Mistral Python Client

Migrating from v1

If you are upgrading from v1 to v2, check the migration guide for details on breaking changes and how to update your code.

API Key Setup

Before you begin, you will need a Mistral AI API key.

1. Get your own Mistral API Key: https://docs.mistral.ai/#api-access
2. Set your Mistral API Key as an environment variable. You only need to do this once.

# set Mistral API Key (using zsh for example)
$ echo 'export MISTRAL_API_KEY=[your_key_here]' >> ~/.zshenv

# reload the environment (or just quit and open a new terminal)
$ source ~/.zshenv

Summary

Mistral AI API: Our Chat Completion and Embeddings APIs specification. Create your account on La Plateforme to get access and read the docs to learn how to use it.

Table of Contents

• Mistral Python Client
  • Migrating from v1
  • API Key Setup
  • SDK Installation
  • SDK Example Usage
  • Providers' SDKs Example Usage
  • Available Resources and Operations
  • Server-sent event streaming
  • Pagination
  • File uploads
  • Retries
  • Error Handling
  • Server Selection
  • Custom HTTP Client
  • Authentication
  • Resource Management
  • Debugging
  • IDE Support
• Development
  • Contributions

SDK Installation

[!NOTE] Python version upgrade policy

Once a Python version reaches its official end of life date, a 3-month grace period is provided for users to upgrade. Following this grace period, the minimum python version supported in the SDK will be updated.

The SDK can be installed with uv, pip, or poetry package managers.

uv

uv is a fast Python package installer and resolver, designed as a drop-in replacement for pip and pip-tools. It's recommended for its speed and modern Python tooling capabilities.

uv add mistralai

PIP

PIP is the default package installer for Python, enabling easy installation and management of packages from PyPI via the command line.

pip install mistralai

Poetry

Poetry is a modern tool that simplifies dependency management and package publishing by using a single pyproject.toml file to handle project metadata and dependencies.

poetry add mistralai

Shell and script usage with uv

You can use this SDK in a Python shell with uv and the uvx command that comes with it like so:

uvx --from mistralai python

It's also possible to write a standalone Python script without needing to set up a whole project like so:

#!/usr/bin/env -S uv run --script
# /// script
# requires-python = ">=3.10"
# dependencies = [
#     "mistralai",
# ]
# ///

from mistralai.client import Mistral

sdk = Mistral(
  # SDK arguments
)

# Rest of script here...

Once that is saved to a file, you can run it with uv run script.py where script.py can be replaced with the actual file name.

Agents extra dependencies

When using the agents related feature it is required to add the agents extra dependencies. This can be added when installing the package:

pip install "mistralai[agents]"

Note: These features require Python 3.10+ (the SDK minimum).

Additional packages

Additional mistralai-* packages (e.g. mistralai-workflows) can be installed separately and are available under the mistralai namespace:

pip install mistralai-workflows

SDK Example Usage

Create Chat Completions

This example shows how to create chat completions.

# Synchronous Example
from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.chat.complete(model="mistral-large-latest", messages=[
        {
            "role": "user",
            "content": "Who is the best French painter? Answer in one short sentence.",
        },
    ], stream=False, response_format={
        "type": "text",
    })

    # Handle response
    print(res)

The same SDK client can also be used to make asynchronous requests by importing asyncio.

# Asynchronous Example
import asyncio
from mistralai.client import Mistral
import os

async def main():

    async with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:

        res = await mistral.chat.complete_async(model="mistral-large-latest", messages=[
            {
                "role": "user",
                "content": "Who is the best French painter? Answer in one short sentence.",
            },
        ], stream=False, response_format={
            "type": "text",
        })

        # Handle response
        print(res)

asyncio.run(main())

Upload a file

This example shows how to upload a file.

# Synchronous Example
from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.files.upload(file={
        "file_name": "example.file",
        "content": open("example.file", "rb"),
    }, visibility="workspace")

    # Handle response
    print(res)

The same SDK client can also be used to make asynchronous requests by importing asyncio.

