microsoft--agent-framework/python/packages/gemini/README.md

Get Started with Microsoft Agent Framework Gemini

Install the provider package:

pip install agent-framework-gemini --pre

Gemini Integration

The Gemini integration enables Microsoft Agent Framework applications to call Google Gemini models with familiar chat abstractions, including streaming, tool/function calling, and structured output.

Structured Output

Gemini structured output can be configured with either a Pydantic model in response_format, a JSON schema mapping in response_format, or a Gemini-specific response_schema. Declarative agents that define outputSchema pass that schema through response_format.

Authentication

The connector supports both google-genai authentication modes.

Gemini Developer API

Obtain an API key from Google AI Studio and set either the package-prefixed or SDK-standard environment variable:

export GEMINI_API_KEY="your-api-key"
# or: export GOOGLE_API_KEY="your-api-key"
export GEMINI_MODEL="gemini-2.5-flash-lite"
# or: export GOOGLE_MODEL="gemini-2.5-flash-lite"

Vertex AI

Set the standard Vertex AI environment variables used by google-genai:

export GOOGLE_GENAI_USE_VERTEXAI=true
export GOOGLE_CLOUD_PROJECT="your-project-id"
export GOOGLE_CLOUD_LOCATION="global"
export GOOGLE_MODEL="gemini-2.5-flash-lite"

Examples

See the Google Gemini samples for runnable end-to-end scripts covering:

• Basic agent with tool calling and streaming
• Extended thinking with ThinkingConfig
• Google Search grounding
• Google Maps grounding
• Built-in code execution