fix: drop some dead links (#29827)

Signed-off-by: yihong0618 <zouzou0208@gmail.com>
This commit is contained in:
yihong
2025-12-18 10:52:19 +08:00
committed by GitHub
parent ae17537470
commit acbeb04edc
2 changed files with 12 additions and 58 deletions

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@@ -18,34 +18,20 @@ This module provides the interface for invoking and authenticating various model
- Model provider display
![image-20231210143654461](./docs/en_US/images/index/image-20231210143654461.png)
Displays a list of all supported providers, including provider names, icons, supported model types list, predefined model list, configuration method, and credentials form rules, etc. For detailed rule design, see: [Schema](./docs/en_US/schema.md).
Displays a list of all supported providers, including provider names, icons, supported model types list, predefined model list, configuration method, and credentials form rules, etc.
- Selectable model list display
![image-20231210144229650](./docs/en_US/images/index/image-20231210144229650.png)
After configuring provider/model credentials, the dropdown (application orchestration interface/default model) allows viewing of the available LLM list. Greyed out items represent predefined model lists from providers without configured credentials, facilitating user review of supported models.
In addition, this list also returns configurable parameter information and rules for LLM, as shown below:
![image-20231210144814617](./docs/en_US/images/index/image-20231210144814617.png)
These parameters are all defined in the backend, allowing different settings for various parameters supported by different models, as detailed in: [Schema](./docs/en_US/schema.md#ParameterRule).
In addition, this list also returns configurable parameter information and rules for LLM. These parameters are all defined in the backend, allowing different settings for various parameters supported by different models.
- Provider/model credential authentication
![image-20231210151548521](./docs/en_US/images/index/image-20231210151548521.png)
![image-20231210151628992](./docs/en_US/images/index/image-20231210151628992.png)
The provider list returns configuration information for the credentials form, which can be authenticated through Runtime's interface. The first image above is a provider credential DEMO, and the second is a model credential DEMO.
The provider list returns configuration information for the credentials form, which can be authenticated through Runtime's interface.
## Structure
![](./docs/en_US/images/index/image-20231210165243632.png)
Model Runtime is divided into three layers:
- The outermost layer is the factory method
@@ -60,9 +46,6 @@ Model Runtime is divided into three layers:
It offers direct invocation of various model types, predefined model configuration information, getting predefined/remote model lists, model credential authentication methods. Different models provide additional special methods, like LLM's pre-computed tokens method, cost information obtaining method, etc., **allowing horizontal expansion** for different models under the same provider (within supported model types).
## Next Steps
## Documentation
- Add new provider configuration: [Link](./docs/en_US/provider_scale_out.md)
- Add new models for existing providers: [Link](./docs/en_US/provider_scale_out.md#AddModel)
- View YAML configuration rules: [Link](./docs/en_US/schema.md)
- Implement interface methods: [Link](./docs/en_US/interfaces.md)
For detailed documentation on how to add new providers or models, please refer to the [Dify documentation](https://docs.dify.ai/).

