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52 lines
1.6 KiB
Markdown
52 lines
1.6 KiB
Markdown
# Get Started with Microsoft Agent Framework Gemini
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Install the provider package:
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```bash
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pip install agent-framework-gemini --pre
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```
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## Gemini Integration
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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.
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## Structured Output
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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`.
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## Authentication
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The connector supports both `google-genai` authentication modes.
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### Gemini Developer API
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Obtain an API key from [Google AI Studio](https://aistudio.google.com/apikey) and set either the package-prefixed or SDK-standard environment variable:
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```bash
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export GEMINI_API_KEY="your-api-key"
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# or: export GOOGLE_API_KEY="your-api-key"
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export GEMINI_MODEL="gemini-2.5-flash-lite"
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# or: export GOOGLE_MODEL="gemini-2.5-flash-lite"
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```
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### Vertex AI
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Set the standard Vertex AI environment variables used by `google-genai`:
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```bash
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export GOOGLE_GENAI_USE_VERTEXAI=true
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export GOOGLE_CLOUD_PROJECT="your-project-id"
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export GOOGLE_CLOUD_LOCATION="global"
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export GOOGLE_MODEL="gemini-2.5-flash-lite"
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```
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## Examples
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See the [Google Gemini samples](samples/) for runnable end-to-end scripts covering:
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- Basic agent with tool calling and streaming
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- Extended thinking with `ThinkingConfig`
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- Google Search grounding
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- Google Maps grounding
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- Built-in code execution
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