GITBOOK-21: change request with no subject merged in GitBook
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@ -55,10 +55,12 @@
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* [接入 LocalAI 部署的本地模型](advanced/model-configuration/localai.md)
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* [更多集成](advanced/more-integration.md)
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* [扩展](advanced/extension/README.md)
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* [API-based 扩展](advanced/extension/api\_based\_extension/README.md)
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* [外部数据工具扩展](advanced/extension/api\_based\_extension/external\_data\_tool.md)
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* [敏感内容审查扩展](advanced/extension/api\_based\_extension/moderation.md)
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* [Code-based 扩展](advanced/extension/code\_based\_extension.md)
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* [API 扩展](advanced/extension/api\_based\_extension/README.md)
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* [外部数据工具](advanced/extension/api\_based\_extension/external\_data\_tool.md)
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* [敏感内容审查](advanced/extension/api\_based\_extension/moderation.md)
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* [代码扩展](advanced/extension/code\_based\_extension/README.md)
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* [外部数据工具](advanced/extension/code\_based\_extension/external\_data\_tool.md)
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* [敏感内容审查](advanced/extension/code\_based\_extension/moderation.md)
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## 使用案例 <a href="#use-cases" id="use-cases"></a>
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@ -4,4 +4,4 @@
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[api\_based\_extension](api\_based\_extension/ "mention")
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[code\_based\_extension.md](code\_based\_extension.md "mention")
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[code\_based\_extension](code\_based\_extension/ "mention")
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@ -1,4 +1,4 @@
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# API-based 扩展
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# API 扩展
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开发者可通过 API 扩展模块能力，当前支持以下模块扩展：
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@ -11,7 +11,7 @@
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<figure><img src="../../../.gitbook/assets/api_based_01.png" alt=""><figcaption><p>基于 API 扩展</p></figcaption></figure>
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### [API 规范](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#api-%E8%A7%84%E8%8C%83) <a href="#usercontentapi-gui-fan" id="usercontentapi-gui-fan"></a>
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### API 规范 <a href="#usercontentapi-gui-fan" id="usercontentapi-gui-fan"></a>
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Dify 将会以以下规范调用您的接口：
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@ -19,14 +19,14 @@ Dify 将会以以下规范调用您的接口：
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POST {Your-API-Endpoint}
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```
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#### [Header](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#header) <a href="#user-content-header" id="user-content-header"></a>
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#### Header <a href="#user-content-header" id="user-content-header"></a>
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| Header | Value | Desc |
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| --------------- | ----------------- | --------------------------------------------------------------------- |
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| `Content-Type` | application/json | 请求内容为 JSON 格式。 |
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| `Authorization` | Bearer {api\_key} | API Key 以 Token 令牌的方式传输，您需要解析该 `api_key` 并确认是否和提供的 API Key 一致，保证接口安全。 |
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#### [Request Body](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#request-body) <a href="#user-content-request-body" id="user-content-request-body"></a>
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#### Request Body <a href="#user-content-request-body" id="user-content-request-body"></a>
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```
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{
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@ -37,7 +37,7 @@ POST {Your-API-Endpoint}
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}
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```
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#### [API 返回](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#api-%E8%BF%94%E5%9B%9E) <a href="#usercontentapi-fan-hui" id="usercontentapi-fan-hui"></a>
