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diff --git a/docs/self-hosting/advanced/auth.mdx b/docs/self-hosting/advanced/auth.mdx
@@ -31,7 +31,7 @@ Before using NextAuth, please set the following variables in LobeChat's environm
 | --- | --- | --- |
 | `NEXT_AUTH_SECRET` | Required | The key used to encrypt Auth.js session tokens. You can use the following command: `openssl rand -base64 32`, or visit `https://generate-secret.vercel.app/32` to generate the key. |
 | `NEXTAUTH_URL` | Required | This URL specifies the callback address for Auth.js when performing OAuth verification. Set this only if the default generated redirect address is incorrect. `https://example.com/api/auth` |
-| `NEXT_AUTH_SSO_PROVIDERS` | Optional | This environment variable is used to enable multiple identity verification sources simultaneously, separated by commas, for example, `auth0,azure-ad,authentik`. |
+| `NEXT_AUTH_SSO_PROVIDERS` | Optional | This environment variable is used to enable multiple identity verification sources simultaneously, separated by commas, for example, `auth0,microsoft-entra-id,authentik`. |
 
 Currently supported identity verification services include:
 
@@ -56,7 +56,7 @@ Click on the links to view the corresponding platform's configuration documentat
 
 ## Advanced Configuration
 
-To simultaneously enable multiple identity verification sources, please set the `NEXT_AUTH_SSO_PROVIDERS` environment variable, separating them with commas, for example, `auth0,azure-ad,authentik`.
+To simultaneously enable multiple identity verification sources, please set the `NEXT_AUTH_SSO_PROVIDERS` environment variable, separating them with commas, for example, `auth0,microsoft-entra-id,authentik`.
 
 The order corresponds to the display order of the SSO providers.
 
@@ -69,7 +69,7 @@ The order corresponds to the display order of the SSO providers.
 | Cloudflare Zero Trust | `cloudflare-zero-trust` |
 | Github             | `github`    |
 | Logto              | `logto`     |
-| Microsoft Entra ID | `azure-ad`  |
+| Microsoft Entra ID | `microsoft-entra-id`  |
 | ZITADEL            | `zitadel`   |
 
 ## Other SSO Providers

diff --git a/docs/self-hosting/advanced/auth.zh-CN.mdx b/docs/self-hosting/advanced/auth.zh-CN.mdx
@@ -28,7 +28,7 @@ LobeChat 与 Clerk 做了深度集成，能够为用户提供一个更加安全
 | --- | --- | --- |
 | `NEXT_AUTH_SECRET` | 必选 | 用于加密 Auth.js 会话令牌的密钥。您可以使用以下命令： `openssl rand -base64 32`，或者访问 `https://generate-secret.vercel.app/32` 生成秘钥。 |
 | `NEXTAUTH_URL` | 必选 | 该 URL 用于指定 Auth.js 在执行 OAuth 验证时的回调地址，当默认生成的重定向地址发生不正确时才需要设置。`https://example.com/api/auth` |
-| `NEXT_AUTH_SSO_PROVIDERS` | 可选 | 该环境变量用于同时启用多个身份验证源，以逗号 `,` 分割，例如 `auth0,azure-ad,authentik`。 |
+| `NEXT_AUTH_SSO_PROVIDERS` | 可选 | 该环境变量用于同时启用多个身份验证源，以逗号 `,` 分割，例如 `auth0,microsoft-entra-id,authentik`。 |
 
 目前支持的身份验证服务有：
 
@@ -53,7 +53,7 @@ LobeChat 与 Clerk 做了深度集成，能够为用户提供一个更加安全
 
 ## 进阶配置
 
-同时启用多个身份验证源请设置 `NEXT_AUTH_SSO_PROVIDERS` 环境变量，以逗号 `,` 分割，例如 `auth0,azure-ad,authentik`。
+同时启用多个身份验证源请设置 `NEXT_AUTH_SSO_PROVIDERS` 环境变量，以逗号 `,` 分割，例如 `auth0,microsoft-entra-id,authentik`。
 
