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yishan-puYishan Pumsampathkumar
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feat(genai): Add tuning examples (#13360)
* feat(genai): Add tuning examples * fix(genai): fix tuning examples test issues - Updates tuning file names to fix cicd - word `test` is reserved for test files - Update region tag and file names. - add word `job` to filenames & region tags * feat: update test file - rename methods and function according to prior changes --------- Co-authored-by: Yishan Pu <yishanpu@google.com> Co-authored-by: Sampath Kumar <sam1990kumar@gmail.com>
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‎genai/tuning/noxfile_config.py‎

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# Copyright 2021 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Default TEST_CONFIG_OVERRIDE for python repos.
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# You can copy this file into your directory, then it will be imported from
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# the noxfile.py.
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# The source of truth:
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# https://github.com/GoogleCloudPlatform/python-docs-samples/blob/main/noxfile_config.py
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TEST_CONFIG_OVERRIDE = {
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# You can opt out from the test for specific Python versions.
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"ignored_versions": ["2.7", "3.7", "3.8", "3.10", "3.11", "3.12"],
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# Old samples are opted out of enforcing Python type hints
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# All new samples should feature them
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"enforce_type_hints": True,
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# An envvar key for determining the project id to use. Change it
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# to 'BUILD_SPECIFIC_GCLOUD_PROJECT' if you want to opt in using a
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# build specific Cloud project. You can also use your own string
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# to use your own Cloud project.
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"gcloud_project_env": "GOOGLE_CLOUD_PROJECT",
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# 'gcloud_project_env': 'BUILD_SPECIFIC_GCLOUD_PROJECT',
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# If you need to use a specific version of pip,
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# change pip_version_override to the string representation
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# of the version number, for example, "20.2.4"
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"pip_version_override": None,
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# A dictionary you want to inject into your test. Don't put any
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# secrets here. These values will override predefined values.
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"envs": {},
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}

‎genai/tuning/requirements-test.txt‎

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google-api-core==2.24.0
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google-cloud-storage==2.19.0
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pytest==8.2.0

‎genai/tuning/requirements.txt‎

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google-genai==1.7.0

‎genai/tuning/test_tuning_examples.py‎

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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from unittest.mock import MagicMock, patch
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from google.genai import types
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import tuning_job_create
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import tuning_job_get
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import tuning_job_list
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import tuning_textgen_with_txt
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@patch("google.genai.Client")
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def test_tuning_job_create(mock_genai_client: MagicMock) -> None:
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# Mock the API response
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mock_tuning_job = types.TuningJob(
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name="test-tuning-job",
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experiment="test-experiment",
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tuned_model=types.TunedModel(
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model="test-model",
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endpoint="test-endpoint"
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)
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)
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mock_genai_client.return_value.tunings.tune.return_value = mock_tuning_job
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response = tuning_job_create.create_tuning_job()
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mock_genai_client.assert_called_once_with(http_options=types.HttpOptions(api_version="v1"))
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mock_genai_client.return_value.tunings.tune.assert_called_once()
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assert response == "test-tuning-job"
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@patch("google.genai.Client")
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def test_tuning_job_get(mock_genai_client: MagicMock) -> None:
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# Mock the API response
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mock_tuning_job = types.TuningJob(
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name="test-tuning-job",
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experiment="test-experiment",
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tuned_model=types.TunedModel(
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model="test-model",
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endpoint="test-endpoint"
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)
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)
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mock_genai_client.return_value.tunings.get.return_value = mock_tuning_job
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response = tuning_job_get.get_tuning_job("test-tuning-job")
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mock_genai_client.assert_called_once_with(http_options=types.HttpOptions(api_version="v1"))
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mock_genai_client.return_value.tunings.get.assert_called_once()
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assert response == "test-tuning-job"
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@patch("google.genai.Client")
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def test_tuning_job_list(mock_genai_client: MagicMock) -> None:
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# Mock the API response
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mock_tuning_job = types.TuningJob(
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name="test-tuning-job",
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experiment="test-experiment",
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tuned_model=types.TunedModel(
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model="test-model",
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endpoint="test-endpoint"
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)
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)
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mock_genai_client.return_value.tunings.list.return_value = [mock_tuning_job]
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tuning_job_list.list_tuning_jobs()
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mock_genai_client.assert_called_once_with(http_options=types.HttpOptions(api_version="v1"))
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mock_genai_client.return_value.tunings.list.assert_called_once()
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@patch("google.genai.Client")
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def test_tuning_textgen_with_txt(mock_genai_client: MagicMock) -> None:
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# Mock the API response
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mock_tuning_job = types.TuningJob(
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name="test-tuning-job",
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experiment="test-experiment",
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tuned_model=types.TunedModel(
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model="test-model",
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endpoint="test-endpoint"
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)
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)
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mock_response = types.GenerateContentResponse._from_response( # pylint: disable=protected-access
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response={
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"candidates": [
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{
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"content": {
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"parts": [{"text": "This is a mocked answer."}]
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}
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}
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]
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},
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kwargs={},
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)
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mock_genai_client.return_value.tunings.get.return_value = mock_tuning_job
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mock_genai_client.return_value.models.generate_content.return_value = mock_response
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tuning_textgen_with_txt.test_tuned_endpoint("test-tuning-job")
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mock_genai_client.assert_called_once_with(http_options=types.HttpOptions(api_version="v1"))
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mock_genai_client.return_value.tunings.get.assert_called_once()
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mock_genai_client.return_value.models.generate_content.assert_called_once()

