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higress/plugins/wasm-cpp/extensions/model_router/README_EN.md
2024-10-21 16:46:18 +08:00

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## Function Description
The `model-router` plugin implements the functionality of routing based on the `model` parameter in the LLM protocol.
## Runtime Properties
Plugin Execution Phase: `Default Phase`
Plugin Execution Priority: `260`
## Configuration Fields
| Name | Data Type | Filling Requirement | Default Value | Description |
| -------------------- | ------------- | --------------------- | ---------------------- | ----------------------------------------------------- |
| `enable` | bool | Optional | false | Whether to enable routing based on the `model` parameter |
| `model_key` | string | Optional | model | The location of the `model` parameter in the request body |
| `add_header_key` | string | Optional | x-higress-llm-provider | The header where the parsed provider name from the `model` parameter will be placed |
## Effect Description
To enable routing based on the `model` parameter, use the following configuration:
```yaml
enable: true
```
After enabling, the plugin extracts the provider part (if any) from the `model` parameter in the request, and sets it in the `x-higress-llm-provider` request header for subsequent routing. It also rewrites the `model` parameter to the model name part. For example, the original LLM request body is:
```json
{
"model": "openai/gpt-4o",
"frequency_penalty": 0,
"max_tokens": 800,
"stream": false,
"messages": [{
"role": "user",
"content": "What is the GitHub address for the main repository of the Higress project?"
}],
"presence_penalty": 0,
"temperature": 0.7,
"top_p": 0.95
}
```
After processing by the plugin, the following request header (which can be used for routing matching) will be added:
`x-higress-llm-provider: openai`
The original LLM request body will be modified to:
```json
{
"model": "gpt-4o",
"frequency_penalty": 0,
"max_tokens": 800,
"stream": false,
"messages": [{
"role": "user",
"content": "What is the GitHub address for the main repository of the Higress project?"
}],
"presence_penalty": 0,
"temperature": 0.7,
"top_p": 0.95
}
```