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https://github.com/mistralai/client-python

Python client library for Mistral AI platform
https://github.com/mistralai/client-python

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Python client library for Mistral AI platform

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README 

        
# Mistral Python Client



## Migration warning

 

This documentation is for Mistral AI SDK v1. You can find more details on how to migrate from v0 to v1 [here](MIGRATION.md)



## API Key Setup



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



1. Get your own Mistral API Key: 

2. Set your Mistral API Key as an environment variable. You only need to do this once.



```bash

# 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](https://console.mistral.ai) to get access and read the [docs](https://docs.mistral.ai) to learn how to use it.



## Table of Contents



* [Mistral Python Client](#mistral-python-client)

  * [Migration warning](#migration-warning)

  * [API Key Setup](#api-key-setup)

  * [SDK Installation](#sdk-installation)

  * [SDK Example Usage](#sdk-example-usage)

  * [Providers' SDKs Example Usage](#providers-sdks-example-usage)

  * [Available Resources and Operations](#available-resources-and-operations)

  * [Server-sent event streaming](#server-sent-event-streaming)

  * [File uploads](#file-uploads)

  * [Retries](#retries)

  * [Error Handling](#error-handling)

  * [Server Selection](#server-selection)

  * [Custom HTTP Client](#custom-http-client)

  * [Authentication](#authentication)

  * [Resource Management](#resource-management)

  * [Debugging](#debugging)

  * [IDE Support](#ide-support)

* [Development](#development)

  * [Contributions](#contributions)



## SDK Installation



> [!NOTE]

> **Python version upgrade policy**

>

> Once a Python version reaches its [official end of life date](https://devguide.python.org/versions/), 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 either *pip* or *poetry* package managers.



### PIP



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



```bash

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.



```bash

poetry add mistralai

```



## SDK Example Usage



### Create Chat Completions



This example shows how to create chat completions.



```python

# Synchronous Example

from mistralai import Mistral

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.chat.complete(model="mistral-small-latest", messages=[

        {

            "content": "Who is the best French painter? Answer in one short sentence.",

            "role": "user",

        },

    ], stream=False)



    # Handle response

    print(res)

```



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

```python

# Asynchronous Example

import asyncio

from mistralai 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-small-latest", messages=[

            {

                "content": "Who is the best French painter? Answer in one short sentence.",

                "role": "user",

            },

        ], stream=False)



        # Handle response

        print(res)



asyncio.run(main())

```



### Upload a file



This example shows how to upload a file.



```python

# Synchronous Example

from mistralai 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"),

    })



    # Handle response

    print(res)

```



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

```python

# Asynchronous Example

import asyncio

from mistralai 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"),

        })



        # Handle response

        print(res)



asyncio.run(main())

```



### Create Agents Completions



This example shows how to create agents completions.



```python

# Synchronous Example

from mistralai import Mistral

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.agents.complete(messages=[

        {

            "content": "Who is the best French painter? Answer in one short sentence.",

            "role": "user",

        },

    ], agent_id="", stream=False)



    # Handle response

    print(res)

```



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

```python

# Asynchronous Example

import asyncio

from mistralai 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=[

            {

                "content": "Who is the best French painter? Answer in one short sentence.",

                "role": "user",

            },

        ], agent_id="", stream=False)



        # Handle response

        print(res)



asyncio.run(main())

```



### Create Embedding Request



This example shows how to create embedding request.



```python

# Synchronous Example

from mistralai import Mistral

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.embeddings.create(inputs=[

        "Embed this sentence.",

        "As well as this one.",

    ], model="mistral-embed")



    # Handle response

    print(res)

```



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

```python

# Asynchronous Example

import asyncio

from mistralai 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(inputs=[

            "Embed this sentence.",

            "As well as this one.",

        ], model="mistral-embed")



        # Handle response

        print(res)



asyncio.run(main())

```



### More examples



You can run the examples in the `examples/` directory using `poetry run` or by entering the virtual environment using `poetry shell`.



## Providers' SDKs Example Usage



### Azure AI



**Prerequisites**



Before you begin, ensure you have `AZUREAI_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](https://docs.mistral.ai/deployment/cloud/azure/).



