SIENTIAPDE-994

Refactor logging in MLFlow and Gates activities; remove print statement in FormatAndExportPrediction; update data handling in PredictionProcess; delete unused redis-feeder script.
This commit is contained in:
vitor-aignosi
2025-05-27 16:49:31 -03:00
parent 35c552e04f
commit 6f81ce7d03
6 changed files with 19 additions and 65 deletions

View File

@@ -73,7 +73,7 @@ class Gates(BaseActivity):
filter_output = []
self.logger.debug(f"Input data:\n {data.to_string()}")
self.logger.debug(f"Input data:\n {data}")
self.logger.debug(f"Filters: {filters}")
for fil, config in filters.items():

View File

@@ -41,6 +41,7 @@ class MLFlow(BaseActivity):
model_name = input_data['model_name']
model_retention = input_data['model_retention']
self.logger.debug("Raw input data:")
self.logger.debug(data)
data = data.pivot(
@@ -50,9 +51,13 @@ class MLFlow(BaseActivity):
data.reset_index(inplace=True)
data.columns.name = None
self.logger.debug("Processed input data:")
self.logger.debug(data)
response_data = self.model_monitoring_repository.transform(
model_name, data, model_retention)
self.logger.debug("Response data:")
self.logger.debug(response_data)
return response_data

View File

@@ -13,7 +13,6 @@ import traceback
import mlflow
import pandas as pd
from sientia.ModelServing import ModelServing
from pathlib import Path
class MLFlowRepository():
@@ -260,7 +259,8 @@ class MLFlowRepository():
try:
return {
'success': True,
'content': self.model_serving.get_cached_transform(model_name, data, model_retention).to_dict()
'content': self.model_serving.get_cached_transform(
model_name, data, model_retention).to_dict()
}
except Exception as e:
@@ -276,7 +276,8 @@ class MLFlowRepository():
try:
start_time = datetime.now()
data = self.model_serving.get_cached_predict(
model_name, data, model_retention)
model_name, data, model_retention)[-1:]
end_time = datetime.now()
data = pd.DataFrame(data, columns=['prediction'])
data['response_time'] = (end_time - start_time).total_seconds()

View File

@@ -40,8 +40,6 @@ class FormatAndExportPrediction():
data = input_data['data']
prediction_confidence = input_data['prediction_confidence']
print(f"Input data: {input_data}")
if path_flag is None:
# proceed with formatting and exporting
prediction = await workflow.execute_local_activity_method(

View File

@@ -97,11 +97,13 @@ class PredictionProcess():
):
return
transformed_data = response_data['content']
path_flag, confidence, comment = await workflow.execute_local_activity_method(
Activities.mlflow_content_gate,
{
'filters': input_data['mlflow_transform_filters'],
'data': response_data,
'data': transformed_data,
'type': 'transform',
'path_priority': input_data['path_priority']
},
@@ -117,7 +119,7 @@ class PredictionProcess():
response_data = await workflow.execute_local_activity_method(
Activities.request_predict,
{
'data': response_data,
'data': transformed_data,
'model_name': model_name,
'model_retention': model_retention
},
@@ -148,11 +150,14 @@ class PredictionProcess():
'path_flag': path_flag,
'data': response_data['content'],
'prediction_confidence': confidence,
'timestamp': response_data['timestamp'],
'timestamp': last_timestamp,
'model_id': model_id,
'model_name': model_name,
'model_retention': model_retention,
'opc_output_config': input_data['opc_output_config']
'opc_output_config': input_data['opc_output_config'],
'schema': input_data['schema'],
'table_name': input_data['table_name'],
'comment': comment
}
)