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 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.

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-2.0.0b5.tar.gz (337.3 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-2.0.0b5-py3-none-any.whl (194.9 kB view details)

Uploaded Python 3

File details

Details for the file mistralai_workflows-2.0.0b5.tar.gz.

File metadata

  • Download URL: mistralai_workflows-2.0.0b5.tar.gz
  • Upload date:
  • Size: 337.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for mistralai_workflows-2.0.0b5.tar.gz
Algorithm Hash digest
SHA256 2302534fd2e23eeee2eb38341aabe2a2f91fb701ff70b556b968b12206d2f739
MD5 f5e1c398c5b906ac3c23b325beb880b1
BLAKE2b-256 789ad17492496237059790368f530f9c469c21e1bbfe274673adbd178559ce82

See more details on using hashes here.

Provenance

The following attestation bundles were made for mistralai_workflows-2.0.0b5.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-2.0.0b5-py3-none-any.whl.

File metadata

File hashes

Hashes for mistralai_workflows-2.0.0b5-py3-none-any.whl
Algorithm Hash digest
SHA256 68eccd603548dc3bf2d8ae526ebcdabe7669c267be6c5ec80476a62b6e25110d
MD5 0860fe810bcde5c3ca1eaeac0c9256fa
BLAKE2b-256 9a73e3425444e6c15a8454482ec796a5b7958dc57536d6d8bdefd1b2114d9306

See more details on using hashes here.

Provenance

The following attestation bundles were made for mistralai_workflows-2.0.0b5-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