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feat(genai): Add new folder and samples for model optimizer (#13385)
* feat(genai): add new folder for model optimizer * chore(genai): sync nox test config files * feat(genai): update README.md * feat(genai): Update caching to use `v1` version
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genai/README.md

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@@ -53,11 +53,23 @@ Demonstrates how to use Express Mode for simpler and faster interactions with Ge
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This mode is ideal for quick prototyping and experimentation. See the [Express Mode documentation](https://cloud.google.com/vertex-ai/generative-ai/docs/start/express-mode/overview)
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for details.
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### [Image Generation](https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/genai/image_generation/)
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Demonstrates how to generate image and edit images using Generative AI models. Check [Image Generation with Gemini Flash](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal/image-generation)
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and [Imagen on Vertex AI](https://cloud.google.com/vertex-ai/generative-ai/docs/image/overview) for details.
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### [Live API](https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/genai/live_api/)
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Provides examples of using the Generative AI [Live API](https://cloud.google.com/vertex-ai/generative-ai/docs/multimodal-live-api).
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This allows for real-time interactions and dynamic content generation.
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### [Model Optimizer](https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/genai/model_optimizer/)
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Provides examples of using the Generative AI [Model Optimizer](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/vertex-ai-model-optimizer).
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Vertex AI Model Optimizer is a dynamic endpoint designed to simplify model selection by automatically applying the
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Gemini model which best meets your needs.
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### [Provisioned Throughput](https://github.com/GoogleCloudPlatform/python-docs-samples/tree/main/genai/live_api/)
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Provides examples demonstrating how to use Provisioned Throughput with Generative AI models. This feature provides a

genai/bounding_box/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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"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,

genai/content_cache/contentcache_create_with_txt_gcs_pdf.py

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from google import genai
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from google.genai.types import Content, CreateCachedContentConfig, HttpOptions, Part
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client = genai.Client(http_options=HttpOptions(api_version="v1beta1"))
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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system_instruction = """
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You are an expert researcher. You always stick to the facts in the sources provided, and never make up new facts.

genai/content_cache/contentcache_delete.py

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def delete_context_caches(cache_name: str) -> str:
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# [START googlegenaisdk_contentcache_delete]
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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="v1beta1"))
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client = genai.Client()
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# Delete content cache using name
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# E.g cache_name = 'projects/111111111111/locations/us-central1/cachedContents/1111111111111111111'
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client.caches.delete(name=cache_name)

genai/content_cache/contentcache_list.py

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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="v1beta1"))
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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content_cache_list = client.caches.list()
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genai/content_cache/contentcache_update.py

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from google import genai
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from google.genai.types import HttpOptions, UpdateCachedContentConfig
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client = genai.Client(http_options=HttpOptions(api_version="v1beta1"))
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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# Get content cache by name
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# cache_name = "projects/111111111111/locations/us-central1/cachedContents/1111111111111111111"

genai/content_cache/contentcache_use_with_txt.py

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from google import genai
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from google.genai.types import GenerateContentConfig, HttpOptions
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client = genai.Client(http_options=HttpOptions(api_version="v1beta1"))
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client = genai.Client(http_options=HttpOptions(api_version="v1"))
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# Use content cache to generate text response
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# E.g cache_name = 'projects/111111111111/locations/us-central1/cachedContents/1111111111111111111'
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response = client.models.generate_content(

genai/embeddings/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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"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,

genai/express_mode/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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"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,

genai/image_generation/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", "3.9", "3.10", "3.11", "3.13"],
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"ignored_versions": ["2.7", "3.7", "3.8", "3.9", "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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