feat: prompt call tool support reason;perf: ai proxy doc (#3982)

* update schema * perf: ai proxy doc * feat: prompt call tool support reason
2025-10-13 22:56:28 +00:00 · 2025-03-05 14:11:52 +08:00
parent e1aa068858
commit 3e3f2165db
23 changed files with 508 additions and 298 deletions
--- a/.vscode/settings.json
+++ b/.vscode/settings.json
@@ -27,7 +27,5 @@
    },
    "markdown.copyFiles.destination": {
        "/docSite/content/**/*": "${documentWorkspaceFolder}/docSite/assets/imgs/"
-    },
-    "markdown.copyFiles.overwriteBehavior": "nameIncrementally",
-    "markdown.copyFiles.transformPath": "const filename = uri.path.split('/').pop(); return `/imgs/${filename}`;"
+    }
 }
--- a/README.md
+++ b/README.md
@@ -115,16 +115,6 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
    <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
 </a>

-## 🏘️ 社区交流群
-
-扫码加入飞书话题群：
-
-![](https://oss.laf.run/otnvvf-imgs/fastgpt-feishu1.png)
-
-<a href="#readme">
-    <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
-</a>
-
 ## 🏘️ 加入我们

 我们正在寻找志同道合的小伙伴，加速 FastGPT 的发展。你可以通过 [FastGPT 2025 招聘](https://fael3z0zfze.feishu.cn/wiki/P7FOwEmPziVcaYkvVaacnVX1nvg)了解 FastGPT 的招聘信息。
@@ -135,17 +125,25 @@ https://github.com/labring/FastGPT/assets/15308462/7d3a38df-eb0e-4388-9250-2409b
 - [Sealos：快速部署集群应用](https://github.com/labring/sealos)
 - [AI Proxy API调用地址](https://sealos.run/aiproxy/?k=fastgpt-github/)
 - [One API：多模型管理，支持 Azure、文心一言等](https://github.com/songquanpeng/one-api)
- [TuShan：5 分钟搭建后台管理系统](https://github.com/msgbyte/tushan)

 <a href="#readme">
    <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
 </a>

-
 ## 🌿 第三方生态

- [COW 个人微信/企微机器人](https://doc.tryfastgpt.ai/docs/use-cases/external-integration/onwechat/)
 - [SiliconCloud (硅基流动) —— 开源模型在线体验平台](https://cloud.siliconflow.cn/i/TR9Ym0c4)
+- [COW 个人微信/企微机器人](https://doc.tryfastgpt.ai/docs/use-cases/external-integration/onwechat/)
+
+<a href="#readme">
+    <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
+</a>
+
+## 🏘️ 社区交流群
+
+扫码加入飞书话题群：
+
+![](https://oss.laf.run/otnvvf-imgs/fastgpt-feishu1.png)

