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260 lines
11 KiB
Markdown
260 lines
11 KiB
Markdown
---
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title: AI Statistics
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keywords: [higress, AI, observability]
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description: AI Statistics plugin configuration reference
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---
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## Introduction
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Provides basic AI observability capabilities, including metric, log, and trace. The ai-proxy plug-in needs to be connected afterwards. If the ai-proxy plug-in is not connected, the user needs to configure it accordingly to take effect.
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## Runtime Properties
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Plugin Phase: `CUSTOM`
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Plugin Priority: `200`
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## Configuration instructions
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The default request of the plug-in conforms to the openai protocol format and provides the following basic observable values. Users do not need special configuration:
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- metric: It provides indicators such as input token, output token, rt of the first token (streaming request), total request rt, etc., and supports observation in the four dimensions of gateway, routing, service, and model.
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- log: Provides input_token, output_token, model, llm_service_duration, llm_first_token_duration and other fields
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Users can also expand observable values through configuration:
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| Name | Type | Required | Default | Description |
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|----------------|-------|------|-----|------------------------|
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| `attributes` | []Attribute | optional | - | Information that the user wants to record in log/span |
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| `disable_openai_usage` | bool | optional | false | When using a non-OpenAI-compatible protocol, the support for model and token is non-standard. Setting the configuration to true can prevent errors. |
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| `value_length_limit` | int | optional | 4000 | length limit for each value |
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| `enable_path_suffixes` | []string | optional | ["/v1/chat/completions","/v1/completions","/v1/embeddings","/v1/models","/generateContent","/streamGenerateContent"] | Only effective for requests with these specific path suffixes, can be configured as "\*" to match all paths |
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| `enable_content_types` | []string | optional | ["text/event-stream","application/json"] | Only buffer response body for these content types |
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Attribute Configuration instructions:
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| Name | Type | Required | Default | Description |
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| ----------------------- | ------ | -------- | ------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
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| `key` | string | required | - | attribute key |
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| `value_source` | string | required | - | attribute value source, optional values are `fixed_value`, `request_header`, `request_body`, `response_header`, `response_body`, `response_streaming_body` |
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| `value` | string | required | - | how to get attribute value |
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| `default_value` | string | optional | - | default value for attribute |
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| `rule` | string | optional | - | Rule to extract attribute from streaming response, optional values are `first`, `replace`, `append` |
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| `apply_to_log` | bool | optional | false | Whether to record the extracted information in the log |
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| `apply_to_span` | bool | optional | false | Whether to record the extracted information in the link tracking span |
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| `trace_span_key` | string | optional | - | span attribute key, default is the value of `key` |
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| `as_separate_log_field` | bool | optional | false | Whether to use a separate log field, the field name is equal to the value of `key` |
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The meanings of various values for `value_source` are as follows:
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- `fixed_value`: fixed value
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- `request_header`: The attribute is obtained through the http request header
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- `request_body`: The attribute is obtained through the http request body
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- `response_header`: The attribute is obtained through the http response header
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- `response_body`: The attribute is obtained through the http response body
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- `response_streaming_body`: The attribute is obtained through the http streaming response body
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When `value_source` is `response_streaming_body`, `rule` should be configured to specify how to obtain the specified value from the streaming body. The meaning of the value is as follows:
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- `first`: extract value from the first valid chunk
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- `replace`: extract value from the last valid chunk
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- `append`: join value pieces from all valid chunks
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## Configuration example
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If you want to record ai-statistic related statistical values in the gateway access log, you need to modify log_format and add a new field based on the original log_format. The example is as follows:
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```yaml
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'{"ai_log":"%FILTER_STATE(wasm.ai_log:PLAIN)%"}'
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```
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If the field is set with `as_separate_log_field`, for example:
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```yaml
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attributes:
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- key: consumer
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value_source: request_header
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value: x-mse-consumer
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apply_to_log: true
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as_separate_log_field: true
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```
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Then to print in the log, you need to set log_format additionally:
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```
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'{"consumer":"%FILTER_STATE(wasm.consumer:PLAIN)%"}'
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```
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### Empty
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#### Metric
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```
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# counter, cumulative count of input tokens
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route_upstream_model_consumer_metric_input_token{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 24
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# counter, cumulative count of output tokens
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route_upstream_model_consumer_metric_output_token{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 507
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# counter, cumulative total duration of both streaming and non-streaming requests
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route_upstream_model_consumer_metric_llm_service_duration{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 6470
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# counter, cumulative count of both streaming and non-streaming requests
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route_upstream_model_consumer_metric_llm_duration_count{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 2
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# counter, cumulative latency of the first token in streaming requests
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route_upstream_model_consumer_metric_llm_first_token_duration{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 340
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# counter, cumulative count of streaming requests
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route_upstream_model_consumer_metric_llm_stream_duration_count{ai_route="ai-route-aliyun.internal",ai_cluster="outbound|443||llm-aliyun.internal.dns",ai_model="qwen-turbo",ai_consumer="none"} 1
