> ## Documentation Index
> Fetch the complete documentation index at: https://docs.chainlit.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Mistral AI

<Warning>
  You shouldn't configure this integration if you're already using another
  integration like Langchain or LlamaIndex. Both integrations would
  record the same generation and create duplicate steps in the UI.
</Warning>

## Prerequisites

Before getting started, make sure you have the following:

* A working installation of Chainlit
* The Mistral AI python client package installed, `mistralai`
* A [Mistral AI API key](https://console.mistral.ai/api-keys/)
* Basic understanding of Python programming

## Step 1: Create a Python file

Create a new Python file named `app.py` in your project directory. This file will contain the main logic for your LLM application.

## Step 2: Write the Application Logic

In `app.py`, import the necessary packages and define one function to handle messages incoming from the UI.

```python theme={null}
import os
import chainlit as cl
from mistralai import Mistral

# Initialize the Mistral client
client = Mistral(api_key=os.getenv("MISTRAL_API_KEY"))

@cl.on_message
async def on_message(message: cl.Message):
    response = await client.chat.complete_async(
        model="mistral-small-latest",
        max_tokens=100,
        temperature=0.5,
        stream=False,
        # ... more setting
        messages=[
            {
                "role": "system",
                "content": "You are a helpful bot, you always reply in French."
            },
            {
                "role": "user",
                "content": message.content # Content of the user message
            }
        ]
    )
    await cl.Message(content=response.choices[0].message.content).send()
```

## Step 3: Fill the environment variables

Create a file named `.env` in the same folder as your `app.py` file. Add your Mistral AI API key in the `MISTRAL_API_KEY` variable.

## Step 4: Run the Application

To start your app, open a terminal and navigate to the directory containing `app.py`. Then run the following command:

```bash theme={null}
chainlit run app.py -w
```

The `-w` flag tells Chainlit to enable auto-reloading, so you don't need to restart the server every time you make changes to your application. Your chatbot UI should now be accessible at [http://localhost:8000](http://localhost:8000).