metorial-mistral 1.0.0rc1

Mistral AI provider for Metorial

metorial-mistral

Mistral AI provider integration for Metorial - enables using Metorial tools with Mistral's language models through function calling.

Installation

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

Features

• 🤖 Mistral Integration: Full support for Mistral Large, Codestral, and other Mistral models
• 🛠️ Function Calling: Native Mistral function calling support
• 📡 Session Management: Automatic tool lifecycle handling
• 🔄 Format Conversion: Converts Metorial tools to Mistral function format
• ✅ Strict Mode: Built-in strict parameter validation
• ⚡ Async Support: Full async/await support

Usage

Basic Usage

import asyncio
from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
from metorial import Metorial
from metorial_mistral import MetorialMistralSession

async def main():
    # Initialize clients
    metorial = Metorial(api_key="your-metorial-api-key")
    mistral = MistralClient(api_key="your-mistral-api-key")
    
    # Create session with your server deployments
    async with metorial.session(["your-server-deployment-id"]) as session:
        # Create Mistral-specific wrapper
        mistral_session = MetorialMistralSession(session.tool_manager)
        
        messages = [
            ChatMessage(role="user", content="What are the latest commits?")
        ]
        
        response = mistral.chat(
            model="mistral-large-latest",
            messages=messages,
            tools=mistral_session.tools
        )
        
        # Handle tool calls
        if response.choices[0].message.tool_calls:
            tool_responses = await mistral_session.call_tools(response.choices[0].message.tool_calls)
            
            # Add assistant message and tool responses
            messages.append(response.choices[0].message)
            messages.extend(tool_responses)
            
            # Continue conversation...

asyncio.run(main())

Using Convenience Functions

from metorial_mistral import build_mistral_tools, call_mistral_tools

async def example_with_functions():
    # Get tools in Mistral format
    tools = build_mistral_tools(tool_manager)
    
    # Call tools from Mistral response
    tool_messages = await call_mistral_tools(tool_manager, tool_calls)

API Reference

MetorialMistralSession

Main session class for Mistral integration.

session = MetorialMistralSession(tool_manager)

Properties:

• tools: List of tools in Mistral format

Methods:

• async call_tools(tool_calls): Execute tool calls and return tool messages

build_mistral_tools(tool_mgr)

Build Mistral-compatible tool definitions.

Returns: List of tool definitions in Mistral format

call_mistral_tools(tool_mgr, tool_calls)

Execute tool calls from Mistral response.

Returns: List of tool messages

Tool Format

Tools are converted to Mistral's function calling format:

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

Error Handling

try:
    tool_messages = await mistral_session.call_tools(tool_calls)
except Exception as e:
    print(f"Tool execution failed: {e}")

Tool errors are returned as tool messages with error content.

Dependencies

• mistralai>=1.0.0
• metorial-mcp-session>=1.0.0
• typing-extensions>=4.0.0

License

MIT License - see LICENSE file for details.