# Asynchronous Example
import asyncio
from mistralai.client import Mistral
import os

async def main():

    async with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:

        res = await mistral.files.upload_async(file={
            "file_name": "example.file",
            "content": open("example.file", "rb"),
        }, visibility="workspace")

        # Handle response
        print(res)

asyncio.run(main())

Create Agents Completions

This example shows how to create agents completions.

# Synchronous Example
from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.agents.complete(messages=[
        {
            "role": "user",
            "content": "Who is the best French painter? Answer in one short sentence.",
        },
    ], agent_id="<id>", stream=False, response_format={
        "type": "text",
    })

    # Handle response
    print(res)

The same SDK client can also be used to make asynchronous requests by importing asyncio.

# Asynchronous Example
import asyncio
from mistralai.client import Mistral
import os

async def main():

    async with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:

        res = await mistral.agents.complete_async(messages=[
            {
                "role": "user",
                "content": "Who is the best French painter? Answer in one short sentence.",
            },
        ], agent_id="<id>", stream=False, response_format={
            "type": "text",
        })

        # Handle response
        print(res)

asyncio.run(main())

Create Embedding Request

This example shows how to create embedding request.

# Synchronous Example
from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.embeddings.create(model="mistral-embed", inputs=[
        "Embed this sentence.",
        "As well as this one.",
    ])

    # Handle response
    print(res)

The same SDK client can also be used to make asynchronous requests by importing asyncio.

# Asynchronous Example
import asyncio
from mistralai.client import Mistral
import os

async def main():

    async with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:

        res = await mistral.embeddings.create_async(model="mistral-embed", inputs=[
            "Embed this sentence.",
            "As well as this one.",
        ])

        # Handle response
        print(res)

asyncio.run(main())

More examples

You can run the examples in the examples/ directory using uv run.

Providers' SDKs Example Usage

Azure AI

Prerequisites

Before you begin, ensure you have AZURE_ENDPOINT and an AZURE_API_KEY. To obtain these, you will need to deploy Mistral on Azure AI. See instructions for deploying Mistral on Azure AI here.

Step 1: Install

pip install mistralai

Step 2: Example Usage

Here's a basic example to get you started. You can also run the example in the examples directory.

import os
from mistralai.azure.client import MistralAzure

# The SDK automatically injects api-version as a query parameter
client = MistralAzure(
    api_key=os.environ["AZURE_API_KEY"],
    server_url=os.environ["AZURE_ENDPOINT"],
    api_version="2024-05-01-preview",  # Optional, this is the default
)

res = client.chat.complete(
    model=os.environ["AZURE_MODEL"],
    messages=[
        {
            "role": "user",
            "content": "Hello there!",
        }
    ],
)
print(res.choices[0].message.content)

Google Cloud

Prerequisites

Before you begin, you will need to create a Google Cloud project and enable the Mistral API. To do this, follow the instructions here.

To run this locally you will also need to ensure you are authenticated with Google Cloud. You can do this by running

gcloud auth application-default login

Step 1: Install

pip install mistralai
# For GCP authentication support (required):
pip install "mistralai[gcp]"

Step 2: Example Usage

Here's a basic example to get you started. You can also run the example in the examples directory.

The SDK automatically:

• Detects credentials via google.auth.default()
• Auto-refreshes tokens when they expire
• Builds the Vertex AI URL from project_id and region

import os
from mistralai.gcp.client import MistralGCP

# The SDK auto-detects credentials and builds the Vertex AI URL
client = MistralGCP(
    project_id=os.environ.get("GCP_PROJECT_ID"),  # Optional: auto-detected from credentials
    region="us-central1",  # Default: europe-west4
)

res = client.chat.complete(
    model="mistral-small-2503",
    messages=[
        {
            "role": "user",
            "content": "Hello there!",
        }
    ],
)
print(res.choices[0].message.content)

Available Resources and Operations

Server-sent event streaming

Server-sent events are used to stream content from certain operations. These operations will expose the stream as Generator that can be consumed using a simple for loop. The loop will terminate when the server no longer has any events to send and closes the underlying connection.

