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Stepfun 阶跃星辰提供的模型进行对话了。
diff --git a/docs/usage/providers/taichu.mdx b/docs/usage/providers/taichu.mdx
index a8f20b9d32..4a7db278ee 100644
--- a/docs/usage/providers/taichu.mdx
+++ b/docs/usage/providers/taichu.mdx
@@ -1,45 +1,45 @@
---
-title: Using Taichu API Key in LobeChat
+title: Using Zidong Taichu API Key in LobeHub
description: >-
- Learn how to integrate Taichu AI into LobeChat for enhanced conversational experiences. Follow the steps to configure Taichu AI and start using its models.
-
+ Learn how to configure and use the Zidong Taichu API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
+ - LobeHub
- Taichu
+ - Zidong Taichu
- API Key
- Web UI
---
-# Using Taichu in LobeChat
+# Using Zidong Taichu in LobeHub
-
- ### Step 1: Obtain Taichu API Key
+ ### Step 1: Obtain a Zidong Taichu API Key
- - Create an account on [Taichu](https://ai-maas.wair.ac.cn/)
- - Create and obtain an [API key](https://ai-maas.wair.ac.cn/#/settlement/api/key)
+ - Create a [Zidong Taichu](https://ai-maas.wair.ac.cn/) account
+ - Generate and retrieve your [API Key](https://ai-maas.wair.ac.cn/#/settlement/api/key)
-
- During usage, you may need to pay the API service provider, please refer to Taichu's relevant
- pricing policies.
+ You may need to pay for API usage depending on the provider’s pricing policy. Please refer to Zidong Taichu’s official pricing for details.
-Now you can start conversing with the models provided by Taichu in LobeChat.
+Now you're all set to start using Zidong Taichu models for conversations in LobeHub.
diff --git a/docs/usage/providers/taichu.zh-CN.mdx b/docs/usage/providers/taichu.zh-CN.mdx
index c7149ac10c..f00ef529ec 100644
--- a/docs/usage/providers/taichu.zh-CN.mdx
+++ b/docs/usage/providers/taichu.zh-CN.mdx
@@ -1,19 +1,19 @@
---
-title: 在 LobeChat 中使用紫东太初 API Key
-description: 学习如何在 LobeChat 中配置和使用紫东太初的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用紫东太初 API Key
+description: 学习如何在 LobeHub 中配置和使用紫东太初的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 太初
- 紫东太初
- API密钥
- Web UI
---
-# 在 LobeChat 中使用紫东太初
+# 在 LobeHub 中使用紫东太初
-
### 步骤一：获取紫东太初 API 密钥
@@ -21,23 +21,23 @@ tags:
- 创建一个[紫东太初](https://ai-maas.wair.ac.cn/)账户
- 创建并获取 [API 密钥](https://ai-maas.wair.ac.cn/#/settlement/api/key)
-
在使用过程中你可能需要向 API 服务提供商付费，请参考紫东太初的相关费用政策。
-至此你已经可以在 LobeChat 中使用紫东太初提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用紫东太初提供的模型进行对话了。
diff --git a/docs/usage/providers/tencentcloud.mdx b/docs/usage/providers/tencentcloud.mdx
index 12284f8677..cee36703ea 100644
--- a/docs/usage/providers/tencentcloud.mdx
+++ b/docs/usage/providers/tencentcloud.mdx
@@ -1,49 +1,51 @@
---
-title: Using Tencent Cloud API Key in LobeChat
-description: Learn how to configure and use Tencent Cloud AI models in LobeChat, obtain an API key, and start a conversation.
+title: Using Tencent Cloud API Key in LobeHub
+description: >-
+ Learn how to configure and use Tencent Cloud AI models in LobeHub, obtain your
+ API key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Tencent Cloud
- API Key
- Web UI
---
-# Using Tencent Cloud in LobeChat
+# Using Tencent Cloud in LobeHub
-
- ### Step 1: Obtain the Tencent Cloud API Key
+ ### Step 1: Obtain a Tencent Cloud API Key
- - First, visit [Tencent Cloud](https://cloud.tencent.com/) and complete the registration and login.
- - Enter the Tencent Cloud Console and navigate to [Large-scale Knowledge Engine Atomic Capability](https://console.cloud.tencent.com/lkeap).
- - Activate the Large-scale Knowledge Engine, which requires real-name authentication during the activation process.
+ - First, visit [Tencent Cloud](https://cloud.tencent.com/) and complete the registration and login process.
+ - Go to the Tencent Cloud Console and navigate to the [Atomic Capabilities of Knowledge Engine](https://console.cloud.tencent.com/lkeap).
+ - Enable the Large Model Knowledge Engine. Real-name verification is required during activation.
-
- You may need to pay the API service provider during use, please refer to Tencent Cloud's relevant fee policy.
+ You may incur charges when using services from the API provider. Please refer to Tencent Cloud’s pricing policy for details.
-You can now use the models provided by Tencent Cloud in LobeChat to have conversations.
+That's it! You’re now ready to use Tencent Cloud’s AI models in LobeHub for conversations.
diff --git a/docs/usage/providers/tencentcloud.zh-CN.mdx b/docs/usage/providers/tencentcloud.zh-CN.mdx
index e90d39ecdd..8bad25fd87 100644
--- a/docs/usage/providers/tencentcloud.zh-CN.mdx
+++ b/docs/usage/providers/tencentcloud.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用腾讯云 API Key
-description: 学习如何在 LobeChat 中配置和使用腾讯云 AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用腾讯云 API Key
+description: 学习如何在 LobeHub 中配置和使用腾讯云 AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- 腾讯云
- API密钥
- Web UI
---
-# 在 LobeChat 中使用腾讯云
+# 在 LobeHub 中使用腾讯云
-
### 步骤一：获取腾讯云 API 密钥
@@ -23,27 +23,27 @@ tags:
- 进入腾讯云控制台并导航至[知识引擎原子能力](https://console.cloud.tencent.com/lkeap)
- 开通大模型知识引擎，开通过程需要实名认证
-
在使用过程中你可能需要向 API 服务提供商付费，请参考腾讯云的相关费用政策。
-至此你已经可以在 LobeChat 中使用腾讯云提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用腾讯云提供的模型进行对话了。
diff --git a/docs/usage/providers/togetherai.mdx b/docs/usage/providers/togetherai.mdx
index aebca3be51..82d061f314 100644
--- a/docs/usage/providers/togetherai.mdx
+++ b/docs/usage/providers/togetherai.mdx
@@ -1,50 +1,50 @@
---
-title: Using Together AI in LobeChat API Key
+title: Using the Together AI API Key in LobeHub
description: >-
- Learn how to integrate Together AI into LobeChat, obtain the API key, configure settings, and start conversations with AI models.
-
+ Learn how to configure and use the Together AI API key in LobeHub to start
+ chatting and interacting.
tags:
+ - LobeHub
- Together AI
- - API key
+ - API Key
- Web UI
---
-# Using Together AI in LobeChat
+# Using Together AI in LobeHub
-
- ### Step 1: Obtain the API Key for Together AI
+ ### Step 1: Get Your Together AI API Key
- Visit and log in to [Together AI API](https://api.together.ai/)
- - Upon initial login, the system will automatically create an API key for you and provide a $5.0 credit
+ - Upon your first login, the system will automatically generate an API key for you and grant you a $5.00 free credit
-
- During usage, you may need to pay the API service provider, please refer to Together AI's pricing
- policy.
+ You may need to pay for API usage depending on your usage. Please refer to Together AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Together AI in LobeChat.
+And that’s it! You’re now ready to use Together AI models for conversations in LobeHub.
diff --git a/docs/usage/providers/togetherai.zh-CN.mdx b/docs/usage/providers/togetherai.zh-CN.mdx
index 4396f112e0..851491346e 100644
--- a/docs/usage/providers/togetherai.zh-CN.mdx
+++ b/docs/usage/providers/togetherai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Together AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Together AI 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 Together AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Together AI 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- Together AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Together AI
+# 在 LobeHub 中使用 Together AI
-
### 步骤一：获取 Together AI 的 API 密钥
@@ -22,27 +22,27 @@ tags:
- 访问并登录 [Together AI API](https://api.together.ai/)
- 初次登录时系统会自动为你创建好 API 密钥并赠送 $5.0 的额度
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Together AI 的费用政策。
-至此你已经可以在 LobeChat 中使用 Together AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Together AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/upstage.mdx b/docs/usage/providers/upstage.mdx
index 0e88f4807b..d06ec1f167 100644
--- a/docs/usage/providers/upstage.mdx
+++ b/docs/usage/providers/upstage.mdx
@@ -1,47 +1,48 @@
---
-title: Using Upstage in LobeChat
-description: Learn how to integrate and utilize Upstage's language model APIs in LobeChat.
+title: Using Upstage in LobeHub
+description: >-
+ Learn how to configure and use Upstage's API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
+ - LobeHub
- Upstage
- API Key
- Web UI
---
-# Using Upstage in LobeChat
+# Using Upstage in LobeHub
-
- ### Step 1: Obtain an Upstage API Key
+ ### Step 1: Obtain an API Key from Upstage
- - Register and log in to the [Upstage Console](https://console.upstage.ai/home)
- - Navigate to the `API Keys` page
+ - Sign up and log in to the [Upstage Console](https://console.upstage.ai/home)
+ - Navigate to the `API Keys` section
- Create a new API key
- - Copy and save the generated API key
+ - Copy and securely save the generated API key
-
- Please note that you may need to pay the API service provider for usage. Refer to Upstage's
- pricing policy for more information.
+ You may need to pay for API usage depending on your usage level. Please refer to Upstage’s pricing policy for more details.
-You can now use the models provided by Upstage for conversations in LobeChat.
+And that’s it! You’re now ready to use Upstage’s models for conversations in LobeHub.
diff --git a/docs/usage/providers/upstage.zh-CN.mdx b/docs/usage/providers/upstage.zh-CN.mdx
index c8a251ee71..66c03554c9 100644
--- a/docs/usage/providers/upstage.zh-CN.mdx
+++ b/docs/usage/providers/upstage.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Upstage
-description: 学习如何在 LobeChat 中配置和使用 Upstage 的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 Upstage
+description: 学习如何在 LobeHub 中配置和使用 Upstage 的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- Upstage
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Upstage
+# 在 LobeHub 中使用 Upstage
-
### 步骤一：获得 Upstage 的 API Key
@@ -24,23 +24,23 @@ tags:
- 创建一个新的 API 密钥
- 复制并保存生成的 API 密钥
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Upstage 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Upstage 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Upstage 提供的模型进行对话了。
diff --git a/docs/usage/providers/vercel-ai-gateway.mdx b/docs/usage/providers/vercel-ai-gateway.mdx
index 0454edc4b4..98fc678d13 100644
--- a/docs/usage/providers/vercel-ai-gateway.mdx
+++ b/docs/usage/providers/vercel-ai-gateway.mdx
@@ -1,59 +1,57 @@
---
-title: Using Vercel AI Gateway in LobeChat
-description: >-
- Learn how to integrate and utilize Vercel AI Gateway's unified API in LobeChat.
-
+title: Using Vercel AI Gateway in LobeHub
+description: Learn how to integrate and use the unified API of Vercel AI Gateway in LobeHub
tags:
- - LobeChat
+ - LobeHub
- Vercel AI Gateway
- API Key
- - Web UI
+ - Web Interface
---
-# Using Vercel AI Gateway in LobeChat
+# Using Vercel AI Gateway in LobeHub
-[Vercel AI Gateway](https://vercel.com/ai-gateway) is a unified API that provides access to 100+ AI models through a single endpoint. It offers features like budget management, usage monitoring, load balancing, and fallback handling.
+[Vercel AI Gateway](https://vercel.com/ai-gateway) is a unified API that provides access to over 100 AI models through a single endpoint. It offers features such as budget management, usage monitoring, load balancing, and fallback handling.
-This article will guide you on how to use Vercel AI Gateway in LobeChat.
+This guide will walk you through how to use Vercel AI Gateway within LobeHub.
### Step 1: Create an API Key in Vercel AI Gateway
- - Go to [Vercel Dashboard](https://vercel.com/dashboard)
- - Click on the **AI Gateway** tab on the left side
- - Click on **API keys** in the left sidebar
- - Click **Create key** and then **Create key** in the dialog to complete
+ - Go to the [Vercel Dashboard](https://vercel.com/dashboard)
+ - Click on the **AI Gateway** tab on the left sidebar
+ - Select **API Keys** from the sidebar
+ - Click **Create Key**, then confirm by clicking **Create Key** in the dialog
- ### Step 2: Configure Vercel AI Gateway in LobeChat
+ ### Step 2: Configure Vercel AI Gateway in LobeHub
- - Go to the `Settings` page in LobeChat
- - Under `AI Service Provider`, find the setting for `Vercel AI Gateway`
- - Enter the API Key you obtained
- - Choose a model from Vercel AI Gateway for your AI assistant to start the conversation
+ - Navigate to the `Settings` page in LobeHub
+ - Under `AI Service Provider`, find the `Vercel AI Gateway` section
+ - Enter the API key you obtained
+ - Choose a model from Vercel AI Gateway and start chatting with the AI assistant
- During usage, you may need to pay the API service provider, so please refer to Vercel AI Gateway's
- [pricing policy](https://vercel.com/docs/ai-gateway/models).
+ You may incur charges from the API service provider during usage. Please refer to the
+ [Vercel AI Gateway pricing policy](https://vercel.com/docs/ai-gateway/models) for details.
-At this point, you can start chatting using the models provided by Vercel AI Gateway in LobeChat.
+That's it! You can now start chatting in LobeHub using models provided by Vercel AI Gateway.
## Model Selection
-Vercel AI Gateway supports various model providers including:
+Vercel AI Gateway supports a variety of model providers, including:
-- **OpenAI**: `openai/gpt-4o`, `openai/gpt-4o-mini`, `openai/o1`, etc.
-- **Anthropic**: `anthropic/claude-3-5-sonnet`, `anthropic/claude-3-opus`, etc.
-- **Google**: `google/gemini-2.5-pro`, `google/gemini-2.0-flash`, etc.
-- **DeepSeek**: `deepseek/deepseek-chat`, `deepseek/deepseek-reasoner`, etc.
-- And many more...
+- **OpenAI**: `openai/gpt-4o`, `openai/gpt-4o-mini`, `openai/o1`, and more
+- **Anthropic**: `anthropic/claude-3-5-sonnet`, `anthropic/claude-3-opus`, and more
+- **Google**: `google/gemini-2.5-pro`, `google/gemini-2.0-flash`, and more
+- **DeepSeek**: `deepseek/deepseek-chat`, `deepseek/deepseek-reasoner`, and more
+- And many others...
-For a complete list of supported models, visit [Vercel AI Gateway Models](https://vercel.com/ai-gateway/models).
+To view the full list of supported models, visit the [Vercel AI Gateway Models](https://vercel.com/ai-gateway/models) page.
## API Configuration
-Vercel AI Gateway uses OpenAI-compatible API format. The base URL is:
+Vercel AI Gateway uses an OpenAI-compatible API format. The base URL is:
```
https://ai-gateway.vercel.sh/v1
diff --git a/docs/usage/providers/vercel-ai-gateway.zh-CN.mdx b/docs/usage/providers/vercel-ai-gateway.zh-CN.mdx
index 9d7385fd09..752be46294 100644
--- a/docs/usage/providers/vercel-ai-gateway.zh-CN.mdx
+++ b/docs/usage/providers/vercel-ai-gateway.zh-CN.mdx
@@ -1,19 +1,18 @@
---
-title: 在 LobeChat 中使用 Vercel AI Gateway
-description: 了解如何在 LobeChat 中集成和使用 Vercel AI Gateway 的统一 API
-
+title: 在 LobeHub 中使用 Vercel AI Gateway
+description: 了解如何在 LobeHub 中集成和使用 Vercel AI Gateway 的统一 API
tags:
- - LobeChat
+ - LobeHub
- Vercel AI Gateway
- API 密钥
- Web 界面
---
-# 在 LobeChat 中使用 Vercel AI Gateway
+# 在 LobeHub 中使用 Vercel AI Gateway
[Vercel AI Gateway](https://vercel.com/ai-gateway) 是一个统一的 API，通过单一端点提供对 100+ AI 模型的访问。它提供预算管理、使用监控、负载均衡和回退处理等功能。
-本文将指导您如何在 LobeChat 中使用 Vercel AI Gateway。
+本文将指导您如何在 LobeHub 中使用 Vercel AI Gateway。
### 第一步：在 Vercel AI Gateway 中创建 API 密钥
@@ -23,9 +22,9 @@ tags:
- 点击左侧边栏的 **API 密钥**
- 点击 **创建密钥**，然后在对话框中点击 **创建密钥** 完成创建
- ### 第二步：在 LobeChat 中配置 Vercel AI Gateway
+ ### 第二步：在 LobeHub 中配置 Vercel AI Gateway
- - 进入 LobeChat 的 `设置` 页面
+ - 进入 LobeHub 的 `设置` 页面
- 在 `AI 服务提供商` 下，找到 `Vercel AI Gateway` 设置
- 输入您获得的 API 密钥
- 选择 Vercel AI Gateway 的模型，开始与 AI 助手对话
@@ -36,7 +35,7 @@ tags:
-至此，您可以在 LobeChat 中使用 Vercel AI Gateway 提供的模型开始聊天了。
+至此，您可以在 LobeHub 中使用 Vercel AI Gateway 提供的模型开始聊天了。
## 模型选择
diff --git a/docs/usage/providers/vertexai.mdx b/docs/usage/providers/vertexai.mdx
index f1caf944e9..c02c0372fd 100644
--- a/docs/usage/providers/vertexai.mdx
+++ b/docs/usage/providers/vertexai.mdx
@@ -1,59 +1,61 @@
---
-title: Using Vertex AI API Key in LobeChat
-description: Learn how to configure and use Vertex AI models in LobeChat, get an API key, and start a conversation.
+title: Using Vertex AI API Key in LobeHub
+description: >-
+ Learn how to configure and use Vertex AI models in LobeHub, obtain your API
+ key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Vertex AI
- API Key
- Web UI
---
-# Using Vertex AI in LobeChat
+# Using Vertex AI in LobeHub
-
- ### Step 1: Prepare a Vertex AI Project
+ ### Step 1: Set Up Your Vertex AI Project
- - First, visit [Google Cloud](https://console.cloud.google.com/) and complete the registration and login process.
+ - First, visit the [Google Cloud Console](https://console.cloud.google.com/) and sign in or create an account.
- Create a new Google Cloud project or select an existing one.
- - Go to the [Vertex AI Console](https://console.cloud.google.com/vertex-ai).
- - Ensure that the Vertex AI API service is enabled for the project.
+ - Navigate to the [Vertex AI Console](https://console.cloud.google.com/vertex-ai).
+ - Ensure that the Vertex AI API is enabled for your project.
-
- You may need to pay the API service provider during usage. Please refer to Google Cloud's relevant fee policies.
+ You may incur charges when using the API services. Please refer to Google Cloud’s pricing documentation for more details.
-Now you can use the models provided by Vertex AI for conversations in LobeChat.
