Spaces:
Sleeping
Sleeping
| from aworld.metrics.context_manager import MetricContext | |
| from aworld.metrics.template import MetricTemplate | |
| from aworld.metrics.metric import MetricType | |
| tokens_usage_histogram = MetricTemplate( | |
| type=MetricType.HISTOGRAM, | |
| name="llm_token_usage", | |
| unit="token", | |
| description="Measures number of input and output tokens used" | |
| ) | |
| chat_choice_counter = MetricTemplate( | |
| type=MetricType.COUNTER, | |
| name="llm_generation_choice_counter", | |
| unit="choice", | |
| description="Number of choices returned by chat completions call" | |
| ) | |
| duration_histogram = MetricTemplate( | |
| type=MetricType.HISTOGRAM, | |
| name="llm_chat_duration", | |
| unit="s", | |
| description="AI chat duration", | |
| ) | |
| chat_exception_counter = MetricTemplate( | |
| type=MetricType.COUNTER, | |
| name="llm_chat_exception_counter", | |
| unit="time", | |
| description="Number of exceptions occurred during chat completions", | |
| ) | |
| streaming_time_to_first_token_histogram = MetricTemplate( | |
| type=MetricType.HISTOGRAM, | |
| name="llm_streaming_time_to_first_token", | |
| unit="s", | |
| description="Time to first token in streaming chat completions", | |
| ) | |
| streaming_time_to_generate_histogram = MetricTemplate( | |
| type=MetricType.HISTOGRAM, | |
| name="streaming_time_to_generate", | |
| unit="s", | |
| description="Time between first token and completion in streaming chat completions", | |
| ) | |
| def record_exception_metric(exception, duration): | |
| ''' | |
| record chat exception to metrics | |
| ''' | |
| if MetricContext.metric_initialized(): | |
| labels = { | |
| "error.type": exception.__class__.__name__, | |
| } | |
| if duration_histogram: | |
| MetricContext.histogram_record( | |
| duration_histogram, duration, labels=labels) | |
| if chat_exception_counter: | |
| MetricContext.count( | |
| chat_exception_counter, 1, labels=labels) | |
| def record_streaming_time_to_first_token(duration, labels): | |
| ''' | |
| Record duration of start time to first token in stream. | |
| ''' | |
| if MetricContext.metric_initialized(): | |
| MetricContext.histogram_record( | |
| streaming_time_to_first_token_histogram, duration, labels=labels) | |
| def record_streaming_time_to_generate(first_token_to_generate_duration, labels): | |
| ''' | |
| Record duration the first token to response to generation | |
| ''' | |
| if MetricContext.metric_initialized(): | |
| MetricContext.histogram_record( | |
| streaming_time_to_generate_histogram, first_token_to_generate_duration, labels=labels) | |
| def record_chat_response_metric(attributes, | |
| prompt_tokens, | |
| completion_tokens, | |
| duration, | |
| choices=None | |
| ): | |
| ''' | |
| Record chat response to metrics | |
| ''' | |
| if MetricContext.metric_initialized(): | |
| if prompt_tokens and tokens_usage_histogram: | |
| labels = { | |
| **attributes, | |
| "llm.prompt_usage_type": "prompt_tokens" | |
| } | |
| MetricContext.histogram_record( | |
| tokens_usage_histogram, prompt_tokens, labels=labels) | |
| if completion_tokens and tokens_usage_histogram: | |
| labels = { | |
| **attributes, | |
| "llm.prompt_usage_type": "completion_tokens" | |
| } | |
| MetricContext.histogram_record( | |
| tokens_usage_histogram, completion_tokens, labels=labels) | |
| if duration and duration_histogram: | |
| MetricContext.histogram_record( | |
| duration_histogram, duration, labels=attributes) | |
| if choices and chat_choice_counter: | |
| MetricContext.count(chat_choice_counter, | |
| len(choices), labels=attributes) | |
| for choice in choices: | |
| if choice.get("finish_reason"): | |
| finish_reason_attr = { | |
| **attributes, | |
| "llm.finish_reason": choice.get("finish_reason") | |
| } | |
| MetricContext.count( | |
| chat_choice_counter, 1, labels=finish_reason_attr) | |