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```
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Below are some example usages of these metrics:
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Average latency of the first token in streaming requests:
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```
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irate(route_upstream_model_consumer_metric_llm_first_token_duration[2m])
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/
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irate(route_upstream_model_consumer_metric_llm_stream_duration_count[2m])
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```
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Average process duration of both streaming and non-streaming requests:
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```
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irate(route_upstream_model_consumer_metric_llm_service_duration[2m])
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/
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irate(route_upstream_model_consumer_metric_llm_duration_count[2m])
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```
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#### Log
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```json
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{
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"ai_log": "{\"model\":\"qwen-turbo\",\"input_token\":\"10\",\"output_token\":\"69\",\"llm_first_token_duration\":\"309\",\"llm_service_duration\":\"1955\"}"
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}
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```
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#### Trace
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When the configuration is empty, no additional attributes will be added to the span.
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### Extract token usage information from non-openai protocols
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When setting the protocol to original in ai-proxy, taking Alibaba Cloud Bailian as an example, you can make the following configuration to specify how to extract `model`, `input_token`, `output_token`
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```yaml
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attributes:
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- key: model
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value_source: response_body
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value: usage.models.0.model_id
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apply_to_log: true
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apply_to_span: false
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- key: input_token
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value_source: response_body
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value: usage.models.0.input_tokens
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apply_to_log: true
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apply_to_span: false
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- key: output_token
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value_source: response_body
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value: usage.models.0.output_tokens
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apply_to_log: true
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apply_to_span: false
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```
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#### Metric
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```
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route_upstream_model_consumer_metric_input_token{ai_route="bailian",ai_cluster="qwen",ai_model="qwen-max"} 343
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route_upstream_model_consumer_metric_output_token{ai_route="bailian",ai_cluster="qwen",ai_model="qwen-max"} 153
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route_upstream_model_consumer_metric_llm_service_duration{ai_route="bailian",ai_cluster="qwen",ai_model="qwen-max"} 3725
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route_upstream_model_consumer_metric_llm_duration_count{ai_route="bailian",ai_cluster="qwen",ai_model="qwen-max"} 1
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```
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#### Log
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```json
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{
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"ai_log": "{\"model\":\"qwen-max\",\"input_token\":\"343\",\"output_token\":\"153\",\"llm_service_duration\":\"19110\"}"
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}
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```
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#### Trace
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Three additional attributes `model`, `input_token`, and `output_token` can be seen in the trace spans.
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### Cooperate with authentication and authentication record consumer
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```yaml
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attributes:
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- key: consumer
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value_source: request_header
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value: x-mse-consumer
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apply_to_log: true
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```
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### Record questions and answers
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```yaml
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attributes:
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- key: question
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value_source: request_body
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value: messages.@reverse.0.content
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apply_to_log: true
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- key: answer
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value_source: response_streaming_body
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value: choices.0.delta.content
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rule: append
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apply_to_log: true
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- key: answer
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value_source: response_body
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value: choices.0.message.content
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apply_to_log: true
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```
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### Path and Content Type Filtering Configuration Examples
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#### Process Only Specific AI Paths
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```yaml
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enable_path_suffixes:
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- "/v1/chat/completions"
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- "/v1/embeddings"
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- "/generateContent"
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```
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#### Process Only Specific Content Types
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```yaml
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enable_content_types:
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- "text/event-stream"
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- "application/json"
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```
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#### Process All Paths (Wildcard)
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```yaml
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enable_path_suffixes:
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- "*"
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```
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#### Complete Configuration Example
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```yaml
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enable_path_suffixes:
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- "/v1/chat/completions"
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- "/v1/embeddings"
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- "/generateContent"
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enable_content_types:
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- "text/event-stream"
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- "application/json"
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attributes:
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- key: model
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value_source: request_body
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value: model
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apply_to_log: true
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- key: consumer
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value_source: request_header
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value: x-mse-consumer
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apply_to_log: true
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```
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