 顺序为 SSO 提供商的显示顺序。
 
@@ -66,7 +66,7 @@ LobeChat 与 Clerk 做了深度集成，能够为用户提供一个更加安全
 | Cloudflare Zero Trust | `cloudflare-zero-trust` |
 | Github             | `github`    |
 | Logto              | `logto`     |
-| Microsoft Entra ID | `azure-ad`  |
+| Microsoft Entra ID | `microsoft-entra-id`  |
 | ZITADEL            | `zitadel`   |
 
 ## 其他 SSO 提供商

diff --git a/docs/self-hosting/advanced/auth/next-auth/microsoft-entra-id.mdx b/docs/self-hosting/advanced/auth/next-auth/microsoft-entra-id.mdx
@@ -25,7 +25,7 @@ Fill in the desired application name to be displayed to organizational users, ch
 In the `Redirect URI (optional)` section, for the application type, select `Web`, and in the Callback URL, enter:
 
 ```bash
-https://your-domain/api/auth/callback/azure-ad
+https://your-domain/api/auth/callback/microsoft-entra-id
 ```
 
 <Callout type={'info'}>
@@ -72,10 +72,10 @@ When deploying LobeChat, you need to configure the following environment variabl
 | Environment Variable | Type | Description |
 | --- | --- | --- |
 | `NEXT_AUTH_SECRET` | Required | Key used to encrypt Auth.js session tokens. You can generate the key using the following command: `openssl rand -base64 32` |
-| `NEXT_AUTH_SSO_PROVIDERS` | Required | Select the single sign-on provider for LoboChat. Use `azure-ad` for Microsoft Entra ID. |
-| `AUTH_AZURE_AD_ID` | Required | Client ID of the Microsoft Entra ID application. |
-| `AUTH_AZURE_AD_SECRET` | Required | Client Secret of the Microsoft Entra ID application. |
-| `AUTH_AZURE_AD_TENANT_ID` | Required | Tenant ID of the Microsoft Entra ID application. |
+| `NEXT_AUTH_SSO_PROVIDERS` | Required | Select the single sign-on provider for LoboChat. Use `microsoft-entra-id` for Microsoft Entra ID. |
+| `AUTH_MICROSOFT_ENTRA_ID_ID` | Required | Client ID of the Microsoft Entra ID application. |
+| `AUTH_MICROSOFT_ENTRA_ID_SECRET` | Required | Client Secret of the Microsoft Entra ID application. |
+| `AUTH_MICROSOFT_ENTRA_ID_TENANT_ID` | Required | Tenant ID of the Microsoft Entra ID application. |
 | `NEXTAUTH_URL` | Required | This URL is used to specify the callback address for Auth.js when performing OAuth authentication. It is only necessary to set it when the default generated redirect address is incorrect. `https://example.com/api/auth` |
 
 <Callout type={'tip'}>

diff --git a/docs/self-hosting/advanced/auth/next-auth/microsoft-entra-id.zh-CN.mdx b/docs/self-hosting/advanced/auth/next-auth/microsoft-entra-id.zh-CN.mdx
@@ -24,7 +24,7 @@ tags:
 在 `Redirect URI (optional)` 中，应用类型选择 `Web`，Callback URL, 处填写：
 
 ```bash
-https://your-domain/api/auth/callback/azure-ad
+https://your-domain/api/auth/callback/microsoft-entra-id
 ```
 
 <Callout type={'info'}>
@@ -69,10 +69,10 @@ https://your-domain/api/auth/callback/azure-ad
 | 环境变量 | 类型 | 描述 |
 | --- | --- | --- |
 | `NEXT_AUTH_SECRET` | 必选 | 用于加密 Auth.js 会话令牌的密钥。您可以使用以下命令生成秘钥： `openssl rand -base64 32` |
-| `NEXT_AUTH_SSO_PROVIDERS` | 必选 | 选择 LoboChat 的单点登录提供商。使用 Microsoft Entra ID 请填写 `azure-ad`。 |
-| `AUTH_AZURE_AD_ID` | 必选 | Microsoft Entra ID 应用程序的 Client ID |
-| `AUTH_AZURE_AD_SECRET` | 必选 | Microsoft Entra ID 应用程序的 Client Secret |
-| `AUTH_AZURE_AD_TENANT_ID` | 必选 | Microsoft Entra ID 应用程序的 Tenant ID |
+| `NEXT_AUTH_SSO_PROVIDERS` | 必选 | 选择 LoboChat 的单点登录提供商。使用 Microsoft Entra ID 请填写 `microsoft-entra-id`。 |
+| `AUTH_MICROSOFT_ENTRA_ID_ID` | 必选 | Microsoft Entra ID 应用程序的 Client ID |
+| `AUTH_MICROSOFT_ENTRA_ID_SECRET` | 必选 | Microsoft Entra ID 应用程序的 Client Secret |
+| `AUTH_MICROSOFT_ENTRA_ID_TENANT_ID` | 必选 | Microsoft Entra ID 应用程序的 Tenant ID |
 | `NEXTAUTH_URL` | 必选 | 该 URL 用于指定 Auth.js 在执行 OAuth 验证时的回调地址，当默认生成的重定向地址发生不正确时才需要设置。`https://example.com/api/auth` |
 
