confident-ai--deepeval
wehub-resource-sync
76 行
2.1 KiB
Python
76 行
2.1 KiB
Python
from deepeval.confident.api import Api, Endpoints, HttpMethods
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from deepeval.tracing.context import current_trace_context
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from deepeval.tracing.offline_evals.api import EvaluateThreadRequestBody
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def evaluate_thread(
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thread_id: str,
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metric_collection: str,
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overwrite_metrics: bool = False,
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chatbot_role: str = None,
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):
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trace = current_trace_context.get()
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api_key = None
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if trace:
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api_key = trace.confident_api_key
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api = Api(api_key=api_key)
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evaluate_thread_request_body = EvaluateThreadRequestBody(
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metricCollection=metric_collection,
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overwriteMetrics=overwrite_metrics,
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chatbotRole=chatbot_role,
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)
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try:
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body = evaluate_thread_request_body.model_dump(
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by_alias=True,
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exclude_none=True,
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)
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except AttributeError:
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# Pydantic version below 2.0
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body = evaluate_thread_request_body.dict(
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by_alias=True, exclude_none=True
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)
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api.send_request(
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method=HttpMethods.POST,
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endpoint=Endpoints.EVALUATE_THREAD_ENDPOINT,
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body=body,
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url_params={"threadId": thread_id},
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)
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async def a_evaluate_thread(
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thread_id: str,
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metric_collection: str,
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overwrite_metrics: bool = False,
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chatbot_role: str = None,
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):
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trace = current_trace_context.get()
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api_key = None
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if trace:
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api_key = trace.confident_api_key
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api = Api(api_key=api_key)
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evaluate_thread_request_body = EvaluateThreadRequestBody(
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metricCollection=metric_collection,
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overwriteMetrics=overwrite_metrics,
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chatbotRole=chatbot_role,
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)
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try:
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body = evaluate_thread_request_body.model_dump(
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by_alias=True,
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exclude_none=True,
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)
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except AttributeError:
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# Pydantic version below 2.0
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body = evaluate_thread_request_body.dict(
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by_alias=True, exclude_none=True
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)
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await api.a_send_request(
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method=HttpMethods.POST,
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endpoint=Endpoints.EVALUATE_THREAD_ENDPOINT,
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body=body,
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url_params={"threadId": thread_id},
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)
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