+You're all set! You can now start using Vertex AI models in LobeHub for your conversations.
diff --git a/docs/usage/providers/vertexai.zh-CN.mdx b/docs/usage/providers/vertexai.zh-CN.mdx
index 41c8677421..1e21e656e5 100644
--- a/docs/usage/providers/vertexai.zh-CN.mdx
+++ b/docs/usage/providers/vertexai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 Vertex AI API Key
-description: 学习如何在 LobeChat 中配置和使用 Vertex AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 Vertex AI API Key
+description: 学习如何在 LobeHub 中配置和使用 Vertex AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- Vertex AI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 Vertex AI
+# 在 LobeHub 中使用 Vertex AI
-
### 步骤一：准备 Vertex AI 项目
@@ -24,36 +24,36 @@ tags:
- 进入 [Vertex AI 控制台](https://console.cloud.google.com/vertex-ai)
- 确认该项目已开通 Vertex AI API 服务
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 Google Cloud 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 Vertex AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 Vertex AI 提供的模型进行对话了。
diff --git a/docs/usage/providers/vllm.mdx b/docs/usage/providers/vllm.mdx
index 15309e6706..e3c8c827b9 100644
--- a/docs/usage/providers/vllm.mdx
+++ b/docs/usage/providers/vllm.mdx
@@ -1,25 +1,27 @@
---
-title: Using vLLM API Key in LobeChat
-description: Learn how to configure and use the vLLM language model in LobeChat, obtain an API key, and start a conversation.
+title: Using vLLM API Key in LobeHub
+description: >-
+ Learn how to configure and use vLLM language models in LobeHub, obtain an API
+ key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- vLLM
- API Key
- Web UI
---
-# Using vLLM in LobeChat
+# Using vLLM in LobeHub
-
- ### Step 1: Preparation
+ ### Step 1: Prerequisites
- vLLM has certain requirements for hardware and software environments. Be sure to configure according to the following requirements:
+ vLLM has specific hardware and software requirements. Please ensure your environment meets the following:
| Hardware Requirements | |
| --------------------- | ----------------------------------------------------------------------- |
@@ -33,7 +35,7 @@ This document will guide you on how to use vLLM in LobeChat:
### Step 2: Install vLLM
- If you are using an NVIDIA GPU, you can directly install vLLM using `pip`. However, it is recommended to use `uv` here, which is a very fast Python environment manager, to create and manage the Python environment. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install uv. After installing uv, you can use the following command to create a new Python environment and install vLLM:
+ If you're using an NVIDIA GPU, you can install vLLM directly via `pip`. However, we recommend using `uv`, a fast Python environment manager, to create and manage your Python environments. Follow the [official guide](https://docs.astral.sh/uv/#getting-started) to install uv. Once installed, you can create a new Python environment and install vLLM with the following commands:
```shell
uv venv myenv --python 3.12 --seed
@@ -41,13 +43,13 @@ This document will guide you on how to use vLLM in LobeChat:
uv pip install vllm
```
- Another method is to use `uv run` with the `--with [dependency]` option, which allows you to run commands such as `vllm serve` without creating an environment:
+ Alternatively, you can use `uv run` with the `--with [dependency]` option to run commands like `vllm serve` without creating a dedicated environment:
```shell
uv run --with vllm vllm --help
```
- You can also use [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html) to create and manage your Python environment.
+ You can also use [conda](https://docs.conda.io/projects/conda/en/latest/user-guide/getting-started.html) to manage your Python environment:
```shell
conda create -n myenv python=3.12 -y
@@ -56,46 +58,43 @@ This document will guide you on how to use vLLM in LobeChat:
```
- For non-CUDA platforms, please refer to the [official
- documentation](https://docs.vllm.ai/en/latest/getting_started/installation/index.html#installation-index)
- to learn how to install vLLM.
+ For non-CUDA platforms, please refer to the [official documentation](https://docs.vllm.ai/en/latest/getting_started/installation/index.html#installation-index) for installation instructions.
- ### Step 3: Start Local Service
+ ### Step 3: Start the Local Server
- vLLM can be deployed as an OpenAI API protocol-compatible server. By default, it will start the server at `http://localhost:8000`. You can specify the address using the `--host` and `--port` parameters. The server currently runs only one model at a time.
+ vLLM can be deployed as a server compatible with the OpenAI API protocol. By default, it starts at `http://localhost:8000`. You can customize the address using the `--host` and `--port` parameters. Note that the server can only run one model at a time.
- The following command will start a vLLM server and run the `Qwen2.5-1.5B-Instruct` model:
+ The following command starts a vLLM server running the `Qwen2.5-1.5B-Instruct` model:
```shell
vllm serve Qwen/Qwen2.5-1.5B-Instruct
```
- You can enable the server to check the API key in the header by passing the parameter `--api-key` or the environment variable `VLLM_API_KEY`. If not set, no API Key is required to access.
+ To enable API key authentication, you can pass the `--api-key` parameter or set the `VLLM_API_KEY` environment variable. If not set, the server will be accessible without an API key.
- For more detailed vLLM server configuration, please refer to the [official
- documentation](https://docs.vllm.ai/en/latest/).
+ For more detailed server configuration options, refer to the [official vLLM documentation](https://docs.vllm.ai/en/latest/).
- ### Step 4: Configure vLLM in LobeChat
+ ### Step 4: Configure vLLM in LobeHub
- - Access the `Application Settings` interface of LobeChat.
- - Find the `vLLM` settings item under `AI Service Provider`.
+ - Open the `App Settings` panel in LobeHub
+ - Under `AI Providers`, locate the `vLLM` configuration section
-
- * If your vLLM is not configured with an API Key, please leave the API Key blank. \* If your vLLM
- is running locally, please make sure to turn on `Client Request Mode`.
+ \* If your vLLM server is not configured with an API key, leave the API key field blank.\
+ \* If your vLLM server is running locally, make sure to enable "Client Request Mode".
- - Add the model you are running to the model list below.
- - Select a vLLM model to run for your assistant and start the conversation.
+ - Add the model you are running to the model list below
+ - Assign the vLLM model to your assistant to start chatting
-
-Now you can use the models provided by vLLM in LobeChat to have conversations.
+You're now ready to use vLLM-powered models in LobeHub for conversations.
diff --git a/docs/usage/providers/vllm.zh-CN.mdx b/docs/usage/providers/vllm.zh-CN.mdx
index eebcbf3eb0..982873bc83 100644
--- a/docs/usage/providers/vllm.zh-CN.mdx
+++ b/docs/usage/providers/vllm.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 vLLM API Key
-description: 学习如何在 LobeChat 中配置和使用 vLLM 语言模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用 vLLM API Key
+description: 学习如何在 LobeHub 中配置和使用 vLLM 语言模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- vLLM
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 vLLM
+# 在 LobeHub 中使用 vLLM
-
### 步骤一：准备工作
@@ -77,12 +77,12 @@ tags:
更详细的 vLLM 服务器配置，请参考[官方文档](https://docs.vllm.ai/en/latest/)
- ### 步骤四：在 LobeChat 中配置 vLLM
+ ### 步骤四：在 LobeHub 中配置 vLLM
- - 访问 LobeChat 的 `应用设置`界面
+ - 访问 LobeHub 的 `应用设置`界面
- 在 `AI 服务商` 下找到 `vLLM` 的设置项
-
-至此你已经可以在 LobeChat 中使用 vLLM 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 vLLM 提供的模型进行对话了。
diff --git a/docs/usage/providers/volcengine.mdx b/docs/usage/providers/volcengine.mdx
index e7d61eb306..7674471fac 100644
--- a/docs/usage/providers/volcengine.mdx
+++ b/docs/usage/providers/volcengine.mdx
@@ -1,49 +1,50 @@
---
-title: Using the Volcano Engine API Key in LobeChat
-description: Learn how to configure and use the Volcano Engine AI model in LobeChat, obtain API keys, and start conversations.
+title: Using Volcengine API Key in LobeHub
+description: >-
+ Learn how to configure and use Volcengine AI models in LobeHub, obtain your
+ API key, and start chatting.
tags:
- - LobeChat
+ - LobeHub
- Volcengine
- Doubao
- API Key
- Web UI
---
-# Using Volcengine in LobeChat
+# Using Volcengine in LobeHub
-
- ### Step 1: Obtain the Volcengine API Key
+ ### Step 1: Obtain a Volcengine API Key
- First, visit the [Volcengine official website](https://www.volcengine.com/) and complete the registration and login process.
- - Access the Volcengine console and navigate to [Volcano Ark](https://console.volcengine.com/ark/).
+ - Navigate to the [Volcano Ark Console](https://console.volcengine.com/ark/)
-
- During usage, you may need to pay the API service provider, so please refer to Volcengine's
- pricing policy.
+ You may incur charges when using the API services. Please refer to Volcengine’s pricing policy for details.
-You can now use the models provided by Volcengine for conversations in LobeChat.
+You're now ready to start chatting with models powered by Volcengine in LobeHub.
diff --git a/docs/usage/providers/volcengine.zh-CN.mdx b/docs/usage/providers/volcengine.zh-CN.mdx
index 9cc835ecd3..fadfc572aa 100644
--- a/docs/usage/providers/volcengine.zh-CN.mdx
+++ b/docs/usage/providers/volcengine.zh-CN.mdx
@@ -1,21 +1,21 @@
---
-title: 在 LobeChat 中使用火山引擎 API Key
-description: 学习如何在 LobeChat 中配置和使用火山引擎 AI 模型，获取 API 密钥并开始对话。
+title: 在 LobeHub 中使用火山引擎 API Key
+description: 学习如何在 LobeHub 中配置和使用火山引擎 AI 模型，获取 API 密钥并开始对话。
tags:
- - LobeChat
+ - LobeHub
- 火山引擎
- 豆包
- API密钥
- Web UI
---
-# 在 LobeChat 中使用火山引擎
+# 在 LobeHub 中使用火山引擎
-
### 步骤一：获取火山引擎 API 密钥
@@ -23,26 +23,26 @@ tags:
- 首先，访问[火山引擎官网](https://www.volcengine.com/)并完成注册登录
- 进入火山引擎控制台并导航至[火山方舟](https://console.volcengine.com/ark/)
-
在使用过程中你可能需要向 API 服务提供商付费，请参考火山引擎的相关费用政策。
-至此你已经可以在 LobeChat 中使用火山引擎提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用火山引擎提供的模型进行对话了。
diff --git a/docs/usage/providers/wenxin.mdx b/docs/usage/providers/wenxin.mdx
index 4a461dc07b..253cb5e8ec 100644
--- a/docs/usage/providers/wenxin.mdx
+++ b/docs/usage/providers/wenxin.mdx
@@ -1,59 +1,58 @@
---
-title: Using Wenxin Qianfan in LobeChat
+title: Using Wenxin Qianfan in LobeHub
description: >-
- Learn how to integrate and utilize Wenxin Qianfan's language model APIs in LobeChat.
-
+ Learn how to configure and use the Wenxin Qianfan API Key in LobeHub to start
+ conversations and interactions.
tags:
- - LobeChat
- - 百度
- - 文心千帆
- - API密钥
+ - LobeHub
+ - Baidu
+ - Wenxin Qianfan
+ - API Key
- Web UI
---
-# Using Wenxin Qianfan in LobeChat
+# Using Wenxin Qianfan in LobeHub
-
- ### Step 1: Obtain the Wenxin Qianfan API Key
+ ### Step 1: Obtain a Wenxin Qianfan API Key
- Register and log in to the [Baidu AI Cloud Console](https://console.bce.baidu.com/)
- Navigate to `Baidu AI Cloud Qianfan ModelBuilder`
- - Select `API Key` from the left menu
+ - In the left-hand menu, select `API Key`
-
- During usage, you may need to pay the API service provider. Please refer to Wenxin Qianfan's
- relevant fee policy.
+ You may incur charges from the API service provider during usage. Please refer to Wenxin Qianfan’s pricing policy for details.
-You can now use the models provided by Wenxin Qianfan for conversations in LobeChat.
+Now you're all set to start using Wenxin Qianfan models for conversations in LobeHub.
diff --git a/docs/usage/providers/wenxin.zh-CN.mdx b/docs/usage/providers/wenxin.zh-CN.mdx
index 4816474c99..7a0901c343 100644
--- a/docs/usage/providers/wenxin.zh-CN.mdx
+++ b/docs/usage/providers/wenxin.zh-CN.mdx
@@ -1,21 +1,21 @@
---
-title: 在 LobeChat 中使用文心千帆
-description: 学习如何在 LobeChat 中配置和使用文心千帆的API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用文心千帆
+description: 学习如何在 LobeHub 中配置和使用文心千帆的API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- 百度
- 文心千帆
- API密钥
- Web UI
---
-# 在 LobeChat 中使用文心千帆
+# 在 LobeHub 中使用文心千帆
-
### 步骤一：获得文心千帆的 API Key
@@ -24,7 +24,7 @@ tags:
- 进入 `百度智能云千帆 ModelBuilder`
- 在左侧菜单中选择 `API Key`
-
在使用过程中你可能需要向 API 服务提供商付费，请参考文心千帆的相关费用政策。
-至此你已经可以在 LobeChat 中使用文心千帆提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用文心千帆提供的模型进行对话了。
diff --git a/docs/usage/providers/xai.mdx b/docs/usage/providers/xai.mdx
index 6a3607d813..221b3ac419 100644
--- a/docs/usage/providers/xai.mdx
+++ b/docs/usage/providers/xai.mdx
@@ -1,53 +1,51 @@
---
-title: Using xAI in LobeChat
+title: Using xAI in LobeHub
description: >-
- Learn how to configure and use xAI's API Key in LobeChat to start conversations and interactions.
-
+ Learn how to configure and use xAI's API Key in LobeHub to start chatting and
+ interacting.
tags:
- - LobeChat
+ - LobeHub
- xAI
- API Key
- Web UI
---
-# Using xAI in LobeChat
+# Using xAI in LobeHub
-
- ### Step 1: Obtain an API Key from xAI
+ ### Step 1: Obtain an xAI API Key
- - Register and login to the [xAI console](https://console.x.ai/)
- - Create an API token
- - Copy and save the API token
+ - Sign up and log in to the [xAI Console](https://console.x.ai/)
+ - Create a new API Token
+ - Copy and securely save your API Token
-
- Make sure to securely save the API token displayed in the popup; it only appears once. If you
- accidentally lose it, you will need to create a new API token.
+ Make sure to save the API token shown in the popup — it will only be displayed once. If you lose it, you’ll need to generate a new one.
- ### Step 2: Configure xAI in LobeChat
+ ### Step 2: Configure xAI in LobeHub
- - Go to the `Settings` menu in LobeChat
- - Locate the `xAI` settings under `AI Service Provider`
+ - Go to the `Settings` page in LobeHub
+ - Under `AI Providers`, locate the `xAI` configuration section
-
- During use, you may need to pay the API service provider, so please refer to xAI's relevant
- pricing policies.
+ Please note that usage may incur charges from the API provider. Refer to xAI’s pricing policy for more details.
-You are now ready to engage in conversations using the models provided by xAI in LobeChat.
+You’re now ready to start using xAI-powered models in LobeHub for conversations and interactions.
diff --git a/docs/usage/providers/xai.zh-CN.mdx b/docs/usage/providers/xai.zh-CN.mdx
index 6edc911810..bfeb3c8aed 100644
--- a/docs/usage/providers/xai.zh-CN.mdx
+++ b/docs/usage/providers/xai.zh-CN.mdx
@@ -1,20 +1,20 @@
---
-title: 在 LobeChat 中使用 xAI
-description: 学习如何在 LobeChat 中配置和使用 xAI 的 API Key，以便开始对话和交互。
+title: 在 LobeHub 中使用 xAI
+description: 学习如何在 LobeHub 中配置和使用 xAI 的 API Key，以便开始对话和交互。
tags:
- - LobeChat
+ - LobeHub
- xAI
- API密钥
- Web UI
---
-# 在 LobeChat 中使用 xAI
+# 在 LobeHub 中使用 xAI
-
### 步骤一：获取 xAI 的 API 密钥
@@ -23,27 +23,27 @@ tags:
- 创建一个 API Token
- 复制并保存 API Token
-
妥善保存弹窗中的 API 令牌，它只会出现一次，如果不小心丢失了，你需要重新创建一个 API 令牌。
- ### 步骤二：在 LobeChat 中配置 xAI
+ ### 步骤二：在 LobeHub 中配置 xAI
- - 访问 LobeChat 的`设置`界面
+ - 访问 LobeHub 的`设置`界面
- 在`AI 服务商`下找到 `xAI` 的设置项
-
在使用过程中你可能需要向 API 服务提供商付费，请参考 xAI 的相关费用政策。
-至此你已经可以在 LobeChat 中使用 xAI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用 xAI 提供的模型进行对话了。
diff --git a/docs/usage/providers/zeroone.mdx b/docs/usage/providers/zeroone.mdx
index 40cab37e77..deba73b081 100644
--- a/docs/usage/providers/zeroone.mdx
+++ b/docs/usage/providers/zeroone.mdx
@@ -1,57 +1,59 @@
---
-title: Using 01 AI API Key in LobeChat
+title: Using the 01.AI API Key in LobeHub
description: >-
- Learn how to integrate and use 01 AI in LobeChat with step-by-step instructions. Obtain an API key, configure 01 AI, and start conversations with AI models.
-
+ Learn how to configure and use AI models provided by 01.AI (Zero One AI) in
+ LobeHub. Get your API key, enter it in the settings, choose a model, and start
+ chatting with your AI assistant.
tags:
+ - LobeHub
- 01.AI
+ - Zero One AI
- Web UI
- - API key
- - AI models
+ - API Key
+ - Configuration Guide
---
-# Using 01 AI in LobeChat
+# Using Zero One AI in LobeHub
-
- ### Step 1: Obtain 01 AI API Key
+ ### Step 1: Get Your 01.AI API Key
- - Register and log in to the [01 AI Large Model Open Platform](https://platform.lingyiwanwu.com/)
- - Go to the `Dashboard` and access the `API Key Management` menu
- - A system-generated API key has been created for you automatically, or you can create a new one on this interface
+ - Register and log in to the [01.AI Developer Platform](https://platform.lingyiwanwu.com/)
+ - Go to the `Dashboard` and navigate to the `API Key Management` section
+ - An API key is automatically generated for you. You can also create a new one if needed
-
- During usage, you may need to pay the API service provider. Please refer to 01 AI's relevant fee
- policies.
+ You may incur charges when using the API. Please refer to 01.AI’s pricing policy for more details.
-You can now use the models provided by 01 AI for conversations in LobeChat.
+And that’s it! You’re now ready to use 01.AI’s models in LobeHub for intelligent conversations.
diff --git a/docs/usage/providers/zeroone.zh-CN.mdx b/docs/usage/providers/zeroone.zh-CN.mdx
index 3f05c31eae..e4b132e622 100644
--- a/docs/usage/providers/zeroone.zh-CN.mdx
+++ b/docs/usage/providers/zeroone.zh-CN.mdx
@@ -1,10 +1,8 @@
---
-title: 在 LobeChat 中使用 01.AI 零一万物 API Key
-description: >-
- 学习如何在 LobeChat 中配置并使用 01.AI 零一万物提供的 AI 模型进行对话。获取 API 密钥、填入设置项、选择模型，开始与 AI 助手交流。
-
+title: 在 LobeHub 中使用 01.AI 零一万物 API Key
+description: 学习如何在 LobeHub 中配置并使用 01.AI 零一万物提供的 AI 模型进行对话。获取 API 密钥、填入设置项、选择模型，开始与 AI 助手交流。
tags:
- - LobeChat
+ - LobeHub
- 01.AI
- Zero One AI
- 零一万物
@@ -13,13 +11,13 @@ tags:
- 配置指南
---
-# 在 LobeChat 中使用零一万物
+# 在 LobeHub 中使用零一万物
-
### 步骤一：获取零一万物 API 密钥
@@ -28,32 +26,32 @@ tags:
- 进入`工作台`并访问`API Key管理`菜单
- 系统已为你自动创建了一个 API 密钥，你也可以在此界面创建新的 API 密钥
-
在使用过程中你可能需要向 API 服务提供商付费，请参考零一万物的相关费用政策。
-至此你已经可以在 LobeChat 中使用零一万物提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用零一万物提供的模型进行对话了。
diff --git a/docs/usage/providers/zhipu.mdx b/docs/usage/providers/zhipu.mdx
index e38d3491f7..f5d0537adf 100644
--- a/docs/usage/providers/zhipu.mdx
+++ b/docs/usage/providers/zhipu.mdx
@@ -1,8 +1,8 @@
---
-title: Using Zhipu ChatGLM API Key in LobeChat
+title: Using Zhipu ChatGLM API Key in LobeHub
description: >-
- Learn how to integrate and utilize Zhipu AI models in LobeChat for enhanced conversational experiences. Obtain the API key, configure settings, and start engaging with cognitive intelligence.