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#### API 返回 <a href="#usercontentapi-fan-hui" id="usercontentapi-fan-hui"></a>
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```
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{
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@ -45,20 +45,20 @@ POST {Your-API-Endpoint}
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}
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```
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### [校验](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#%E6%A0%A1%E9%AA%8C) <a href="#usercontent-xiao-yan" id="usercontent-xiao-yan"></a>
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### 校验 <a href="#usercontent-xiao-yan" id="usercontent-xiao-yan"></a>
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在 Dify 配置 API-based Extension 时，Dify 将会发送一个请求至 API Endpoint，以检验 API 的可用性。
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当 API Endpoint 接收到 `point=ping` 时，接口应返回 `result=pong`，具体如下：
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#### [Header](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#header-1) <a href="#user-content-header-1" id="user-content-header-1"></a>
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#### Header <a href="#user-content-header-1" id="user-content-header-1"></a>
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```
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Content-Type: application/json
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Authorization: Bearer {api_key}
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```
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#### [Request Body](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#request-body-1) <a href="#user-content-request-body-1" id="user-content-request-body-1"></a>
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#### Request Body <a href="#user-content-request-body-1" id="user-content-request-body-1"></a>
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```
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{
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@ -66,7 +66,7 @@ Authorization: Bearer {api_key}
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}
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```
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#### [API 期望返回](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#api-%E6%9C%9F%E6%9C%9B%E8%BF%94%E5%9B%9E) <a href="#usercontentapi-qi-wang-fan-hui" id="usercontentapi-qi-wang-fan-hui"></a>
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#### API 期望返回 <a href="#usercontentapi-qi-wang-fan-hui" id="usercontentapi-qi-wang-fan-hui"></a>
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```
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{
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@ -74,24 +74,24 @@ Authorization: Bearer {api_key}
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}
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```
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### [范例](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#%E8%8C%83%E4%BE%8B) <a href="#usercontent-fan-li" id="usercontent-fan-li"></a>
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### 范例 <a href="#usercontent-fan-li" id="usercontent-fan-li"></a>
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此处以外部数据工具为例，场景为根据地区获取外部天气信息作为上下文。
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#### [API 范例](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#api-%E8%8C%83%E4%BE%8B) <a href="#usercontentapi-fan-li" id="usercontentapi-fan-li"></a>
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#### API 范例 <a href="#usercontentapi-fan-li" id="usercontentapi-fan-li"></a>
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```
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POST https://fake-domain.com/api/dify/receive
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```
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[**Header**](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#header-2)
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**Header**
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```
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Content-Type: application/json
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Authorization: Bearer 123456
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```
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[**Request Body**](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#request-body-2)
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**Request Body**
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```
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{
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@ -107,7 +107,7 @@ Authorization: Bearer 123456