Here's a basic example to get you started. You can also run [the example in the `examples` directory](/examples/azure).



```python

import asyncio

import os



from mistralai_azure import MistralAzure



client = MistralAzure(

    azure_api_key=os.getenv("AZURE_API_KEY", ""),

    azure_endpoint=os.getenv("AZURE_ENDPOINT", "")

)



async def main() -> None:

    res = await client.chat.complete_async( 

        max_tokens= 100,

        temperature= 0.5,

        messages= [

            {

                "content": "Hello there!",

                "role": "user"

            }

        ]

    )

    print(res)



asyncio.run(main())

```

The documentation for the Azure SDK is available [here](packages/mistralai_azure/README.md).



### 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](https://docs.mistral.ai/deployment/cloud/vertex/).



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



```bash

gcloud auth application-default login

```



**Step 1: Install**



Install the extras dependencies specific to Google Cloud:



```bash

pip install mistralai[gcp]

```



**Step 2: Example Usage**



Here's a basic example to get you started.



```python

import asyncio

from mistralai_gcp import MistralGoogleCloud



client = MistralGoogleCloud()



async def main() -> None:

    res = await client.chat.complete_async(

        model= "mistral-small-2402",

        messages= [

            {

                "content": "Hello there!",

                "role": "user"

            }

        ]

    )

    print(res)



asyncio.run(main())

```



The documentation for the GCP SDK is available [here](packages/mistralai_gcp/README.md).



## Available Resources and Operations



Available methods



### [agents](docs/sdks/agents/README.md)



* [complete](docs/sdks/agents/README.md#complete) - Agents Completion

* [stream](docs/sdks/agents/README.md#stream) - Stream Agents completion



### [batch](docs/sdks/batch/README.md)



#### [batch.jobs](docs/sdks/mistraljobs/README.md)



* [list](docs/sdks/mistraljobs/README.md#list) - Get Batch Jobs

* [create](docs/sdks/mistraljobs/README.md#create) - Create Batch Job

* [get](docs/sdks/mistraljobs/README.md#get) - Get Batch Job

* [cancel](docs/sdks/mistraljobs/README.md#cancel) - Cancel Batch Job



### [chat](docs/sdks/chat/README.md)



* [complete](docs/sdks/chat/README.md#complete) - Chat Completion

* [stream](docs/sdks/chat/README.md#stream) - Stream chat completion



### [classifiers](docs/sdks/classifiers/README.md)



* [moderate](docs/sdks/classifiers/README.md#moderate) - Moderations

* [moderate_chat](docs/sdks/classifiers/README.md#moderate_chat) - Moderations Chat



### [embeddings](docs/sdks/embeddings/README.md)



* [create](docs/sdks/embeddings/README.md#create) - Embeddings



### [files](docs/sdks/files/README.md)



* [upload](docs/sdks/files/README.md#upload) - Upload File

* [list](docs/sdks/files/README.md#list) - List Files

* [retrieve](docs/sdks/files/README.md#retrieve) - Retrieve File

* [delete](docs/sdks/files/README.md#delete) - Delete File

* [download](docs/sdks/files/README.md#download) - Download File

* [get_signed_url](docs/sdks/files/README.md#get_signed_url) - Get Signed Url



### [fim](docs/sdks/fim/README.md)



* [complete](docs/sdks/fim/README.md#complete) - Fim Completion

* [stream](docs/sdks/fim/README.md#stream) - Stream fim completion



### [fine_tuning](docs/sdks/finetuning/README.md)



#### [fine_tuning.jobs](docs/sdks/jobs/README.md)



* [list](docs/sdks/jobs/README.md#list) - Get Fine Tuning Jobs

* [create](docs/sdks/jobs/README.md#create) - Create Fine Tuning Job

* [get](docs/sdks/jobs/README.md#get) - Get Fine Tuning Job

* [cancel](docs/sdks/jobs/README.md#cancel) - Cancel Fine Tuning Job

* [start](docs/sdks/jobs/README.md#start) - Start Fine Tuning Job



### [models](docs/sdks/models/README.md)



* [list](docs/sdks/models/README.md#list) - List Models

* [retrieve](docs/sdks/models/README.md#retrieve) - Retrieve Model

* [delete](docs/sdks/models/README.md#delete) - Delete Model

* [update](docs/sdks/models/README.md#update) - Update Fine Tuned Model

* [archive](docs/sdks/models/README.md#archive) - Archive Fine Tuned Model

* [unarchive](docs/sdks/models/README.md#unarchive) - Unarchive Fine Tuned Model



## Server-sent event streaming



[Server-sent events][mdn-sse] are used to stream content from certain

operations. These operations will expose the stream as [Generator][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][context-manager] and can be used with the `with` statement and will close the