-
+ Learn how to configure and use Zhipu AI's API Key in LobeHub to start chatting
+ with models provided by Zhipu AI.
tags:
- Zhipu AI
- ChatGLM
@@ -10,39 +10,38 @@ tags:
- Web UI
---
-# Using Zhipu ChatGLM in LobeChat
+# Using Zhipu ChatGLM in LobeHub
-
- ### Step 1: Obtain the API Key for Zhipu AI
+ ### Step 1: Get Your Zhipu AI API Key
- Visit and log in to the [Zhipu AI Open Platform](https://open.bigmodel.cn/)
- - Upon initial login, the system will automatically create an API key for you and gift you a resource package of 25M Tokens
- - Navigate to the `API Key` section at the top to view your API key
+ - Upon your first login, the system will automatically generate an API key for you and grant a free 25M token package
+ - Navigate to the top menu and click on `API Key` to view your key
-
- During usage, you may need to pay the API service provider, please refer to Zhipu AI's pricing
- policy.
+ You may need to pay for API usage depending on your usage. Please refer to Zhipu AI’s pricing policy for more details.
-You can now engage in conversations using the models provided by Zhipu AI in LobeChat.
+And that’s it! You’re now ready to start chatting with models provided by Zhipu AI in LobeHub.
diff --git a/docs/usage/providers/zhipu.zh-CN.mdx b/docs/usage/providers/zhipu.zh-CN.mdx
index 8c649654e9..86f10e14ad 100644
--- a/docs/usage/providers/zhipu.zh-CN.mdx
+++ b/docs/usage/providers/zhipu.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用智谱 ChatGLM API Key
-description: 学习如何在 LobeChat 中配置和使用智谱AI的 API Key，开始与智谱AI提供的模型进行对话。
+title: 在 LobeHub 中使用智谱 ChatGLM API Key
+description: 学习如何在 LobeHub 中配置和使用智谱AI的 API Key，开始与智谱AI提供的模型进行对话。
tags:
- 智谱AI
- ChatGLM
@@ -8,13 +8,13 @@ tags:
- Web UI
---
-# 在 LobeChat 中使用智谱 ChatGLM
+# 在 LobeHub 中使用智谱 ChatGLM
-
### 步骤一：获取智谱 AI 的 API 密钥
@@ -23,23 +23,23 @@ tags:
- 初次登录时系统会自动为你创建好 API 密钥并赠送 25M Tokens 的资源包
- 进入顶部的 `API密钥` 可以查看你的 API
-
在使用过程中你可能需要向 API 服务提供商付费，请参考智谱 AI 的费用政策。
-至此你已经可以在 LobeChat 中使用智谱 AI 提供的模型进行对话了。
+至此你已经可以在 LobeHub 中使用智谱 AI 提供的模型进行对话了。
diff --git a/docs/usage/start.mdx b/docs/usage/start.mdx
index 8e2addf4cf..3632411b89 100644
--- a/docs/usage/start.mdx
+++ b/docs/usage/start.mdx
@@ -1,62 +1,33 @@
---
-title: Get started with LobeChat
-description: >-
- Explore the exciting features in LobeChat, including Vision Model, TTS & STT, Local LLMs, and Multi AI Providers. Discover more about Agent Market, Plugin System, and Personalization.
-
+title: Getting Started
+description: Getting started with LobeHub
tags:
- - Feature Overview
- - Vision Model
- - TTS & STT
- - Local LLMs
- - Multi AI Providers
- - Agent Market
+ - LobeHub
+ - LobeHub
+ - Features
+ - Visual Recognition
+ - Voice Conversations
+ - AI Providers
+ - Assistant Marketplace
+ - Local Large Language Models
- Plugin System
---
-# ✨ Feature Overview
+# LobeHub User Guide
-## 2024 Overview
+Welcome to the official LobeHub User Guide.
-
+ For self-hosting assistance, please visit the [Self-Hosting Guide](/docs/self-hosting/start). For developer resources, check out the [Developer Guide](/docs/development/start).
+
-
-
-
-
- -## 2023 Overview - -
-
+If you need assistance, please refer to our [Help & Support](/docs/usage/help) section.
diff --git a/docs/usage/start.zh-CN.mdx b/docs/usage/start.zh-CN.mdx
index 31771469ea..23bfc5e697 100644
--- a/docs/usage/start.zh-CN.mdx
+++ b/docs/usage/start.zh-CN.mdx
@@ -1,8 +1,9 @@
---
-title: 开始使用 LobeChat
-description: 了解 LobeChat 的功能特性，包括视觉识别、语音会话、多 AI 服务商等，体验助手市场、本地大语言模型、插件系统等功能。
+title: 开始
+description: 上手使用 LobeHub
tags:
- - LobeChat
+ - LobeHub
+ - LobeHub
- 功能特性
- 视觉识别
- 语音会话
@@ -12,50 +13,21 @@ tags:
- 插件系统
---
-# ✨ LobeChat 功能特性一览
+# LobeHub 用户指南
-## 2024 特性一览
+欢迎来到 LobeHub 官方用户指南。
-
+ 欲获取自部署帮助，请访问[私有化部署指南](/docs/self-hosting/start)。欲获取开发者指南，请访问[开发指南](/docs/development/start)
+
-
-
-
-
- -## 2023 特性一览 - -
-
+如果你需要帮助，可以参考 [帮助与支持](/docs/usage/help)。
diff --git a/docs/usage/tools-calling.mdx b/docs/usage/tools-calling.mdx
deleted file mode 100644
index acc025dc99..0000000000
--- a/docs/usage/tools-calling.mdx
+++ /dev/null
@@ -1,12 +0,0 @@
----
-title: Tools Calling
-description: Discover the best tools to enhance your calling experience and productivity.
-tags:
- - Calling Tools
- - Productivity
- - Communication
----
-
-# Tools Calling
-
-TODO
diff --git a/docs/usage/tools-calling.zh-CN.mdx b/docs/usage/tools-calling.zh-CN.mdx
deleted file mode 100644
index 92ef954d45..0000000000
--- a/docs/usage/tools-calling.zh-CN.mdx
+++ /dev/null
@@ -1,248 +0,0 @@
----
-title: 大模型工具调用（Tools Calling）评测
-description: 基于 LobeChat 测试主流支持工具调用（Tools Calling） 的大模型，并客观呈现评测结果
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling 评测
- - 工具调用
- - LobeChat 插件
----
-
-# 大模型工具调用（Tools Calling）评测
-
-Tools Calling 是大语言模型的高级能力。你可以通过在 API 请求中传入一组工具列表，让模型智能地选择具体使用哪个工具，并在返回请求中输出工具调用的 JSON 参数。
-
-
- 如果你之前没有了解过 Tools Calling， 可以查看 [Function Call： Chat
- 应用的插件基石与交互技术的变革黎明](https://lobehub.com/zh/blog/openai-function-call) 这篇文章。
-
-
-随着社区中越来越多的大语言模型支持了 Tools Calling 能力，同时得益于 LobeChat 的 Agent Runtime 架构，我们几乎实现了所有主流大语言模型（ OpenAI 、Claude 、Gemini 等等）的 Tools Calling 调用能力。
-
-LobeChat 的插件实现基于模型的 Tools Calling 能力，模型本身的 Tools Calling 能力决定插件调用是否正常。作为上层应用，我们针对各个模型的 Tools Calling 做了较为完善的测试，以便帮助我们的用户了解现有的模型能力，更好地进行抉择。
-
-## 评测任务介绍
-
-我们基于实际真实的用户场景出发构建了两大组测试任务，第一组为简单的调用指令（天气查询），第二组为复杂调用指令（文生图）。这两组指令的系统描述如下：
-
-
-
- ```md
- ## Tools
-
- You can use these tools below:
-
- ### Realtime Weather
-
- Get realtime weather information
-
- The APIs you can use:
-
- #### `realtime-weather____fetchCurrentWeather`
-
- 获取当前天气情况
- ```
-
-
-
- ```md
- ## Tools
-
- You can use these tools below:
-
- ### DALL·E 3
-
- Whenever a description of an image is given, use lobe-image-designer to create the images and then summarize the prompts used to generate the images in plain text. If the user does not ask for a specific number of images, default to creating four captions to send to lobe-image-designer that are written to be as diverse as possible.
-
- All captions sent to lobe-image-designer must abide by the following policies:
-
- 1. If the description is not in English, then translate it.
- 2. Do not create more than 4 images, even if the user requests more.
- 3. Don't create images of politicians or other public figures. Recommend other ideas instead.
- 4. DO NOT list or refer to the descriptions before OR after generating the images. They should ONLY ever be written out ONCE, in the `prompts` field of the request. You do not need to ask for permission to generate, just do it!
- 5. Always mention the image type (photo, oil painting, watercolor painting, illustration, cartoon, drawing, vector, render, etc.) at the beginning of the caption. Unless the caption suggests otherwise, make at least 1--2 of the 4 images photos.
- 6. Diversify depictions of ALL images with people to include DESCENT and GENDER for EACH person using direct terms. Adjust only human descriptions.
-
- - EXPLICITLY specify these attributes, not abstractly reference them. The attributes should be specified in a minimal way and should directly describe their physical form.
- - Your choices should be grounded in reality. For example, all of a given OCCUPATION should not be the same gender or race. Additionally, focus on creating diverse, inclusive, and exploratory scenes via the properties you choose during rewrites. Make choices that may be insightful or unique sometimes.
- - Use "various" or "diverse" ONLY IF the description refers to groups of more than 3 people. Do not change the number of people requested in the original description.
- - Don't alter memes, fictional character origins, or unseen people. Maintain the original prompt's intent and prioritize quality.
- - Do not create any imagery that would be offensive.
-
- 8. Silently modify descriptions that include names or hints or references of specific people or celebrities by carefully selecting a few minimal modifications to substitute references to the people with generic descriptions that don't divulge any information about their identities, except for their genders and physiques. Do this EVEN WHEN the instructions ask for the prompt to not be changed. Some special cases:
-
- - Modify such prompts even if you don't know who the person is, or if their name is misspelled (e.g. "Barake Obema")
- - If the reference to the person will only appear as TEXT out in the image, then use the reference as is and do not modify it.
- - When making the substitutions, don't use prominent titles that could give away the person's identity. E.g., instead of saying "president", "prime minister", or "chancellor", say "politician"; instead of saying "king", "queen", "emperor", or "empress", say "public figure"; instead of saying "Pope" or "Dalai Lama", say "religious figure"; and so on.
- - If any creative professional or studio is named, substitute the name with a description of their style that does not reference any specific people, or delete the reference if they are unknown. DO NOT refer to the artist or studio's style.
-
- The prompt must intricately describe every part of the image in concrete, objective detail. THINK about what the end goal of the description is, and extrapolate that to what would make satisfying images. All descriptions sent to lobe-image-designer should be a paragraph of text that is extremely descriptive and detailed. Each should be more than 3 sentences long.
-
- The APIs you can use:
-
- #### `lobe-image-designer____text2image____builtin`
-
- Create images from a text-only prompt.
- ```
-
-
-
-如上所示，简单调用指令在插件调用时它的系统描述 (system role) 相对简单，复杂调用指令的系统描述会复杂很多。这两组不同复杂度的指令可以比较好地区分出模型对于系统指令的遵循能力：
-
-- **天气查询可以测试模型的基础 Tools Calling 能力，确认模型是否存在「虚假宣传」的情况。** 就我们实际的测试来看，的确存在一些模型号称具有 Tools Calling 能力，但是处于完全不可用的状态；
-- **文生图可以测试模型指令跟随能力的上限。** 例如基础模型（例如 GPT-3.5）可能只能生成 1 张图片的 prompt，而高级模型（例如 GPT-4o）则能够生成 1\~4 张图片的 prompt。
-
-### 简单调用指令：天气查询
-
-天气查询是 Tools Calling 中一个经典的例子。
-
-天气查询插件采用的是我们自己做的一个简单的插件，它的工具定义如下：
-
-```json
-{
- "function": {
- "description": "获取当前天气情况",
- "name": "realtime-weather____fetchCurrentWeather",
- "parameters": {
- "properties": {
- "city": {
- "description": "城市名称",
- "type": "string"
- }
- },
- "required": ["city"],
- "type": "object"
- }
- },
- "type": "function"
-}
-```
-
-针对这一个工具，我们构建的测试组中包含了三个指令：
-
-| 指令编号 | 指令内容 | 基础 Tools Calling 调用 | 并发调用 | 复合指令跟随 |
-| ---- | ------------------ | ------------------- | ---- | ------ |
-| 指令 ① | 告诉我杭州和北京的天气，先回答我好的 | 🟢 | 🟢 | 🟢 |
-| 指令 ② | 告诉我杭州和北京的天气 | 🟢 | 🟢 | - |
-| 指令 ③ | 告诉我杭州的天气 | 🟢 | - | - |
-
-上述三个指令的复杂度逐渐递减，我们可以通过这三个指令来测试模型对于简单指令的处理能力。
-
-- 指令 ① 测试的能力项包含 「基础 Tools Calling 调用」、「并发调用」、「复合指令跟随」三项。
-- 指令 ② 测试的能力项包含 「基础 Tools Calling 调用」、「并发调用」 两项。
-- 指令 ③ 测试的能力项仅包含「基础 Tools Calling 调用」。
-
-
- 将指令 ① 、② 、③ 按照难度递减的方式排序的目的，是为了降低测试的成本。因为当模型能通过指令 ①
- 的测试时，我们就不需要继续测试指令 ② 和指令 ③ ，必然能通过。
-
-
-测试能力项详细说明:
-
-
-
- 根据我们实际的日常使用，工具调用往往会和普通文本生成结合在一起回答。例如比较经典的 Code Interpreter 插件，ChatGPT 往往会先回复一些代码生成的思路，然后再调用 Code Interpreter 插件生成代码。
-
- 这种情况下，我们需要模型能够正确地识别出用户的意图，然后调用对应的工具。
-
- 因此， 指令 ① 中的「告诉我杭州和北京的天气，先回答我好的」就是一个复合指令跟随的例子。前半句期望模型调用天气查询工具，后半句期望模型回答「好的」。并且理想的顺序应该是先回答「好的」，然后再调用天气查询工具。
-
-
-
- 并发工具调用（Parallel function calling）是指模型能够同时调用多个工具，或同时调用一个工具多次，这在对话中可以大大降低用户等待的时间，提升用户体验。
-
- 并发工具调用能力由 OpenAI 于 2023 年 11 月率先提出，目前支持并发工具调用的模型并不算多，属于是 Tools Calling 的进阶能力。
-
- 指令 ② 中的「告诉我杭州和北京的天气」就是一个期望执行并发调用的例子。理想的情况下，单个模型的返回应该存在两个工具的调用返回。
-
-
-
- 基础工具调用不必再赘述，这是 Tools Calling 的基础能力。
-
- 指令 ③ 中的「告诉我杭州的天气」就是最基本的工具调用的例子。
-
-
-
-### 复杂调用指令：文生图
-
-文生图的 Tools Calling 基本照搬了 ChatGPT Plus 的指令，它的复杂度相对较高，可以测试模型对于复杂指令的跟随能力。工具定义如下：
-
-```json
-{
- "function": {
- "description": "Create images from a text-only prompt.",
- "name": "lobe-image-designer____text2image____builtin",
- "parameters": {
- "properties": {
- "prompts": {
- "description": "The user's original image description, potentially modified to abide by the lobe-image-designer policies. If the user does not suggest a number of captions to create, create four of them. If creating multiple captions, make them as diverse as possible. If the user requested modifications to previous images, the captions should not simply be longer, but rather it should be refactored to integrate the suggestions into each of the captions. Generate no more than 4 images, even if the user requests more.",
- "items": {
- "type": "string"
- },
- "maxItems": 4,
- "minItems": 1,
- "type": "array"
- },
- "quality": {
- "default": "standard",
- "description": "The quality of the image that will be generated. hd creates images with finer details and greater consistency across the image.",
- "enum": ["standard", "hd"],
- "type": "string"
- },
- "seeds": {
- "description": "A list of seeds to use for each prompt. If the user asks to modify a previous image, populate this field with the seed used to generate that image from the image lobe-image-designer metadata.",
- "items": {
- "type": "integer"
- },
- "type": "array"
- },
- "size": {
- "default": "1024x1024",
- "description": "The resolution of the requested image, which can be wide, square, or tall. Use 1024x1024 (square) as the default unless the prompt suggests a wide image, 1792x1024, or a full-body portrait, in which case 1024x1792 (tall) should be used instead. Always include this parameter in the request.",
- "enum": ["1792x1024", "1024x1024", "1024x1792"],
- "type": "string"
- },
- "style": {
- "default": "vivid",
- "description": "The style of the generated images. Must be one of vivid or natural. Vivid causes the model to lean towards generating hyper-real and dramatic images. Natural causes the model to produce more natural, less hyper-real looking images.",
- "enum": ["vivid", "natural"],
- "type": "string"
- }
- },
- "required": ["prompts"],
- "type": "object"
- }
- },
- "type": "function"
-}
-```
-
-针对这一个工具，我们构建的测试组中包含了两个指令：
-
-| 指令编号 | 指令内容 | 流式调用 | 复杂 Tools Calling 调用 | 并发调用 | 复合指令跟随 |
-| ---- | ------------------------------------------------------------------------------------------------ | ---- | ------------------- | ---- | ------ |
-| 指令 ① | 我要画 3 幅画，第一幅画的主体为一只达芬奇风格的小狗，第二幅是毕加索风格的大雁，最后一幅是莫奈风格的狮子。每一幅都需要产出 2 个 prompts。请先说明你的构思，然后开始生成相应的图片。 | 🟢 | 🟢 | 🟢 | 🟢 |
-| 指令 ② | 画一只小狗 | 🟢 | 🟢 | - | - |
-
-此外，由于文生图的 prompts 的生成时间较长，这一组指令也可以清晰地测试出模型的 API 是否支持流式 Tools Calling。
-
-## 评测结果
-
-各模型的评测细节可以点击查看：
-
-
-
-
-### 结果汇总
-
-TODO
diff --git a/docs/usage/tools-calling/anthropic.mdx b/docs/usage/tools-calling/anthropic.mdx
deleted file mode 100644
index 9d0410ad92..0000000000
--- a/docs/usage/tools-calling/anthropic.mdx
+++ /dev/null
@@ -1,152 +0,0 @@
----
-title: Anthropic Claude 系列 Tools Calling 评测
-description: >-
- 使用 LobeChat 测试 Anthropic Claude 系列模型（Claude 3.5 sonnet / Claude 3 Opus / Claude 3 haiku） 的工具调用（Function Calling）能力，并展现评测结果
-
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling 评测
- - 工具调用
- - 插件
----
-
-# Anthropic Claude Series Tools Calling
-
-Overview of Anthropic Claude Series model Tools Calling capabilities:
-
-| Model | Support Tools Calling | Stream | Parallel | Simple Instruction Score | Complex Instruction |
-| ----------------- | --------------------- | ------ | -------- | ------------------------ | ------------------- |
-| Claude 3.5 Sonnet | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟🌟 |
-| Claude 3 Opus | ✅ | ✅ | ❌ | 🌟 | ⛔️ |
-| Claude 3 Sonnet | ✅ | ✅ | ❌ | 🌟🌟 | ⛔️ |
-| Claude 3 Haiku | ✅ | ✅ | ❌ | 🌟🌟 | ⛔️ |
-
-## Claude 3.5 Sonnet
-
-### Simple Instruction Call: Weather Query
-
-Test Instruction: Instruction ①
-
-
-
-` tag at the beginning of Tools Calling, which is not very helpful for users and consumes more tokens;
-2. Opus triggers Tools Calling twice, indicating that it does not support Parallel Tools Calling;
-3. The raw output of Tools Calling shows that Opus also supports Stream Tools Calling.
