feat: Add samples for the Tuning API reference doc (#11631)

* Add samples for the Tuning API reference doc: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning#python
---------

Co-authored-by: Holt Skinner <[email protected]>
Co-authored-by: Owl Bot <gcf-owl-bot[bot]@users.noreply.github.com>

Author: 3 people

generative_ai/gemini_tuning.py

@@ -0,0 +1,117 @@
+# Copyright 2024 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 typing import List
+
+from vertexai.preview.tuning import sft
+
+
+def gemini_supervised_tuning(project_id: str) -> sft.SupervisedTuningJob:
+    # [START generativeaionvertexai_supervised_tuning]
+
+    import time
+    import vertexai
+    from vertexai.preview.tuning import sft
+
+    # TODO(developer): Update and un-comment below lines
+    # project_id = "PROJECT_ID"
+
+    vertexai.init(project=project_id, location="us-central1")
+
+    sft_tuning_job = sft.train(
+        source_model="gemini-1.0-pro-002",
+        train_dataset="gs://cloud-samples-data/ai-platform/generative_ai/sft_train_data.jsonl",
+        # The following parameters are optional
+        validation_dataset="gs://cloud-samples-data/ai-platform/generative_ai/sft_validation_data.jsonl",
+        epochs=4,
+        learning_rate_multiplier=1.0,
+        tuned_model_display_name="tuned_gemini_pro",
+    )
+
+    # Polling for job completion
+    while not sft_tuning_job.has_ended:
+        time.sleep(60)
+        sft_tuning_job.refresh()
+
+    print(sft_tuning_job.tuned_model_name)
+    print(sft_tuning_job.tuned_model_endpoint_name)
+    print(sft_tuning_job.experiment)
+    # [END generativeaionvertexai_supervised_tuning]
+
+    return sft_tuning_job
+
+
+def get_supervised_tuning_job(
+    project_id: str, location: str, tuning_job_id: str
+) -> sft.SupervisedTuningJob:
+    # [START generativeaionvertexai_get_supervised_tuning_job]
+    import vertexai
+    from vertexai.preview.tuning import sft
+
+    # TODO(developer): Update and un-comment below lines
+    # project_id = "PROJECT_ID"
+    # location = "us-central1"
+    # tuning_job_id = "TUNING_JOB_ID"
+
+    vertexai.init(project=project_id, location="us-central1")
+
+    response = sft.SupervisedTuningJob(
+        f"projects/{project_id}/locations/{location}/tuningJobs/{tuning_job_id}"
+    )
+
+    print(response)
+    # [END generativeaionvertexai_get_supervised_tuning_job]
+
+    return response
+
+
+def list_supervised_tuning_jobs(project_id: str) -> List[sft.SupervisedTuningJob]:
+    # [START generativeaionvertexai_list_supervised_tuning_jobs]
+    import vertexai
+    from vertexai.preview.tuning import sft
+
+    # TODO(developer): Update and un-comment below lines
+    # project_id = "PROJECT_ID"
+
+    vertexai.init(project=project_id, location="us-central1")
+
+    responses = sft.SupervisedTuningJob.list()
+
+    for response in responses:
+        print(response)
+    # [END generativeaionvertexai_list_supervised_tuning_jobs]
+
+    return responses
+
+
+def cancel_supervised_tuning_job(
+    project_id: str, location: str, tuning_job_id: str
+) -> None:
+    # [START generativeaionvertexai_cancel_supervised_tuning_job]
+    import vertexai
+    from vertexai.preview.tuning import sft
+
+    # TODO(developer): Update and un-comment below lines
+    # project_id = "PROJECT_ID"
+    # location = "us-central1"
+    # tuning_job_id = "TUNING_JOB_ID"
+
+    vertexai.init(project=project_id, location="us-central1")
+
+    job = sft.SupervisedTuningJob(
+        f"projects/{project_id}/locations/{location}/tuningJobs/{tuning_job_id}"
+    )
+    job.cancel()
+
+    # [END generativeaionvertexai_cancel_supervised_tuning_job]

generative_ai/gemini_tuning_test.py

@@ -0,0 +1,47 @@
+# Copyright 2024 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.
+
+import os
+
+import pytest
+
+import gemini_tuning
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+REGION = "us-central1"
+MODEL_ID = "gemini-1.5-pro-preview-0409"
+TUNING_JOB_ID = "4982013113894174720"
+
+
+@pytest.mark.skip(reason="Skip due to tuning taking a long time.")
+def test_supervised_tuning() -> None:
+    response = gemini_tuning.gemini_supervised_tuning(PROJECT_ID)
+    assert response
+
+
+def test_get_supervised_tuning_job() -> None:
+    response = gemini_tuning.get_supervised_tuning_job(
+        PROJECT_ID, REGION, TUNING_JOB_ID
+    )
+    assert response
+
+
+def test_list_supervised_tuning_jobs() -> None:
+    response = gemini_tuning.list_supervised_tuning_jobs(PROJECT_ID)
+    assert response
+
+
+@pytest.mark.skip(reason="Skip due to tuning taking a long time.")
+def test_cancel_supervised_tuning_job() -> None:
+    gemini_tuning.cancel_supervised_tuning_job(PROJECT_ID, REGION, TUNING_JOB_ID)