   <Callout type={'tip'}>

diff --git a/docs/self-hosting/environment-variables/auth.mdx b/docs/self-hosting/environment-variables/auth.mdx
@@ -29,9 +29,9 @@ LobeChat provides a complete authentication service capability when deployed. Th
 #### `NEXT_AUTH_SSO_PROVIDERS`
 
 - Type: Optional
-- Description: Select the single sign-on provider for LoboChat. For multiple SSO Providers separating them with commas, for example, `auth0,azure-ad,authentik`.
+- Description: Select the single sign-on provider for LoboChat. For multiple SSO Providers separating them with commas, for example, `auth0,microsoft-entra-id,authentik`.
 - Default: `auth0`
-- Example: `auth0,azure-ad,authentik`
+- Example: `auth0,microsoft-entra-id,authentik`
 
 #### `NEXTAUTH_URL`
 

diff --git a/docs/self-hosting/environment-variables/auth.zh-CN.mdx b/docs/self-hosting/environment-variables/auth.zh-CN.mdx
@@ -27,9 +27,9 @@ LobeChat 在部署时提供了完善的身份验证服务能力，以下是相
 #### `NEXT_AUTH_SSO_PROVIDERS`
 
 - 类型：可选
-- 描述：选择 LoboChat 的单点登录提供商。如果有多个单点登录提供商，请用逗号分隔，例如 `auth0,azure-ad,authentik`
+- 描述：选择 LoboChat 的单点登录提供商。如果有多个单点登录提供商，请用逗号分隔，例如 `auth0,microsoft-entra-id,authentik`
 - 默认值: `auth0`
-- 示例: `auth0,azure-ad,authentik`
+- 示例: `auth0,microsoft-entra-id,authentik`
 
 #### `NEXTAUTH_URL`
 

diff --git a/docs/self-hosting/server-database/docker.zh-CN.mdx b/docs/self-hosting/server-database/docker.zh-CN.mdx
@@ -20,10 +20,8 @@ tags:
 </div>
 
 <Callout type="info">
-  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
-  版的部署原理，请先查阅 [使用服务端数据库部署](https://lobehub.com/zh/docs/self-hosting/advanced/s3/tencent-cloud) 。
-  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](https://lobehub.com/zh/docs/self-hosting/advanced/s3/tencent-cloud)。
+  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 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)。
 </Callout>
 
 <Callout type="warning">
@@ -165,6 +163,7 @@ $ docker run -it -d --name lobe-chat-database -p 3210:3210 \
   ，将会走到自身容器的 `localhost`，此时请尝试用 `host.docker.internal` 替代 `localhost`
 </Callout>
 
+
 [docker-pulls-link]: https://hub.docker.com/r/lobehub/lobe-chat-database
 [docker-pulls-shield]: https://img.shields.io/docker/pulls/lobehub/lobe-chat-database?color=45cc11&labelColor=black&style=flat-square
 [docker-release-link]: https://hub.docker.com/r/lobehub/lobe-chat-database

diff --git a/package.json b/package.json
@@ -120,7 +120,7 @@
     "@huggingface/inference": "^2.8.1",
     "@icons-pack/react-simple-icons": "9.6.0",
     "@khmyznikov/pwa-install": "^0.3.9",
-    "@langchain/community": "^0.2.33",
+    "@langchain/community": "^0.3.0",
     "@lobehub/chat-plugin-sdk": "^1.32.4",
     "@lobehub/chat-plugins-gateway": "^1.9.0",
     "@lobehub/icons": "^1.35.4",