-
-` tag, which significantly impacts the user experience;
-2. Opus outputs the prompts field as a string instead of an array, causing an error and preventing the plugin from being called correctly.
-
-` 标签的内容，这段内容对于用户来说几乎没有什么帮助，反而带来了较多的 Token 消耗；
-2. Opus 会触发两次 Tools Calling，说明它并不支持 Parallel Tools Calling；
-3. 从 Tools Calling 的原始输出来看， Opus 也是支持流式 Tools Calling 的
-
-` 标签，这其实对体验影响非常大
-2. Opus 输出的 prompts 字段是字符串，而不是数组，导致报错，无法正常调用插件。
-
-
- Based on our actual tests, we strongly recommend not enabling plugins for Gemini because as of
- July 7, 2024, its Tools Calling capability is extremely poor.
-
-
-## Gemini 1.5 Pro
-
-### Simple Instruction Call: Weather Query
-
-Test Instruction: Instruction ①
-
-
-
-In the json output from Gemini, the name is incorrect, so LobeChat cannot recognize which plugin it called. (In the input, the name of the weather plugin is `realtime-weather____fetchCurrentWeather`, while Gemini returns `weather____fetchCurrentWeather`).
-
-
- 根据我们的的实际测试，强烈建议不要给 Gemini 开启插件，因为目前（截止 2024.07.07）它的 Tools
- Calling 能力实在太烂了。
-
-
-## Gemini 1.5 Pro
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-Gemini 输出的 json 中，name 是错误的，因此 LobeChat 无法识别到它调用了什么插件。（入参中，天气插件的 name 为 `realtime-weather____fetchCurrentWeather`，而 Gemini 返回的是 `weather____fetchCurrentWeather`）。
-
-由于 Groq 本身不支持 stream，因此 Tools Calling 的调用是普通请求。
-
-Groq 平台的模型 Tools Calling 能力一览：
-
-| 模型 | 支持 Tools Calling | 流式 （Stream） | 并发（Parallel） | 简单指令得分 | 复杂指令 |
-| ------------ | ---------------- | ----------- | ------------ | ------ | ---- |
-| LLAMA3 70B | ✅ | ❌ | ✅ | 🌟🌟 | 🌟🌟 |
-| LLAMA3 8B | ✅ | ❌ | ✅ | 🌟🌟 | 🌟 |
-| Mixtral-8x7B | ✅ | ❌ | ✅ | ⛔ | 🌟🌟 |
-
-## LLAMA3 70B
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-从上述视频中可以看到 LLAMA3 70B 支持并发 Tools Calling，可以同时调用多次天气查询。
-
-
- For testing instructions, see [Tools Calling - Evaluation Task
- Introduction](/docs/usage/tools-calling#evaluation-task-introduction)
-
-
-## GPT 3.5-turbo
-
-### Simple Instruction Call: Weather Inquiry
-
-Test Instruction: Instruction ①
-
-
-
-
- 关于测试指令，详见 [工具调用 Tools Calling -
- 评测任务介绍](/zh/docs/usage/tools-calling#评测任务介绍)
-
-
-## GPT 3.5-turbo
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-
+ By [🤖/🏪 Submitting Your Assistant](https://github.com/lobehub/lobe-chat-agents), you can easily publish your assistant to our platform. One of the standout features of LobeHub is its robust automated internationalization (i18n) workflow, which seamlessly translates your assistant into multiple languages. This ensures that users around the world can enjoy your assistant without language barriers.
+
+
+
+ We invite all users to join this ever-growing ecosystem and take part in the continuous improvement and evolution of assistants. Together, we can create more engaging, practical, and innovative assistants, enriching the diversity and utility of the marketplace.
+
diff --git a/docs/usage/workspace/manage-quota.zh-CN.mdx b/docs/usage/workspace/manage-quota.zh-CN.mdx
new file mode 100644
index 0000000000..98c6075977
--- /dev/null
+++ b/docs/usage/workspace/manage-quota.zh-CN.mdx
@@ -0,0 +1,30 @@
+---
+title: 在 LobeHub 助手市场找到创新 AI 助手
+description: >-
+ LobeHub助手市场是一个充满活力和创新的社区，汇聚了众多精心设计的助手，为工作场景和学习提供便利。欢迎提交你的助手作品，共同创造更多有趣、实用且具有创新性的助手。
+tags:
+ - LobeHub
+ - 助手市场
+ - 创新社区
+ - 协作空间
+ - 助手作品
+ - 自动化国际化
+ - 多语言版本
+---
+
+# 助手市场
+
+
+ 通过 [🤖/🏪 提交助手](https://github.com/lobehub/lobe-chat-agents)
+ ，你可以轻松地将你的助手作品提交到我们的平台。我们特别强调的是，LobeHub
+ 建立了一套精密的自动化国际化（i18n）工作流程，
+ 它的强大之处在于能够无缝地将你的助手转化为多种语言版本。这意味着，不论你的用户使用何种语言，他们都能无障碍地体验到你的助手。
+
+
+
+ 我们欢迎所有用户加入这个不断成长的生态系统，共同参与到助手的迭代与优化中来。共同创造出更多有趣、实用且具有创新性的助手，进一步丰富助手的多样性和实用性。
+
diff --git a/docs/usage/workspace/manage-team.mdx b/docs/usage/workspace/manage-team.mdx
new file mode 100644
index 0000000000..1c4101b251
--- /dev/null
+++ b/docs/usage/workspace/manage-team.mdx
@@ -0,0 +1,31 @@
+---
+title: Discover Innovative AI Assistants in the LobeHub Assistant Marketplace
+description: >-
+ The LobeHub Assistant Marketplace is a vibrant and innovative community that
+ brings together a wide range of thoughtfully designed assistants to enhance
+ productivity and learning. You're welcome to submit your own assistant
+ creations and help build a more diverse, practical, and creative ecosystem.
+tags:
+ - LobeHub
+ - Assistant Marketplace
+ - Innovation Community
+ - Collaborative Space
+ - Assistant Creations
+ - Automated Internationalization
+ - Multilingual Support
+---
+
+# Assistant Marketplace
+
+
+ Easily submit your assistant to our platform via [🤖/🏪 Submit an Assistant](https://github.com/lobehub/lobe-chat-agents).\
+ One of LobeHub’s standout features is its robust automated internationalization (i18n) workflow, which seamlessly translates your assistant into multiple languages. This ensures that users around the world can enjoy your assistant without language barriers.
+
+
+
+ We invite all users to join this ever-growing ecosystem and take part in the continuous improvement and evolution of assistants. Let’s work together to create more engaging, practical, and innovative assistants that enrich the diversity and functionality of the marketplace.
+
diff --git a/docs/usage/workspace/manage-team.zh-CN.mdx b/docs/usage/workspace/manage-team.zh-CN.mdx
new file mode 100644
index 0000000000..98c6075977
--- /dev/null
+++ b/docs/usage/workspace/manage-team.zh-CN.mdx
@@ -0,0 +1,30 @@
+---
+title: 在 LobeHub 助手市场找到创新 AI 助手
+description: >-
+ LobeHub助手市场是一个充满活力和创新的社区，汇聚了众多精心设计的助手，为工作场景和学习提供便利。欢迎提交你的助手作品，共同创造更多有趣、实用且具有创新性的助手。
+tags:
+ - LobeHub
+ - 助手市场
+ - 创新社区
+ - 协作空间
+ - 助手作品
+ - 自动化国际化
+ - 多语言版本
+---
+
+# 助手市场
+
+
+ 通过 [🤖/🏪 提交助手](https://github.com/lobehub/lobe-chat-agents)
+ ，你可以轻松地将你的助手作品提交到我们的平台。我们特别强调的是，LobeHub
+ 建立了一套精密的自动化国际化（i18n）工作流程，
+ 它的强大之处在于能够无缝地将你的助手转化为多种语言版本。这意味着，不论你的用户使用何种语言，他们都能无障碍地体验到你的助手。
+
+
+
+ 我们欢迎所有用户加入这个不断成长的生态系统，共同参与到助手的迭代与优化中来。共同创造出更多有趣、实用且具有创新性的助手，进一步丰富助手的多样性和实用性。
+
diff --git a/docs/wiki/HOME.zh-CN.md b/docs/wiki/HOME.zh-CN.md
new file mode 100644
index 0000000000..3b8f9c47e7
--- /dev/null
+++ b/docs/wiki/HOME.zh-CN.md
@@ -0,0 +1,11 @@
+ {
+ if (link.startsWith(GITHUB_CDN)) {
+ const filename = link.replaceAll(GITHUB_CDN, '');
+ return uploader(file, filename);
+ } else if (CHECK_CDN.some((cdn) => link.startsWith(cdn))) {
+ const buffer = await file.arrayBuffer();
+ const hash = createHash('md5').update(Buffer.from(buffer)).digest('hex');
+ return uploader(file, hash);
+ }
+
+ return;
+ }
+
+ // 替换文章中的图片链接
+ private replaceLinksInPosts() {
+ let count = 0;
+
+ for (const post of posts) {
+ const mdx = readFileSync(post, 'utf8');
+ let { content, data } = matter(mdx);
+ const inlineLinks = extractHttpsLinks(content);
+
+ for (const link of inlineLinks) {
+ if (this.cache[link]) {
+ content = content.replaceAll(link, this.cache[link]);
+ count++;
+ }
+ }
+
+ // 更新特定字段的图片链接
+
+ if (data['image'] && this.cache[data['image']]) {
+ data['image'] = this.cache[data['image']];
+ count++;
+ }
+
+ if (data['seo']?.['image'] && this.cache[data['seo']?.['image']]) {
+ data['seo']['image'] = this.cache[data['seo']['image']];
+ count++;
+ }
+
+ writeFileSync(post, matter.stringify(content, data));
+ }
+
+ consola.success(`${count} images have been uploaded to CDN and links have been replaced`);
+ }
+
+ // 运行上传过程
+ async run() {
+ const links = this.collectImageLinks();
+
+ if (links.length > 0) {
+ consola.info("Found images that haven't been uploaded to CDN:");
+ consola.info(links);
+ await this.uploadImagesToCDN(links);
+ this.replaceLinksInPosts();
+ } else {
+ consola.info('No new images to upload.');
+ }
+ }
+}
+
+// 实例化并运行
+const instance = new ImageCDNUploader();
+
+instance.run();
diff --git a/scripts/docsWorkflow/optimized.ts b/scripts/docsWorkflow/optimized.ts
new file mode 100644
index 0000000000..6cfcd3a2ca
--- /dev/null
+++ b/scripts/docsWorkflow/optimized.ts
@@ -0,0 +1,21 @@
+import sharp from 'sharp';
+
+const WIDTH = 1600;
+
+export const opimized = async (
+ inputBuffer: ArrayBuffer,
+ width: number = WIDTH,
+): Promise => {
+ return await sharp(inputBuffer)
+ .resize({ width: width, withoutEnlargement: true })
+ .webp()
+ .toBuffer();
+};
+
+export const opimizedGif = async (inputBuffer: ArrayBuffer): Promise => {
+ try {
+ return await sharp(inputBuffer, { animated: true }).webp().toBuffer();
+ } catch {
+ return await sharp(inputBuffer, { animated: true, limitInputPixels: false }).webp().toBuffer();
+ }
+};
diff --git a/scripts/docsWorkflow/utils.ts b/scripts/docsWorkflow/utils.ts
index 73890c054c..8168f0dd4b 100644
--- a/scripts/docsWorkflow/utils.ts
+++ b/scripts/docsWorkflow/utils.ts
@@ -1,10 +1,13 @@
+import { globSync } from 'glob';
import { readFileSync, writeFileSync } from 'node:fs';
+import { resolve } from 'node:path';
import remarkGfm from 'remark-gfm';
import remarkParse from 'remark-parse';
import { unified } from 'unified';
import { visit } from 'unist-util-visit';
import { SPLIT } from './const';
+import { opimized, opimizedGif } from './optimized';
export const updateDocs = (path: string, content: string) => {
const md = readFileSync(path, 'utf8');
@@ -36,3 +39,87 @@ export const getTitle = async (path: string) => {
export const genMdLink = (title: string, url: string) => {
return `[${title}](${url})`;
};
+
+export const fixWinPath = (path: string) => path.replaceAll('\\', '/');
+
+export const root = resolve(__dirname, '../..');
+
+export const posts = globSync(fixWinPath(resolve(root, 'docs/**/*.mdx')));
+
+export const extractHttpsLinks = (text: string) => {
+ const regex = /https:\/\/[^\s"')>]+/g;
+ const links = text.match(regex);
+ return links || [];
+};
+
+export const mergeAndDeduplicateArrays = (...arrays: string[][]) => {
+ const combinedArray = arrays.flat();
+ const uniqueSet = new Set(combinedArray);
+ return Array.from(uniqueSet);
+};
+
+const mimeToExtensions = {
+ 'image/gif': '.gif',
+ // 图片类型
+ 'image/jpeg': '.jpg',
+ 'image/png': '.png',
+ 'image/svg+xml': '.svg',
+ 'image/webp': '.webp',
+ // 视频类型
+ 'video/mp4': '.mp4',
+ 'video/mpeg': '.mpeg',
+ 'video/ogg': '.ogv',
+ 'video/quicktime': '.mov',
+ 'video/webm': '.webm',
+ 'video/x-flv': '.flv',
+ 'video/x-matroska': '.mkv',
+ 'video/x-ms-wmv': '.wmv',
+ 'video/x-msvideo': '.avi',
+};
+
+// @ts-ignore
+const getExtension = (type: string) => mimeToExtensions?.[type] || '.png';
+
+export const fetchImageAsFile = async (url: string, width: number) => {
+ try {
+ // Step 1: Fetch the image
+ const githubToken = process.env.GITHUB_TOKEN;
+ const headers =
+ githubToken && url.startsWith('https://github.com/')
+ ? {
+ 'Authorization': `Bearer ${githubToken}`,
+ 'User-Agent': 'lobe-chat-docs-cdn',
+ }
+ : undefined;
+
+ const response = await fetch(url, { headers });
+ if (!response.ok) {
+ throw new Error(`HTTP error! status: ${response.status}`);
+ }
+
+ // Step 2: Create a blob from the response data
+ const blob = await response.blob();
+ let buffer: any = await blob.arrayBuffer();
+ let type = getExtension(blob.type);
+ if (type === '.gif') {
+ buffer = await opimizedGif(buffer);
+ type = '.webp';
+ } else if (type === '.png' || type === '.jpg') {
+ buffer = await opimized(buffer, width);
+ type = '.webp';
+ }
+
+ const now = Date.now();
+ const filename = now.toString() + type;
+
+ // Step 3: Create a file from the blob
+ const file: File = new File([buffer], filename, {
+ lastModified: now,
+ type: type === '.webp' ? 'image/webp' : blob.type,
+ });
+
+ return file;
+ } catch (error) {
+ console.error('Error fetching image as file:', error);
+ }
+};
[![][docker-release-shield]][docker-release-link]
@@ -66,11 +66,11 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
你需要在脚本运行结束后查看配置生成报告，包括 Casdoor 管理员的帐号、用户账号和它们的初始登录密码。
- 请使用用户账号登录 LobeChat，管理员账号仅用于管理 Casdoor。
+ 请使用用户账号登录 LobeHub，管理员账号仅用于管理 Casdoor。
```log
安全密钥生成结果如下：
- LobeChat:
+ LobeHub:
- URL: http://localhost:3210
- Username: user
- Password: c66f8c
@@ -112,7 +112,7 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
### 访问应用
- 通过 [http://localhost:3210](http://localhost:3210) 访问你的 LobeChat 服务。应用的账号密码在步骤`2`的报告中。
+ 通过 [http://localhost:3210](http://localhost:3210) 访问你的 LobeHub 服务。应用的账号密码在步骤`2`的报告中。
### 端口模式
@@ -129,11 +129,11 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
你需要在脚本运行结束后查看配置生成报告，包括 Casdoor 管理员的帐号、用户账号和它们的初始登录密码。
- 请使用用户账号登录 LobeChat，管理员账号仅用于管理 Casdoor。
+ 请使用用户账号登录 LobeHub，管理员账号仅用于管理 Casdoor。
```log
安全密钥生成结果如下：
- LobeChat:
+ LobeHub:
- URL: http://your_server_ip:3210
- Username: user
- Password: 837e26
@@ -174,7 +174,7 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
### 访问应用
- 你可以通过 `http://your_server_ip:3210` 访问你的 LobeChat 服务。应用的账号密码在步骤`2`的报告中。
+ 你可以通过 `http://your_server_ip:3210` 访问你的 LobeHub 服务。应用的账号密码在步骤`2`的报告中。
请注意，如果你的服务能够被公网访问，我们强烈建议你参考 [文档](https://lobehub.com/docs/self-hosting/advanced/auth/next-auth/casdoor) 关闭注册功能。
@@ -218,7 +218,7 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
在域名模式中，你需要根据脚本提示完成：
- - LobeChat 服务的域名设置：`lobe.example.com`
+ - LobeHub 服务的域名设置：`lobe.example.com`
- Minio 服务的域名设置：`minio.example.com`
- Casdoor 服务的域名设置：`auth.example.com`
- 选择访问协议：`http` 或 `https`
@@ -238,11 +238,11 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
你需要在脚本运行结束后查看配置生成报告，包括 Casdoor 管理员的初始登录密码。
- 请使用用户账号登录 LobeChat，管理员账号仅用于管理 Casdoor。
+ 请使用用户账号登录 LobeHub，管理员账号仅用于管理 Casdoor。
```log
安全密钥生成结果如下：
- LobeChat:
+ LobeHub:
- URL: https://lobe.example.com
- Username: user
- Password: 837e26
@@ -283,7 +283,7 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
### 访问应用
- 你可以通过 `https://lobe.example.com` 访问你的 LobeChat 服务。应用的账号密码在步骤`3`的报告中。
+ 你可以通过 `https://lobe.example.com` 访问你的 LobeHub 服务。应用的账号密码在步骤`3`的报告中。
请注意，如果你的服务能够被公网访问，我们强烈建议你参考 [文档](https://lobehub.com/docs/self-hosting/advanced/auth/next-auth/casdoor) 关闭注册功能。
@@ -292,7 +292,7 @@ bash <(curl -fsSL https://lobe.li/setup.sh) -l zh_CN