 <a href="#readme">
    <img src="https://img.shields.io/badge/-返回顶部-7d09f1.svg" alt="#" align="right">
--- a/deploy/docker/docker-compose-milvus.yml
+++ b/deploy/docker/docker-compose-milvus.yml
@@ -141,10 +141,9 @@ services:
      - AIPROXY_API_ENDPOINT=http://aiproxy:3000
      # AI Proxy 的 Admin Token，与 AI Proxy 中的环境变量 ADMIN_KEY
      - AIPROXY_API_TOKEN=aiproxy
-      # AI模型的API地址哦。务必加 /v1。这里默认填写了OneApi的访问地址。
-      - OPENAI_BASE_URL=http://oneapi:3000/v1
-      # AI模型的API Key。（这里默认填写了OneAPI的快速默认key，测试通后，务必及时修改）
-      - CHAT_API_KEY=sk-fastgpt
+      # 模型中转地址（如果用了 AI Proxy，下面 2 个就不需要了，旧版 OneAPI 用户，使用下面的变量）
+      # - OPENAI_BASE_URL=http://oneapi:3000/v1
+      # - CHAT_API_KEY=sk-fastgpt
      # 数据库最大连接数
      - DB_MAX_LINK=30
      # 登录凭证密钥
@@ -180,32 +179,37 @@ services:
    container_name: aiproxy
    restart: unless-stopped
    depends_on:
-      pgsql:
+      aiproxy_pg:
        condition: service_healthy
    ports:
-      - '3002:3000/tcp'
+      - '3002:3000'
    networks:
      - fastgpt
    environment:
-      - ADMIN_KEY=aiproxy # 对应 fastgpt 里的AIPROXY_API_TOKEN
-      - LOG_DETAIL_STORAGE_HOURS=1 # 日志详情保存时间（小时）
-      - TZ=Asia/Shanghai
-      - SQL_DSN=postgres://postgres:aiproxy@pgsql:5432/aiproxy
+      # 对应 fastgpt 里的AIPROXY_API_TOKEN
+      - ADMIN_KEY=aiproxy
+      # 错误日志详情保存时间（小时）
+      - LOG_DETAIL_STORAGE_HOURS=1
+      # 数据库连接地址
+      - SQL_DSN=postgres://postgres:aiproxy@aiproxy_pg:5432/aiproxy
+      # 最大重试次数
+      - RetryTimes=3
+      # 不需要计费
+      - BILLING_ENABLED=false
+      # 不需要严格检测模型
      - DISABLE_MODEL_CONFIG=true
    healthcheck:
      test: ['CMD', 'curl', '-f', 'http://localhost:3000/api/status']
      interval: 5s
      timeout: 5s
      retries: 10
-
-  # AI Proxy
-  pgsql:
-    # image: "postgres:latest"
-    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.7.0 # 阿里云
+  aiproxy_pg:
+    # image: pgvector/pgvector:0.8.0-pg15 # docker hub
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.8.0-pg15 # 阿里云
    restart: unless-stopped
-    container_name: pgsql
+    container_name: aiproxy_pg
    volumes:
-      - ./pgsql:/var/lib/postgresql/data
+      - ./aiproxy_pg:/var/lib/postgresql/data
    networks:
      - fastgpt
    environment:
--- a/deploy/docker/docker-compose-pgvector.yml
+++ b/deploy/docker/docker-compose-pgvector.yml
@@ -11,8 +11,8 @@ services:
    # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.8.0-pg15 # 阿里云
    container_name: pg
    restart: always
-    ports: # 生产环境建议不要暴露
-      - 5432:5432
+    # ports: # 生产环境建议不要暴露
+    #   - 5432:5432
    networks:
      - fastgpt
    environment:
@@ -99,10 +99,9 @@ services:
      - AIPROXY_API_ENDPOINT=http://aiproxy:3000
      # AI Proxy 的 Admin Token，与 AI Proxy 中的环境变量 ADMIN_KEY
      - AIPROXY_API_TOKEN=aiproxy
-      # AI模型的API地址哦。务必加 /v1。这里默认填写了OneApi的访问地址。
-      - OPENAI_BASE_URL=http://oneapi:3000/v1
-      # AI模型的API Key。（这里默认填写了OneAPI的快速默认key，测试通后，务必及时修改）
-      - CHAT_API_KEY=sk-fastgpt
+      # 模型中转地址（如果用了 AI Proxy，下面 2 个就不需要了，旧版 OneAPI 用户，使用下面的变量）
+      # - OPENAI_BASE_URL=http://oneapi:3000/v1
+      # - CHAT_API_KEY=sk-fastgpt
      # 数据库最大连接数
      - DB_MAX_LINK=30
      # 登录凭证密钥
@@ -137,32 +136,37 @@ services:
    container_name: aiproxy
    restart: unless-stopped
    depends_on:
-      pgsql:
+      aiproxy_pg:
        condition: service_healthy
    ports:
-      - '3002:3000/tcp'
+      - '3002:3000'
    networks:
      - fastgpt
    environment:
-      - ADMIN_KEY=aiproxy # 对应 fastgpt 里的AIPROXY_API_TOKEN
-      - LOG_DETAIL_STORAGE_HOURS=1 # 日志详情保存时间（小时）
-      - TZ=Asia/Shanghai
-      - SQL_DSN=postgres://postgres:aiproxy@pgsql:5432/aiproxy
+      # 对应 fastgpt 里的AIPROXY_API_TOKEN
+      - ADMIN_KEY=aiproxy
+      # 错误日志详情保存时间（小时）
+      - LOG_DETAIL_STORAGE_HOURS=1
+      # 数据库连接地址
+      - SQL_DSN=postgres://postgres:aiproxy@aiproxy_pg:5432/aiproxy
+      # 最大重试次数
+      - RetryTimes=3
+      # 不需要计费
+      - BILLING_ENABLED=false
+      # 不需要严格检测模型
      - DISABLE_MODEL_CONFIG=true
    healthcheck:
      test: ['CMD', 'curl', '-f', 'http://localhost:3000/api/status']
      interval: 5s
      timeout: 5s
      retries: 10
-
-  # AI Proxy
-  pgsql:
-    # image: "postgres:latest"
-    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.7.0 # 阿里云
+  aiproxy_pg:
+    # image: pgvector/pgvector:0.8.0-pg15 # docker hub
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.8.0-pg15 # 阿里云
    restart: unless-stopped
-    container_name: pgsql
+    container_name: aiproxy_pg
    volumes:
-      - ./pgsql:/var/lib/postgresql/data
+      - ./aiproxy_pg:/var/lib/postgresql/data
    networks:
      - fastgpt
    environment:
--- a/deploy/docker/docker-compose-zilliz.yml
+++ b/deploy/docker/docker-compose-zilliz.yml
@@ -79,10 +79,9 @@ services:
      - AIPROXY_API_ENDPOINT=http://aiproxy:3000
      # AI Proxy 的 Admin Token，与 AI Proxy 中的环境变量 ADMIN_KEY
      - AIPROXY_API_TOKEN=aiproxy
-      # AI模型的API地址哦。务必加 /v1。这里默认填写了OneApi的访问地址。
-      - OPENAI_BASE_URL=http://oneapi:3000/v1
-      # AI模型的API Key。（这里默认填写了OneAPI的快速默认key，测试通后，务必及时修改）
-      - CHAT_API_KEY=sk-fastgpt
+      # 模型中转地址（如果用了 AI Proxy，下面 2 个就不需要了，旧版 OneAPI 用户，使用下面的变量）
+      # - OPENAI_BASE_URL=http://oneapi:3000/v1
+      # - CHAT_API_KEY=sk-fastgpt
      # 数据库最大连接数
      - DB_MAX_LINK=30
      # 登录凭证密钥
@@ -118,32 +117,37 @@ services:
    container_name: aiproxy
    restart: unless-stopped
    depends_on:
-      pgsql:
+      aiproxy_pg:
        condition: service_healthy
    ports:
-      - '3002:3000/tcp'
+      - '3002:3000'
    networks:
      - fastgpt
    environment:
-      - ADMIN_KEY=aiproxy # 对应 fastgpt 里的AIPROXY_API_TOKEN
-      - LOG_DETAIL_STORAGE_HOURS=1 # 日志详情保存时间（小时）
-      - TZ=Asia/Shanghai
-      - SQL_DSN=postgres://postgres:aiproxy@pgsql:5432/aiproxy
+      # 对应 fastgpt 里的AIPROXY_API_TOKEN
+      - ADMIN_KEY=aiproxy
+      # 错误日志详情保存时间（小时）
+      - LOG_DETAIL_STORAGE_HOURS=1
+      # 数据库连接地址
+      - SQL_DSN=postgres://postgres:aiproxy@aiproxy_pg:5432/aiproxy
+      # 最大重试次数
+      - RetryTimes=3
+      # 不需要计费
+      - BILLING_ENABLED=false
+      # 不需要严格检测模型
      - DISABLE_MODEL_CONFIG=true
    healthcheck:
      test: ['CMD', 'curl', '-f', 'http://localhost:3000/api/status']
      interval: 5s
      timeout: 5s
      retries: 10
-
-  # AI Proxy
-  pgsql:
-    # image: "postgres:latest"
-    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.7.0 # 阿里云
+  aiproxy_pg:
+    # image: pgvector/pgvector:0.8.0-pg15 # docker hub
+    image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.8.0-pg15 # 阿里云
    restart: unless-stopped
-    container_name: pgsql
+    container_name: aiproxy_pg
    volumes:
-      - ./pgsql:/var/lib/postgresql/data
+      - ./aiproxy_pg:/var/lib/postgresql/data
    networks:
      - fastgpt
    environment:
--- a/docSite/assets/imgs/aiproxy1.png
+++ b/docSite/assets/imgs/aiproxy1.png
--- a/docSite/content/zh-cn/docs/development/docker.md
+++ b/docSite/content/zh-cn/docs/development/docker.md
@@ -30,7 +30,7 @@ weight: 707

 ### PgVector版本

-非常轻量，适合数据量在 5000 万以下。
+非常轻量，适合知识库索引量在 5000 万以下。

 {{< table "table-hover table-striped-columns" >}}
 | 环境 | 最低配置（单节点） | 推荐配置 |
@@ -149,18 +149,14 @@ curl -o docker-compose.yml https://raw.githubusercontent.com/labring/FastGPT/mai
 {{< tab tabName="PgVector版本" >}}
 {{< markdownify >}}