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}
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```
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[**API 返回**](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#api-%E8%BF%94%E5%9B%9E-1)
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**API 返回**
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```
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{
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}
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```
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#### [代码范例](https://github.com/langgenius/dify-docs/diffs/2?branch=main\&name=main\&qualified\_name=refs%2Fheads%2Fmain\&sha1=fb07d2bea301bd6388c393d5f3d8a80386c4dfdb\&sha2=a72d056812efe42f153d649085811e5b49ee131e\&short\_path=e2d7adb\&unchanged=expanded\&w=false#%E4%BB%A3%E7%A0%81%E8%8C%83%E4%BE%8B) <a href="#usercontent-dai-ma-fan-li" id="usercontent-dai-ma-fan-li"></a>
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#### 代码范例 <a href="#usercontent-dai-ma-fan-li" id="usercontent-dai-ma-fan-li"></a>
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代码基于 Python FastAPI 框架。
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@ -190,16 +190,15 @@ Authorization: Bearer 123456
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```
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3. 启动 API 服务，默认端口为 8000，API 完整地址为：`http://127.0.0.1:8000/api/dify/receive`，配置的 API Key 为 `123456`。
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```
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uvicorn main:app --reload
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```
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<pre><code><strong>uvicorn main:app --reload
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</strong></code></pre>
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4. 在 Dify 配置该 API。
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[](../../../.gitbook/assets/api\_based\_01.png)
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<figure><img src="https://github.com/langgenius/dify-docs/raw/main/zh_CN/.gitbook/assets/api_based_01.png" alt=""><figcaption><p>配置 API </p></figcaption></figure>
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5. 在 App 中选择该 API 扩展。
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[](../../../.gitbook/assets/api\_based\_02.png)
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<figure><img src="https://github.com/langgenius/dify-docs/raw/main/zh_CN/.gitbook/assets/api_based_02.png" alt=""><figcaption><p>选择扩展</p></figcaption></figure>
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App 调试时，Dify 将请求配置的 API，并发送以下内容（范例）：
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"result": "City: London\nTemperature: 10°C\nRealFeel®: 8°C\nAir Quality: Poor\nWind Direction: ENE\nWind Speed: 8 km/h\nWind Gusts: 14 km/h\nPrecipitation: Light rain"
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}
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```
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### 本地调试
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由于 Dify 云端版无法访问内网 API 服务，为了方便本地调试 API 服务，可以使用 [Ngrok](https://ngrok.com) 将 API 服务的端点暴露到公网，实现云端调试本地代码。操作步骤：
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1. 进入 [https://ngrok.com](https://ngrok.com) 官网，注册并下载 Ngrok 文件。
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<figure><img src="../../../.gitbook/assets/download.png" alt=""><figcaption><p>Download</p></figcaption></figure>
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2. 下载完成后，进入下载目录，根据下方说明解压压缩包，并执行说明中的初始化脚本。
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* ```Shell
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$ unzip /path/to/ngrok.zip
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$ ./ngrok config add-authtoken 你的Token
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```
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3. 查看本地 API 服务的端口：
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<figure><img src="../../../.gitbook/assets/8000.png" alt=""><figcaption><p>查看端口</p></figcaption></figure>
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并运行以下命令启动：
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* ```Shell
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$ ./ngrok http 端口号
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```
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启动成功的样例如下：
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<figure><img src="../../../.gitbook/assets/ngrock.png" alt=""><figcaption><p>Ngrok 启动</p></figcaption></figure>
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4. 我们找到 Forwarding 中，如上图：`https://177e-159-223-41-52.ngrok-free.app`（此为示例域名，请替换为自己的）即为公网域名。
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* 按照上述的范例，我们把本地已经启动的服务端点暴露出去，将代码范例接口：`http://127.0.0.1:8000/api/dify/receive` 替换为 `https://177e-159-223-41-52.ngrok-free.app/api/dify/receive`
