feat(batch predition): Adds get_batch_prediction_job.py code sample (#13512)

* Adds get_batch_prediction_job.py code sample

* Adds test_batch prediction_job.

* Fixes lint and formatting errors.

* Fixes errors in test file

* Updates method definition.

* Fix lint errors

Author: br1mendez

genai/batch_prediction/get_batch_job.py

@@ -0,0 +1,43 @@
+# Copyright 2025 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from google.genai import types
+
+
+def get_batch_job(batch_job_name: str) -> types.BatchJob:
+    # [START googlegenaisdk_batch_job_get]
+    from google import genai
+    from google.genai.types import HttpOptions
+
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
+
+    # Get the batch job
+    # Eg. batch_job_name = "projects/123456789012/locations/us-central1/batchPredictionJobs/1234567890123456789"
+    batch_job = client.batches.get(name=batch_job_name)
+
+    print(f"Job state: {batch_job.state}")
+    # Example response:
+    # Job state: JOB_STATE_PENDING
+    # Job state: JOB_STATE_RUNNING
+    # Job state: JOB_STATE_SUCCEEDED
+
+    # [END googlegenaisdk_batch_job_get]
+    return batch_job
+
+
+if __name__ == "__main__":
+    try:
+        get_batch_job(input("Batch job name: "))
+    except Exception as e:
+        print(f"An error occurred: {e}")

genai/batch_prediction/test_batch_prediction_examples.py

@@ -15,19 +15,20 @@
 #
 # Using Google Cloud Vertex AI to test the code samples.
 #
-
 from datetime import datetime as dt
-
 import os
 
+from unittest.mock import MagicMock, patch
+
 from google.cloud import bigquery, storage
+from google.genai import types
 from google.genai.types import JobState
-
 import pytest
 
 import batchpredict_embeddings_with_gcs
 import batchpredict_with_bq
 import batchpredict_with_gcs
+import get_batch_job
 
 
 os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "True"
@@ -77,3 +78,20 @@ def test_batch_prediction_with_bq(bq_output_uri: str) -> None:
 def test_batch_prediction_with_gcs(gcs_output_uri: str) -> None:
     response = batchpredict_with_gcs.generate_content(output_uri=gcs_output_uri)
     assert response == JobState.JOB_STATE_SUCCEEDED
+
+
+@patch("google.genai.Client")
+def test_get_batch_job(mock_genai_client: MagicMock) -> None:
+    # Mock the API response
+    mock_batch_job = types.BatchJob(
+        name="test-batch-job",
+        state="JOB_STATE_PENDING"
+    )
+
+    mock_genai_client.return_value.batches.get.return_value = mock_batch_job
+
+    response = get_batch_job.get_batch_job("test-batch-job")
+
+    mock_genai_client.assert_called_once_with(http_options=types.HttpOptions(api_version="v1"))
+    mock_genai_client.return_value.batches.get.assert_called_once()
+    assert response == mock_batch_job