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@@ -18,34 +18,20 @@
- 模型供应商展示
![image-20231210143654461](./docs/zh_Hans/images/index/image-20231210143654461.png)
展示所有已支持的供应商列表,除了返回供应商名称、图标之外,还提供了支持的模型类型列表,预定义模型列表、配置方式以及配置凭据的表单规则等等,规则设计详见:[Schema](./docs/zh_Hans/schema.md)。
展示所有已支持的供应商列表,除了返回供应商名称、图标之外,还提供了支持的模型类型列表,预定义模型列表、配置方式以及配置凭据的表单规则等等。
- 可选择的模型列表展示
![image-20231210144229650](./docs/zh_Hans/images/index/image-20231210144229650.png)
配置供应商/模型凭据后,可在此下拉(应用编排界面/默认模型)查看可用的 LLM 列表,其中灰色的为未配置凭据供应商的预定义模型列表,方便用户查看已支持的模型。
配置供应商/模型凭据后,可在此下拉(应用编排界面/默认模型)查看可用的 LLM 列表,其中灰色的为未配置凭据供应商的预定义模型列表,方便用户查看已支持的模型
除此之外,该列表还返回了 LLM 可配置的参数信息和规则,如下图:
![image-20231210144814617](./docs/zh_Hans/images/index/image-20231210144814617.png)
这里的参数均为后端定义,相比之前只有 5 种固定参数,这里可为不同模型设置所支持的各种参数,详见:[Schema](./docs/zh_Hans/schema.md#ParameterRule)。
除此之外,该列表还返回了 LLM 可配置的参数信息和规则。这里的参数均为后端定义,相比之前只有 5 种固定参数,这里可为不同模型设置所支持的各种参数
- 供应商/模型凭据鉴权
![image-20231210151548521](./docs/zh_Hans/images/index/image-20231210151548521.png)
![image-20231210151628992](./docs/zh_Hans/images/index/image-20231210151628992.png)
供应商列表返回了凭据表单的配置信息,可通过 Runtime 提供的接口对凭据进行鉴权,上图 1 为供应商凭据 DEMO上图 2 为模型凭据 DEMO。
供应商列表返回了凭据表单的配置信息,可通过 Runtime 提供的接口对凭据进行鉴权。
## 结构
![](./docs/zh_Hans/images/index/image-20231210165243632.png)
Model Runtime 分三层:
- 最外层为工厂方法
@@ -59,8 +45,7 @@ Model Runtime 分三层:
对于供应商/模型凭据,有两种情况
- 如 OpenAI 这类中心化供应商,需要定义如**api_key**这类的鉴权凭据
- 如[**Xinference**](https://github.com/xorbitsai/inference)这类本地部署的供应商,需要定义如**server_url**这类的地址凭据,有时候还需要定义**model_uid**之类的模型类型凭据,就像下面这样,当在供应商层定义了这些凭据后,就可以在前端页面上直接展示,无需修改前端逻辑。
![Alt text](docs/zh_Hans/images/index/image.png)
- 如[**Xinference**](https://github.com/xorbitsai/inference)这类本地部署的供应商,需要定义如**server_url**这类的地址凭据,有时候还需要定义**model_uid**之类的模型类型凭据当在供应商层定义了这些凭据后,就可以在前端页面上直接展示,无需修改前端逻辑。
当配置好凭据后,就可以通过 DifyRuntime 的外部接口直接获取到对应供应商所需要的**Schema**(凭据表单规则),从而在可以在不修改前端逻辑的情况下,提供新的供应商/模型的支持。
@@ -74,20 +59,6 @@ Model Runtime 分三层:
- 模型凭据 (**在供应商层定义**):这是一类不经常变动,一般在配置好后就不会再变动的参数,如 **api_key**、**server_url** 等。在 DifyRuntime 中,他们的参数名一般为**credentials: dict[str, any]**Provider 层的 credentials 会直接被传递到这一层,不需要再单独定义。
## 下一步
## 文档
### [增加新供应商配置 👈🏻](./docs/zh_Hans/provider_scale_out.md)
当添加后,这里将会出现一个新的供应商
![Alt text](docs/zh_Hans/images/index/image-1.png)
### [为已存在的供应商新增模型 👈🏻](./docs/zh_Hans/provider_scale_out.md#%E5%A2%9E%E5%8A%A0%E6%A8%A1%E5%9E%8B)
当添加后,对应供应商的模型列表中将会出现一个新的预定义模型供用户选择,如 GPT-3.5 GPT-4 ChatGLM3-6b 等,而对于支持自定义模型的供应商,则不需要新增模型。
![Alt text](docs/zh_Hans/images/index/image-2.png)
### [接口的具体实现 👈🏻](./docs/zh_Hans/interfaces.md)
你可以在这里找到你想要查看的接口的具体实现,以及接口的参数和返回值的具体含义。
有关如何添加新供应商或模型的详细文档,请参阅 [Dify 文档](https://docs.dify.ai/)。