The stream is also a Context Manager and can be used with the with statement and will close the underlying connection when the context is exited.

from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    })

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

Pagination

Some of the endpoints in this SDK support pagination. To use pagination, you make your SDK calls as usual, but the returned response object will have a Next method that can be called to pull down the next group of results. If the return value of Next is None, then there are no more pages to be fetched.

Here's an example of one such pagination call:

from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.workflows.get_workflows(active_only=False, include_shared=True, limit=50)

    while res is not None:
        # Handle items

        res = res.next()

File uploads

Certain SDK methods accept file objects as part of a request body or multi-part request. It is possible and typically recommended to upload files as a stream rather than reading the entire contents into memory. This avoids excessive memory consumption and potentially crashing with out-of-memory errors when working with very large files. The following example demonstrates how to attach a file stream to a request.

[!TIP]

For endpoints that handle file uploads bytes arrays can also be used. However, using streams is recommended for large files.

from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.transcriptions.complete(model="Model X", diarize=False)

    # Handle response
    print(res)

Retries

Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.

To change the default retry strategy for a single API call, simply provide a RetryConfig object to the call:

from mistralai.client import Mistral
from mistralai.client.utils import BackoffStrategy, RetryConfig
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    },
        RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False))

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

If you'd like to override the default retry strategy for all operations that support retries, you can use the retry_config optional parameter when initializing the SDK:

from mistralai.client import Mistral
from mistralai.client.utils import BackoffStrategy, RetryConfig
import os


with Mistral(
    retry_config=RetryConfig("backoff", BackoffStrategy(1, 50, 1.1, 100), False),
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    })

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

Error Handling

MistralError is the base class for all HTTP error responses. It has the following properties:

Example

from mistralai.client import Mistral, errors
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:
    res = None
    try:

        res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

        })

        with res as event_stream:
            for event in event_stream:
                # handle event
                print(event, flush=True)


    except errors.MistralError as e:
        # The base class for HTTP error responses
        print(e.message)
        print(e.status_code)
        print(e.body)
        print(e.headers)
        print(e.raw_response)

        # Depending on the method different errors may be thrown
        if isinstance(e, errors.HTTPValidationError):
            print(e.data.detail)  # Optional[List[models.ValidationError]]

Error Classes

Primary error:

• MistralError: The base class for HTTP error responses.

* Check the method documentation to see if the error is applicable.

Server Selection

Select Server by Name

You can override the default server globally by passing a server name to the server: str optional parameter when initializing the SDK client instance. The selected server will then be used as the default on the operations that use it. This table lists the names associated with the available servers:

Example

from mistralai.client import Mistral
import os


with Mistral(
    server="eu",
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    })

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

Override Server URL Per-Client

The default server can also be overridden globally by passing a URL to the server_url: str optional parameter when initializing the SDK client instance. For example:

from mistralai.client import Mistral
import os


with Mistral(
    server_url="https://api.mistral.ai",
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    })

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

Custom HTTP Client

The Python SDK makes API calls using the httpx HTTP library. In order to provide a convenient way to configure timeouts, cookies, proxies, custom headers, and other low-level configuration, you can initialize the SDK client with your own HTTP client instance. Depending on whether you are using the sync or async version of the SDK, you can pass an instance of HttpClient or AsyncHttpClient respectively, which are Protocol's ensuring that the client has the necessary methods to make API calls. This allows you to wrap the client with your own custom logic, such as adding custom headers, logging, or error handling, or you can just pass an instance of httpx.Client or httpx.AsyncClient directly.

