8000 docs(genai): Add Veo Generation Sample (#13186) · katiemn/python-docs-samples@aa24c20 · GitHub
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docs(genai): Add Veo Generation Sample (GoogleCloudPlatform#13186)
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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", "3.13"],
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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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}
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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
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google-genai==1.3.0
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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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#
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# Using Google Cloud Vertex AI to test the code samples.
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#
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from datetime import datetime as dt
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import os
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from google.cloud import storage
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import pytest
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import videogen_with_txt
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os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "True"
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os.environ["GOOGLE_CLOUD_LOCATION"] = "us-central1"
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# The project name is included in the CICD pipeline
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# os.environ['GOOGLE_CLOUD_PROJECT'] = "add-your-project-name"
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GCS_OUTPUT_BUCKET = "python-docs-samples-tests"
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@pytest.fixture(scope="session")
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def output_gcs_uri() -> str:
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prefix = f"text_output/{dt.now()}"
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yield f"gs://{GCS_OUTPUT_BUCKET}/{prefix}"
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storage_client = storage.Client()
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bucket = storage_client.get_bucket(GCS_OUTPUT_BUCKET)
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blobs = bucket.list_blobs(prefix=prefix)
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for blob in blobs:
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blob.delete()
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def test_videogen_with_txt(output_gcs_uri: str) -> None:
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response = videogen_with_txt.generate_videos(output_gcs_uri=output_gcs_uri)
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assert response
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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 generate_videos(output_gcs_uri: str) -> str:
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# [START googlegenaisdk_videogen_with_txt]
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import time
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from google import genai
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from google.genai.types import GenerateVideosConfig
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client = genai.Client()
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# TODO(developer): Update and un-comment below line
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# output_gcs_uri = "gs://your-bucket/your-prefix"
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operation = client.models.generate_videos(
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model="veo-2.0-generate-001",
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prompt="a cat reading a book",
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config=GenerateVideosConfig(
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aspect_ratio="16:9",
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output_gcs_uri=output_gcs_uri,
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),
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)
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while not operation.done:
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time.sleep(15)
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operation = client.operations.get(operation)
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print(operation)
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if operation.response:
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print(operation.result.generated_videos[0].video.uri)
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# Example response:
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# gs://your-bucket/your-prefix
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# [END googlegenaisdk_videogen_with_txt]
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return operation.result.generated_videos[0].video.uri
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if __name__ == "__main__":
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generate_videos(output_gcs_uri="gs://your-bucket/your-prefix")