Description

Vertex AI SDK for Python ================================================= |GA| |pypi| |versions| |unit-tests| |system-tests| |sample-tests| `Vertex AI`_: Google Vertex AI is an integrated suite of machine learning tools and services for building and using ML models with AutoML or custom code. It offers both novices and experts the best workbench for the entire machine learning development lifecycle. - `Client Library Documentation`_ - `Product Documentation`_ .. |GA| image:: https://img.shields.io/badge/support-ga-gold.svg :target: https://github.com/googleapis/google-cloud-python/blob/main/README.rst#general-availability .. |pypi| image:: https://img.shields.io/pypi/v/google-cloud-aiplatform.svg :target: https://pypi.org/project/google-cloud-aiplatform/ .. |versions| image:: https://img.shields.io/pypi/pyversions/google-cloud-aiplatform.svg :target: https://pypi.org/project/google-cloud-aiplatform/ .. |unit-tests| image:: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-unit-tests.svg :target: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-unit-tests.html .. |system-tests| image:: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-system-tests.svg :target: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-system-tests.html .. |sample-tests| image:: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-sample-tests.svg :target: https://storage.googleapis.com/cloud-devrel-public/python-aiplatform/badges/sdk-sample-tests.html .. _Vertex AI: https://cloud.google.com/vertex-ai/docs .. _Client Library Documentation: https://cloud.google.com/python/docs/reference/aiplatform/latest .. _Product Documentation: https://cloud.google.com/vertex-ai/docs Installation ~~~~~~~~~~~~ .. code-block:: console pip install google-cloud-aiplatform With :code:`uv`: .. code-block:: console uv pip install google-cloud-aiplatform Generative AI in the Vertex AI SDK ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ To use Gen AI features from the Vertex AI SDK, you can instantiate a Vertex SDK client with the following: .. code-block:: Python import vertexai from vertexai import types # Instantiate GenAI client from Vertex SDK # Replace with your project ID and location client = vertexai.Client(project='my-project', location='us-central1') See the examples below for guidance on how to use specific features supported by the Vertex SDK client. Gen AI Evaluation ^^^^^^^^^^^^^^^^^ To run evaluation, first generate model responses from a set of prompts. .. code-block:: Python import pandas as pd prompts_df = pd.DataFrame({ "prompt": [ "What is the capital of France?", "Write a haiku about a cat.", "Write a Python function to calculate the factorial of a number.", "Translate 'How are you?' to French.", ], "reference": [ "Paris", "Sunbeam on the floor,\nA furry puddle sleeping,\nTwitching tail tells tales.", "def factorial(n):\n if n < 0:\n return 'Factorial does not exist for negative numbers'\n elif n == 0:\n return 1\n else:\n fact = 1\n i = 1\n while i <= n:\n fact *= i\n i += 1\n return fact", "Comment ça va ?", ] }) inference_results = client.evals.run_inference( model="gemini-2.5-flash-preview-05-20", src=prompts_df ) Then run evaluation by providing the inference results and specifying the metric types. .. code-block:: Python eval_result = client.evals.evaluate( dataset=inference_results, metrics=[ types.Metric(name='exact_match'), types.Metric(name='rouge_l_sum'), types.RubricMetric.TEXT_QUALITY, ] ) Agent Engine with Agent Development Kit (ADK) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ First, define a function that looks up the exchange rate: .. code-block:: Python def get_exchange_rate( currency_from: str = "USD", currency_to: str = "EUR", currency_date: str = "latest", ): """Retrieves the exchange rate between two currencies on a specified date. Uses the Frankfurter API (https://api.frankfurter.app/) to obtain exchange rate data. Returns: dict: A dictionary containing the exchange rate information. Example: {"amount": 1.0, "base": "USD", "date": "2023-11-24", "rates": {"EUR": 0.95534}} """ import requests response = requests.get( f"https://api.frankfurter.app/{currency_date}", params={"from": currency_from, "to": currency_to}, ) return response.json() Next, define an ADK Agent: .. code-block:: Python