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此 API 端点即可公网访问。至此，我们即可在 Dify 配置该 API 端点进行本地调试代码，配置步骤请参考 [external\_data\_tool.md](../../../application/prompt-engineering/external\_data\_tool.md "mention")。
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# Code-based 扩展
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对于本地部署 Dify 的开发者，如果想实现扩展能力，无需重新写一个 API 服务，可以使用 Code-based Extension 即在 Dify 功能的基础上，以代码形式扩展或增强程序的能力（即插件能力），而不破坏 Dify 原有代码逻辑。它遵循一定的接口或规范，以实现与主程序的兼容和可插拔性。 目前，Dify 开放了两种 Code-based Extension，分别为：
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* 新增一种新的外部数据工具类型[external\_data\_tool.md](api\_based\_extension/external\_data\_tool.md "mention")
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* 扩展敏感内容审查策略[moderation.md](api\_based\_extension/moderation.md "mention")
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可在上述功能的基础上，遵循代码层 interface 的规范，来实现横向扩展的目的。
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# 代码扩展
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对于本地部署 Dify 的开发者，如果想实现扩展能力，无需重新写一个 API 服务，可以使用代码扩展，即在 Dify 功能的基础上，以代码形式扩展或增强程序的能力（即插件能力），而不破坏 Dify 原有代码逻辑。它遵循一定的接口或规范，以实现与主程序的兼容和可插拔性。 目前，Dify 开放了两种代码扩展，分别为：
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* 新增一种新的外部数据工具类型 [external\_data\_tool.md](external\_data\_tool.md "mention")
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* 扩展敏感内容审查策略 [moderation.md](moderation.md "mention")
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可在上述功能的基础上，遵循代码层 interface 的规范，来实现横向扩展的目的。
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### schema.json 规范定义
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Code-based Extension 前端样式通过 `schema.json` 定义，以下是定义规范。
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* label：自定义类型名称，支持系统语言切换
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* form\_schema：表单内容列表
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* type：组件类型
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* select：下拉选项
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* text-input：文本
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* paragraph：段落
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* label：组件名称，支持系统语言切换
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* variable：变量名称
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* required：是否必填
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* default：默认值
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* placeholder：组件提示内容
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* options：组件「select」专有属性，定义下拉内容
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* label：下拉名称，支持系统语言切换
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* value：下拉选项值
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* max\_length：组件「text-input」专有属性，最大长度
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# 外部数据工具
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外部数据工具用于在终端用户提交数据后，利用外部工具获取额外数据组装至提示词中作为 LLM 额外上下文信息。Dify 默认提供了外部 API 调用的工具，具体参见 [api\_based\_extension](../api\_based\_extension/ "mention")。
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|
||||
而对于本地部署 Dify 的开发者，为了满足更加定制化的需求，或者不希望额外开发一个 API Server，可以直接在 Dify 服务的基础上，以插件的形式插入定制的外部数据工具实现逻辑。扩展自定义工具后，将会在工具类型的下拉列表中增加您的自定义工具选项，团队成员即可使用自定义的工具来获取外部数据。
|
||||
|
||||
## 如何开发扩展
|
||||
|
||||
开发新的外部数据工具需要准备下面几个文件：
|
||||
|
||||
* `{your_tool_name}.py` 工具扩展实现代码
|
||||
|
||||
*   `your_tool_name` 为您定义的工具唯一标识，唯一标识不可与其他工具重复，建议以 `custom_` 为开头，目录结构示例如下：
|
||||
|
||||
|
||||
|
||||
```Python
|
||||
.
|
||||
└── external_data_tool
|
||||
└── custom_db_search
|
||||
├── custom_db_search.py
|
||||
└── schema.json
|
||||
```
|
||||
|
||||
PS. Python 文件名称必须与文件夹名称保持一致。
|
||||
* `schema.json` 前端表单结构规范
|
||||
|
||||
|
||||
|
||||
<figure><img src="../../../.gitbook/assets/红框.png" alt=""><figcaption><p>Front-end Form Structure</p></figcaption></figure>
|
||||
|
||||
红框上的为固定表单项，红框中的表单项可在 schema.json 中的 form\_schema 自定义，规范见：[.](./ "mention")
|
||||
|
||||
### 实现代码
|
||||
|
||||
```python
|
||||
from typing import Optional
|
||||
|
||||
from core.external_data_tool.base import ExternalDataTool
|
||||
|
||||
|
||||
class YourToolNameTool(ExternalDataTool):
|
||||
name: str = "{your_tool_name}"
|
||||
|
||||
@classmethod
|
||||
def validate_config(cls, tenant_id: str, config: dict) -> None:
|
||||
"""
|
||||
Validate the incoming form config data.
|
||||
|
||||
:param tenant_id: the id of workspace
|
||||
:param config: the form config data
|
||||
:return:
|
||||
"""
|
||||
|
||||
# implement your own validate logic here
|
||||
|
||||
def query(self, inputs: dict, query: Optional[str] = None) -> str:
|
||||
"""
|
||||
Query the external data tool.
|
||||
|
||||
:param inputs: user inputs
|
||||
:param query: the query of chat app
|
||||
:return: the tool query result
|
||||
"""
|
||||
# TODO implement your own query logic here
|
||||
|
||||
return ''
|
||||
```
|
||||
|
||||
代码需要放置在 `api/core/external_data_tool`中，目录结构如下：
|
||||
|
||||
```python
|
||||
.