-```
-FE_DOMAIN=你的前端你访问地址,例如 http://192.168.0.1:3000;https://cloud.fastgpt.cn
-```
+无需操作

 {{< /markdownify >}}
 {{< /tab >}}
 {{< tab tabName="Milvus版本" >}}
 {{< markdownify >}}

-```
-FE_DOMAIN=你的前端你访问地址,例如 http://192.168.0.1:3000;https://cloud.fastgpt.cn
-```
+无需操作

 {{< /markdownify >}}
 {{< /tab >}}
@@ -174,7 +170,6 @@ FE_DOMAIN=你的前端你访问地址,例如 http://192.168.0.1:3000;https://clo
 {{% alert icon="🤖" context="success" %}}

 1. 修改`MILVUS_ADDRESS`和`MILVUS_TOKEN`链接参数，分别对应 `zilliz` 的 `Public Endpoint` 和 `Api key`，记得把自己ip加入白名单。
-2. 修改FE_DOMAIN=你的前端你访问地址,例如 http://192.168.0.1:3000;https://cloud.fastgpt.cn

 {{% /alert %}}

@@ -189,30 +184,28 @@ FE_DOMAIN=你的前端你访问地址,例如 http://192.168.0.1:3000;https://clo
 ```bash
 # 启动容器
 docker-compose up -d
-# 等待10s，OneAPI第一次总是要重启几次才能连上Mysql
-sleep 10
-# 重启一次oneapi(由于OneAPI的默认Key有点问题，不重启的话会提示找不到渠道，临时手动重启一次解决，等待作者修复)
-docker restart oneapi
 ```

 ### 4. 访问 FastGPT

-目前可以通过 `ip:3000` 直接访问(注意防火墙)。登录用户名为 `root`，密码为`docker-compose.yml`环境变量里设置的 `DEFAULT_ROOT_PSW`。
+目前可以通过 `ip:3000` 直接访问(注意开放防火墙)。登录用户名为 `root`，密码为`docker-compose.yml`环境变量里设置的 `DEFAULT_ROOT_PSW`。

 如果需要域名访问，请自行安装并配置 Nginx。

-首次运行，会自动初始化 root 用户，密码为 `1234`（与环境变量中的`DEFAULT_ROOT_PSW`一致），日志里会提示一次`MongoServerError: Unable to read from a snapshot due to pending collection catalog changes;`可忽略。
+首次运行，会自动初始化 root 用户，密码为 `1234`（与环境变量中的`DEFAULT_ROOT_PSW`一致），日志可能会提示一次`MongoServerError: Unable to read from a snapshot due to pending collection catalog changes;`可忽略。

 ### 5. 配置模型

-登录FastGPT后，进入“模型提供商”页面，首先配置模型渠道，[点击查看相关教程](/docs/development/modelconfig/ai-proxy)
-
-然后配置具体模型，务必先配置至少一个语言模型和一个向量模型，否则系统无法正常使用。
-
-[点击查看模型配置教程](/docs/development/modelConfig/intro/)
+- 首次登录FastGPT后，系统会提示未配置`语言模型`和`索引模型`，并自动跳转模型配置页面。系统必须至少有这两类模型才能正常使用。
+- 如果系统未正常跳转，可以在`账号-模型提供商`页面，进行模型配置。[点击查看相关教程](/docs/development/modelconfig/ai-proxy)
+- 目前已知可能问题：首次进入系统后，整个浏览器 tab 无法响应。此时需要删除该tab，重新打开一次即可。

 ## FAQ

+### 登录系统后，浏览器无法响应
+
+无法点击任何内容，刷新也无效。此时需要删除该tab，重新打开一次即可。
+
 ### Mongo 副本集自动初始化失败

 最新的 docker-compose 示例优化 Mongo 副本集初始化，实现了全自动。目前在 unbuntu20,22 centos7, wsl2, mac, window 均通过测试。仍无法正常启动，大部分是因为 cpu 不支持 AVX 指令集，可以切换 Mongo4.x 版本。
--- a/docSite/content/zh-cn/docs/development/modelConfig/ai-proxy.md
+++ b/docSite/content/zh-cn/docs/development/modelConfig/ai-proxy.md
@@ -7,7 +7,7 @@ toc: true
 weight: 744
 ---

-从 FastGPT 4.8.23 版本开始，引入 AI Proxy 来进一步方便模型的配置。
+从 `FastGPT 4.8.23` 版本开始，引入 AI Proxy 来进一步方便模型的配置。

 AI Proxy 与 One API 类似，也是作为一个 OpenAI 接口管理 & 分发系统，可以通过标准的 OpenAI API 格式访问所有的大模型，开箱即用。

@@ -15,13 +15,29 @@ AI Proxy 与 One API 类似，也是作为一个 OpenAI 接口管理 & 分发系

 ### Docker 版本

-`docker-compose.yml` 文件已加入了 AI Proxy 配置，可直接使用。
+`docker-compose.yml` 文件已加入了 AI Proxy 配置，可直接使用。[点击查看最新的 yml 配置](https://raw.githubusercontent.com/labring/FastGPT/main/deploy/docker/docker-compose-pgvector.yml)

-## 基础使用
+从旧版升级的用户，可以复制 yml 里，ai proxy 的配置，加入到旧的 yml 文件中。
+
+## 运行原理
+
+AI proxy 核心模块: 
+
+1. 渠道管理：管理各家模型提供商的 API Key 和可用模型列表。
+2. 模型调用：根据请求的模型，选中对应的渠道；根据渠道的 API 格式，构造请求体，发送请求；格式化响应体成标准格式返回。
+3. 调用日志：详细记录模型调用的日志，并在错误时候可以记录其入参和报错信息，方便排查。
+
+运行流程：
+
+![aiproxy12](/imgs/aiproxy1.png)
+
+## 在 FastGPT 中使用
+
+AI proxy 相关功能，可以在`账号-模型提供商`页面找到。

 ### 1. 创建渠道

-如果 FastGPT 的环境变量中，设置了 AIPROXY_API_ENDPOINT 的值，那么在“模型提供商”的配置页面，会多出两个 tab，可以直接在 FastGPT 平台上配置模型渠道，以及查看模型实际调用日志。
+在`模型提供商`的配置页面，点击`模型渠道`，进入渠道配置页面

 ![aiproxy1](/imgs/aiproxy-1.png)