## 自定义部署
-该章节主要为你介绍在不同的网络环境下自定义部署 LobeChat 服务必须要修改的配置。在开始前，你可以先下载 [Docker Compose 配置文件](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml) 以及 [环境变量配置文件](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/.env.zh-CN.example)。
+该章节主要为你介绍在不同的网络环境下自定义部署 LobeHub 服务必须要修改的配置。在开始前，你可以先下载 [Docker Compose 配置文件](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml) 以及 [环境变量配置文件](https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/.env.zh-CN.example)。
```sh
curl -O https://raw.githubusercontent.com/lobehub/lobe-chat/HEAD/docker-compose/local/docker-compose.yml
@@ -307,14 +307,14 @@ mv .env.zh-CN.example .env
### 预备知识
-一般来讲，想要完整的运行 LobeChat 数据库版本，你需要至少拥有如下四个服务
+一般来讲，想要完整的运行 LobeHub 数据库版本，你需要至少拥有如下四个服务
-- LobeChat 数据库版本自身
+- LobeHub 数据库版本自身
- 带有 PGVector 插件的 PostgreSQL 数据库
- 支持 S3 协议的对象存储服务
-- 受 LobeChat 支持的 SSO 登录鉴权服务
+- 受 LobeHub 支持的 SSO 登录鉴权服务
-这些服务可以通过自建或者在线云服务组合搭配，以满足不同层次的部署需求。本文中，我们提供了完全基于开源自建服务的 Docker Compose 配置，你可以直接使用这份配置文件来启动 LobeChat 数据库版本，也可以对之进行修改以适应你的需求。
+这些服务可以通过自建或者在线云服务组合搭配，以满足不同层次的部署需求。本文中，我们提供了完全基于开源自建服务的 Docker Compose 配置，你可以直接使用这份配置文件来启动 LobeHub 数据库版本，也可以对之进行修改以适应你的需求。
我们默认使用 [MinIO](https://github.com/minio/minio) 作为本地 S3 对象存储服务，使用 [Casdoor](https://github.com/casdoor/casdoor) 作为本地鉴权服务。
@@ -328,15 +328,15 @@ mv .env.zh-CN.example .env
1. Casdoor
-- LobeChat 需要与 Casdoor 通讯，因此你需要配置 Casdoor 的 Issuer 。
+- LobeHub 需要与 Casdoor 通讯，因此你需要配置 Casdoor 的 Issuer 。
```env
AUTH_CASDOOR_ISSUER=https://auth.example.com
```
-该配置会影响 LobeChat 的登录鉴权服务，你需要确保 Casdoor 服务的地址正确。你可以在 [常见问题](#常见问题) 中找到该配置错误的常见现象及解决方案。
+该配置会影响 LobeHub 的登录鉴权服务，你需要确保 Casdoor 服务的地址正确。你可以在 [常见问题](#常见问题) 中找到该配置错误的常见现象及解决方案。
-- 同时，你也需要在 Casdoor 中允许回调地址为 LobeChat 的地址：
+- 同时，你也需要在 Casdoor 中允许回调地址为 LobeHub 的地址：
请在 Casdoor 的 Web 面板的 `身份认证 -> 应用` -> `<应用ID，默认为 app-built-in>` -> `重定向URL` 中添加一行：
@@ -352,7 +352,7 @@ origin=https://auth.example.com
2. MinIO
-- LobeChat 需要为 LLM 服务提供商提供文件对象的公网访问地址，因此你需要配置 MinIO 的 Endpoint 。
+- LobeHub 需要为 LLM 服务提供商提供文件对象的公网访问地址，因此你需要配置 MinIO 的 Endpoint 。
```env
S3_PUBLIC_DOMAIN=https://minio.example.com
@@ -403,13 +403,13 @@ lobe-chat | [auth][error] r3: "response" is not a conform Authorization Ser
lobe-chat | [auth][error] TypeError: fetch failed
```
-成因：LobeChat 无法访问鉴权服务。
+成因：LobeHub 无法访问鉴权服务。
解决方案：
-- 请检查你的鉴权服务是否正常运行，以及 LobeChat 所在的网络是否能够访问到鉴权服务。
+- 请检查你的鉴权服务是否正常运行，以及 LobeHub 所在的网络是否能够访问到鉴权服务。
-- 一个直接的排查方式，你可以在 LobeChat 容器的终端中，使用 `curl` 命令访问你的鉴权服务 `https://auth.example.com/.well-known/openid-configuration`，如果返回了 JSON 格式的数据，则说明你的鉴权服务正常运行。
+- 一个直接的排查方式，你可以在 LobeHub 容器的终端中，使用 `curl` 命令访问你的鉴权服务 `https://auth.example.com/.well-known/openid-configuration`，如果返回了 JSON 格式的数据，则说明你的鉴权服务正常运行。
#### 反向代理下 OAuth 令牌交换失败
@@ -424,7 +424,7 @@ docker compose up -d
## 拓展配置
-为了完善你的 LobeChat 服务，你可以根据你的需求进行以下拓展配置。
+为了完善你的 LobeHub 服务，你可以根据你的需求进行以下拓展配置。
### 使用 MinIO 存储 Casdoor 头像
@@ -473,7 +473,7 @@ docker compose up -d
3. 在 Casdoor 的 `身份认证 -> 提供商` 中关联 MinIO S3 服务，以下是一个示例配置：
- 
+ 
其中，客户端 ID、客户端密钥为上一步创建的访问密钥中的 `Access Key` 和 `Secret Key`，`192.168.31.251` 应当被替换为 `your_server_ip`。
@@ -496,7 +496,7 @@ docker compose up -d
域名和配套服务端口说明如下：
-- `lobe.example.com`：为你的 LobeChat 服务端域名，需要反向代理到 LobeChat 服务端口，默认为 `3210`
+- `lobe.example.com`：为你的 LobeHub 服务端域名，需要反向代理到 LobeHub 服务端口，默认为 `3210`
- `auth.example.com`：为你的 Logto UI 域名，需要反向代理到 Logto WebUI 服务端口，默认为 `8000`
- `minio.example.com`：为你的 MinIO API 域名，需要反向代理到 MinIO API 服务端口，默认为 `9000`
- `minio-ui.example.com`：可选，为你的 MinIO UI 域名，需要反向代理到 MinIO WebUI 服务端口，默认为 `9001`
@@ -609,7 +609,7 @@ docker compose up -d # 重新启动
1. 在 `用户管理 -> 组织` 中，添加一个新的组织。名称与显示名称为 `Lobe Users`。其余保持默认即可。
2. 在 `身份认证 -> 应用` 中，添加一个新的应用。
-- 名称与显示名称为 `LobeChat`。
+- 名称与显示名称为 `LobeHub`。
- 组织为 `Lobe Users`。
- 重定向 URLS 中添加一行 为 `https://lobe.example.com/api/auth/callback/casdoor`。
- 关闭除密码外的登录方式 。
@@ -626,7 +626,7 @@ docker compose up -d # 重新启动
本文以 MinIO 为例，解释配置过程，如果你使用的是其他 S3 服务商，请参照其文档进行配置。
- 请记得注意配置对应 S3 服务商的 CORS 跨域配置，以确保 LobeChat 能够正常访问 S3 服务。
+ 请记得注意配置对应 S3 服务商的 CORS 跨域配置，以确保 LobeHub 能够正常访问 S3 服务。
在本文中，你需要允许 `https://lobe.example.com` 的跨域请求。这既可以在 MinIO WebUI 的 `Configuration - API - Cors Allow Origin` 中配置，也可以在 Docker Compose 中的 `minio - environment - MINIO_API_CORS_ALLOW_ORIGIN` 中配置。
@@ -642,20 +642,20 @@ docker compose up -d # 重新启动
2. 在左侧面板 User / Access Keys 处，点击 `Create New Access Key`，无需额外修改，将生成的 `Access Key` 和 `Secret Key` 填入你的 `.env` 文件中的 `S3_ACCESS_KEY_ID` 和 `S3_SECRET_ACCESS_KEY` 中
-
- 如果你在 CDN（如 Cloudflare）或反向代理后部署 LobeChat，你可以配置内部服务器到服务器通信以绕过 CDN / 代理层，以获得更好的性能。
+ 如果你在 CDN（如 Cloudflare）或反向代理后部署 LobeHub，你可以配置内部服务器到服务器通信以绕过 CDN / 代理层，以获得更好的性能。
你可以配置 `INTERNAL_APP_URL` 环境变量：
@@ -708,7 +708,7 @@ CASDOOR_PORT=8000
MINIO_PORT=9000
# Postgres related, which are the necessary environment variables for DB
-LOBE_DB_NAME=lobechat
+LOBE_DB_NAME=LobeHub
POSTGRES_PASSWORD=uWNZugjBqixf8dxC
# Casdoor secret
@@ -737,7 +737,7 @@ services:
- '${MINIO_PORT}:${MINIO_PORT}' # MinIO API
- '9001:9001' # MinIO Console
- '${CASDOOR_PORT}:${CASDOOR_PORT}' # Casdoor
- - '${LOBE_PORT}:3210' # LobeChat
+ - '${LOBE_PORT}:3210' # LobeHub
command: tail -f /dev/null
networks:
- lobe-network
diff --git a/docs/self-hosting/server-database/docker.mdx b/docs/self-hosting/server-database/docker.mdx
index 43e80ca4e7..ad7c1bdf98 100644
--- a/docs/self-hosting/server-database/docker.mdx
+++ b/docs/self-hosting/server-database/docker.mdx
@@ -1,10 +1,10 @@
---
-title: Deploying LobeChat Database with Docker
+title: Deploying LobeHub Database with Docker
description: >-
- Learn how to deploy the LobeChat server database version using Docker on Linux
+ Learn how to deploy the LobeHub server database version using Docker on Linux
and local machines.
tags:
- - LobeChat
+ - LobeHub
- Docker
- Database Deployment
- Postgres
@@ -22,16 +22,21 @@ tags:
This article assumes that you are familiar with the basic principles and processes of deploying
- the LobeChat server database version, so it only includes content related to core environment
- variable configuration. If you are not familiar with the deployment principles of the LobeChat
+ the LobeHub server database version, so it only includes content related to core environment
+ variable configuration. If you are not familiar with the deployment principles of the LobeHub
server database version, please refer to [Deploying Server
Database](/docs/self-hosting/server-database) first.
+
+ Due to the inability to expose `NEXT_PUBLIC_CLERK_PUBLISHABLE_KEY` using Docker environment variables, you cannot use Clerk as an authentication service when deploying LobeHub using Docker / Docker Compose.
+
+ If you do need Clerk as an authentication service, you might consider deploying using Vercel or building your own image.
+
## Deploying on a Linux Server
-Here is the process for deploying the LobeChat server database version on a Linux server:
+Here is the process for deploying the LobeHub server database version on a Linux server:
### Create a Postgres Database Instance
@@ -48,7 +53,7 @@ Here is the process for deploying the LobeChat server database version on a Linu
The pgvector plugin provides vector search capabilities for Postgres, which is an important
- component for LobeChat to implement RAG.
+ component for LobeHub to implement RAG.
@@ -79,8 +84,8 @@ Here is the process for deploying the LobeChat server database version on a Linu
S3_ACCESS_KEY_ID=xxxxxxxxxx
S3_SECRET_ACCESS_KEY=xxxxxxxxxx
S3_ENDPOINT=https://xxxxxxxxxx.r2.cloudflarestorage.com
- S3_BUCKET=lobechat
- S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com
+ S3_BUCKET=LobeHub
+ S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com
```
@@ -120,7 +125,7 @@ Here is the process for deploying the LobeChat server database version on a Linu
## Using Locally (Mac / Windows)
-The data version of LobeChat also supports direct use on a local Mac/Windows machine.
+The data version of LobeHub also supports direct use on a local Mac/Windows machine.
Here, we assume that you have a pg instance available on port 5432 locally on your Mac/Windows, with the account `postgres` and password `mysecretpassword`, accessible at `localhost:5432`.
@@ -136,8 +141,8 @@ $ docker run -it -d --name lobe-chat-database -p 3210:3210 \
-e S3_ACCESS_KEY_ID=xxxxxxxxxx \
-e S3_SECRET_ACCESS_KEY=xxxxxxxxxx \
-e S3_ENDPOINT=https://xxxxxxxxxx.r2.cloudflarestorage.com \
- -e S3_BUCKET=lobechat \
- -e S3_PUBLIC_DOMAIN=https://s3-for-lobechat.your-domain.com \
+ -e S3_BUCKET=LobeHub \
+ -e S3_PUBLIC_DOMAIN=https://s3-for-LobeHub.your-domain.com \
lobehub/lobe-chat-database
```
diff --git a/docs/self-hosting/server-database/docker.zh-CN.mdx b/docs/self-hosting/server-database/docker.zh-CN.mdx
index d59597b4d4..acf4b8b18f 100644
--- a/docs/self-hosting/server-database/docker.zh-CN.mdx
+++ b/docs/self-hosting/server-database/docker.zh-CN.mdx
@@ -1,9 +1,9 @@
---
-title: 使用 Docker 部署 LobeChat 数据库
-description: 详细步骤教你如何在 Docker 中部署 LobeChat 服务端数据库。
+title: 使用 Docker 部署 LobeHub 数据库
+description: 详细步骤教你如何在 Docker 中部署 LobeHub 服务端数据库。
tags:
- Docker
- - LobeChat
+ - LobeHub
- 数据库部署
- Postgres
---
@@ -19,17 +19,23 @@ tags:
- -### `top_p` - -`top_p` is also a sampling parameter, but it differs from temperature in its sampling method. Before outputting, the model generates a bunch of tokens, and these tokens are ranked based on their quality. In the top-p sampling mode, the candidate word list is dynamic, and tokens are selected from the tokens based on a percentage. Top\_p introduces randomness in token selection, allowing other high-scoring tokens to have a chance of being selected, rather than always choosing the highest-scoring one. - -
- -### `presence_penalty` - -The presence penalty parameter can be seen as a punishment for repetitive content in the generated text. When this parameter is set high, the generation model will try to avoid producing repeated words, phrases, or sentences. Conversely, if the presence penalty parameter is set low, the generated text may contain more repetitive content. By adjusting the value of the presence penalty parameter, control over the originality and diversity of the generated text can be achieved. The importance of this parameter is mainly reflected in the following aspects: - -- Enhancing the originality and diversity of the generated text: In certain applications, such as creative writing or generating news headlines, it is necessary for the generated text to have high originality and diversity. By increasing the value of the presence penalty parameter, the amount of repeated content in the generated text can be effectively reduced, thereby enhancing its originality and diversity. -- Preventing the generation of loops and meaningless content: In some cases, the generation model may produce repetitive or meaningless text that usually fails to convey useful information. By appropriately increasing the value of the presence penalty parameter, the probability of generating such meaningless content can be reduced, thereby improving the readability and practicality of the generated text. - -
- -### `reasoning_effort` - -The `reasoning_effort` parameter controls the strength of the reasoning process. This setting affects the depth of reasoning the model performs when generating a response. The available values are **`low`**, **`medium`**, and **`high`**, with the following meanings: - -- **low**: Lower reasoning effort, resulting in faster response times. Suitable for scenarios where quick responses are needed, but it may sacrifice some reasoning accuracy. -- **medium** (default): Balances reasoning accuracy and response speed, suitable for most scenarios. -- **high**: Higher reasoning effort, producing more detailed and complex responses, but slower response times and greater token consumption. - -By adjusting the `reasoning_effort` parameter, you can find an appropriate balance between response speed and reasoning depth based on your needs. For example, in conversational scenarios, if fast responses are a priority, you can choose low reasoning effort; if more complex analysis or reasoning is needed, you can opt for high reasoning effort. - -
- -### `top_p` - -核采样 `top_p` 也是采样参数，跟 temperature 不一样的采样方式。模型在输出之前，会生成一堆 token，这些 token 根据质量高低排名，核采样模式中候选词列表是动态的，从 tokens 里按百分比选择候选词。 top\_p 为选择 token 引入了随机性，让其他高分的 token 有被选择的机会，不会总是选最高分的。 - -
- -### `presence_penalty` - -Presence Penalty 参数可以看作是对生成文本中重复内容的一种惩罚。当该参数设置较高时，生成模型会尽量避免产生重复的词语、短语或句子。相反，如果 Presence Penalty 参数较低，则生成的文本可能会包含更多重复的内容。通过调整 Presence Penalty 参数的值，可以实现对生成文本的原创性和多样性的控制。参数的重要性主要体现在以下几个方面： - -- 提高生成文本的独创性和多样性：在某些应用场景下，如创意写作、生成新闻标题等，需要生成的文本具有较高的独创性和多样性。通过增加 Presence Penalty 参数的值，可以有效减少生成文本中的重复内容，从而提高文本的独创性和多样性。 -- 防止生成循环和无意义的内容：在某些情况下，生成模型可能会产生循环、重复的文本，这些文本通常无法传达有效的信息。通过适当增加 Presence Penalty 参数的值，可以降低生成这类无意义内容的概率，提高生成文本的可读性和实用性。 - -
- -### `frequency_penalty` - -是一种机制，通过对文本中频繁出现的新词汇施加惩罚，以减少模型重复同一词语的可能性，值越大，越有可能降低重复字词。 - -- `-2.0` 当早间新闻开始播出，我发现我家电视现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在现在 *（频率最高的词是 “现在”，占比 44.79%）* -- `-1.0` 他总是在清晨看新闻，在电视前看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看看 *（频率最高的词是 “看”，占比 57.69%）* -- `0.0` 当清晨的阳光洒进小餐馆时，一名疲倦的邮递员出现在门口，他的手中提着一袋信件。店主热情地为他准备了一份早餐，他在享用早餐的同时开始整理邮件。**（频率最高的词是 “的”，占比 8.45%）** -- `1.0` 一个深度睡眠的女孩被一阵温暖的阳光唤醒，她看到了早晨的第一缕阳光，周围是鸟语花香，一切都充满了生机。*（频率最高的词是 “的”，占比 5.45%）* -- `2.0` 每天早上，他都会在阳台上坐着吃早餐。在柔和的夕阳照耀下，一切看起来都非常宁静。然而有一天，当他准备端起早餐的时候，一只乐观的小鸟飞过，给他带来了一天的好心情。 *（频率最高的词是 “的”，占比 4.94%）* - -
- -### `reasoning_effort` - -`reasoning_effort` 参数用于控制推理过程的强度。此参数的设置会影响模型在生成回答时的推理深度。可选值包括 **`low`**、**`medium`** 和 **`high`**，具体含义如下： - -- **low（低）**：推理强度较低，生成速度较快，适用于需要快速响应的场景，但可能牺牲一定的推理精度。 -- **medium（中，默认值）**：平衡推理精度与响应速度，适用于大多数场景。 -- **high（高）**：推理强度较高，生成更为详细和复杂的回答，但响应时间较长，且消耗更多的 Token。 - -通过调整 `reasoning_effort` 参数，可以根据需求在生成速度与推理深度之间找到适合的平衡。例如，在对话场景中，如果更关注快速响应，可以选择低推理强度；如果需要更复杂的分析或推理，可以选择高推理强度。 - -
- -## 如何提升其质量和效果 - -
-
-
-### 2. How to Handle "Model not found" Errors
-
-When you see errors like `Model not found: flux1-dev.safetensors, flux1-krea-dev.safetensors, flux1-schnell.safetensors`, it means the required model files are missing from the server.