|
||||
└── api
|
||||
└── core
|
||||
└── external_data_tool
|
||||
├── base.py
|
||||
├── external_data_tool_factory.py
|
||||
├── api
|
||||
│ ├── api.py
|
||||
│ └── schema.json
|
||||
├── {your_tool_name}
|
||||
│ ├── {your_tool_name}.py
|
||||
│ └── schema.json
|
||||
```
|
||||
|
|
@ -0,0 +1,318 @@
|
|||
# 敏感内容审查
|
||||
|
||||
## **内容审查扩展**
|
||||
|
||||
除了系统内置的内容审查类型，Dify 也支持用户扩展自定义实现，该方法适用于私有部署的用户定制开发，如果您愿意将扩展功能贡献给我们的话，非常欢迎给 Dify 提交 PR。
|
||||
|
||||
## 快速开始
|
||||
|
||||
这里以一个 `Cloud Service` 内容审查扩展为例：大致步骤如下：
|
||||
|
||||
1. 初始化目录
|
||||
2. 添加前端组件定义文件
|
||||
3. 添加实现类
|
||||
4. 预览前端界面
|
||||
5. 调试扩展
|
||||
6. ### 初始化目录
|
||||
|
||||
新增自定义类型 `Cloud Service`，需要在 `api/core/moderation` 目录下新建相关的目录和文件。
|
||||
|
||||
```Plain
|
||||
.
|
||||
└── api
|
||||
└── core
|
||||
└── moderation
|
||||
└── cloud_service
|
||||
├── __init__.py
|
||||
├── cloud_service.py
|
||||
└── schema.json
|
||||
```
|
||||
|
||||
2. ### 添加前端组件规范
|
||||
|
||||
* `schema.json`，这里定义了前端组件规范，详细见 [.](./ "mention")
|
||||
|
||||
```JSON
|
||||
{
|
||||
"label": {
|
||||
"en-US": "Cloud Service",
|
||||
"zh-Hans": "云服务"
|
||||
},
|
||||
"form_schema": [
|
||||
{
|
||||
"type": "select",
|
||||
"label": {
|
||||
"en-US": "Cloud Provider",
|
||||
"zh-Hans": "云厂商"
|
||||
},
|
||||
"variable": "cloud_provider",
|
||||
"required": true,
|
||||
"options": [
|
||||
{
|
||||
"label": {
|
||||
"en-US": "AWS",
|
||||
"zh-Hans": "亚马逊"
|
||||
},
|
||||
"value": "AWS"
|
||||
},
|
||||
{
|
||||
"label": {
|
||||
"en-US": "Google Cloud",
|
||||
"zh-Hans": "谷歌云"
|
||||
},
|
||||
"value": "GoogleCloud"
|
||||
},
|
||||
{
|
||||
"label": {
|
||||
"en-US": "Azure Cloud",
|
||||
"zh-Hans": "微软云"
|
||||
},
|
||||
"value": "Azure"
|
||||
}
|
||||
],
|
||||
"default": "GoogleCloud",
|
||||
"placeholder": ""
|
||||
},
|
||||
{
|
||||
"type": "text-input",
|
||||
"label": {
|
||||
"en-US": "API Endpoint",
|
||||
"zh-Hans": "API Endpoint"
|
||||
},
|
||||
"variable": "api_endpoint",
|
||||
"required": true,
|
||||
"max_length": 100,
|
||||
"default": "",
|
||||
"placeholder": "https://api.example.com"
|
||||
},
|
||||
{
|
||||
"type": "paragraph",
|
||||
"label": {
|
||||
"en-US": "API Key",
|
||||
"zh-Hans": "API Key"
|
||||
},
|
||||
"variable": "api_keys",
|
||||
"required": true,
|
||||
"default": "",
|
||||
"placeholder": "Paste your API key here"
|
||||
}
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
3. ### 添加实现类
|
||||
|
||||
`cloud_service.py` 代码模版，你可以在这里实现具体的业务逻辑。
|
||||
|
||||
> 注意：类变量 name 为自定义类型名称，需要跟目录和文件名保持一致，而且唯一。
|
||||
|
||||
```Python
|
||||
from core.moderation.base import Moderation, ModerationAction, ModerationInputsResult, ModerationOutputsResult
|
||||
|
||||
class CloudServiceModeration(Moderation):
|
||||
"""
|
||||
The name of custom type must be unique, keep the same with directory and file name.
