Files
agent-framework/python/packages/gemini/README.md
cooleryu d5335fbeae Python (fix:gemini): make Gemini honor declarative outputSchema, not just JSON mode (#5893)
* fix(gemini): preserve schema response_format

* fix(gemini): satisfy pyright strict in response schema extraction

Cast Any-narrowed mappings to Mapping[str, Any] in the structured-output
schema helpers so pyright strict no longer reports partially-unknown
member, argument, and variable types. Pass response_format["format"]
straight into the recursive extractor, which already guards non-mapping
inputs. No behavior change.

* fix(gemini): use Sequence[object] cast to satisfy both mypy and pyright

The Sequence[Any] cast pyright strict needs to know the loop element type
is reported as a redundant-cast by mypy, which already narrows the
isinstance branch to Sequence[Any]. Cast to Sequence[object] instead:
pyright gets a fully known element type and mypy no longer sees an
identical-type cast. No behavior change.

---------

Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
2026-06-05 15:17:51 +00:00

52 lines
1.6 KiB
Markdown

# Get Started with Microsoft Agent Framework Gemini
Install the provider package:
```bash
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](https://aistudio.google.com/apikey) and set either the package-prefixed or SDK-standard environment variable:
```bash
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`:
```bash
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](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