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Enhance debug logging in MLFlowRepository to improve data traceability

- Added a debug logging statement to capture received data for model prediction, improving visibility into input data.
- Changed an existing info logging statement to debug level for consistency, ensuring all relevant data is logged at the appropriate level.
This commit is contained in:
vitor-aignosi
2025-09-16 11:54:35 -03:00
parent 74f7e6c024
commit b1951ea2c0
1 changed files with 4 additions and 1 deletions
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5
laborious/utils/repository/model_repository.py
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@@ -84,6 +84,9 @@ class MLFlowRepository():
input_index = data.index input_index = data.index
start_time = datetime.now() start_time = datetime.now()
self.logger.debug(
f"Data received for model prediction: {data.to_string()}")
data = self.model_serving.get_cached_predict( data = self.model_serving.get_cached_predict(
model_name, data, model_retention, flavor, model_name, data, model_retention, flavor,
compressed, retention_target compressed, retention_target
@@ -91,7 +94,7 @@ class MLFlowRepository():
end_time = datetime.now() end_time = datetime.now()
data = pd.DataFrame(data, columns=['prediction']) data = pd.DataFrame(data, columns=['prediction'])
self.logger.info( self.logger.debug(
f"Data received from model prediction: {data.to_string()}") f"Data received from model prediction: {data.to_string()}")
data.index = input_index data.index = input_index
data['response_time'] = (end_time - start_time).total_seconds() data['response_time'] = (end_time - start_time).total_seconds()