|
||||
"""
|
||||
name: str = "cloud_service"
|
||||
|
||||
@classmethod
|
||||
def validate_config(cls, tenant_id: str, config: dict) -> None:
|
||||
"""
|
||||
schema.json validation. It will be called when user save the config.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
config = {
|
||||
"cloud_provider": "GoogleCloud",
|
||||
"api_endpoint": "https://api.example.com",
|
||||
"api_keys": "123456",
|
||||
"inputs_config": {
|
||||
"enabled": True,
|
||||
"preset_response": "Your content violates our usage policy. Please revise and try again."
|
||||
},
|
||||
"outputs_config": {
|
||||
"enabled": True,
|
||||
"preset_response": "Your content violates our usage policy. Please revise and try again."
|
||||
}
|
||||
}
|
||||
|
||||
:param tenant_id: the id of workspace
|
||||
:param config: the variables of form config
|
||||
:return:
|
||||
"""
|
||||
|
||||
cls._validate_inputs_and_outputs_config(config, True)
|
||||
|
||||
if not config.get("cloud_provider"):
|
||||
raise ValueError("cloud_provider is required")
|
||||
|
||||
if not config.get("api_endpoint"):
|
||||
raise ValueError("api_endpoint is required")
|
||||
|
||||
if not config.get("api_keys"):
|
||||
raise ValueError("api_keys is required")
|
||||
|
||||
def moderation_for_inputs(self, inputs: dict, query: str = "") -> ModerationInputsResult:
|
||||
"""
|
||||
Moderation for inputs.
|
||||
|
||||
:param inputs: user inputs
|
||||
:param query: the query of chat app, there is empty if is completion app
|
||||
:return: the moderation result
|
||||
"""
|
||||
flagged = False
|
||||
preset_response = ""
|
||||
|
||||
if self.config['inputs_config']['enabled']:
|
||||
preset_response = self.config['inputs_config']['preset_response']
|
||||
|
||||
if query:
|
||||
inputs['query__'] = query
|
||||
flagged = self._is_violated(inputs)
|
||||
|
||||
# return ModerationInputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, inputs=inputs, query=query)
|
||||
return ModerationInputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
|
||||
|
||||
def moderation_for_outputs(self, text: str) -> ModerationOutputsResult:
|
||||
"""
|
||||
Moderation for outputs.
|
||||
|
||||
:param text: the text of LLM response
|
||||
:return: the moderation result
|
||||
"""
|
||||
flagged = False
|
||||
preset_response = ""
|
||||
|
||||
if self.config['outputs_config']['enabled']:
|
||||
preset_response = self.config['outputs_config']['preset_response']
|
||||
|
||||
flagged = self._is_violated({'text': text})
|
||||
|
||||
# return ModerationOutputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, text=text)
|
||||
return ModerationOutputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
|
||||
|
||||
def _is_violated(self, inputs: dict):
|
||||
"""
|
||||
The main logic of moderation.
|
||||
|
||||
:param inputs:
|
||||
:return: the moderation result
|
||||
"""
|
||||
return False
|
||||
```
|
||||
|
||||
4. ### 预览前端界面
|
||||
|
||||
按照上面步骤执行，运行服务即可见新增的自定义类型。
|
||||
|
||||
5. #### 调试扩展
|
||||
|
||||
至此，即可在 Dify 应用编排界面选择自定义的 `Cloud Service` 内容审查扩展类型进行调试。\
|
||||
|
||||
|
||||
## 前端组件规范
|
||||
|
||||
* 请参考 [.](./ "mention")
|
||||
|
||||
## 实现类模版
|
||||
|
||||
```Python
|
||||
from core.moderation.base import Moderation, ModerationAction, ModerationInputsResult, ModerationOutputsResult
|
||||
|
||||
class CloudServiceModeration(Moderation):
|
||||
"""
|
||||
The name of custom type must be unique, keep the same with directory and file name.
