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Step-by-Step Tutorial for Integrating Google Vertex PaLM API with PaLM2 Model

Tutorial for integrating Google Vertex PaLM API in monday.com using PaLM2 model

Creating an AI-Powered Assistant App on monday.com Using Google Vertex PaLM API

In today's tutorial, we'll dive into how to create an AI-powered Assistant App on monday.com using Google Vertex PaLM API powered by the advanced PaLM2 model. This guide will cover everything from setting up your project to integrating your app with powerful AI capabilities.

Prerequisites

Before we jump in, make sure you have joined the waitlist for the Google Vertex PaLM API. This access is crucial to leverage the AI model in your application.

Learning Objectives

  • Creating a React App
  • Styling your app with Tailwind CSS
  • Creating a custom API using FastAPI
  • Working with GraphQL
  • Handling requests and responses
  • Managing PDF files
  • Building an app on monday.com
  • Integrating Google Vertex PaLM API with monday.com
  • Publishing an App on monday.com

Time to Code and Learn!

Now, let's get started by creating a new project!

Create a New Project

Open Visual Studio Code and create a new folder for our project. You can name it monday-palm-tutorial or something that suits your preference.

Step 1: Create a React App

In your terminal, run the following command to create a new React App:

npx create-react-app monday-palm-tutorial

Step 2: Install Tailwind CSS

Next, we'll install Tailwind CSS. Execute the command below in your terminal:

npm install -D tailwindcss postcss autoprefixer

Step 3: Configure Tailwind CSS

Open the tailwind.config.js file and replace its content with the following configuration:

module.exports = {
  content: ['./src/**/*.{js,jsx,ts,tsx}'],
  theme: {
    extend: {},
  },
  plugins: [],
}

Step 4: Add Tailwind Directives

To utilize Tailwind CSS, open src/index.css and replace its content:

@tailwind base;
@tailwind components;
@tailwind utilities;

Step 5: Create UI Interface

Open src/App.js and replace its content with the following:

import React from 'react';

function App() {
  return (
    

AI Assistant App

); } export default App;

Implementing App Logic

Inside the App component, use the useState hook to manage app states, and useEffect to fetch data from the monday.com API. Create functions to handle requests intuitively.

Creating the Dropdown Menus

Create dropdown menus to select specific boards, items, and files. Set up onChange event handlers to store the selected items correctly.

Testing Your App

Open your terminal and run:

npm start

If everything is correct, you should see your app loading smoothly.

Step 6: Create a Custom API using FastAPI

For the backend, create a new folder named backend inside your project folder. Create an api.py file to handle custom API operations.

Backend Implementations

  • Create a function to handle file uploads.
  • Implement a function to read the contents of files.
  • Create a function that integrates with Google Vertex PaLM API.

Testing Your Backend

Run the following command to start your backend server:

uvicorn api:app --reload

Verify all functions work harmoniously.

Conclusion

Congratulations! You have successfully built a full-stack AI-powered Assistant App on monday.com integrated with Google Vertex PaLM API.

For more detailed instructions on publishing your application, check out the monday.com + Stable Diffusion Tutorial.

If you have further questions or feedback, feel free to leave a comment below!

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