-
-📦 Install Comfy-Manager Steps
+📦 Steps to Install Comfy-Manager
#### Method 1: Manual Installation (Recommended) @@ -198,619 +212,45 @@ Comfy-Manager is ComfyUI's extension manager that allows you to easily install a # Navigate to ComfyUI's custom_nodes directory cd ComfyUI/custom_nodes - # Clone Comfy-Manager repository + # Clone the Comfy-Manager repository git clone https://github.com/ltdrdata/ComfyUI-Manager.git - # Restart ComfyUI server - # After restart, you'll see the Manager button in the UI + # Restart the ComfyUI server + # After restarting, you should see a "Manager" button in the UI ``` - #### Method 2: One-Click Installation Script + #### Method 2: One-Click Install Script ```bash - # Execute in ComfyUI root directory + # Run from the ComfyUI root directory curl -fsSL https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/install.sh | bash ``` #### Verify Installation - 1. Restart ComfyUI server - 2. Visit `http://localhost:8188` - 3. You should see the "Manager" button in the bottom-right corner + 1. Restart the ComfyUI server + 2. Visit `http://localhost:8000` + 3. You should see a "Manager" button in the bottom-right corner #### Using Comfy-Manager **Install Models**: - 1. Click "Manager" button + 1. Click the "Manager" button 2. Select "Install Models" - 3. Search for needed models (e.g., FLUX, SD3.5) - 4. Click "Install" to automatically download to correct directory + 3. Search for the desired model (e.g., FLUX, SD3.5) + 4. Click "Install" to download automatically **Install Node Extensions**: - 1. Click "Manager" button + 1. Click the "Manager" button 2. Select "Install Custom Nodes" - 3. Search for needed nodes (e.g., ControlNet, AnimateDiff) - 4. Click "Install" and restart server + 3. Search for nodes (e.g., ControlNet, AnimateDiff) + 4. Click "Install" and restart the server **Manage Installed Content**: - 1. Click "Manager" button + 1. Click the "Manager" button 2. Select "Installed" to view installed extensions - 3. Update, disable, or uninstall extensions + 3. You can update, disable, or uninstall extensions
-
-
-### 3. How to Handle Missing System Component Errors
-
-When you see errors like `Missing VAE encoder: ae.safetensors` or other component files missing, you need to download the corresponding system components.
-
-🔧 Resolve Model not found Errors
- - #### Error Example - - ```plaintext - Model not found: flux1-dev.safetensors, flux1-krea-dev.safetensors, flux1-schnell.safetensors - ``` - - This error indicates the system expects to find these model files but couldn't locate them on the server. - - #### Resolution Methods - - **Method 1: Download using Comfy-Manager (Recommended)** - - 1. Open ComfyUI interface - 2. Click "Manager" → "Install Models" - 3. Search for the model name from the error (e.g., "flux1-dev") - 4. Click "Install" to automatically download - - **Method 2: Manual Model Download** - - 1. **Download Model Files**: - - Visit [Hugging Face](https://huggingface.co/black-forest-labs/FLUX.1-dev) or other model sources - - Download the files mentioned in the error (e.g., `flux1-dev.safetensors`) - - 2. **Place in Correct Directory**: - ```bash - # FLUX and SD3.5 main models go to - ComfyUI/models/diffusion_models/flux1-dev.safetensors - - # SD1.5 and SDXL models go to - ComfyUI/models/checkpoints/ - ``` - - 3. **Verify Files**: - ```bash - # Check if file exists - ls -la ComfyUI/models/diffusion_models/flux1-dev.safetensors - - # Check file integrity (optional) - sha256sum flux1-dev.safetensors - ``` - - 4. **Restart ComfyUI Server** - - **Method 3: Direct Download with wget/curl** - - ```bash - # Navigate to models directory - cd ComfyUI/models/diffusion_models/ - - # Download using wget (replace with actual download link) - wget https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/flux1-dev.safetensors - - # Or use curl - curl -L -o flux1-dev.safetensors https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/flux1-dev.safetensors - ``` - - #### Common Model Download Sources - - - **Hugging Face**: [https://huggingface.co/models](https://huggingface.co/models) - - **Civitai**: [https://civitai.com/models](https://civitai.com/models) - - **Official Sources**: - - FLUX: [https://huggingface.co/black-forest-labs](https://huggingface.co/black-forest-labs) - - SD3.5: [https://huggingface.co/stabilityai](https://huggingface.co/stabilityai) - - #### Prevention Measures - - 1. **Basic Model Package**: Download at least one base model - - FLUX: `flux1-schnell.safetensors` (fast) or `flux1-dev.safetensors` (high quality) - - SD3.5: `sd3.5_large.safetensors` - - 2. **Check Disk Space**: - ```bash - # Check available space - df -h ComfyUI/models/ - ``` - - 3. **Set Model Path** (optional): - If your models are stored elsewhere, create symbolic links: - ```bash - ln -s /path/to/your/models ComfyUI/models/diffusion_models/ - ``` -
-
-
-## ComfyUI Server Installation
-
-🛠️ Resolve Missing System Component Errors
- - #### Common Component Errors - - ```plaintext - Missing VAE encoder: ae.safetensors. Please download and place it in the models/vae folder. - Missing CLIP encoder: clip_l.safetensors. Please download and place it in the models/clip folder. - Missing T5 encoder: t5xxl_fp16.safetensors. Please download and place it in the models/clip folder. - ``` - - #### Component Types Description - - | Component Type | Example Filename | Purpose | Storage Directory | - | -------------- | ------------------------------ | ----------------------- | ------------------ | - | **VAE** | ae.safetensors | Image encoding/decoding | models/vae/ | - | **CLIP** | clip\_l.safetensors | Text encoding (CLIP) | models/clip/ | - | **T5** | t5xxl\_fp16.safetensors | Text encoding (T5) | models/clip/ | - | **ControlNet** | flux-controlnet-\*.safetensors | Control networks | models/controlnet/ | - - #### Resolution Methods - - **Method 1: Use Comfy-Manager (Recommended)** - - 1. Click "Manager" → "Install Models" - 2. Select component type in "Filter" (VAE/CLIP/T5) - 3. Download corresponding component files - - **Method 2: Manual Component Download** - - ##### FLUX Required Components - - ```bash - # 1. VAE Encoder - cd ComfyUI/models/vae/ - wget https://huggingface.co/black-forest-labs/FLUX.1-dev/resolve/main/ae.safetensors - - # 2. CLIP-L Encoder - cd ComfyUI/models/clip/ - wget https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/clip_l.safetensors - - # 3. T5-XXL Encoder (choose different precisions) - # FP16 version (recommended, balanced performance) - wget https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp16.safetensors - - # Or FP8 version (saves VRAM) - wget https://huggingface.co/comfyanonymous/flux_text_encoders/resolve/main/t5xxl_fp8_e4m3fn.safetensors - ``` - - ##### SD3.5 Required Components - - ```bash - # SD3.5 uses different encoders - cd ComfyUI/models/clip/ - - # CLIP-G Encoder - wget https://huggingface.co/stabilityai/stable-diffusion-3.5-large/resolve/main/text_encoders/clip_g.safetensors - - # CLIP-L Encoder - wget https://huggingface.co/stabilityai/stable-diffusion-3.5-large/resolve/main/text_encoders/clip_l.safetensors - - # T5-XXL Encoder - wget https://huggingface.co/stabilityai/stable-diffusion-3.5-large/resolve/main/text_encoders/t5xxl_fp16.safetensors - ``` - - ##### SDXL Required Components - - ```bash - # SDXL VAE - cd ComfyUI/models/vae/ - wget https://huggingface.co/stabilityai/sdxl-vae/resolve/main/sdxl_vae.safetensors - - # SDXL uses built-in CLIP encoders, usually no separate download needed - ``` - - #### Component Compatibility Matrix - - | Model Series | Required VAE | Required CLIP | Required T5 | Optional Components | - | ------------ | -------------- | ------------------- | ----------------------- | ------------------- | - | **FLUX** | ae.safetensors | clip\_l.safetensors | t5xxl\_fp16.safetensors | ControlNet | - | **SD3.5** | Built-in | clip\_g + clip\_l | t5xxl\_fp16 | - | - | **SDXL** | sdxl\_vae | Built-in | - | Refiner | - | **SD1.5** | vae-ft-mse | Built-in | - | ControlNet | - - #### Precision Selection Recommendations - - **T5 Encoder Precision Selection**: - - | VRAM Capacity | Recommended Version | Filename | - | ------------- | ------------------- | ------------------------------ | - | \< 12GB | FP8 Quantized | t5xxl\_fp8\_e4m3fn.safetensors | - | 12-16GB | FP16 | t5xxl\_fp16.safetensors | - | > 16GB | FP32 | t5xxl.safetensors | - - #### Verify Component Installation - - ```bash - # Check all required components - echo "=== VAE Components ===" - ls -la ComfyUI/models/vae/ - - echo "=== CLIP/T5 Components ===" - ls -la ComfyUI/models/clip/ - - echo "=== ControlNet Components ===" - ls -la ComfyUI/models/controlnet/ - ``` - - #### Troubleshooting - - **Issue: Still getting errors after download** - - 1. **Check File Permissions**: - ```bash - chmod 644 ComfyUI/models/vae/*.safetensors - chmod 644 ComfyUI/models/clip/*.safetensors - ``` - - 2. **Clear Cache**: - ```bash - # Clear ComfyUI cache - rm -rf ComfyUI/temp/* - rm -rf ComfyUI/__pycache__/* - ``` - - 3. **Restart Server**: - ```bash - # Fully restart ComfyUI - pkill -f "python main.py" - python main.py --listen 0.0.0.0 --port 8188 - ``` - - **Issue: Insufficient VRAM** - - Use quantized component versions: - - - T5: Use `t5xxl_fp8_e4m3fn.safetensors` instead of FP16/FP32 - - VAE: Some models support FP16 VAE versions - - **Issue: Slow Downloads** - - 1. Use mirror sources (if applicable) - 2. Use download tools (like aria2c) with resume support: - ```bash - aria2c -x 16 -s 16 -k 1M [download_link] - ``` -
-
- **Smart Model Selection**: LobeChat will automatically select the best model based on available model files on the server. You don't need to download all models; the system will automatically choose from available models by priority (Official > Enterprise > Community).
-
-
-
-## Supported Models
-
-LobeChat's ComfyUI integration uses a configuration-driven architecture, supporting **223 models**, providing complete coverage from official models to community-optimized versions.
-
-### FLUX Series Recommended Parameters
-
-| Model Type | Recommended Steps | CFG Scale | Resolution Range |
-| ----------- | ----------------- | --------- | -------------------- |
-| **Schnell** | 4 steps | - | 512×512 to 1536×1536 |
-| **Dev** | 20 steps | 3.5 | 512×512 to 2048×2048 |
-| **Kontext** | 20 steps | 3.5 | 512×512 to 2048×2048 |
-| **Krea** | 20 steps | 4.5 | 512×512 to 2048×2048 |
-
-### SD3.5 Series Parameters
-
-| Model Type | Recommended Steps | CFG Scale | Resolution Range |
-| --------------- | ----------------- | --------- | -------------------- |
-| **Large** | 25 steps | 7.0 | 512×512 to 2048×2048 |
-| **Large Turbo** | 8 steps | 3.5 | 512×512 to 1536×1536 |
-| **Medium** | 20 steps | 6.0 | 512×512 to 1536×1536 |
-
-🚀 Install and Configure ComfyUI Server
- - ### 1. Install ComfyUI - - ```bash - # Clone ComfyUI repository - git clone https://github.com/comfyanonymous/ComfyUI.git - cd ComfyUI - - # Install dependencies - pip install -r requirements.txt - - # Optional: Install JWT support (for Token authentication) - pip install PyJWT - - # Start ComfyUI server - python main.py --listen 0.0.0.0 --port 8188 - ``` - - ### 2. Download Model Files - - **Recommended Basic Configuration** (Minimal installation): - - **Main Models** (place in `models/diffusion_models/` directory): - - - `flux1-schnell.safetensors` - Fast generation (4 steps) - - `flux1-dev.safetensors` - High-quality creation (20 steps) - - **Required Components** (place in respective directories): - - - `models/vae/ae.safetensors` - VAE encoder - - `models/clip/clip_l.safetensors` - CLIP text encoder - - `models/clip/t5xxl_fp16.safetensors` - T5 text encoder - - ### 3. Verify Server Running - - Visit `http://localhost:8188` to confirm ComfyUI interface loads properly. - -
-
-
-## Performance Optimization Recommendations
-
-### Hardware Requirements
-
-**Minimum Configuration** (GGUF quantized models):
-
-- GPU: 6GB VRAM (using Q4 quantization)
-- RAM: 12GB
-- Storage: 30GB available space
-
-**Recommended Configuration** (standard models):
-
-- GPU: 12GB+ VRAM (RTX 4070 Ti or higher)
-- RAM: 24GB+
-- Storage: SSD 100GB+ available space
-
-### VRAM Optimization Strategy
-
-| VRAM Capacity | Recommended Quantization | Model Example | Performance Characteristics |
-| ------------- | ------------------------ | ---------------------------------- | --------------------------- |
-| **6-8GB** | Q4\_0, Q4\_K\_S | `flux1-dev-Q4_0.gguf` | Minimal VRAM usage |
-| **10-12GB** | Q6\_K, Q8\_0 | `flux1-dev-Q6_K.gguf` | Balance performance/quality |
-| **16GB+** | FP8, FP16 | `flux1-dev-fp8-e4m3fn.safetensors` | Near-original quality |
-| **24GB+** | Full model | `flux1-dev.safetensors` | Best quality |
-
-## Custom Model Usage
-
-📋 Complete Supported Model List
- - ### Model Classification System - - #### Priority 1: Official Core Models - - **FLUX.1 Official Series**: - - - `flux1-dev.safetensors` - High-quality creation model - - `flux1-schnell.safetensors` - Fast generation model - - `flux1-kontext-dev.safetensors` - Image editing model - - `flux1-krea-dev.safetensors` - Safety-enhanced model - - **SD3.5 Official Series**: - - - `sd3.5_large.safetensors` - SD3.5 large base model - - `sd3.5_large_turbo.safetensors` - Fast generation version - - `sd3.5_medium.safetensors` - Medium-scale model - - #### Priority 2: Enterprise Optimized Models (106 FLUX) - - **Quantization Optimization Series**: - - - **GGUF Quantization**: Each variant supports 11 quantization levels (F16, Q8\_0, Q6\_K, Q5\_K\_M, Q5\_K\_S, Q4\_K\_M, Q4\_K\_S, Q4\_0, Q3\_K\_M, Q3\_K\_S, Q2\_K) - - **FP8 Precision**: fp8\_e4m3fn, fp8\_e5m2 optimized versions - - **Enterprise Lightweight**: FLUX.1-lite-8B series - - **Technical Experiments**: NF4, SVDQuant, TorchAO, optimum-quanto, MFLUX optimized versions - - #### Priority 3: Community Fine-tuned Models (48 FLUX) - - **Community Optimization Series**: - - - **Jib Mix Flux** Series: High-quality mixed models - - **Real Dream FLUX** Series: Realism style - - **Vision Realistic** Series: Visual realism - - **PixelWave FLUX** Series: Pixel art optimization - - **Fluxmania** Series: Diverse style support - - ### SD Series Model Support (93 models) - - **SD3.5 Series**: 5 models - **SD1.5 Series**: 37 models (including official, quantized, and community versions) - **SDXL Series**: 50 models (including base, Refiner, and Playground models) - - ### Workflow Support - - System supports **6 workflows**: - - - **flux-dev**: High-quality creation workflow - - **flux-schnell**: Fast generation workflow - - **flux-kontext**: Image editing workflow - - **sd35**: SD3.5 dedicated workflow - - **simple-sd**: Simple SD workflow - - **index**: Workflow entry point -
-
-
-## Troubleshooting
-
-### Smart Error Diagnosis System
-
-LobeChat integrates a smart error handling system that can automatically diagnose and provide targeted solutions.
-
-#### Error Types and Solutions
-
-| Error Type | User Prompt | Automatic Diagnosis |
-| ------------------ | ---------------------------------- | --------------------------------------------------- |
-| **Connection** | "Cannot connect to ComfyUI server" | Auto-detect server status and connectivity |
-| **Authentication** | "API key invalid or expired" | Auto-verify authentication credentials |
-| **Permissions** | "Access permissions insufficient" | Auto-check user permissions and file access |
-| **Model Issues** | "Cannot find specified model file" | Auto-scan available models and suggest alternatives |
-| **Configuration** | "Configuration file error" | Auto-verify config completeness and syntax |
-
-🎨 Configure Custom SD Models
- - LobeChat supports using custom Stable Diffusion models. The system uses fixed filenames to identify custom models. - - ### 1. Model File Preparation - - **Required Files**: - - - **Main Model File**: `custom_sd_lobe.safetensors` - - **VAE File (Optional)**: `custom_sd_vae_lobe.safetensors` - - ### 2. Add Custom Model - - **Method 1: Rename Existing Model** - - ```bash - # Rename your model to fixed filename - mv your_custom_model.safetensors custom_sd_lobe.safetensors - - # Move to correct directory - mv custom_sd_lobe.safetensors ComfyUI/models/diffusion_models/ - ``` - - **Method 2: Create Symbolic Link (Recommended)** - - ```bash - # Create soft link for easy model switching - ln -s /path/to/your_model.safetensors ComfyUI/models/diffusion_models/custom_sd_lobe.safetensors - ``` - - ### 3. Use Custom Model - - In LobeChat, custom models will appear as: - - - **stable-diffusion-custom**: Standard custom model - - **stable-diffusion-custom-refiner**: Refiner custom model - - ### Custom Model Parameter Recommendations - - | Parameter | SD 1.5 Models | SDXL Models | - | ---------- | ------------- | ----------- | - | **steps** | 20-30 | 25-40 | - | **cfg** | 7.0 | 6.0-8.0 | - | **width** | 512 | 1024 | - | **height** | 512 | 1024 | -
-
-
-## Best Practices
-
-### Prompt Writing
-
-1. **Detailed Description**: Provide clear, detailed image descriptions
-2. **Style Specification**: Clearly specify artistic style, color style, etc.
