mistralai-workflows 3.6.1

Mistral Workflows - Build reliable AI workflows with Python

Mistral Workflows

Build reliable, production-grade AI workflows with Python.

Overview

Mistral Workflows is a Python SDK for building AI-powered workflows with built-in reliability, observability, and scalability. It provides fault tolerance, durability, and exactly-once execution guarantees.

Features

• Simple Python API: Define workflows using Python decorators
• Built-in Reliability: Automatic retries, timeouts, and error handling
• Distributed Execution: Scale workflows across multiple workers
• LLM Integration: Native support for Mistral AI and other LLM providers
• Observability: Distributed tracing, structured logging, and event streaming
• Type Safety: Full type hints and Pydantic validation

Installation

pip install mistralai-workflows

Quick Start

from datetime import timedelta

from mistralai.workflows import workflow, activity

@activity
async def get_weather(city: str) -> str:
    # Your activity implementation
    return f"Weather in {city}: Sunny"

@workflow.define
class WeatherWorkflow:
    @workflow.run
    async def run(self, city: str) -> str:
        weather = await workflow.execute_activity(
            get_weather,
            city,
            start_to_close_timeout=timedelta(seconds=10),
        )
        return weather

Documentation

For full documentation, visit docs.mistral.ai/workflows/getting-started/introduction

Examples

The SDK includes comprehensive examples in the mistralai/workflows/examples directory. You can run all examples with a single command:

# Run all example workflows in a single worker
python -m mistralai_workflow_tests.examples.all_workflows_worker

License

Apache License 2.0 - see LICENSE for details.