underlying connection when the context is exited.



```python

from mistralai import Mistral

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.chat.stream(model="mistral-small-latest", messages=[

        {

            "content": "Who is the best French painter? Answer in one short sentence.",

            "role": "user",

        },

    ], stream=True)



    with res as event_stream:

        for event in event_stream:

            # handle event

            print(event, flush=True)



```



[mdn-sse]: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events

[generator]: https://book.pythontips.com/en/latest/generators.html

[context-manager]: https://book.pythontips.com/en/latest/context_managers.html



## 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.

>



```python

from mistralai 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"),

    })



    # 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:

```python

from mistralai import Mistral

from mistralai.utils import BackoffStrategy, RetryConfig

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.models.list(,

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



    # Handle response

    print(res)



```



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:

```python

from mistralai import Mistral

from mistralai.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.models.list()



    # Handle response

    print(res)



```



## Error Handling



Handling errors in this SDK should largely match your expectations. All operations return a response object or raise an exception.



By default, an API error will raise a models.SDKError exception, which has the following properties:



| Property        | Type             | Description           |

|-----------------|------------------|-----------------------|

| `.status_code`  | *int*            | The HTTP status code  |

| `.message`      | *str*            | The error message     |

| `.raw_response` | *httpx.Response* | The raw HTTP response |

| `.body`         | *str*            | The response content  |



When custom error responses are specified for an operation, the SDK may also raise their associated exceptions. You can refer to respective *Errors* tables in SDK docs for more details on possible exception types for each operation. For example, the `list_async` method may raise the following exceptions:



| Error Type                 | Status Code | Content Type     |

| -------------------------- | ----------- | ---------------- |

| models.HTTPValidationError | 422         | application/json |

| models.SDKError            | 4XX, 5XX    | \*/\*            |



### Example



```python

from mistralai import Mistral, models

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:

    res = None

    try:



        res = mistral.models.list()



        # Handle response

        print(res)



    except models.HTTPValidationError as e:

        # handle e.data: models.HTTPValidationErrorData

        raise(e)

    except models.SDKError as e:

        # handle exception

        raise(e)

```



## 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:



| Name | Server                   |

| ---- | ------------------------ |

| `eu` | `https://api.mistral.ai` |



#### Example



```python

from mistralai import Mistral

import os



with Mistral(

    server="eu",

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.models.list()



    # Handle response

    print(res)



```



### 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:

```python

from mistralai import Mistral

import os



with Mistral(

    server_url="https://api.mistral.ai",

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.models.list()



    # Handle response

    print(res)



```



## Custom HTTP Client



The Python SDK makes API calls using the [httpx](https://www.python-httpx.org/) 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:

```python

from mistralai 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:

```python

from mistralai import Mistral

from mistralai.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:



| Name      | Type | Scheme      | Environment Variable |

| --------- | ---- | ----------- | -------------------- |

| `api_key` | http | HTTP Bearer | `MISTRAL_API_KEY`    |



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

```python

from mistralai import Mistral

import os



with Mistral(

    api_key=os.getenv("MISTRAL_API_KEY", ""),

) as mistral:



    res = mistral.models.list()



    # Handle response

    print(res)



```



## 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][context-manager] and reuse it across the application.



[context-manager]: https://docs.python.org/3/reference/datamodel.html#context-managers



```python

from mistralai 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.

```python

from mistralai import Mistral

import logging



logging.basicConfig(level=logging.DEBUG)

s = Mistral(debug_logger=logging.getLogger("mistralai"))

```



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](https://docs.pydantic.dev/latest/integrations/pycharm/)



# 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.