-3. **Quality Keywords**: Add "4K", "high quality", "detailed" keywords
-4. **Avoid Contradictions**: Ensure description content is logically consistent
-
-**Example**:
-
-```plaintext
-A young woman with flowing long hair, wearing an elegant blue dress, standing in a cherry blossom park,
-sunlight filtering through leaves, warm atmosphere, cinematic lighting, 4K high resolution, detailed, photorealistic
-```
-
-### Parameter Optimization
-
-1. **FLUX Schnell**: Suitable for quick previews, use 4-step generation
-2. **FLUX Dev**: Balance quality and speed, CFG 3.5, 20 steps
-3. **FLUX Krea-dev**: Safe creation, CFG 4.5, note content filtering
-4. **FLUX Kontext-dev**: Image editing, strength 0.6-0.9
-
-🔍 Traditional Troubleshooting Methods
- - #### 1. Connection Failure - - **Issue**: Cannot connect to ComfyUI server - - **Solution**: - - ```bash - # Confirm server running - curl http://localhost:8188/system_stats - - # Check port - netstat -tulpn | grep 8188 - ``` - - #### 2. Out of Memory - - **Issue**: Memory errors during generation - - **Solution**: - - - Lower image resolution - - Reduce generation steps - - Use quantized models - - #### 3. Authentication Failure - - **Issue**: 401 or 403 errors - - **Solution**: - - - Verify authentication configuration - - Check if Token is expired - - Confirm user permissions -
-
-
-You can now use ComfyUI in LobeChat for high-quality AI image generation and editing. If you encounter issues, please refer to the troubleshooting section or consult the [ComfyUI official documentation](https://github.com/comfyanonymous/ComfyUI).
diff --git a/docs/usage/providers/comfyui.zh-CN.mdx b/docs/usage/providers/comfyui.zh-CN.mdx
index 069bb5169c..c68b98d6ac 100644
--- a/docs/usage/providers/comfyui.zh-CN.mdx
+++ b/docs/usage/providers/comfyui.zh-CN.mdx
@@ -1,6 +1,6 @@
---
-title: 在 LobeChat 中使用 ComfyUI 生成图像
-description: 学习如何在 LobeChat 中配置和使用 ComfyUI 服务，支持 FLUX 系列模型的高质量图像生成和编辑功能
+title: 在 LobeHub 中使用 ComfyUI 生成图像
+description: 学习如何在 LobeHub 中配置和使用 ComfyUI 服务，支持 FLUX 系列模型的高质量图像生成和编辑功能
tags:
- ComfyUI
- FLUX
@@ -9,15 +9,15 @@ tags:
- AI 图像生成
---
-# 在 LobeChat 中使用 ComfyUI
+# 在 LobeHub 中使用 ComfyUI
-📚 API Documentation
- - ### Request Format - - ```typescript - interface ComfyUIRequest { - model: string; // Model ID, e.g., 'flux-schnell' - prompt: string; // Text prompt - width: number; // Image width - height: number; // Image height - steps: number; // Generation steps - seed: number; // Random seed - cfg?: number; // CFG Scale (Dev/Krea/Kontext specific) - strength?: number; // Edit strength (Kontext specific) - imageUrl?: string; // Input image (Kontext specific) - } - ``` - - ### Response Format - - ```typescript - interface ComfyUIResponse { - images: Array<{ - url: string; // Generated image URL - filename: string; // Filename - subfolder: string; // Subdirectory - type: string; // File type - }>; - prompt_id: string; // Prompt ID - } - ``` - - ### Error Codes - - | Error Code | Description | Resolution Suggestions | - | ---------- | ------------------------ | -------------------------------- | - | `400` | Invalid parameters | Check parameter format and range | - | `401` | Authentication failed | Verify API key and auth config | - | `403` | Insufficient permissions | Check user permissions | - | `404` | Model not found | Confirm model file exists | - | `500` | Server error | Check ComfyUI logs | -🎨 配置自定义 SD 模型
- LobeChat 支持使用自定义的 Stable Diffusion 模型。系统使用固定的文件名来识别自定义模型。 + LobeHub 支持使用自定义的 Stable Diffusion 模型。系统使用固定的文件名来识别自定义模型。 ### 1. 模型文件准备 @@ -667,7 +667,7 @@ LobeChat ComfyUI 集成采用配置驱动的架构，支持 **223 个模型**， ### 3. 使用自定义模型 - 在 LobeChat 中，自定义模型会显示为： + 在 LobeHub 中，自定义模型会显示为： - **stable-diffusion-custom**：标准自定义模型 - **stable-diffusion-custom-refiner**：Refiner 自定义模型 @@ -686,7 +686,7 @@ LobeChat ComfyUI 集成采用配置驱动的架构，支持 **223 个模型**， ### 智能错误诊断系统 -LobeChat 集成了智能错误处理系统，能够自动诊断并提供针对性的解决方案。 +LobeHub 集成了智能错误处理系统，能够自动诊断并提供针对性的解决方案。 #### 错误类型与解决方案 @@ -813,4 +813,4 @@ sunlight filtering through leaves, warm atmosphere, cinematic lighting, 4K high | `500` | 服务器错误 | 检查 ComfyUI 日志 |- -## 2023 Overview - -
- -## 2023 特性一览 - -
-
-
-### Complex Instruction Call: Literary Map
-
-Test Instruction: Instruction ②
-
-
-
-From the above video:
-
-1. Sonnet 3.5 supports Stream Tools Calling and Parallel Tools Calling;
-2. In Stream Tools Calling, it is observed that creating long sentences will cause a delay (as seen in the Tools Calling raw output `[chunk 40]` and `[chunk 41]` with a delay of 6s). Therefore, there will be a relatively long waiting time at the beginning stage of Tools Calling.
-
-Tools Calling Raw Output:
- - ```yml - ``` -
-
-
-## Claude 3 Opus
-
-### Simple Instruction Call: Weather Query
-
-Test Instruction: Instruction ①
-
-
-
-From the above video:
-
-1. Claude 3 Opus outputs a `Tools Calling Raw Output:
- - ```yml - ``` -
-
-
-### Complex Instruction Call: Literary Map
-
-Test Instruction: Instruction ②
-
-
-
-From the above video:
-
-1. Combining with simple tasks, Opus will always output a `Tools Calling Raw Output:
-
-
-
-## Claude 3 Sonnet
-
-### Simple Instruction Call: Weather Query
-
-Test Instruction: Instruction ①
-
-
-
-From the above video, it can be seen that Claude 3 Sonnet triggers Tools Calling twice, indicating that it does not support Parallel Tools Calling.
-
-Tools Calling Raw Output:
-
-
-
-### Complex Instruction Call: Literary Map
-
-Test Instruction: Instruction ②
-
-
-
-From the above video, it can be seen that Sonnet 3 fails in the complex instruction call. The error is due to prompts being expected as an array but generated as a string.
-
-Tools Calling Raw Output:
-
-
-
-## Claude 3 Haiku
-
-
-
-From the above video:
-
-1. Claude 3 Haiku triggers Tools Calling twice, indicating that it also does not support Parallel Tools Calling;
-2. Haiku does not provide a good response and directly calls the tool;
-
-Tools Calling Raw Output:
-
-
diff --git a/docs/usage/tools-calling/anthropic.zh-CN.mdx b/docs/usage/tools-calling/anthropic.zh-CN.mdx
deleted file mode 100644
index b8bc158b5b..0000000000
--- a/docs/usage/tools-calling/anthropic.zh-CN.mdx
+++ /dev/null
@@ -1,152 +0,0 @@
----
-title: Anthropic Claude 系列 Tools Calling 评测
-description: >-
- 使用 LobeChat 测试 Anthropic Claude 系列模型（Claude 3.5 sonnet / Claude 3 Opus / Claude 3 haiku） 的工具调用（Function Calling）能力，并展现评测结果
-
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling 评测
- - 工具调用
- - 插件
----
-
-# Anthropic Claude 系列 Tools Calling
-
-Anthropic Claude 系列模型 Tools Calling 能力一览：
-
-| 模型 | 支持 Tools Calling | 流式 （Stream） | 并发（Parallel） | 简单指令得分 | 复杂指令 |
-| ----------------- | ---------------- | ----------- | ------------ | ------ | ---- |
-| Claude 3.5 Sonnet | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟🌟 |
-| Claude 3 Opus | ✅ | ✅ | ❌ | 🌟 | ⛔️ |
-| Claude 3 Sonnet | ✅ | ✅ | ❌ | 🌟🌟 | ⛔️ |
-| Claude 3 Haiku | ✅ | ✅ | ❌ | 🌟🌟 | ⛔️ |
-
-## Claude 3.5 Sonnet
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-Tools Calling Raw Output:
-
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-从上述视频中可以看到：
-
-1. Sonnet 3.5 支持流式 Tools Calling 和 Parallel Tools Calling；
-2. 在流式 Tools Calling 时，表现出来的特征是在创建长句会等待住（详见 Tools Calling 原始输出 `[chunk 40]` 和 `[chunk 41]` 中间的耗时达到 6s）。所以相对来说会在 Tools Calling 的起始阶段有一个较长的等待时间。
-
-Tools Calling 原始输出：
- - ```yml - ``` -
-
-
-## Claude 3 Opus
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-从上述视频中看到：
-
-1. Claude 3 Opus 在调用 Tools 的起点会输出一段 `Tools Calling 原始输出：
- - ```yml - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-从上述视频中看到：
-
-1. 结合简单任务， Opus 的工具调用一定会输出 `Tools Calling 原始输出：
-
-
-
-## Claude 3 Sonnet
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-从上述视频中可以看出，Claude 3 Sonnet 会调用两次 Tools Calling，说明它并不支持 Parallel Tools Calling。
-
-Tools Calling 原始输出：
-
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-从上述视频中可以看到， Sonnet 3 在复杂指令调用下就失败了。报错原因是 prompts 原本预期为一个数组，但是生成的却是一个字符串。
-
-Tools Calling 原始输出：
-
-
-
-## Claude 3 Haiku
-
-
-
-从上述视频中可以看出：
-
-1. Claude 3 Haiku 会调用两次 Tools Calling，说明它也不支持 Parallel Tools Calling；
-2. Haiku 并没有回答好的，也是直接调用的工具；
-
-Tools Calling 原始输出：
-
-
diff --git a/docs/usage/tools-calling/google.mdx b/docs/usage/tools-calling/google.mdx
deleted file mode 100644
index 646131f6b8..0000000000
--- a/docs/usage/tools-calling/google.mdx
+++ /dev/null
@@ -1,109 +0,0 @@
----
-title: Google Gemini 系列 Tool Calling 评测
-description: >-
- 使用 LobeChat 测试 Google Gemini 系列模型（Gemini 1.5 Pro / Gemini 1.5 Flash） 的工具调用（Function Calling）能力，并展现评测结果
-
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling 评测
- - 工具调用
- - 插件
----
-
-# Google Gemini Series Tool Calling
-
-Overview of Google Gemini series model Tools Calling capabilities:
-
-| Model | Tools Calling Support | Streaming | Parallel | Simple Instruction Score | Complex Instruction |
-| ---------------- | --------------------- | --------- | -------- | ------------------------ | ------------------- |
-| Gemini 1.5 Pro | ✅ | ❌ | ✅ | ⛔ | ⛔ |
-| Gemini 1.5 Flash | ❌ | ❌ | ❌ | ⛔ | ⛔ |
-
-Tools Calling 原始输出：
-
-
-
-### Complex Instruction Call: Image Generation
-
-Test Instruction: Instruction ②
-
-Original Tools Calling Output:
- - ```yml - [stream start] 2024-7-7 17:53:25.647 - [chunk 0] 2024-7-7 17:53:25.654 - {"candidates":[{"content":{"parts":[{"text":"好的"}],"role":"model"},"finishReason":"STOP","index":0}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":1,"totalTokenCount":96}} - - [chunk 1] 2024-7-7 17:53:26.288 - {"candidates":[{"content":{"parts":[{"text":"\n\n"}],"role":"model"},"finishReason":"STOP","index":0,"safetyRatings":[{"category":"HARM_CATEGORY_SEXUALLY_EXPLICIT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HATE_SPEECH","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HARASSMENT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_DANGEROUS_CONTENT","probability":"NEGLIGIBLE"}]}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":1,"totalTokenCount":96}} - - [chunk 2] 2024-7-7 17:53:26.336 - {"candidates":[{"content":{"parts":[{"functionCall":{"name":"weather____fetchCurrentWeather","args":{"city":"Hangzhou"}}},{"functionCall":{"name":"weather____fetchCurrentWeather","args":{"city":"Beijing"}}}],"role":"model"},"finishReasoSTOP","index":0,"safetyRatings":[{"category":"HARM_CATEGORY_SEXUALLY_EXPLICIT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HATE_SPEECH","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HARASSMENT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_DANGEROUS_CONTENT","probability":"NEGLIGIBLE"}]}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":79,"totalTokenCount":174}} - - [stream finished] total chunks: 3 - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-Tools Calling 原始输出：
- - ```yml - [stream start] 2024-7-7 17:53:25.647 - [chunk 0] 2024-7-7 17:53:25.654 - {"candidates":[{"content":{"parts":[{"text":"好的"}],"role":"model"},"finishReason":"STOP","index":0}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":1,"totalTokenCount":96}} - - [chunk 1] 2024-7-7 17:53:26.288 - {"candidates":[{"content":{"parts":[{"text":"\n\n"}],"role":"model"},"finishReason":"STOP","index":0,"safetyRatings":[{"category":"HARM_CATEGORY_SEXUALLY_EXPLICIT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HATE_SPEECH","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HARASSMENT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_DANGEROUS_CONTENT","probability":"NEGLIGIBLE"}]}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":1,"totalTokenCount":96}} - - [chunk 2] 2024-7-7 17:53:26.336 - {"candidates":[{"content":{"parts":[{"functionCall":{"name":"weather____fetchCurrentWeather","args":{"city":"杭州"}}},{"functionCall":{"name":"weather____fetchCurrentWeather","args":{"city":"北京"}}}],"role":"model"},"finishReasoSTOP","index":0,"safetyRatings":[{"category":"HARM_CATEGORY_SEXUALLY_EXPLICIT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HATE_SPEECH","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_HARASSMENT","probability":"NEGLIGIBLE"},{"category":"HARM_CATEGORY_DANGEROUS_CONTENT","probability":"NEGLIGIBLE"}]}],"usageMetadata":{"promptTokenCount":95,"candidatesTokenCount":79,"totalTokenCount":174}} - - [stream finished] total chunks: 3 - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-Tools Calling 原始输出：
- - ```yml - [no stream response] 2024-7-8 15:50:40.166 - - {"id":"chatcmpl-ec4b6c0b-1078-4f50-a39c-e58b3b1f9c31","object":"chat.completion","created":1720425030,"model":"llama3-70b-8192","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_v89g","type":"function","function":{"name":"realtime-weather____fetchCurrentWeather","arguments":"{\"city\":\"杭州\"}"}},{"id":"call_jxwk","type":"function","function":{"name":"realtime-weather____fetchCurrentWeather","arguments":"{\"city\":\"北京}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":969,"prompt_time":0.224209489,"completion_tokens":68,"completion_time":0.194285714,"total_tokens":1037,"total_time":0.418495203},"system_fingerprint":"fp_87cbfbbc4d","x_groq":{"id":"req_01j28n57x9e78a6bfbn9sdn139"}} - - ``` -
-
-
-## LLAMA3-8B
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-从上述视频中可以看到 LLAMA3-8B 对于天气插件可以正常调用，并获得正确的总结结果。但是它并没有完全 follow 我们的描述指令，没有回答「好的」。
-
-Tools Calling 原始输出：
- - ```yml - [no stream response] 2024-7-8 18:0:34.811 - - {"id":"chatcmpl-e3b59ca9-1172-4ae2-96c7-3d6997a1f8a8","object":"chat.completion","created":1720432834,"model":"llama3-70b-8192","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_azm9","type":"function","function":{"name":"lobe-image-designer____text2image____builtin","arguments":"{\"prompts\":[\"A small, fluffy, and playful golden retriever puppy with a white patch on its forehead, sitting on a green grass field with a bright blue sky in the background, photo.\",\"A cute, little, brown and white Dalmatian puppy with a red collar, running around in a park with a sunny day, illustration.\",\"A tiny, grey and white Poodle puppy with a pink ribbon, sitting on a white couch with a few toys surrounding it, watercolor painting.\",\"A sweet, small, black and white Chihuahua puppy with a pink bow, lying on a soft, white blanket with a few stuffed animals nearby, oil painting.\"],\"quality\":\"standard\",\"seeds\":[],\"size\":\"1024x1024\",\"style\":\"vivid\"}"}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":2305,"prompt_time":3.027052298,"completion_tokens":246,"completion_time":0.702857143,"total_tokens":2551,"total_time":3.729909441},"system_fingerprint":"fp_7ab5f7e105","x_groq":{"id":"req_01j28wk2q0efvs22qatw7rd0ds"}} - - POST /api/chat/groq 200 in 17462ms - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-LLAMA3 8B 在 DallE 的输出场景下，只会输出 1 张图片，而不是像 LLAMA3 70B 一样输出 4 张，意味着在复杂 Tools 指令层面，能力和 GPT 3.5 Turbo 接近，不如 GPT 4。
-
-Tools Calling 原始输出：
- - ```yml - [no stream response] 2024-7-9 11:33:16.920 - - {"id":"chatcmpl-f3672d59-e91d-4253-af1b-bfc4e0912085","object":"chat.completion","created":1720495996,"model":"llama3-8b-8192","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_rjtk","type":"function","function":{"name":"realtime-weather____fetchCurrentWeather","arguments":"{\"city\":\"杭州市\"}"}},{"id":"call_7pqh","type":"functi,"function":{"name":"realtime-weather____fetchCurrentWeather","arguments":"{\"city\":\"北京市\"}"}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":969,"ppt_time":0.145428625,"completion_tokens":128,"completion_time":0.101364747,"total_tokens":1097,"total_time":0.246793372},"system_fingerprint":"fp_33d61fdfc3","x_groq":{"id":"req_01j2artze1exz82nettf2h9066"}} - - POST /api/chat/groq 200 in 1649ms - ``` -
-
-
-## Mixtral-8x7B
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-
-
-从上述视频中可以看到 Mixtral-8x7B 对于天气插件的查询输出的参数有问题，导致无法正常调用插件。
-
-Tools Calling 原始输出：
- - ```yml - [no stream response] 2024-7-9 11:58:27.40 - - {"id":"chatcmpl-3c38f4d2-3424-416c-9fb0-0969d2683959","object":"chat.completion","created":1720497506,"model":"llama3-8b-8192","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_k6xj","type":"function","function":{"name":"lobe-image-designer____text2image____builtin","arguments":"{\"prompts\":[\"Create a watercolor painting of a small white dog with a pink nose, wearing a red collar and sitting on a green grass. The dog's ears should be floppy and its fur should be curly.\"],\"quality\":\"standard\",\"seeds\":[],\"size\":\"1024x1024\",\"style\":\"natural\"}"}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":2282,"prompt_time":0.342335558,"completion_tokens":148,"completion_time":0.118023813,"total_tokens":2430,"total_time":0.460359371},"system_fingerprint":"fp_179b0f92c9","x_groq":{"id":"req_01j2at921tec8aymdq48czcw1y"}} - - POST /api/chat/groq 200 in 2517ms - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-非常意外地，Mixtral 8x7B 在文生图的 Tools Calling 的场景下，居然可以正常出图，而且出图的能力基本和 LLAMA3 70B 持平。
-
-Tools Calling 原始输出：
- - ```yml - - [no stream response] 2024-7-8 22:18:19.682 - - {"id":"chatcmpl-9f89d669-5642-48be-b5cd-7a29756800c0","object":"chat.completion","created":1720448299,"model":"mixtral-8x7b-32768","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_719t","type":"function","function":{"name":"realtime-weather____fetchCurrentWeather","arguments":"{\"city\":\"Hangzhou,Beijing\"}"}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":1262,"prompt_time":0.116684046,"completion_tokens":102,"completion_time":0.163113006,"total_tokens":1364,"total_time":0.279797052},"system_fingerprint":"fp_c5f20b5bb1","x_groq":{"id":"req_01j29bbc8xen2s3thp9qen5bys"}} - - POST /api/chat/groq 200 in 4860ms - ``` -
-
diff --git a/docs/usage/tools-calling/moonshot.mdx b/docs/usage/tools-calling/moonshot.mdx
deleted file mode 100644
index 422f796b92..0000000000
--- a/docs/usage/tools-calling/moonshot.mdx
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: ''
-description: 学习如何有效管理待办事项，提高工作效率和生产力。
-tags:
- - 待办事项
- - 工作效率
- - 生产力
----
-
-TODO
diff --git a/docs/usage/tools-calling/moonshot.zh-CN.mdx b/docs/usage/tools-calling/moonshot.zh-CN.mdx
deleted file mode 100644
index 7b532b736b..0000000000
--- a/docs/usage/tools-calling/moonshot.zh-CN.mdx
+++ /dev/null
@@ -1,24 +0,0 @@
----
-title: Moonshot 系列 Tools Calling 评测
-description: 使用 LobeChat 测试 Moonshot 系列模型（Moonshot-1） 的工具调用（Function Calling）能力，并展现评测结果
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling
- - 工具调用
- - 插件
----
-
-# Moonshot 系列工具调用（Tools Calling）
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-TODO
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-TODO
diff --git a/docs/usage/tools-calling/openai.mdx b/docs/usage/tools-calling/openai.mdx
deleted file mode 100644
index a8ec1cc0eb..0000000000
--- a/docs/usage/tools-calling/openai.mdx
+++ /dev/null
@@ -1,114 +0,0 @@
----
-title: OpenAI GPT 系列 Tools Calling 评测
-description: >-
- 使用 LobeChat 测试 OpenAI GPT 系列模型（GPT 3.5-turbo / GPT-4 /GPT-4o） 的工具调用（Function Calling）能力，并展现评测结果
-
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling
- - 工具调用
- - 插件
----
-
-# OpenAI GPT Series Tool Calling
-
-Overview of the Tool Calling capabilities of OpenAI GPT series models:
-
-| Model | Tool Calling Support | Streaming | Parallel | Simple Instruction Score | Complex Instruction Score |
-| ------------- | -------------------- | --------- | -------- | ------------------------ | ------------------------- |
-| GPT-3.5-turbo | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟 |
-| GPT-4-turbo | ✅ | ✅ | ✅ | 🌟🌟 | 🌟🌟 |
-| GPT-4o | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟🌟 |
-
-Tools Calling 原始输出：
- - ```yml - [no stream response] 2024-7-9 12:6:38.11 - - {"id":"chatcmpl-a90069f3-b119-41b9-b8d7-c7f97373529e","object":"chat.completion","created":1720497998,"model":"mixtral-8x7b-32768","choices":[{"index":0,"message":{"role":"assistant","tool_calls":[{"id":"call_hw8t","type":"function","function":{"name":"lobe-image-designer____text2image____builtin","arguments":"{\"prompts\":[\"A colorful and playful illustration of a friendly small dog, looking directly at the viewer with a wagging tail and bright, expressive eyes. The dog's fur is glossy and well-groomed, with a mix of black, white, and brown colors. The background is a lush, green park with a clear blue sky and a few fluffy clouds.\",\"An oil painting of a small, energetic dog in a sunlit park, chasing a frisbee. The dog is a mix of black and white fur, with a distinct brown spot above its left eye. The park features tall trees, providing dappled shade across the grassy landscape. The frisbee is bright orange and stands out against the natural surroundings.\",\"A realistic watercolor painting of a small, fluffy white dog curled up next to a warm fireplace during a cozy winter evening. The dog's eyes are closed in contentment, and a single red bow is tied around its neck. The background includes a plush armchair, a stack of books, and a softly lit room.\",\"A fun and engaging cartoon of a small dog sitting at a café table, enjoying a cup of coffee and a croissant. The dog has a expressive face and a blue scarf around its neck. The café has a vintage, 1920's style and a red awning, with a bustling city background.\"],\"quality\":\"standard\",\"size\":\"1024x1024\",\"style\":\"vivid\"}"}}]},"logprobs":null,"finish_reason":"tool_calls"}],"usage":{"prompt_tokens":2920,"prompt_time":0.228639219,"completion_tokens":465,"completion_time":0.755757988,"total_tokens":3385,"total_time":0.984397207},"system_fingerprint":"fp_c5f20b5bb1","x_groq":{"id":"req_01j2atr155f0nv8rmfk448e2at"}} - - POST /api/chat/groq 200 in 6216ms - - ``` -
-
-
-### Complex Instruction Call: Wenshengtu
-
-Test Instruction: Instruction ②
-
-
-
-Streaming Tool Calling Raw Output:
-
-
-
-## GPT-4 Turbo
-
-### Simple Instruction Call: Weather Inquiry
-
-Test Instruction: Instruction ①
-
-Unlike GPT-3.5 Turbo, GPT-4 Turbo did not respond with "okay" when calling Tool Calling, and after multiple tests, it remained the same. Therefore, in this follow-up of a compound instruction, it is not as good as GPT-3.5 Turbo, but the remaining two capabilities are still good.
