Skip to main content

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 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.workflows.examples.all_workflows_worker

License

Apache License 2.0 - see LICENSE for details.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mistralai_workflows-3.3.0.tar.gz (505.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mistralai_workflows-3.3.0-py3-none-any.whl (390.4 kB view details)

Uploaded Python 3

File details

Details for the file mistralai_workflows-3.3.0.tar.gz.

File metadata

  • Download URL: mistralai_workflows-3.3.0.tar.gz
  • Upload date:
  • Size: 505.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mistralai_workflows-3.3.0.tar.gz
Algorithm Hash digest
SHA256 e462bbed75840d9099728c39bd92f7a562f88e4cc0c97305c369cfa4e5019613
MD5 99a0b8449e9b7ba4244f908f4c78604f
BLAKE2b-256 42abb7952d7f9ec11eb326b6ff3912d9378a7fa0b09767d7ec1c862bcfc95564

See more details on using hashes here.

Provenance

The following attestation bundles were made for mistralai_workflows-3.3.0.tar.gz:

Publisher: workflow-sdk.yaml on mistralai/dashboard

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file mistralai_workflows-3.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for mistralai_workflows-3.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 bedd37e16ef5d95eb9551415a5a2bfb5c92d6b2ae8c0e92883d0870da7b49645
MD5 c23be246706b8f2940604cc27b4bf0fd
BLAKE2b-256 128c17ed0974d2ea5e75dd9690b35178cf0b51b32b3b9156d2d6375da7239b0d

See more details on using hashes here.

Provenance

The following attestation bundles were made for mistralai_workflows-3.3.0-py3-none-any.whl:

Publisher: workflow-sdk.yaml on mistralai/dashboard

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page