Create Your Own AI with PaLM2: A Step-by-Step Tutorial

Introduction to Google's PaLM2

Google's PaLM2 is the next generation large language model that enhances the capabilities established by the previous models. It stands out due to its superior performance in various reasoning tasks, including, but not limited to:

• Code generation
• Mathematical problem-solving
• Classification tasks
• Question answering
• Translation of languages
• Natural language generation

This advancement marks a significant milestone in machine learning and responsible AI, setting new benchmarks for the industry.

Prerequisites for Using Google's PaLM2 API

To effectively utilize Google's PaLM2 API, you will need to:

1. Join the waitlist for API access.
2. Create an account on Streamlit, which is free of charge.
3. It's advisable to use your GitHub account for Streamlit, as this will facilitate future app deployments on Streamlit's Sharing Cloud.

Getting Started with Streamlit and PaLM2

Step 1: Create a New Project Directory

First, create a new project directory and navigate to it using your terminal:

mkdir my_palm2_app
cd my_palm2_app

Step 2: Set Up Your Environment

1. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`

2. Install Streamlit and Google's PaLM API dependencies:

pip install streamlit google-auth

Step 3: Create Your Streamlit App

Create a new file called app.py and import the necessary packages:

import streamlit as st
from google.auth import default

Adding Functionality to Your App

Add a title to your app:

st.title("AI-Powered Virtual Assistant")

Initialize the Message State

Set up the initial state for the messages:

if 'messages' not in st.session_state:
    st.session_state.messages = []

Create a Form for User Input

Utilize Streamlit's st.form() to gather user input:

with st.form(key='my_form'):
    user_input = st.text_input('Type your message here', '')
    submit_button = st.form_submit_button('Send')

Configure Google's PaLM API

Set up the API key and implement functionality to get responses:

from google.cloud import openai
client = openai.Client()

if submit_button:
    response = client.Completions.create(
        prompt=user_input,
        api_key='YOUR_API_KEY'
    )

Step 4: Running Your App

Run the app using the following command:

streamlit run app.py

Your app should launch in a new tab, showcasing your AI-powered virtual assistant!

Conclusion

In this tutorial, we successfully built an AI-powered Virtual Assistant using Google's PaLM2 model coupled with Streamlit. This combination allows for quick app development with minimal coding.

If you have further questions or need assistance, don't hesitate to connect with me on LinkedIn or Twitter. I’m here to help!