@@ -36,9 +52,18 @@ AI Proxy 与 One API 类似，也是作为一个 OpenAI 接口管理 & 分发系
 1. 渠道名：展示在外部的渠道名称，仅作标识;
 2. 厂商：模型对应的厂商，不同厂商对应不同的默认地址和 API 密钥格式;
 3. 模型：当前渠道具体可以使用的模型，系统内置了主流的一些模型，如果下拉框中没有想要的选项，可以点击“新增模型”，[增加自定义模型](/docs/development/modelconfig/intro/#新增自定义模型);
-4. 模型映射：将 FastGPT 请求的模型，映射到具体提供的模型上；
-5. 代理地址：具体请求的地址，系统给每个主流渠道配置了默认的地址，如果无需改动则不用填
-6. API 密钥：从模型厂商处获取的 API 凭证
+4. 模型映射：将 FastGPT 请求的模型，映射到具体提供的模型上。例如：
+   
+```json
+{
+    "gpt-4o-test": "gpt-4o",
+}
+```
+
+FatGPT 中的模型为 `gpt-4o-test`，向 AI Proxy 发起请求时也是 `gpt-4o-test`。AI proxy 在向上游发送请求时，实际的`model`为 `gpt-4o`。
+
+5. 代理地址：具体请求的地址，系统给每个主流渠道配置了默认的地址，如果无需改动则不用填。
+6. API 密钥：从模型厂商处获取的 API 凭证。注意部分厂商需要提供多个密钥组合，可以根据提示进行输入。

 最后点击“新增”，就能在“模型渠道”下看到刚刚配置的渠道

@@ -60,16 +85,15 @@ AI Proxy 与 One API 类似，也是作为一个 OpenAI 接口管理 & 分发系

 ### 3. 启用模型

-最后在“模型配置”中，可以选择启用对应的模型，这样就能在平台中使用了
+最后在`模型配置`中，可以选择启用对应的模型，这样就能在平台中使用了，更多模型配置可以参考[模型配置](/docs/development/modelconfig/intro)

 ![aiproxy8](/imgs/aiproxy-8.png)

-
-## 渠道设置
+## 其他功能介绍

 ### 优先级

-在 FastGPT 中，可以给渠道设置优先级，对于同样的模型，优先级越高的渠道会越优先请求
+范围1～100。数值越大，越容易被优先选中。

 ![aiproxy9](/imgs/aiproxy-9.png)

@@ -81,13 +105,15 @@ AI Proxy 与 One API 类似，也是作为一个 OpenAI 接口管理 & 分发系

 ### 调用日志

-在 “调用日志” 页面，会展示发送到模型处的请求记录，包括具体的输入输出 tokens、请求时间、请求耗时、请求地址等等
+在 `调用日志` 页面，会展示发送到模型处的请求记录，包括具体的输入输出 tokens、请求时间、请求耗时、请求地址等等。错误的请求，则会详细的入参和错误信息，方便排查，但仅会保留 1 小时(环境变量里可配置)。

 ![aiproxy11](/imgs/aiproxy-11.png)

