Gemini API reference

The Gemini API lets you access the latest generative models from Google. This API reference provides detailed information for the classes and methods available in the Gemini API SDKs. Pick a language and follow the setup steps to get started with building generative applications on your platform of choice.

Python Node.js Go Dart (Flutter) Android Swift Web

Install the Gemini API library

Using Python 3.9+, install the google-generativeai package using the following pip command:

pip install -q -U google-generativeai

Make your first request

Use the generateContent method to send a request to the Gemini API.

import google.generativeai as genai

genai.configure(api_key="YOUR_API_KEY")
model = genai.GenerativeModel("gemini-1.5-flash")
response = model.generate_content("Explain how AI works")
print(response.text)

What's next

Now that you have a model client, you can start programming with the Gemini API. You can find the Python SDK docs on GitHub, or read through the reference to learn how to use key API features:

• Generating content
• Working with models
• Understanding tokens

If you're just getting started, check out the following guides, which will help you understand the Gemini API programming model:

• Gemini API quickstart
• Gemini model guide
• About generative models
• Introduction to prompt design

You might also want to check out the capabilities guides, which introduce Gemini API features and provide examples of programming with the SDKs:

• Text generation
• Tokens
• Prompting with media files
• Context caching
• Embeddings
• Tuning

Then, for more in-depth documentation of Gemini API methods and request parameters, browse the guides in this reference.