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mistralai-workflows

Mistral Workflows - Build reliable AI workflows with Python

With conditionsPyPI Python ModulesReleased Aug 2026196.5K downloads / moApache-2.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — mistralai_workflows-3.11.0-py3-none-any.whl
v3.11.0 · released 2026-08-11 · Python <3.15,>=3.12 · 17 runtime deps: asynciolimiter, httpx, jsonpatch, mistralai, opentelemetry-api, opentelemetry-exporter-otlp-proto-http, opentelemetry-instrumentation-httpx, opentelemetry-sdk

Yes, if you are building production AI workflows with Mistral AI and need built-in reliability, distributed execution, and observability. The low install friction and active maintenance are strong signals. However, the Beta status, Python 3.12+ requirement, and temporalio dependency complexity mean you should verify that the maturity level and backend setup align with your deployment model before committing to a large workflow system.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.12 or later; temporalio dependency may require additional system setup for workflow persistence and distributed coordination.
  • Low install friction with a pure-wheel distribution.
  • Active maintenance (released 3 days ago).

License · maintenance · safety

Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—standard for open-source infrastructure.

last release 2026-08-11 (3 days)

0 known vulnerabilities (OSV.dev, 2026-08-14) · 196,477 downloads/mo, #9,785 on PyPI

Verify before relying

pip install mistralai-workflows

from mistralai.workflows import workflow, activity
from datetime import timedelta

@activity
async def get_weather(city: str) -> str:
    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
  • Whether temporalio backend requires external service deployment or can run in-process for development.
  • Performance characteristics and scalability limits for concurrent workflows.
  • Maturity and stability guarantees given Beta development status.
Same gist for agents: .md · .json

What it is and what it does

Mistral Workflows is a Python framework for defining and executing reliable, distributed AI workflows using decorators and async/await syntax. It wraps Mistral AI LLM calls and custom activities (tasks) into workflows with automatic retry logic, timeouts, and exactly-once execution semantics. The SDK is built on temporalio for durability and state management, integrates the opentelemetry stack for observability, and uses Pydantic for type validation.

You define activities (individual tasks) and workflows (orchestrations of activities) using Python decorators, then execute them with built-in fault tolerance and distributed scaling. It's aimed at production AI applications that need reliability guarantees—retries on failure, timeout enforcement, and structured logging—without manually implementing those patterns.

Use it for

  • Build multi-step LLM pipelines (e.g., research → analysis → report generation) with automatic retries and timeout protection.
  • Orchestrate long-running AI tasks across multiple workers with exactly-once semantics and durable state.
  • Integrate Mistral AI calls with external APIs and custom Python logic in a single declarative workflow.
  • Monitor and trace distributed AI workflows using built-in OpenTelemetry instrumentation.
  • Deploy fault-tolerant AI agents that survive worker failures and resume from checkpoints.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

With conditions

Yes, if you are building production AI workflows with Mistral AI and need built-in reliability, distributed execution, and observability.

The low install friction and active maintenance are strong signals. However, the Beta status, Python 3.12+ requirement, and temporalio dependency complexity mean you should verify that the maturity level and backend setup align with your deployment model before committing to a large workflow system.

Install

mistralai-workflows on PyPI

Before you install

Low install friction with a pure-wheel distribution. Active maintenance (released 3 days ago). Requires Python 3.12–3.14 and pulls in 17 runtime dependencies including temporalio, httpx, and observability libraries (opentelemetry stack), which adds moderate complexity to your environment.

Requires Python 3.12 or later; temporalio dependency may require additional system setup for workflow persistence and distributed coordination.

License in practice

Apache-2.0 permissive license allows commercial use, modification, and distribution with minimal restrictions—standard for open-source infrastructure.

Quickstart

pip install mistralai-workflows

from mistralai.workflows import workflow, activity
from datetime import timedelta

@activity
async def get_weather(city: str) -> str:
    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

Verify before relying

  • Whether temporalio backend requires external service deployment or can run in-process for development.
  • Performance characteristics and scalability limits for concurrent workflows.
  • Maturity and stability guarantees given Beta development status.

Package facts

LicenseApache-2.0 permissive
Python supportSupports the current Python release <3.15,>=3.12
Install frictionLow. Pure-Python wheel
Runtime dependencies
17 packages
asynciolimiterhttpxjsonpatchmistralaiopentelemetry-apiopentelemetry-exporter-otlp-proto-httpopentelemetry-instrumentation-httpxopentelemetry-sdkorjsonpydantic-settingspydanticpyjwtstarlettestructlogtemporaliotenacityurllib3
MaintenanceActively maintained 3 days since the last release
First released
Downloads196,477 / month, #9,785 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.12Topic :: Scientific/Engineering :: Artificial IntelligenceTopic :: Software Development :: Libraries :: Python Modules

Evidence: mistralai_workflows-3.11.0-py3-none-any.whl

Tags

Capabilities
ai workflow orchestration pythonmistral llm workflow enginedistributed task execution frameworkfault-tolerant workflow automationtemporal-based workflow sdkllm pipeline orchestrationreliable ai task scheduling
Topics
workflow-orchestrationllm-integrationdistributed-execution
PyPI keywords
aillmmistralorchestrationtemporalworkflows

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See also mistralai · temporalio · opentelemetry-instrumentation-mistralai · vellum-ai · mistral_common · simpleflow · langchain-mistralai · langflow-base · hatchet-sdk · mistral-vibe

Further reading