‎genai/tuning/tuning_job_create.py‎

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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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def create_tuning_job() -> str:
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# [START googlegenaisdk_tuning_job_create]
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import time
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from google import genai
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from google.genai.types import HttpOptions, CreateTuningJobConfig
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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tuning_job = client.tunings.tune(
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base_model="gemini-2.0-flash-lite-001",
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training_dataset="gs://cloud-samples-data/ai-platform/generative_ai/gemini-2_0/text/sft_train_data.jsonl",
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config=CreateTuningJobConfig(
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tuned_model_display_name="Example tuning job",
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),
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)
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running_states = set([
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"JOB_STATE_PENDING",
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"JOB_STATE_RUNNING",
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])
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while tuning_job.state in running_states:
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print(tuning_job.state)
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tuning_job = client.tunings.get(name=tuning_job.name)
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time.sleep(60)
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print(tuning_job.tuned_model.model)
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print(tuning_job.tuned_model.endpoint)
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print(tuning_job.experiment)
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# Example response:
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# projects/123456789012/locations/us-central1/models/1234567890@1
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# projects/123456789012/locations/us-central1/endpoints/123456789012345
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# projects/123456789012/locations/us-central1/metadataStores/default/contexts/tuning-experiment-2025010112345678
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# [END googlegenaisdk_tuning_job_create]
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return tuning_job.name
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if __name__ == "__main__":
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create_tuning_job()

‎genai/tuning/tuning_job_get.py‎

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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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def get_tuning_job(name: str) -> str:
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# [START googlegenaisdk_tuning_job_get]
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from google import genai
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from google.genai.types import HttpOptions
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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# Get the tuning job and the tuned model.
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# Eg. name = "projects/123456789012/locations/us-central1/tuningJobs/123456789012345"
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tuning_job = client.tunings.get(name=name)
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print(tuning_job.tuned_model.model)
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print(tuning_job.tuned_model.endpoint)
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print(tuning_job.experiment)
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# Example response:
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# projects/123456789012/locations/us-central1/models/1234567890@1
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# projects/123456789012/locations/us-central1/endpoints/123456789012345
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# projects/123456789012/locations/us-central1/metadataStores/default/contexts/tuning-experiment-2025010112345678
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# [END googlegenaisdk_tuning_job_get]
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return tuning_job.name
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if __name__ == "__main__":
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tuning_job_name = input("Tuning job name: ")
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get_tuning_job(tuning_job_name)

‎genai/tuning/tuning_job_list.py‎

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# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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def list_tuning_jobs() -> None:
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# [START googlegenaisdk_tuning_job_list]
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from google import genai
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from google.genai.types import HttpOptions
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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responses = client.tunings.list()
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for response in responses:
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print(response.name)
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# Example response:
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# projects/123456789012/locations/us-central1/tuningJobs/123456789012345
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# [END googlegenaisdk_tuning_job_list]
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return
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if __name__ == "__main__":
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tuning_job_name = input("Tuning job name: ")
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list_tuning_jobs()

‎genai/tuning/tuning_textgen_with_txt.py‎

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# Copyright 2024 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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def test_tuned_endpoint(name: str) -> str:
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# [START googlegenaisdk_tuning_textgen_with_txt]
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from google import genai
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from google.genai.types import HttpOptions
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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# Get the tuning job and the tuned model.
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# Eg. name = "projects/123456789012/locations/us-central1/tuningJobs/123456789012345"
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tuning_job = client.tunings.get(name=name)
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contents = "Why is the sky blue?"
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# Tests the default checkpoint
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response = client.models.generate_content(
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model=tuning_job.tuned_model.endpoint,
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contents=contents,
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)
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print(response.text)
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# [END googlegenaisdk_tuning_textgen_with_txt]
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return response.text
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if __name__ == "__main__":
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tuning_job_name = input("Tuning job name: ")
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test_tuned_endpoint(tuning_job_name)

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