diff --git a/src/config/modelProviders/github.ts b/src/config/modelProviders/github.ts
@@ -149,7 +149,7 @@ const Github: ModelProviderCard = {
     {
       description: 'Phi-3-mini模型的更新版。',
       displayName: 'Phi-3.5-mini 128K',
-      id: 'Phi-3-5-mini-instruct',
+      id: 'Phi-3.5-mini-instruct',
       maxOutput: 4096,
       tokens: 131_072,
     },

diff --git a/src/config/modelProviders/hunyuan.ts b/src/config/modelProviders/hunyuan.ts
@@ -71,31 +71,30 @@ const Hunyuan: ModelProviderCard = {
       tokens: 32_000,
     },
     {
-      description: '混元最新代码生成模型，经过 200B 高质量代码数据增训基座模型，迭代半年高质量 SFT 数据训练，上下文长窗口长度增大到 8K，五大语言代码生成自动评测指标上位居前列；五大语言10项考量各方面综合代码任务人工高质量评测上，性能处于第一梯队',
-      displayName: 'Hunyuan Code',
+      description: '混元最新多模态模型，支持图片+文本输入生成文本内容。',
+      displayName: 'Hunyuan Vision',
       enabled: true,
-      id: 'hunyuan-code',
+      id: 'hunyuan-vision',
       maxOutput: 4000,
       pricing: {
         currency: 'CNY',
-        input: 4,
-        output: 8,
+        input: 18,
+        output: 18,
       },
       tokens: 8000,
+      vision: true,
     },
     {
-      description: '混元最新多模态模型，支持图片+文本输入生成文本内容。',
-      displayName: 'Hunyuan Vision',
-      enabled: true,
-      id: 'hunyuan-vision',
+      description: '混元最新代码生成模型，经过 200B 高质量代码数据增训基座模型，迭代半年高质量 SFT 数据训练，上下文长窗口长度增大到 8K，五大语言代码生成自动评测指标上位居前列；五大语言10项考量各方面综合代码任务人工高质量评测上，性能处于第一梯队',
+      displayName: 'Hunyuan Code',
+      id: 'hunyuan-code',
       maxOutput: 4000,
       pricing: {
         currency: 'CNY',
-        input: 18,
-        output: 18,
+        input: 4,
+        output: 8,
       },
       tokens: 8000,
-      vision: true,
     },
     {
       description: '混元最新 MOE 架构 FunctionCall 模型，经过高质量的 FunctionCall 数据训练，上下文窗口达 32K，在多个维度的评测指标上处于领先。',

