From 62b885afaeb6a219bc8a671f5a96b00646c95ff2 Mon Sep 17 00:00:00 2001
From: vitor-aignosi <vitor.santos@aignosi.com.br>
Date: Mon, 23 Mar 2026 09:26:49 -0300
Subject: [PATCH] SIENTIAPDE-1712  SIENTIAPDE-1712 Add last_timestamp parameter
 to MLFlow and Gates activities for enhanced tracking

- Introduced last_timestamp parameter in the MLFlow and Gates classes to improve tracking of data processing times.
- Updated MinioDataFramePayload to handle last_timestamp, ensuring it defaults to the maximum timestamp from the dataframe if not provided.
---
 laborious/activities/gates.py                     | 3 ++-
 laborious/activities/mlflow.py                    | 4 ++++
 laborious/utils/models/minio_dataframe_payload.py | 5 ++++-
 3 files changed, 10 insertions(+), 2 deletions(-)

diff --git a/laborious/activities/gates.py b/laborious/activities/gates.py
index 0b747f9..f9eeb16 100644
--- a/laborious/activities/gates.py
+++ b/laborious/activities/gates.py
@@ -479,7 +479,8 @@ class Gates(MinioManager):
             minio_repo=self.minio_repository,
             model_name=input_data['model_name'],
             operation='transform',
-            workflow_metadata=metadata
+            workflow_metadata=metadata,
+            last_timestamp=payload.last_timestamp,
         )
 
     @activity.defn(name='format_prediction')
diff --git a/laborious/activities/mlflow.py b/laborious/activities/mlflow.py
index e6522f0..ea97f3b 100644
--- a/laborious/activities/mlflow.py
+++ b/laborious/activities/mlflow.py
@@ -178,6 +178,7 @@ class MLFlow(MinioManager):
                 operation='transform',
                 status=response_data,
                 workflow_metadata=metadata,
+                last_timestamp=payload.last_timestamp,
             )
 
         return await MinioDataFramePayload.from_dataframe(
@@ -189,6 +190,7 @@ class MLFlow(MinioManager):
             status={
                 'success': True,
             },
+            last_timestamp=payload.last_timestamp,
         )
 
     @activity.defn(name='request_predict')
@@ -260,6 +262,7 @@ class MLFlow(MinioManager):
                 operation='predict',
                 status=response_data,
                 workflow_metadata=metadata,
+                last_timestamp=payload.last_timestamp,
             )
 
         return await MinioDataFramePayload.from_dataframe(
@@ -271,6 +274,7 @@ class MLFlow(MinioManager):
             status={
                 'success': True,
             },
+            last_timestamp=payload.last_timestamp,
         )
 
     @activity.defn(name='retrain_model')
diff --git a/laborious/utils/models/minio_dataframe_payload.py b/laborious/utils/models/minio_dataframe_payload.py
index c49218d..7e0d865 100644
--- a/laborious/utils/models/minio_dataframe_payload.py
+++ b/laborious/utils/models/minio_dataframe_payload.py
@@ -173,6 +173,7 @@ class MinioDataFramePayload:
         operation: OperationKind,
         status: dict[str, Any] | None = None,
         workflow_metadata: dict | None = None,
+        last_timestamp: str | None = None,
     ) -> 'MinioDataFramePayload':
         """
         Evaluate the DataFrame size, then either inline dict or upload parquet to MinIO.
@@ -199,7 +200,9 @@ class MinioDataFramePayload:
                 data=None, last_timestamp=now().strftime(DATETIME_FORMAT_WITH_TZ), status=status
             )
 
-        last_timestamp = max(dataframe['timestamp'].values.tolist())
+
+        if last_timestamp is None:
+            last_timestamp = max(dataframe['timestamp'].values.tolist())
 
         if cls.estimate_size_bytes(dataframe) <= OFFLOAD_THRESHOLD_BYTES:
             return cls(data=dataframe.to_dict(), last_timestamp=last_timestamp)