Eduard van Valkenburg
d08200d00e
* Bump Python package versions for 1.12.0 release Bump packages represented in the 1.12.0 changelog, promote Foundry Hosting, Azure Content Understanding, Gemini, Mistral, Monty, and Tools to beta, and apply the requested beta cohort date stamp. Root and core move to 1.12.0, released and RC packages use their selected increments, alpha packages including Hosting MCP use the 260721 stamp, and core floors are raised only for proven consumers. Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf * fix version in readme * Add Responses conversation ID changes to release notes Include the breaking Hosting Responses conversation ID helper changes from #7234 in the Python 1.12.0 changelog. Copilot-Session: 2dd9980a-b869-4c16-8642-75b7a6d6ebdf
37 lines
1.6 KiB
Markdown
37 lines
1.6 KiB
Markdown
# Gemini Package (agent-framework-gemini)
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Integration with Google's Gemini Developer API and Vertex AI via the `google-genai` SDK.
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## Core Classes
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- **`RawGeminiChatClient`** - Lightweight chat client without any layers, for custom pipeline composition
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- **`GeminiChatClient`** - Full-featured chat client with function invocation, middleware, and telemetry
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- **`GeminiChatOptions`** - Options TypedDict for Gemini-specific parameters
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- **`GeminiSettings`** - Settings loaded from environment variables
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- **`GoogleGeminiSettings`** - SDK-standard `GOOGLE_*` settings loaded from environment variables
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- **`ThinkingConfig`** - Configuration for extended thinking
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## Gemini-specific Options
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- **`thinking_config`** - Enable extended thinking via `ThinkingConfig`
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- **`response_schema`** - Raw JSON schema dict for structured output (alternative to `response_format`)
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- **`top_k`** - Top-K sampling parameter
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## Built-in Tool Factory Methods
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- **`get_web_search_tool()`** - Google Search grounding for up-to-date web answers
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- **`get_code_interpreter_tool()`** - Sandboxed code execution
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- **`get_maps_grounding_tool()`** - Google Maps grounding for location and mapping
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- **`get_file_search_tool()`** - Retrieval from Gemini file search stores
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- **`get_mcp_tool()`** - Model Context Protocol server integration
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## Usage
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```python
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from agent_framework import Content, Message
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from agent_framework.gemini import GeminiChatClient
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client = GeminiChatClient(model="gemini-2.5-flash")
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response = await client.get_response([Message(role="user", contents=[Content.from_text("Hello")])])
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```
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