diff --git a/src/config/modelProviders/mistral.ts b/src/config/modelProviders/mistral.ts
@@ -11,6 +11,10 @@ const Mistral: ModelProviderCard = {
       enabled: true,
       functionCall: true,
       id: 'open-mistral-nemo',
+      pricing: {
+        input: 0.15,
+        output: 0.15,
+      },
       tokens: 128_000,
     },
     {
@@ -20,6 +24,10 @@ const Mistral: ModelProviderCard = {
       enabled: true,
       functionCall: true,
       id: 'mistral-small-latest',
+      pricing: {
+        input: 0.2,
+        output: 0.6,
+      },
       tokens: 128_000,
     },
     {
@@ -29,13 +37,20 @@ const Mistral: ModelProviderCard = {
       enabled: true,
       functionCall: true,
       id: 'mistral-large-latest',
+      pricing: {
+        input: 2,
+        output: 6,
+      },
       tokens: 128_000,
     },
     {
       description: 'Codestral是专注于代码生成的尖端生成模型，优化了中间填充和代码补全任务。',
       displayName: 'Codestral',
-      enabled: true,
       id: 'codestral-latest',
+      pricing: {
+        input: 0.2,
+        output: 0.6,
+      },
       tokens: 32_768,
     },
     {
@@ -44,21 +59,55 @@ const Mistral: ModelProviderCard = {
       displayName: 'Pixtral 12B',
       enabled: true,
       id: 'pixtral-12b-2409',
+      pricing: {
+        input: 0.15,
+        output: 0.15,
+      },
       tokens: 128_000,
       vision: true,
     },
+    {
+      description:
+        'Ministral 3B 是Mistral的世界顶级边缘模型。',
+      displayName: 'Ministral 3B',
+      id: 'ministral-3b-latest',
+      pricing: {
+        input: 0.04,
+        output: 0.04,
+      },
+      tokens: 128_000,
+    },
+    {
+      description:
+        'Ministral 8B 是Mistral的性价比极高的边缘模型。',
+      displayName: 'Ministral 8B',
+      id: 'ministral-8b-latest',
+      pricing: {
+        input: 0.1,
+        output: 0.1,
+      },
+      tokens: 128_000,
+    },
     {
       description:
         'Mistral 7B是一款紧凑但高性能的模型，擅长批量处理和简单任务，如分类和文本生成，具有良好的推理能力。',
       displayName: 'Mistral 7B',
       id: 'open-mistral-7b',
+      pricing: {
+        input: 0.25,
+        output: 0.25,
+      },
       tokens: 32_768,
     },
     {
       description:
         'Mixtral 8x7B是一个稀疏专家模型，利用多个参数提高推理速度，适合处理多语言和代码生成任务。',
       displayName: 'Mixtral 8x7B',
       id: 'open-mixtral-8x7b',
+      pricing: {
+        input: 0.7,
+        output: 0.7,
+      },
       tokens: 32_768,
     },
     {
@@ -67,17 +116,25 @@ const Mistral: ModelProviderCard = {
       displayName: 'Mixtral 8x22B',
       functionCall: true,
       id: 'open-mixtral-8x22b',
+      pricing: {
+        input: 2,
+        output: 6,
+      },
       tokens: 65_536,
     },
     {
       description:
         'Codestral Mamba是专注于代码生成的Mamba 2语言模型，为先进的代码和推理任务提供强力支持。',
       displayName: 'Codestral Mamba',
       id: 'open-codestral-mamba',
+      pricing: {
+        input: 0.15,
+        output: 0.15,
+      },
       tokens: 256_000,
     },
   ],
-  checkModel: 'open-mistral-7b',
+  checkModel: 'ministral-3b-latest',
   description:
     'Mistral 提供先进的通用、专业和研究型模型，广泛应用于复杂推理、多语言任务、代码生成等领域，通过功能调用接口，用户可以集成自定义功能，实现特定应用。',
   id: 'mistral',

diff --git a/src/config/modelProviders/moonshot.ts b/src/config/modelProviders/moonshot.ts
@@ -5,12 +5,12 @@ const Moonshot: ModelProviderCard = {
   chatModels: [
     {
       description:
-        'Moonshot V1 128K 是一款拥有超长上下文处理能力的模型，适用于生成超长文本，满足复杂的生成任务需求，能够处理多达128,000个tokens的内容，非常适合科研、学术和大型文档生成等应用场景。',
-      displayName: 'Moonshot V1 128K',
+        'Moonshot V1 8K 专为生成短文本任务设计，具有高效的处理性能，能够处理8,192个tokens，非常适合简短对话、速记和快速内容生成。',
+      displayName: 'Moonshot V1 8K',
       enabled: true,
       functionCall: true,
-      id: 'moonshot-v1-128k',
-      tokens: 128_000,
+      id: 'moonshot-v1-8k',
+      tokens: 8192,
     },
     {
       description:
@@ -23,12 +23,12 @@ const Moonshot: ModelProviderCard = {
     },
     {
       description:
-        'Moonshot V1 8K 专为生成短文本任务设计，具有高效的处理性能，能够处理8,192个tokens，非常适合简短对话、速记和快速内容生成。',
-      displayName: 'Moonshot V1 8K',
+        'Moonshot V1 128K 是一款拥有超长上下文处理能力的模型，适用于生成超长文本，满足复杂的生成任务需求，能够处理多达128,000个tokens的内容，非常适合科研、学术和大型文档生成等应用场景。',
+      displayName: 'Moonshot V1 128K',
       enabled: true,
       functionCall: true,
-      id: 'moonshot-v1-8k',
-      tokens: 8192,
+      id: 'moonshot-v1-128k',
+      tokens: 128_000,
     },
   ],
   checkModel: 'moonshot-v1-8k',