1 month ago - Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications. - googleapis/python-genai

Google Gen AI Python SDK provides an interface for developers to integrate Google’s generative models into their Python applications. It supports the Gemini Developer API and Vertex AI APIs. ... Please run one of the following code blocks to create a client for different services (Gemini Developer API or Vertex AI). from google import genai # Only run this block for Gemini Developer API client = genai.Client(api_key='GEMINI_API_KEY')

Usage: .. code-block:: python ... class genai.client.Client(*, enterprise=None, vertexai=None, api_key=None, credentials=None, project=None, location=None, debug_config=None, http_options=None)¶

May 21, 2026 - Weights & Biases, developer tools for machine learning

April 28, 2026 - The Google GenAI SDK is available for the Python, JavaScript/TypeScript, Go and Java languages.

from google import genai # TODO(developer): Update below line API_KEY = "YOUR_API_KEY" client = genai.Client(vertexai=True, api_key=API_KEY) response = client.models.generate_content( model="gemini-3.5-flash", contents="Explain bubble sort to me.", ) print(response.text) # Example response: # Bubble Sort is a simple sorting algorithm that repeatedly steps through the list · The Google Gen AI SDK for Go is available on go.dev and GitHub:

With Gemini 2.0, we took the chance to create a single unified SDK for all developers who want to use Google's GenAI models (Gemini, Veo, Imagen, etc).

2 weeks ago - Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications.

August 17, 2025 - The genai module creates a client used for API interaction, while the types module has data structures and classes that serve as helpers used to build requests and configure request parameters.

from google import genai from google.genai import types as genai_types # Create a Client in the Gen AI SDK genai_client = genai.Client(vertexai=True, project="your-project", location="your-location") # Call generate_content() with the prompt response = genai_client.models.generate_content( model=retrieved_prompt.prompt_data.model, contents=retrieved_prompt.assemble_contents(), )

Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications. - python-genai/codegen_instructions.md at main · googleapis/python-genai

Google Gen AI Python SDK provides an interface for developers to integrate Google's generative models into their Python applications. - Releases · googleapis/python-genai

July 24, 2025 - With the new SDK, the library does everything for you, provided you define your function using type annotations and you write its docstring (like we always do for every function, right? 😉). from google.genai import types def get_current_weather(location: str) -> str: """Returns the current weather.

Getting started with Instructor and the genai SDK is straightforward. Just create a Pydantic model defining your output structure, patch the genai client, and make your request with a response_model parameter: from google import genai import instructor from pydantic import BaseModel # Define your Pydantic model class User(BaseModel): name: str age: int # Initialize and patch the client client = instructor.from_provider("google/gemini-2.5-flash") # Extract structured data response = client.create( messages=[{"role": "user", "content": "Extract: Jason is 25 years old"}], response_model=User, ) print(response) # User(name='Jason', age=25)

2 weeks ago - The Interactions API is available through the Python and JavaScript SDKs, as well as through REST. To use the Gemini API, you need an API key. Create one for free to get started: ... Install the SDK and generate text with a single API call.

April 6, 2025 - ✅ Unified Access: Use the same SDK for both Gemini Developer API and Vertex AI—no major code changes needed 🔁 🛠️ Core Features: ... 📦 Installation: pip install -U google-genai 🔐 Authentication: Use API key or Google Cloud ...

March 11, 2025 - # Provide project details from google import genai from IPython.display import Markdown, display from google.colab import userdata PROJECT_ID = userdata.get('PROJECT_ID') LOCATION = userdata.get('LOCATION') # Create a client instance using Vertex AI in Google Cloud client = genai.Client(vertexai=True, project=PROJECT_ID, location=LOCATION) response = client.models.generate_content( model='gemini-2.0-flash', contents='Create a short bedtime story for a 3 year old using unicorns and rainbows' ) display(Markdown(response.text)) With the unified SDK, the code is identical whether you're using the developer API or Vertex AI.

May 3, 2026 - Weights & Biases, developer tools for machine learning

Please be advised that this repository is now considered legacy. For the latest features, performance improvements, and active development, we strongly recommend migrating to the official Google Generative AI SDK for Python.