|
||||
"""
|
||||
name: str = "cloud_service"
|
||||
|
||||
@classmethod
|
||||
def validate_config(cls, tenant_id: str, config: dict) -> None:
|
||||
"""
|
||||
schema.json validation. It will be called when user save the config.
|
||||
|
||||
:param tenant_id: the id of workspace
|
||||
:param config: the variables of form config
|
||||
:return:
|
||||
"""
|
||||
cls._validate_inputs_and_outputs_config(config, True)
|
||||
|
||||
# implement your own logic here
|
||||
|
||||
def moderation_for_inputs(self, inputs: dict, query: str = "") -> ModerationInputsResult:
|
||||
"""
|
||||
Moderation for inputs.
|
||||
|
||||
:param inputs: user inputs
|
||||
:param query: the query of chat app, there is empty if is completion app
|
||||
:return: the moderation result
|
||||
"""
|
||||
flagged = False
|
||||
preset_response = ""
|
||||
|
||||
# implement your own logic here
|
||||
|
||||
# return ModerationInputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, inputs=inputs, query=query)
|
||||
return ModerationInputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
|
||||
|
||||
def moderation_for_outputs(self, text: str) -> ModerationOutputsResult:
|
||||
"""
|
||||
Moderation for outputs.
|
||||
|
||||
:param text: the text of LLM response
|
||||
:return: the moderation result
|
||||
"""
|
||||
flagged = False
|
||||
preset_response = ""
|
||||
|
||||
# implement your own logic here
|
||||
|
||||
# return ModerationOutputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, text=text)
|
||||
return ModerationOutputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
|
||||
```
|
||||
|
||||
## 实现类开发详细介绍
|
||||
|
||||
### def validate\_config
|
||||
|
||||
`schema.json` 表单校验方法，当用户点击「发布」保存配置时调用
|
||||
|
||||
* `config` 表单参数
|
||||
* `{{variable}}` 表单自定义变量
|
||||
* `inputs_config` 输入审查预设回复
|
||||
* `enabled` 是否开启
|
||||
* `preset_response` 输入预设回复
|
||||
* `outputs_config`输出审查预设回复
|
||||
* `enabled` 是否开启
|
||||
* `preset_respons` 输出预设回复
|
||||
|
||||
### def moderation\_for\_inputs
|
||||
|
||||
输入校验函数
|
||||
|
||||
* `inputs` ：终端用户传入变量值
|
||||
* `query` ：终端用户当前对话输入内容，对话型应用固定参数。
|
||||
* `ModerationInputsResult`
|
||||
* `flagged` 是否违反校验规则
|
||||
* `action` 执行动作
|
||||
* `direct_output` 直接输出预设回复
|
||||
* `overrided` 覆写传入变量值
|
||||
* `preset_response` 预设回复（仅当 action=direct\_output 返回）
|
||||
* `inputs` 终端用户传入变量值，key 为变量名，value 为变量值（仅当 action=overrided 返回）
|
||||