-## 如何从 OneAPI 迁移到 AI Proxy
+## 从 OneAPI 迁移到 AI Proxy

-可以从任意终端，发起 1 个 HTTP 请求。其中 {{host}} 替换成 AI Proxy 地址，{{admin_key}} 替换成 AI Proxy 中 ADMIN_KEY 的值，参数 dsn 为 OneAPI 的 mysql 连接串
+可以从任意终端，发起 1 个 HTTP 请求。其中 `{{host}}` 替换成 AI Proxy 地址，`{{admin_key}}` 替换成 AI Proxy 中 `ADMIN_KEY` 的值。
+
+Body 参数 `dsn` 为 OneAPI 的 mysql 连接串。

 ```bash
 curl --location --request POST '{{host}}/api/channels/import/oneapi' \
@@ -100,4 +126,4 @@ curl --location --request POST '{{host}}/api/channels/import/oneapi' \

 执行成功的情况下会返回 "success": true

-脚本目前不是完全准，可能会有部分渠道遗漏，还需要手动再检查下
+脚本目前不是完全准，仅是简单的做数据映射，主要是迁移`代理地址`、`模型`和`API 密钥`，建议迁移后再进行手动检查。
--- a/docSite/content/zh-cn/docs/development/upgrading/490.md
+++ b/docSite/content/zh-cn/docs/development/upgrading/490.md
@@ -46,6 +46,7 @@ curl --location --request POST 'https://{{host}}/api/admin/initv490' \

 1. 知识库数据不再限制索引数量，可无限自定义。同时可自动更新输入文本的索引，不影响自定义索引。
 2. Markdown 解析，增加链接后中文标点符号检测，增加空格。
+3. Prompt 模式工具调用，支持思考模型。同时优化其格式检测，减少空输出的概率。

 ## 🐛 修复

--- a/packages/global/core/chat/adapt.ts
+++ b/packages/global/core/chat/adapt.ts
@@ -1,8 +1,11 @@
 import type {
+  AIChatItemValueItemType,
  ChatItemType,
  ChatItemValueItemType,
  RuntimeUserPromptType,
-  UserChatItemType
+  SystemChatItemValueItemType,
+  UserChatItemType,
+  UserChatItemValueItemType
 } from '../../core/chat/type.d';
 import { ChatFileTypeEnum, ChatItemValueTypeEnum, ChatRoleEnum } from '../../core/chat/constants';
 import type {
@@ -174,137 +177,24 @@ export const GPTMessages2Chats = (
 ): ChatItemType[] => {
  const chatMessages = messages
    .map((item) => {
-      const value: ChatItemType['value'] = [];
      const obj = GPT2Chat[item.role];

-      if (
-        obj === ChatRoleEnum.System &&
-        item.role === ChatCompletionRequestMessageRoleEnum.System
-      ) {
-        if (Array.isArray(item.content)) {
-          item.content.forEach((item) => [
-            value.push({
-              type: ChatItemValueTypeEnum.text,
-              text: {
-                content: item.text
-              }
-            })
-          ]);
-        } else {
-          value.push({
-            type: ChatItemValueTypeEnum.text,
-            text: {
-              content: item.content
-            }
-          });
-        }
-      } else if (
-        obj === ChatRoleEnum.Human &&
-        item.role === ChatCompletionRequestMessageRoleEnum.User
-      ) {
-        if (typeof item.content === 'string') {
-          value.push({
-            type: ChatItemValueTypeEnum.text,
-            text: {
-              content: item.content
-            }
-          });
-        } else if (Array.isArray(item.content)) {
-          item.content.forEach((item) => {
-            if (item.type === 'text') {
+      const value = (() => {
+        if (
+          obj === ChatRoleEnum.System &&
+          item.role === ChatCompletionRequestMessageRoleEnum.System
+        ) {
+          const value: SystemChatItemValueItemType[] = [];
+
+          if (Array.isArray(item.content)) {
+            item.content.forEach((item) => [
              value.push({
                type: ChatItemValueTypeEnum.text,
                text: {
                  content: item.text
                }
-              });
-            } else if (item.type === 'image_url') {
-              value.push({
-                //@ts-ignore
-                type: ChatItemValueTypeEnum.file,
-                file: {
-                  type: ChatFileTypeEnum.image,
-                  name: '',
-                  url: item.image_url.url
-                }
-              });
-            } else if (item.type === 'file_url') {
-              value.push({
-                // @ts-ignore
-                type: ChatItemValueTypeEnum.file,
-                file: {
-                  type: ChatFileTypeEnum.file,
-                  name: item.name,
-                  url: item.url
-                }
-              });
-            }
-          });
-        }
-      } else if (
-        obj === ChatRoleEnum.AI &&
-        item.role === ChatCompletionRequestMessageRoleEnum.Assistant
-      ) {
-        if (item.tool_calls && reserveTool) {
-          // save tool calls
-          const toolCalls = item.tool_calls as ChatCompletionMessageToolCall[];
-          value.push({
-            //@ts-ignore
-            type: ChatItemValueTypeEnum.tool,
-            tools: toolCalls.map((tool) => {
-              let toolResponse =
-                messages.find(
-                  (msg) =>
-                    msg.role === ChatCompletionRequestMessageRoleEnum.Tool &&
-                    msg.tool_call_id === tool.id
-                )?.content || '';
-              toolResponse =
-                typeof toolResponse === 'string' ? toolResponse : JSON.stringify(toolResponse);
-
-              return {
-                id: tool.id,
-                toolName: tool.toolName || '',
-                toolAvatar: tool.toolAvatar || '',
-                functionName: tool.function.name,
-                params: tool.function.arguments,
-                response: toolResponse as string
-              };
-            })
-          });
-        } else if (item.function_call && reserveTool) {
-          const functionCall = item.function_call as ChatCompletionMessageFunctionCall;
-          const functionResponse = messages.find(
-            (msg) =>
-              msg.role === ChatCompletionRequestMessageRoleEnum.Function &&
-              msg.name === item.function_call?.name
-          ) as ChatCompletionFunctionMessageParam;
-
-          if (functionResponse) {
-            value.push({
-              //@ts-ignore
-              type: ChatItemValueTypeEnum.tool,
-              tools: [
-                {
-                  id: functionCall.id || '',
-                  toolName: functionCall.toolName || '',
-                  toolAvatar: functionCall.toolAvatar || '',
-                  functionName: functionCall.name,
-                  params: functionCall.arguments,
-                  response: functionResponse.content || ''
-                }
-              ]
-            });
-          }
-        } else if (item.interactive) {
-          value.push({
-            //@ts-ignore
-            type: ChatItemValueTypeEnum.interactive,
-            interactive: item.interactive
-          });
-        } else if (typeof item.content === 'string') {
-          const lastValue = value[value.length - 1];
-          if (lastValue && lastValue.type === ChatItemValueTypeEnum.text && lastValue.text) {
-            lastValue.text.content += item.content;
+              })
+            ]);
          } else {
            value.push({
              type: ChatItemValueTypeEnum.text,
@@ -313,8 +203,145 @@ export const GPTMessages2Chats = (
              }
            });
          }
+          return value;
+        } else if (
+          obj === ChatRoleEnum.Human &&
+          item.role === ChatCompletionRequestMessageRoleEnum.User
+        ) {
+          const value: UserChatItemValueItemType[] = [];
+
+          if (typeof item.content === 'string') {
+            value.push({
+              type: ChatItemValueTypeEnum.text,
+              text: {
+                content: item.content
+              }
+            });
+          } else if (Array.isArray(item.content)) {
+            item.content.forEach((item) => {
