Mistral Workflows - Build reliable AI workflows with Python
Project description
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 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
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_workflows.examples.all_workflows_worker
License
Apache License 2.0 - see LICENSE for details.
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