Building a Chatbot with Mistral AI Step by Step Guide

Posted By :Mohd Ubaish |24th February 2024

Building a Chatbot with Mistral AI  : Step by Step Guide




Before we get started, you'll need to have the following:

1. Basic understanding of JavaScript and Node.js.

2. Node.js installed on your machine.

3. Understand RESTful APIs.

4. Access to Mistral AI API credentials.


Step 1: Setting Up Your Node.js Project

To begin, create a new Node.js project. Navigate to your project directory in your terminal and run the following command:


mkdir mistral-chatbot

cd mistral-chatbot

npm init -y


This will create a new directory named mistral-chatbot and initialize a new Node.js project with the default settings.


Step 2: Installing Dependencies

Next, install the necessary dependencies that we'll need for our project. In this tutorial, we'll use Axios to make HTTP requests. Run the following command to install Axios:


npm install axios


Step 3: Environment Setup


 a. Create a file named .env in the root of your project to store environment variables.

 b. Add the following variables to the .env file, replacing "MISTRAL_API_URL" and "YOUR_MISTRAL_API_KEY" with your actual Mistral API URL and API key, respectively 




Step 4: Writing the Chatbot Logic
Now, let's write the logic for our chatbot. Create a new file named chatbot.js in your project directory and add the following code:



const MistralChatbot = async (req,res) => {
    try {
    	let {message, mistralChatHistory, conversationId} = req.body;
        const history = JSON.parse(mistralChatHistory);
        const format = TEXT_RESPONSE_FORMAT;  // if you want any type of formating in response , provide here 

        // Append format to the last message in chat history
        history[history.length - 1].content += format;

        // Prepare data for Mistral API request
        const requestData = {
            model: 'mistral-tiny',
            messages: history,
            temperature: 0,

        // Send request to Mistral API
        const response = await, requestData, {
            headers: {
                'Content-Type': 'application/json',
                'Accept': 'application/json',
                'Authorization': `Bearer ${process.env.MISTRAL_API_KEY}`

        // Extract response from Mistral AI
        const data =[0].message.content;

        return res.status(200).json({success:true,data}); // Return response to the user
    } catch (error) {
        throw new Error('Failed to process message');

module.exports = MistralChatbot;



Step 5: Testing Your Chatbot
You can now test your chatbot by sending messages to your application and observing the responses generated by Mistral AI. Ensure that your Mistral API credentials are valid and that your application can communicate with the Mistral API endpoint.

About Author

Mohd Ubaish

Mohd Ubaish is a highly skilled Backend Developer with expertise in a wide range of technologies, including React, Node.js, Express.js, MongoDB, and JavaScript.With a deep understanding of both front-end and back-end development, he is currently dedicated to the development of TripCongo Web Discovery.He is committed to creating a user-friendly experience on the frontend while ensuring the seamless functionality of the backend. By staying up-to-date with the latest industry trends and advancements, he strives to provide innovative solutions and optimize the performance of the application.

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