For example, you could specify a header for every request that this sdk makes as follows:

from mistralai.client import Mistral
import httpx

http_client = httpx.Client(headers={"x-custom-header": "someValue"})
s = Mistral(client=http_client)

or you could wrap the client with your own custom logic:

from mistralai.client import Mistral
from mistralai.client.httpclient import AsyncHttpClient
import httpx

class CustomClient(AsyncHttpClient):
    client: AsyncHttpClient

    def __init__(self, client: AsyncHttpClient):
        self.client = client

    async def send(
        self,
        request: httpx.Request,
        *,
        stream: bool = False,
        auth: Union[
            httpx._types.AuthTypes, httpx._client.UseClientDefault, None
        ] = httpx.USE_CLIENT_DEFAULT,
        follow_redirects: Union[
            bool, httpx._client.UseClientDefault
        ] = httpx.USE_CLIENT_DEFAULT,
    ) -> httpx.Response:
        request.headers["Client-Level-Header"] = "added by client"

        return await self.client.send(
            request, stream=stream, auth=auth, follow_redirects=follow_redirects
        )

    def build_request(
        self,
        method: str,
        url: httpx._types.URLTypes,
        *,
        content: Optional[httpx._types.RequestContent] = None,
        data: Optional[httpx._types.RequestData] = None,
        files: Optional[httpx._types.RequestFiles] = None,
        json: Optional[Any] = None,
        params: Optional[httpx._types.QueryParamTypes] = None,
        headers: Optional[httpx._types.HeaderTypes] = None,
        cookies: Optional[httpx._types.CookieTypes] = None,
        timeout: Union[
            httpx._types.TimeoutTypes, httpx._client.UseClientDefault
        ] = httpx.USE_CLIENT_DEFAULT,
        extensions: Optional[httpx._types.RequestExtensions] = None,
    ) -> httpx.Request:
        return self.client.build_request(
            method,
            url,
            content=content,
            data=data,
            files=files,
            json=json,
            params=params,
            headers=headers,
            cookies=cookies,
            timeout=timeout,
            extensions=extensions,
        )

s = Mistral(async_client=CustomClient(httpx.AsyncClient()))

Authentication

Per-Client Security Schemes

This SDK supports the following security scheme globally:

To authenticate with the API the api_key parameter must be set when initializing the SDK client instance. For example:

from mistralai.client import Mistral
import os


with Mistral(
    api_key=os.getenv("MISTRAL_API_KEY", ""),
) as mistral:

    res = mistral.audio.speech.complete(input="<value>", stream=False, additional_properties={

    })

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

Resource Management

The Mistral class implements the context manager protocol and registers a finalizer function to close the underlying sync and async HTTPX clients it uses under the hood. This will close HTTP connections, release memory and free up other resources held by the SDK. In short-lived Python programs and notebooks that make a few SDK method calls, resource management may not be a concern. However, in longer-lived programs, it is beneficial to create a single SDK instance via a context manager and reuse it across the application.

from mistralai.client import Mistral
import os
def main():

    with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:
        # Rest of application here...


# Or when using async:
async def amain():

    async with Mistral(
        api_key=os.getenv("MISTRAL_API_KEY", ""),
    ) as mistral:
        # Rest of application here...

Debugging

You can setup your SDK to emit debug logs for SDK requests and responses.

You can pass your own logger class directly into your SDK.

from mistralai.client import Mistral
import logging

logging.basicConfig(level=logging.DEBUG)
s = Mistral(debug_logger=logging.getLogger("mistralai.client"))

You can also enable a default debug logger by setting an environment variable MISTRAL_DEBUG to true.

IDE Support

PyCharm

Generally, the SDK will work well with most IDEs out of the box. However, when using PyCharm, you can enjoy much better integration with Pydantic by installing an additional plugin.

• PyCharm Pydantic Plugin

Development

Contributions

While we value open-source contributions to this SDK, this library is generated programmatically. Any manual changes added to internal files will be overwritten on the next generation. We look forward to hearing your feedback. Feel free to open a PR or an issue with a proof of concept and we'll do our best to include it in a future release.