-
-Of course, it is also possible that GPT-4 Turbo's model has more "autonomy" and believes that it does not need to output this "okay."
-
-
-
-Streaming Tool Calling Raw Output:
-
-
-
-### Complex Instruction Call: Wenshengtu
-
-Test Instruction: Instruction ②
-
-
-
-Streaming Tool Calling Raw Output:
-
-
-
-## GPT-4o
-
-### Simple Instruction Call: Weather Inquiry
-
-Test Instruction: Instruction ①
-
-Similar to GPT-3.5, GPT-4o performs very well in following compound instructions in simple instruction calls.
-
-
-
-Streaming Tool Calling Raw Output:
-
-
-
-### Complex Instruction Call: Wenshengtu
-
-Test Instruction: Instruction ②
-
-
-
-Streaming Tool Calling Raw Output:
-
-
diff --git a/docs/usage/tools-calling/openai.zh-CN.mdx b/docs/usage/tools-calling/openai.zh-CN.mdx
deleted file mode 100644
index 19e5396da3..0000000000
--- a/docs/usage/tools-calling/openai.zh-CN.mdx
+++ /dev/null
@@ -1,114 +0,0 @@
----
-title: OpenAI GPT 系列 Tools Calling 评测
-description: >-
- 使用 LobeChat 测试 OpenAI GPT 系列模型（GPT 3.5-turbo / GPT-4 /GPT-4o） 的工具调用（Function Calling）能力，并展现评测结果
-
-tags:
- - Tools Calling
- - Benchmark
- - Function Calling
- - 工具调用
- - 插件
----
-
-# OpenAI GPT 系列工具调用（Tools Calling）
-
-OpenAI GPT 系列模型 Tool Calling 能力一览：
-
-| 模型 | 支持 Tool Calling | 流式 （Stream） | 并发（Parallel） | 简单指令得分 | 复杂指令 |
-| ------------- | --------------- | ----------- | ------------ | ------ | ---- |
-| GPT-3.5-turbo | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟 |
-| GPT-4-turbo | ✅ | ✅ | ✅ | 🌟🌟 | 🌟🌟 |
-| GPT-4o | ✅ | ✅ | ✅ | 🌟🌟🌟 | 🌟🌟 |
-
-Streaming Tool Calling Raw Output:
- - ```yml - ``` -
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-流式 Tool Calling 原始输出：
-
-
-
-## GPT-4 Turbo
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-GPT-4 Turbo 在调用 Tool Calling 时并没有像 GPT-3.5 Turbo 一样回复「好的」，且经过多次测试始终一样，因此在这一条复合指令的跟随中反而不如 GPT-3.5 Turbo，但剩余两项能力均不错。
-
-当然，也有可能是因为 GPT-4 Turbo 的模型更加有 “自主意识”，认为不需要输出这一句 “好的”。
-
-
-
-流式 Tool Calling 原始输出：
-
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-流式 Tool Calling 原始输出：
-
-
-
-## GPT 4o
-
-### 简单调用指令：天气查询
-
-测试指令：指令 ①
-
-GPT-4o 和 3.5 一样，在简单调用指令中，能够达到非常不错的复合指令遵循能力。
-
-
-
-流式 Tool Calling 原始输出：
-
-
-
-### 复杂调用指令：文生图
-
-测试指令：指令 ②
-
-
-
-流式 Tool Calling 原始输出：
-
-
diff --git a/docs/usage/user-interface/appearance.mdx b/docs/usage/user-interface/appearance.mdx
new file mode 100644
index 0000000000..08c6e5a82c
--- /dev/null
+++ b/docs/usage/user-interface/appearance.mdx
@@ -0,0 +1,53 @@
+---
+title: Interface Appearance
+description: >-
+ LobeHub supports various large language models with visual recognition
+ capabilities. Users can upload or drag and drop images, and the assistant will
+ recognize the content and initiate intelligent conversations, creating a
+ smarter and more diverse chat experience.
+tags:
+ - LobeHub
+ - LobeHub
+ - Interface Appearance
+ - Language
+ - Theme
+ - Animation Mode
+ - Context Menu Mode
+---
+
+# Interface Appearance
+
+Click on your user avatar in the top-right corner of the homepage, then select "App Settings" from the dropdown menu. Click on "Appearance" to enter the customization page. This section gathers all visual-related configuration options. \[Image]
+
+## Language
+
+You can switch the interface language in the settings.
+
+## Theme Mode
+
+LobeHub supports three theme modes:
+
+- Light Mode
+- Dark Mode
+- Follow System (default)
+
+## Theme Colors
+
+In addition to light and dark modes, you can also customize the theme color to create a personalized visual style. LobeHub offers a variety of preset theme and neutral colors. Simply click on a color swatch to apply it—buttons, highlights, and other interface elements will instantly update to reflect the selected theme color.
+
+## Assistant Language
+
+Set the default language for AI assistant responses. Once selected, the assistant will prioritize replying in this language unless you explicitly request another language during the conversation.
+
+## Animation Effects
+
+When your conversation or document includes code, you can choose a syntax highlighting theme. Select a code highlight style that complements the overall theme to make your code more readable and visually appealing.
+
+## Mermaid Theme
+
+Mermaid is a tool for creating diagrams using text. When your conversation or document includes Mermaid diagrams, you can choose a theme style for them. Select a Mermaid theme that aligns with the overall interface theme to make flowcharts, sequence diagrams, and other visuals more attractive.
+
+## Mode Selection
+
+- Professional Mode
+- Simplified Mode
diff --git a/docs/usage/user-interface/appearance.zh-CN.mdx b/docs/usage/user-interface/appearance.zh-CN.mdx
new file mode 100644
index 0000000000..34844c771d
--- /dev/null
+++ b/docs/usage/user-interface/appearance.zh-CN.mdx
@@ -0,0 +1,49 @@
+---
+title: 界面外观
+description: LobeHub 支持多种具有视觉识别能力的大语言模型，用户可上传或拖拽图片，助手将识别内容并展开智能对话，打造更智能、多元化的聊天场景。
+tags:
+ - LobeHub
+ - LobeHub
+ - 界面外观
+ - 语言
+ - 主题
+ - 动画模式
+ - 上下文菜单模式
+---
+
+# 界面外观
+
+在首页右上角点击用户头像，在下拉菜单中选择「应用设置」，点击「外观」，进入自定义页面。这里汇集了所有视觉相关的配置选项。\[Image]
+
+## 语言
+
+你可以在设置中切换语言。
+
+## 主题模式
+
+LobeHub 支持三种主题模式：
+
+- 亮色模式
+- 深色模式
+- 跟随系统（默认）
+
+## 主题色彩
+
+除了明暗模式，你还可以自定义主题色彩，打造个性化的视觉风格。LobeHub 提供多种预设主题色和中性色，点击色卡即可应用，界面的按钮、高亮等元素会立即切换为选中的主题色。
+
+## 助手语言
+
+设置 AI 助手回复的默认语言。选择后，助手会优先使用该语言回答问题，除非你在对话中明确要求使用其他语言。
+
+## 动画效果
+
+当对话或文稿中包含代码时，可以选择代码高亮的配色方案。选择与整体主题协调的代码高亮方案，让代码更易读、更美观。
+
+## Mermaid 主题
+
+Mermaid 是一种用文本描述图表的工具。当对话或文稿中包含 Mermaid 图表时，可以选择图表的主题样式。选择与整体主题协调的 Mermaid 主题，让流程图、时序图等图表更美观。
+
+## 模式选择
+
+- 专业模式
+- 精简模式
diff --git a/docs/usage/user-interface/command-menu.mdx b/docs/usage/user-interface/command-menu.mdx
new file mode 100644
index 0000000000..eaae83f100
--- /dev/null
+++ b/docs/usage/user-interface/command-menu.mdx
@@ -0,0 +1,56 @@
+---
+title: Command Menu
+description: >-
+ The Command Menu is the quick action center of LobeHub. Instantly accessible via keyboard shortcuts, it allows you to search and execute various actions without navigating through multiple interface layers. This makes navigation and operations faster and more efficient.
+
+
+tags:
+ - Command Menu
+ - LobeHub
+ - Quick Navigation
+ - Action Center
+ - Keyboard Shortcuts
+---
+
+# Command Menu
+
+The Command Menu is the quick action center of LobeHub. Instantly accessible via keyboard shortcuts, it allows you to search and execute various actions without navigating through multiple interface layers. This makes navigation and operations faster and more efficient.
+
+The Command Menu supports fuzzy search, so you don’t need to type the full name—just a few keywords will do. For example, typing "programming" will bring up "Python Programming Assistant." When frequently switching between assistants, using the Command Menu is much faster than browsing through the sidebar.
+
+## Open the Command Menu
+
+Use the following keyboard shortcuts to open the Command Menu:\
+macOS: Cmd + K\
+Windows/Linux: Ctrl + K\
+The Command Menu will appear as an overlay in the center of the screen.
+
+流式 Tool Calling 原始输出：
- - ```yml - ``` -
+
+
+
+
+
+
+
+
+
+我们已将贡献指南迁移至[此页面](https://lobehub.com/zh/docs/development/start)。
diff --git a/package.json b/package.json
index 7ee43c7f9d..64d1682804 100644
--- a/package.json
+++ b/package.json
@@ -57,7 +57,8 @@
"dev:desktop": "cross-env NEXT_PUBLIC_IS_DESKTOP_APP=1 tsx scripts/runNextDesktop.mts dev -p 3015",
"dev:desktop:static": "cross-env DESKTOP_RENDERER_STATIC=1 npm run electron:dev --prefix=./apps/desktop",
"dev:mobile": "next dev -p 3018",
- "docs:i18n": "lobe-i18n md && npm run lint:md && npm run lint:mdx && prettier -c --write locales/**/*",
+ "docs:cdn": "npm run workflow:docs-cdn && npm run lint:mdx",
+ "docs:i18n": "lobe-i18n md && npm run lint:mdx",
"docs:seo": "lobe-seo && npm run lint:mdx",
"e2e": "cd e2e && npm run test",
"e2e:install": "playwright install",
@@ -100,6 +101,7 @@
"workflow:countCharters": "tsx scripts/countEnWord.ts",
"workflow:dbml": "tsx ./scripts/dbmlWorkflow/index.ts",
"workflow:docs": "tsx ./scripts/docsWorkflow/index.ts",
+ "workflow:docs-cdn": "tsx ./scripts/docsWorkflow/autoCDN.ts",
"workflow:i18n": "tsx ./scripts/i18nWorkflow/index.ts",
"workflow:mdx": "tsx ./scripts/mdxWorkflow/index.ts",
"workflow:readme": "tsx ./scripts/readmeWorkflow/index.ts",
diff --git a/scripts/cdnWorkflow/index.ts b/scripts/cdnWorkflow/index.ts
index fa907d08a0..b069a06229 100644
--- a/scripts/cdnWorkflow/index.ts
+++ b/scripts/cdnWorkflow/index.ts
@@ -27,6 +27,8 @@ const CHECK_CDN = [
'https://miro.medium.com/v2/',
'https://images.unsplash.com/',
'https://github.com/user-attachments/assets',
+ 'https://i.imgur.com/',
+ 'https://file.rene.wang',
];
const CACHE_FILE = resolve(root, 'docs', '.cdn.cache.json');
diff --git a/scripts/docsWorkflow/autoCDN.ts b/scripts/docsWorkflow/autoCDN.ts
new file mode 100644
index 0000000000..7462d500d2
--- /dev/null
+++ b/scripts/docsWorkflow/autoCDN.ts
@@ -0,0 +1,172 @@
+import { consola } from 'consola';
+import matter from 'gray-matter';
+import { createHash } from 'node:crypto';
+import { readFileSync, writeFileSync } from 'node:fs';
+import { resolve } from 'node:path';
+import pMap from 'p-map';
+
+import { uploader } from '../cdnWorkflow/uploader';
+import {
+ extractHttpsLinks,
+ fetchImageAsFile,
+ mergeAndDeduplicateArrays,
+ posts,
+ root,
+} from './utils';
+
+// 定义常量
+const GITHUB_CDN = 'https://github.com/lobehub/lobe-chat/assets/';
+const CHECK_CDN = [
+ 'https://cdn.nlark.com/yuque/0/',
+ 'https://s.imtccdn.com/',
+ 'https://oss.home.imtc.top/',
+ 'https://www.anthropic.com/_next/image',
+ 'https://miro.medium.com/v2/',
+ 'https://images.unsplash.com/',
+ 'https://github.com/user-attachments/assets',
+ 'https://i.imgur.com/',
+ 'https://file.rene.wang',
+];
+
+const CACHE_FILE = resolve(root, 'docs', '.cdn.cache.json');
+
+class ImageCDNUploader {
+ private cache: { [link: string]: string } = {};
+
+ constructor() {
+ this.loadCache();
+ }
+
+ // 从文件加载缓存数据
+ private loadCache() {
+ try {
+ this.cache = JSON.parse(readFileSync(CACHE_FILE, 'utf8'));
+ } catch (error) {
+ consola.error('Failed to load cache', error);
+ }
+ }
+
+ // 将缓存数据写入文件
+ private writeCache() {
+ try {
+ writeFileSync(CACHE_FILE, JSON.stringify(this.cache, null, 2));
+ } catch (error) {
+ consola.error('Failed to write cache', error);
+ }
+ }
+
+ // 收集所有的图片链接
+ private collectImageLinks(): string[] {
+ const links: string[][] = posts.map((post) => {
+ const mdx = readFileSync(post, 'utf8');
+ const { content, data } = matter(mdx);
+ let inlineLinks: string[] = extractHttpsLinks(content);
+
+ // 添加特定字段中的图片链接
+ if (data?.image) inlineLinks.push(data.image);
+ if (data?.seo?.image) inlineLinks.push(data.seo.image);
+
+ // 过滤出有效的 CDN 链接
+ return inlineLinks.filter(
+ (link) =>
+ (link.startsWith(GITHUB_CDN) || CHECK_CDN.some((cdn) => link.startsWith(cdn))) &&
+ !this.cache[link],
+ );
+ });
+
+ // 合并和去重链接数组
+ return mergeAndDeduplicateArrays(...links);
+ }
+
+ // 上传图片到 CDN
+ private async uploadImagesToCDN(links: string[]) {
+ const cdnLinks: { [link: string]: string } = {};
+
+ await pMap(links, async (link) => {
+ consola.start('Uploading image to CDN', link);
+ const file = await fetchImageAsFile(link, 1600);
+
+ if (!file) {
+ consola.error('Failed to fetch image as file', link);
+ return;
+ }
+
+ const cdnUrl = await this.uploadFileToCDN(file, link);
+ if (cdnUrl) {
+ consola.success(link, '>>>', cdnUrl);
+ cdnLinks[link] = cdnUrl.replaceAll(process.env.DOC_S3_PUBLIC_DOMAIN || '', '');
+ }
+ });
+
+ // 更新缓存
+ this.cache = { ...this.cache, ...cdnLinks };
+ this.writeCache();
+ }
+
+ // 根据不同的 CDN 来处理文件上传
+ private async uploadFileToCDN(file: File, link: string): Promise
+
+
+
+