Building a Chatbot with Mistral AI : Step by Step Guide
Prerequisites
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
MISTRAL_API_URL = MISTRAL_API_URL
MISTRAL_API_KEY = YOUR_MISTRAL_API_KEY
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 axios.post(process.env.MISTRAL_API_URL, requestData, {
headers: {
'Content-Type': 'application/json',
'Accept': 'application/json',
'Authorization': `Bearer ${process.env.MISTRAL_API_KEY}`
}
});
// Extract response from Mistral AI
const data = response.data.choices[0].message.content;
return res.status(200).json({success:true,data}); // Return response to the user
} catch (error) {
console.log(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.