feat(genai/model_tuning) Migrate samples to genai/model_tuning using vertexai.language_models.

genai/model_tuning/evaluate_model_example.py

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+# Copyright 2026 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.
+
+# [START aiplatform_genai_evaluate_model]
+import os
+
+import vertexai
+from vertexai.evaluation import EvalResult, EvalTask
+
+# TODO (Developer) Set environment variables
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+LOCATION_ID = os.getenv("LOCATION_ID", "us-central1")
+MODEL_NAME = os.getenv("MODEL_NAME", "gemini-2.5-flash")
+
+
+def evaluate_model() -> EvalResult:
+    """Evaluate the performance of a generative AI model."""
+
+    vertexai.init(project=PROJECT_ID, location=LOCATION_ID)
+
+    # Dataset URI containing input prompts and ground truth labels
+    dataset_uri = "gs://cloud-samples-data/ai-platform/generative_ai/llm_classification_bp_input_prompts_with_ground_truth.jsonl"
+
+    metric_column_mapping = {"reference": "ground_truth"}
+
+    # Define evaluation task
+    eval_task = EvalTask(
+        dataset=dataset_uri,
+        metrics=["exact_match"],
+        experiment="gemini-classification-eval",
+        metric_column_mapping=metric_column_mapping,
+    )
+
+    # Define a prompt template so the generative Gemini model produces formatted labels
+    prompt_template = (
+        "Classify the following text into exactly one category from "
+        "[nature, news, sports, health, startups]. Return only the category name:\n\n{prompt}"
+    )
+
+    # Evaluate using a modern Gemini model
+    eval_result = eval_task.evaluate(
+        model=MODEL_NAME,
+        prompt_template=prompt_template,
+    )
+
+    print("=== SUMMARY METRICS ===")
+    print(eval_result.summary_metrics)
+
+    print("\n=== METRICS TABLE SAMPLE ===")
+    print(eval_result.metrics_table.head())
+
+    return eval_result
+
+
+# [END aiplatform_genai_evaluate_model]

genai/model_tuning/evaluate_model_example_test.py

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+# Copyright 2026 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 backoff
+
+import evaluate_model_example
+from google.api_core.exceptions import ResourceExhausted
+
+
+@backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
+def test_evaluate_model() -> None:
+    eval_metrics = evaluate_model_example.evaluate_model()
+    assert hasattr(eval_metrics, "metrics_table")

genai/model_tuning/noxfile_config.py

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+# Copyright 2026 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
+#
+#      http://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.
+
+# Default TEST_CONFIG_OVERRIDE for python repos.
+
+# You can copy this file into your directory, then it will be imported from
+# the noxfile.py.
+
+# The source of truth:
+# https://github.com/GoogleCloudPlatform/python-docs-samples/blob/main/noxfile_config.py
+
+TEST_CONFIG_OVERRIDE = {
+    # You can opt out from the test for specific Python versions.
+    "ignored_versions": ["3.8", "3.9", "3.11", "3.12", "3.13"],
+    # Old samples are opted out of enforcing Python type hints
+    # All new samples should feature them
+    "enforce_type_hints": True,
+    # An envvar key for determining the project id to use. Change it
+    # to 'BUILD_SPECIFIC_GCLOUD_PROJECT' if you want to opt in using a
+    # build specific Cloud project. You can also use your own string
+    # to use your own Cloud project.
+    "gcloud_project_env": "GOOGLE_CLOUD_PROJECT",
+    # 'gcloud_project_env': 'BUILD_SPECIFIC_GCLOUD_PROJECT',
+    # If you need to use a specific version of pip,
+    # change pip_version_override to the string representation
+    # of the version number, for example, "20.2.4"
+    "pip_version_override": None,
+    # A dictionary you want to inject into your test. Don't put any
+    # secrets here. These values will override predefined values.
+    "envs": {},
+}

genai/model_tuning/pretrained_codegen_example.py

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+# Copyright 2026 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.
+
+# [START aiplatform_genai_tune_code_generation_model]
+import os
+
+from google import genai
+
+# TODO (Developer) Set environment variables
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+LOCATION_ID = os.getenv("LOCATION_ID", "us-central1")
+
+# Resource format: 'publishers/google/models/{model_id}'
+BASE_MODEL_RESOURCE = "publishers/google/models/gemini-2.5-flash"
+TRAINING_DATASET = (
+    "gs://cloud-samples-data/ai-platform/generative_ai/gemini/text/sft_train_data.jsonl"
+)
+
+
+def tune_code_generation_model() -> genai.types.TuningJob:
+    """Submits a supervised fine-tuning job for a Gemini model on code/text tasks."""
+
+    client = genai.Client(
+        enterprise=True,
+        project=PROJECT_ID,
+        location=LOCATION_ID,
+    )
+
+    tuning_job = client.tunings.tune(
+        base_model=BASE_MODEL_RESOURCE,
+        training_dataset=genai.types.TuningDataset(
+            gcs_uri=TRAINING_DATASET,
+        ),
+        config=genai.types.CreateTuningJobConfig(
+            tuned_model_display_name="tuned_gemini_code_model",
+            epoch_count=2,
+            learning_rate_multiplier=1.0,
+        ),
+    )
+
+    print(f"Tuning job submitted successfully: {tuning_job.name}")
+    print(f"Current State: {tuning_job.state}")
+
+    return tuning_job
+
+
+# [END aiplatform_genai_tune_code_generation_model]

genai/model_tuning/pretrained_examples_test.py

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+# Copyright 2026 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
+
+from google import genai
+
+import pretrained_codegen_example
+
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+LOCATION_ID = os.getenv("LOCATION_ID", "us-central1")
+
+JOB_STATES_CANCELLABLE = [
+    genai.types.JobState.JOB_STATE_RUNNING,
+    genai.types.JobState.JOB_STATE_PENDING,
+]
+JOB_STATES_DELETABLE = [
+    genai.types.JobState.JOB_STATE_SUCCEEDED,
+    genai.types.JobState.JOB_STATE_CANCELLED,
+    genai.types.JobState.JOB_STATE_FAILED,
+]
+
+
+def test_tuning_code_generation_model() -> None:
+    """Validate tuning creation, and cleans after execution."""
+
+    client = genai.Client(enterprise=True, project=PROJECT_ID, location=LOCATION_ID)
+
+    tuned_model = None
+    job_is_finished = False
+    job_is_pending = False
+
+    try:
+
+        tuned_model = pretrained_codegen_example.tune_code_generation_model()
+
+        job_is_pending = tuned_model.state in JOB_STATES_CANCELLABLE
+        job_is_finished = tuned_model.state in JOB_STATES_DELETABLE
+        result = job_is_finished or job_is_pending
+
+        assert result
+
+    finally:
+
+        # cleanup
+        if job_is_pending:
+            client.tunings.cancel(name=tuned_model.name)
+        if job_is_finished:
+            client.models.delete(model=tuned_model.model)

genai/model_tuning/requirements-test.txt

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+backoff==2.2.1
+google-api-core==2.33.0
+pytest==9.1.1

genai/model_tuning/requirements.txt

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+google-genai==2.16.0
+google-cloud-aiplatform[pipelines, evaluation]==1.163.0