+              if (item.type === 'text') {
+                value.push({
+                  type: ChatItemValueTypeEnum.text,
+                  text: {
+                    content: item.text
+                  }
+                });
+              } else if (item.type === 'image_url') {
+                value.push({
+                  //@ts-ignore
+                  type: ChatItemValueTypeEnum.file,
+                  file: {
+                    type: ChatFileTypeEnum.image,
+                    name: '',
+                    url: item.image_url.url
+                  }
+                });
+              } else if (item.type === 'file_url') {
+                value.push({
+                  // @ts-ignore
+                  type: ChatItemValueTypeEnum.file,
+                  file: {
+                    type: ChatFileTypeEnum.file,
+                    name: item.name,
+                    url: item.url
+                  }
+                });
+              }
+            });
+          }
+          return value;
+        } else if (
+          obj === ChatRoleEnum.AI &&
+          item.role === ChatCompletionRequestMessageRoleEnum.Assistant
+        ) {
+          const value: AIChatItemValueItemType[] = [];
+
+          if (typeof item.reasoning_text === 'string') {
+            value.push({
+              type: ChatItemValueTypeEnum.reasoning,
+              reasoning: {
+                content: item.reasoning_text
+              }
+            });
+          }
+          if (item.tool_calls && reserveTool) {
+            // save tool calls
+            const toolCalls = item.tool_calls as ChatCompletionMessageToolCall[];
+            value.push({
+              //@ts-ignore
+              type: ChatItemValueTypeEnum.tool,
+              tools: toolCalls.map((tool) => {
+                let toolResponse =
+                  messages.find(
+                    (msg) =>
+                      msg.role === ChatCompletionRequestMessageRoleEnum.Tool &&
+                      msg.tool_call_id === tool.id
+                  )?.content || '';
+                toolResponse =
+                  typeof toolResponse === 'string' ? toolResponse : JSON.stringify(toolResponse);
+
+                return {
+                  id: tool.id,
+                  toolName: tool.toolName || '',
+                  toolAvatar: tool.toolAvatar || '',
+                  functionName: tool.function.name,
+                  params: tool.function.arguments,
+                  response: toolResponse as string
+                };
+              })
+            });
+          }
+          if (item.function_call && reserveTool) {
+            const functionCall = item.function_call as ChatCompletionMessageFunctionCall;
+            const functionResponse = messages.find(
+              (msg) =>
+                msg.role === ChatCompletionRequestMessageRoleEnum.Function &&
+                msg.name === item.function_call?.name
+            ) as ChatCompletionFunctionMessageParam;
+
+            if (functionResponse) {
+              value.push({
+                //@ts-ignore
+                type: ChatItemValueTypeEnum.tool,
+                tools: [
+                  {
+                    id: functionCall.id || '',
+                    toolName: functionCall.toolName || '',
+                    toolAvatar: functionCall.toolAvatar || '',
+                    functionName: functionCall.name,
+                    params: functionCall.arguments,
+                    response: functionResponse.content || ''
+                  }
+                ]
+              });
+            }
+          }
+          if (item.interactive) {
+            value.push({
+              //@ts-ignore
+              type: ChatItemValueTypeEnum.interactive,
+              interactive: item.interactive
+            });
+          }
+          if (typeof item.content === 'string') {
+            const lastValue = value[value.length - 1];
+            if (lastValue && lastValue.type === ChatItemValueTypeEnum.text && lastValue.text) {
+              lastValue.text.content += item.content;
+            } else {
+              value.push({
+                type: ChatItemValueTypeEnum.text,
+                text: {
+                  content: item.content
+                }
+              });
+            }
+          }
+
+          return value;
        }
-      }
+
+        return [];
+      })();

      return {
        dataId: item.dataId,
--- a/packages/global/core/chat/type.d.ts
+++ b/packages/global/core/chat/type.d.ts
@@ -77,6 +77,7 @@ export type AIChatItemValueItemType = {
    | ChatItemValueTypeEnum.reasoning
    | ChatItemValueTypeEnum.tool
    | ChatItemValueTypeEnum.interactive;
+
  text?: {
    content: string;
  };
--- a/packages/global/core/workflow/template/system/aiChat/index.ts
+++ b/packages/global/core/workflow/template/system/aiChat/index.ts
@@ -55,7 +55,7 @@ export const AiChatModule: FlowNodeTemplateType = {
  showStatus: true,
  isTool: true,
  courseUrl: '/docs/guide/workbench/workflow/ai_chat/',
-  version: '4813',
+  version: '490',
  inputs: [
    Input_Template_SettingAiModel,
    // --- settings modal
--- a/packages/global/core/workflow/template/system/tools.ts
+++ b/packages/global/core/workflow/template/system/tools.ts
@@ -58,6 +58,13 @@ export const ToolModule: FlowNodeTemplateType = {
      valueType: WorkflowIOValueTypeEnum.boolean,
      value: true
    },
+    {
+      key: NodeInputKeyEnum.aiChatReasoning,
+      renderTypeList: [FlowNodeInputTypeEnum.hidden],
+      label: '',
+      valueType: WorkflowIOValueTypeEnum.boolean,
+      value: true
+    },
    {
      key: NodeInputKeyEnum.aiChatTopP,
      renderTypeList: [FlowNodeInputTypeEnum.hidden],
--- a/packages/service/common/file/read/utils.ts
+++ b/packages/service/common/file/read/utils.ts
@@ -245,7 +245,7 @@ export const readRawContentByFileBuffer = async ({
        if (result_data.data.status === 'success') {
          const result = result_data.data.result.pages
            .map((page) => page.md)
-            .join('\n')
+            .join('')
            // Do some post-processing
            .replace(/\\[\(\)]/g, '$')
            .replace(/\\[\[\]]/g, '$$')
--- a/packages/service/core/ai/config/provider/Moonshot.json
+++ b/packages/service/core/ai/config/provider/Moonshot.json
@@ -75,6 +75,81 @@
      "showTopP": true,
      "showStopSign": true,
      "responseFormatList": ["text", "json_object"]
+    },
+    {
+      "model": "moonshot-v1-8k-vision-preview",
+      "name": "moonshot-v1-8k-vision-preview",
+      "maxContext": 8000,
+      "maxResponse": 4000,
+      "quoteMaxToken": 6000,
+      "maxTemperature": 1,
+      "vision": true,
+      "toolChoice": true,
+      "functionCall": false,
+      "defaultSystemChatPrompt": "",
+      "datasetProcess": true,
+      "usedInClassify": true,
+      "customCQPrompt": "",
+      "usedInExtractFields": true,
+      "usedInQueryExtension": true,
+      "customExtractPrompt": "",
+      "usedInToolCall": true,
+      "defaultConfig": {},
+      "fieldMap": {},
+      "type": "llm",
+      "showTopP": true,
+      "showStopSign": true,
+      "responseFormatList": ["text", "json_object"]
+    },
+    {
+      "model": "moonshot-v1-32k-vision-preview",
+      "name": "moonshot-v1-32k-vision-preview",
