metorial-google 1.0.0rc1

Google (Gemini) provider for Metorial

metorial-google

Google (Gemini) provider integration for Metorial - enables using Metorial tools with Google's Gemini models through function calling.

Installation

pip install metorial-google
# or
uv add metorial-google
# or
poetry add metorial-google

Features

• 🤖 Gemini Integration: Full support for Gemini Pro, Gemini Flash, and other Google AI models
• 🛠️ Function Calling: Native Google function calling support
• 📡 Session Management: Automatic tool lifecycle handling
• 🔄 Format Conversion: Converts Metorial tools to Google function declaration format
• ⚡ Async Support: Full async/await support

Usage

Basic Usage

import asyncio
import google.generativeai as genai
from metorial import Metorial
from metorial_google import MetorialGoogleSession

async def main():
    # Initialize clients
    metorial = Metorial(api_key="your-metorial-api-key")
    genai.configure(api_key="your-google-api-key")
    
    # Create session with your server deployments
    async with metorial.session(["your-server-deployment-id"]) as session:
        # Create Google-specific wrapper
        google_session = MetorialGoogleSession(session.tool_manager)
        
        model = genai.GenerativeModel(
            model_name="gemini-pro",
            tools=google_session.tools
        )
        
        response = model.generate_content("What can you help me with?")
        
        # Handle function calls if present
        if response.candidates[0].content.parts:
            function_calls = [
                part.function_call for part in response.candidates[0].content.parts
                if hasattr(part, 'function_call') and part.function_call
            ]
            
            if function_calls:
                tool_response = await google_session.call_tools(function_calls)
                # Continue conversation with tool_response

asyncio.run(main())

Using Convenience Functions

from metorial_google import build_google_tools, call_google_tools

async def example_with_functions():
    # Get tools in Google format
    tools = build_google_tools(tool_manager)
    
    # Call tools from Google response
    response = await call_google_tools(tool_manager, function_calls)

API Reference

MetorialGoogleSession

Main session class for Google integration.

session = MetorialGoogleSession(tool_manager)

Properties:

• tools: List of tools in Google function declaration format

Methods:

• async call_tools(function_calls): Execute function calls and return user content

build_google_tools(tool_mgr)

Build Google-compatible tool definitions.

Returns: List of tool definitions in Google format

call_google_tools(tool_mgr, function_calls)

Execute function calls from Google response.

Returns: User content with function responses

Tool Format

Tools are converted to Google's function declaration format:

[{
    "function_declarations": [
        {
            "name": "tool_name",
            "description": "Tool description",
            "parameters": {
                "type": "object",
                "properties": {...},
                "required": [...]
            }
        }
    ]
}]

Error Handling

try:
    response = await google_session.call_tools(function_calls)
except Exception as e:
    print(f"Tool execution failed: {e}")

Tool errors are returned as error objects in the response format.

Dependencies

• google-generativeai>=0.3.0
• metorial-mcp-session>=1.0.0
• typing-extensions>=4.0.0

License

MIT License - see LICENSE file for details.