* `query` 覆写的终端用户当前对话输入内容，对话型应用固定参数。（仅当 action=overrided 返回）
|
||||
|
||||
### def moderation\_for\_outputs
|
||||
|
||||
输出校验函数
|
||||
|
||||
* `text` ：模型输出内容
|
||||
* `moderation_for_outputs` ：输出校验函数
|
||||
* `text` ：LLM 回答内容。当 LLM 输出为流式时，此处为 100 字为一个分段的内容。
|
||||
* `ModerationOutputsResult`
|
||||
* `flagged` 是否违反校验规则
|
||||
* `action` 执行动作
|
||||
* `direct_output`直接输出预设回复
|
||||
* `overrided`覆写传入变量值
|
||||
* `preset_response` 预设回复（仅当 action=direct\_output 返回）
|
||||
* `text` 覆写的 LLM 回答内容。（仅当 action=overrided 返回）
|
||||
|
||||
\
|
||||
|
|
@ -4,11 +4,11 @@
|
|||
|
||||
此前 [datasets](../../advanced/datasets/ "mention") 功能允许开发者可以直接上传各类格式的长文本、结构化数据来构建数据集，使 AI 应用基于用户上传的最新上下文进行对话。
|
||||
|
||||
而本次更新的**外部数据工具**赋能开发者可以使用自有的搜索能力或内部知识库等外部数据作为 LLM 的上下文，通过 API 扩展的方式实现外部数据的获取并嵌入 Prompt。相比在云端上传数据集，使用**外部数据工具**可以在保障私有数据安全，自定义搜索，获取实时数据等方面有显著优势。
|
||||
而本次更新的**外部数据工具**赋能开发者可以使用自有的搜索能力或内部知识库等外部数据作为 LLM 的上下文，通过 API 扩展的方式实现外部数据的获取并嵌入提示词。相比在云端上传数据集，使用**外部数据工具**可以在保障私有数据安全，自定义搜索，获取实时数据等方面有显著优势。
|
||||
|
||||
## 具体实现
|
||||
|
||||
当终端用户向对话系统提出请求时，平台后端会触发外部数据工具（即调用自己的 API），它会查询用户问题相关的外部信息，如员工资料、实时记录等，通过 API 返回与当前请求相关的部分。平台后端会将返回的结果组装成文本作为上下文注入到 Prompt 中，以输出更加个性化和符合用户需求的回复内容。
|
||||
当终端用户向对话系统提出请求时，平台后端会触发外部数据工具（即调用自己的 API），它会查询用户问题相关的外部信息，如员工资料、实时记录等，通过 API 返回与当前请求相关的部分。平台后端会将返回的结果组装成文本作为上下文注入到提示词中，以输出更加个性化和符合用户需求的回复内容。
|
||||
|
||||
## 操作说明
|
||||
|
||||
|
|
@ -21,11 +21,11 @@
|
|||
|
||||
<figure><img src="../../.gitbook/assets/weather inquiry.png" alt=""><figcaption><p>Weather Inquiry</p></figcaption></figure>
|
||||
|
||||
4. 在提示词编排页面，点击“工具”右侧的“+添加”按钮，在打开的“添加 工具”对话框，填写名称和变量名称（变量名称会被引用到 Prompt 中，请填写英文），以及选择第 2 步中已经添加的基于 API 的扩展。
|
||||
4. 在提示词编排页面，点击“工具”右侧的“+添加”按钮，在打开的“添加 工具”对话框，填写名称和变量名称（变量名称会被引用到提示词中，请填写英文），以及选择第 2 步中已经添加的基于 API 的扩展。
|
||||
|
||||
<figure><img src="../../.gitbook/assets/api_based_extension1.png" alt=""><figcaption><p>External_data_tool</p></figcaption></figure>
|
||||
|
||||
5. 这样，我们在提示词编排框就可以把查询到的外部数据拼装到 Prompt 中。比如我们要查询今天的伦敦天气，可以添加`location` 变量，输入"London"，结合外部数据工具的扩展变量名称`weather_data`，调试输出如下：
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5. 这样，我们在提示词编排框就可以把查询到的外部数据拼装到提示词中。比如我们要查询今天的伦敦天气，可以添加`location` 变量，输入"London"，结合外部数据工具的扩展变量名称`weather_data`，调试输出如下：
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<figure><img src="../../.gitbook/assets/Weather_search_tool.jpeg" alt=""><figcaption><p>Weather_search_tool</p></figcaption></figure>
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Reference in New Issue