+      "maxContext": 32000,
+      "maxResponse": 4000,
+      "quoteMaxToken": 32000,
+      "maxTemperature": 1,
+      "vision": true,
+      "toolChoice": true,
+      "functionCall": false,
+      "defaultSystemChatPrompt": "",
+      "datasetProcess": true,
+      "usedInClassify": true,
+      "customCQPrompt": "",
+      "usedInExtractFields": true,
+      "usedInQueryExtension": true,
+      "customExtractPrompt": "",
+      "usedInToolCall": true,
+      "defaultConfig": {},
+      "fieldMap": {},
+      "type": "llm",
+      "showTopP": true,
+      "showStopSign": true,
+      "responseFormatList": ["text", "json_object"]
+    },
+    {
+      "model": "moonshot-v1-128k-vision-preview",
+      "name": "moonshot-v1-128k-vision-preview",
+      "maxContext": 128000,
+      "maxResponse": 4000,
+      "quoteMaxToken": 60000,
+      "maxTemperature": 1,
+      "vision": true,
+      "toolChoice": true,
+      "functionCall": false,
+      "defaultSystemChatPrompt": "",
+      "datasetProcess": true,
+      "usedInClassify": true,
+      "customCQPrompt": "",
+      "usedInExtractFields": true,
+      "usedInQueryExtension": true,
+      "customExtractPrompt": "",
+      "usedInToolCall": true,
+      "defaultConfig": {},
+      "fieldMap": {},
+      "type": "llm",
+      "showTopP": true,
+      "showStopSign": true,
+      "responseFormatList": ["text", "json_object"]
    }
  ]
 }
--- a/packages/service/core/app/templates/templateSchema.ts
+++ b/packages/service/core/app/templates/templateSchema.ts
@@ -9,41 +9,23 @@ const AppTemplateSchema = new Schema({
    type: String,
    required: true
  },
-  name: {
-    type: String
-  },
-  intro: {
-    type: String
-  },
-  avatar: {
-    type: String
-  },
-  author: {
-    type: String
-  },
+  name: String,
+  intro: String,
+  avatar: String,
+  author: String,
  tags: {
    type: [String],
    default: undefined
  },
-  type: {
-    type: String
-  },
-  isActive: {
-    type: Boolean
-  },
-  userGuide: {
-    type: Object
-  },
-  isQuickTemplate: {
-    type: Boolean
-  },
+  type: String,
+  isActive: Boolean,
+  userGuide: Object,
+  isQuickTemplate: Boolean,
  order: {
    type: Number,
    default: -1
  },
-  workflow: {
-    type: Object
-  }
+  workflow: Object
 });

 AppTemplateSchema.index({ templateId: 1 });
--- a/packages/service/core/workflow/dispatch/agent/runTool/index.ts
+++ b/packages/service/core/workflow/dispatch/agent/runTool/index.ts
@@ -55,7 +55,8 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
      userChatInput,
      history = 6,
      fileUrlList: fileLinks,
-      aiChatVision
+      aiChatVision,
+      aiChatReasoning
    }
  } = props;

@@ -63,6 +64,9 @@ export const dispatchRunTools = async (props: DispatchToolModuleProps): Promise<
  const useVision = aiChatVision && toolModel.vision;
  const chatHistories = getHistories(history, histories);

+  props.params.aiChatVision = aiChatVision && toolModel.vision;
+  props.params.aiChatReasoning = aiChatReasoning && toolModel.reasoning;
+
  const toolNodeIds = filterToolNodeIdByEdges({ nodeId, edges: runtimeEdges });

  // Gets the module to which the tool is connected
--- a/packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts
+++ b/packages/service/core/workflow/dispatch/agent/runTool/promptCall.ts
@@ -24,7 +24,12 @@ import {
 import { AIChatItemType } from '@fastgpt/global/core/chat/type';
 import { GPTMessages2Chats } from '@fastgpt/global/core/chat/adapt';
 import { formatToolResponse, initToolCallEdges, initToolNodes } from './utils';
-import { computedMaxToken, llmCompletionsBodyFormat } from '../../../../ai/utils';
+import {
+  computedMaxToken,
+  llmCompletionsBodyFormat,
+  parseReasoningContent,
+  parseReasoningStreamContent
+} from '../../../../ai/utils';
 import { WorkflowResponseType } from '../../type';
 import { toolValueTypeList } from '@fastgpt/global/core/workflow/constants';
 import { WorkflowInteractiveResponseType } from '@fastgpt/global/core/workflow/template/system/interactive/type';
@@ -58,6 +63,7 @@ export const runToolWithPromptCall = async (
      temperature,
      maxToken,
      aiChatVision,
+      aiChatReasoning,
      aiChatTopP,
      aiChatStopSign,
      aiChatResponseFormat,
@@ -216,7 +222,7 @@ export const runToolWithPromptCall = async (
  const [requestMessages] = await Promise.all([
    loadRequestMessages({
      messages: filterMessages,
-      useVision: toolModel.vision && aiChatVision,
+      useVision: aiChatVision,
      origin: requestOrigin
    })
  ]);
@@ -251,22 +257,46 @@ export const runToolWithPromptCall = async (
    }
  });

-  const answer = await (async () => {
+  const { answer, reasoning } = await (async () => {
    if (res && isStreamResponse) {
-      const { answer } = await streamResponse({
+      const { answer, reasoning } = await streamResponse({
        res,
        toolNodes,
        stream: aiResponse,
-        workflowStreamResponse
+        workflowStreamResponse,
+        aiChatReasoning
      });

-      return answer;
+      return { answer, reasoning };
    } else {
-      const result = aiResponse as ChatCompletion;
+      const content = aiResponse.choices?.[0]?.message?.content || '';
+      const reasoningContent: string = aiResponse.choices?.[0]?.message?.reasoning_content || '';

-      return result.choices?.[0]?.message?.content || '';
+      // API already parse reasoning content
+      if (reasoningContent || !aiChatReasoning) {
+        return {
+          answer: content,
+          reasoning: reasoningContent
+        };
+      }
+
+      const [think, answer] = parseReasoningContent(content);
+      return {
+        answer,
+        reasoning: think
+      };
    }
  })();
+
+  if (stream && !isStreamResponse && aiChatReasoning && reasoning) {
+    workflowStreamResponse?.({
+      event: SseResponseEventEnum.fastAnswer,
+      data: textAdaptGptResponse({
+        reasoning_content: reasoning
+      })
+    });
+  }
+
  const { answer: replaceAnswer, toolJson } = parseAnswer(answer);
  if (!answer && !toolJson) {
    return Promise.reject(getEmptyResponseTip());
@@ -294,11 +324,16 @@ export const runToolWithPromptCall = async (
    }

    // No tool is invoked, indicating that the process is over
-    const gptAssistantResponse: ChatCompletionAssistantMessageParam = {
+    const gptAssistantResponse: ChatCompletionMessageParam = {
      role: ChatCompletionRequestMessageRoleEnum.Assistant,
-      content: replaceAnswer
+      content: replaceAnswer,
+      reasoning_text: reasoning
    };
-    const completeMessages = filterMessages.concat(gptAssistantResponse);
+    const completeMessages = filterMessages.concat({
+      ...gptAssistantResponse,
+      reasoning_text: undefined
+    });
+
    const inputTokens = await countGptMessagesTokens(requestMessages);
    const outputTokens = await countGptMessagesTokens([gptAssistantResponse]);

@@ -379,9 +414,10 @@ export const runToolWithPromptCall = async (
  })();

  // 合并工具调用的结果，使用 functionCall 格式存储。
-  const assistantToolMsgParams: ChatCompletionAssistantMessageParam = {
+  const assistantToolMsgParams: ChatCompletionMessageParam = {
    role: ChatCompletionRequestMessageRoleEnum.Assistant,
-    function_call: toolJson
+    function_call: toolJson,
+    reasoning_text: reasoning
  };

  // Only toolCall tokens are counted here, Tool response tokens count towards the next reply
@@ -502,12 +538,14 @@ ANSWER: `;
 async function streamResponse({
  res,
  stream,
-  workflowStreamResponse
+  workflowStreamResponse,
+  aiChatReasoning
 }: {
  res: NextApiResponse;
  toolNodes: ToolNodeItemType[];
  stream: StreamChatType;
  workflowStreamResponse?: WorkflowResponseType;
+  aiChatReasoning?: boolean;
 }) {
  const write = responseWriteController({
    res,
@@ -515,7 +553,9 @@ async function streamResponse({
  });

  let startResponseWrite = false;
-  let textAnswer = '';
+  let answer = '';
+  let reasoning = '';
+  const { parsePart, getStartTagBuffer } = parseReasoningStreamContent();

  for await (const part of stream) {
    if (res.closed) {
@@ -523,13 +563,21 @@ async function streamResponse({
      break;
    }

-    const responseChoice = part.choices?.[0]?.delta;
-    // console.log(responseChoice, '---===');
+    const [reasoningContent, content] = parsePart(part, aiChatReasoning);
+    answer += content;
+    reasoning += reasoningContent;

-    if (responseChoice?.content) {
-      const content = responseChoice?.content || '';
-      textAnswer += content;
+    if (aiChatReasoning && reasoningContent) {
+      workflowStreamResponse?.({
+        write,
+        event: SseResponseEventEnum.answer,
+        data: textAdaptGptResponse({
+          reasoning_content: reasoningContent
+        })
+      });
+    }

+    if (content) {
      if (startResponseWrite) {
        workflowStreamResponse?.({
          write,
@@ -538,18 +586,20 @@ async function streamResponse({
            text: content
          })
        });
-      } else if (textAnswer.length >= 3) {
-        textAnswer = textAnswer.trim();
-        if (textAnswer.startsWith('0')) {
+      } else if (answer.length >= 3) {
+        answer = answer.trimStart();
+        if (/0(:|：)/.test(answer)) {
          startResponseWrite = true;
+
          // find first : index
-          const firstIndex = textAnswer.indexOf(':');
-          textAnswer = textAnswer.substring(firstIndex + 1).trim();
+          const firstIndex =
+            answer.indexOf('0:') !== -1 ? answer.indexOf('0:') : answer.indexOf('0：');
+          answer = answer.substring(firstIndex + 2).trim();
          workflowStreamResponse?.({
            write,
            event: SseResponseEventEnum.answer,
            data: textAdaptGptResponse({
-              text: textAnswer
+              text: answer
            })
          });
        }
@@ -557,7 +607,23 @@ async function streamResponse({
    }
  }

-  return { answer: textAnswer.trim() };
+  if (answer === '') {
+    answer = getStartTagBuffer();
+    if (/0(:|：)/.test(answer)) {
+      // find first : index
+      const firstIndex = answer.indexOf('0:') !== -1 ? answer.indexOf('0:') : answer.indexOf('0：');
+      answer = answer.substring(firstIndex + 2).trim();
+      workflowStreamResponse?.({
+        write,
+        event: SseResponseEventEnum.answer,
+        data: textAdaptGptResponse({
+          text: answer
+        })
+      });
+    }
+  }
+
+  return { answer, reasoning };
 }

 const parseAnswer = (
@@ -568,8 +634,7 @@ const parseAnswer = (
 } => {
  str = str.trim();
  // 首先，使用正则表达式提取TOOL_ID和TOOL_ARGUMENTS
-  const prefixReg = /^1(:|：)/;
-  const answerPrefixReg = /^0(:|：)/;
+  const prefixReg = /1(:|：)/;

  if (prefixReg.test(str)) {
    const toolString = sliceJsonStr(str);
@@ -585,13 +650,21 @@ const parseAnswer = (
        }
      };
    } catch (error) {
-      return {
-        answer: ERROR_TEXT
-      };
+      if (/^1(:|：)/.test(str)) {
+        return {
+          answer: ERROR_TEXT
+        };
+      } else {
+        return {
+          answer: str
+        };
+      }
    }
  } else {
+    const firstIndex = str.indexOf('0:') !== -1 ? str.indexOf('0:') : str.indexOf('0：');
+    const answer = str.substring(firstIndex + 2).trim();
    return {
-      answer: str.replace(answerPrefixReg, '')
+      answer
    };
  }
 };
--- a/packages/service/core/workflow/dispatch/agent/runTool/type.d.ts
+++ b/packages/service/core/workflow/dispatch/agent/runTool/type.d.ts
@@ -22,6 +22,7 @@ export type DispatchToolModuleProps = ModuleDispatchProps<{
  [NodeInputKeyEnum.aiChatTemperature]: number;
  [NodeInputKeyEnum.aiChatMaxToken]: number;
  [NodeInputKeyEnum.aiChatVision]?: boolean;
+  [NodeInputKeyEnum.aiChatReasoning]?: boolean;
  [NodeInputKeyEnum.aiChatTopP]?: number;
  [NodeInputKeyEnum.aiChatStopSign]?: string;
  [NodeInputKeyEnum.aiChatResponseFormat]?: string;
--- a/packages/service/core/workflow/dispatch/chat/oneapi.ts
+++ b/packages/service/core/workflow/dispatch/chat/oneapi.ts
@@ -563,6 +563,15 @@ async function streamResponse({
  // if answer is empty, try to get value from startTagBuffer. (Cause: The response content is too short to exceed the minimum parse length)
  if (answer === '') {
    answer = getStartTagBuffer();
+    if (isResponseAnswerText && answer) {
+      workflowStreamResponse?.({
+        write,
+        event: SseResponseEventEnum.answer,
+        data: textAdaptGptResponse({
+          text: answer
+        })
+      });
+    }
  }

  return { answer, reasoning };
--- a/packages/service/worker/readFile/index.ts
+++ b/packages/service/worker/readFile/index.ts
@@ -27,7 +27,9 @@ parentPort?.on('message', async (props: ReadRawTextProps<Uint8Array>) => {
      case 'csv':
        return readCsvRawText(params);
      default:
-        return Promise.reject('Only support .txt, .md, .html, .pdf, .docx, pptx, .csv, .xlsx');
+        return Promise.reject(
+          `Only support .txt, .md, .html, .pdf, .docx, pptx, .csv, .xlsx. "${params.extension}" is not supported.`
+        );
    }
  };

--- a/projects/app/src/pageComponents/account/model/Channel/index.tsx
+++ b/projects/app/src/pageComponents/account/model/Channel/index.tsx
@@ -139,14 +139,14 @@ const ChannelTable = ({ Tab }: { Tab: React.ReactNode }) => {
                    </Td>
                    <Td>
                      <MyNumberInput
-                        defaultValue={item.priority || 0}
-                        min={0}
+                        defaultValue={item.priority || 1}
+                        min={1}
                        max={100}
                        h={'32px'}
                        w={'80px'}
                        onBlur={(e) => {
                          const val = (() => {
-                            if (!e) return 0;
+                            if (!e) return 1;
                            return e;
                          })();
                          updateChannel({
--- a/projects/app/src/web/core/ai/channel.ts
+++ b/projects/app/src/web/core/ai/channel.ts
@@ -130,7 +130,8 @@ export const postCreateChannel = (data: CreateChannelProps) =>
    base_url: data.base_url,
    models: data.models,
    model_mapping: data.model_mapping,
-    key: data.key
+    key: data.key,
+    priority: 1
  });

 export const putChannelStatus = (id: number, status: ChannelStatusEnum) =>
@@ -146,7 +147,7 @@ export const putChannel = (data: ChannelInfoType) =>
    model_mapping: data.model_mapping,
    key: data.key,
    status: data.status,
-    priority: data.priority
+    priority: data.priority ? Math.max(data.priority, 1) : undefined
  });

 export const deleteChannel = (id: number) => DELETE(`/channel/${id}`);