app.py

import streamlit as st
import openai
from dotenv import load_dotenv
import os

# Load environment variables from .env file
load_dotenv()

# Get your OpenAI API key from the environment variables
openai.api_key = os.getenv('OPENAI_API_KEY')

# Function to classify email
def classify_email(email_text):
    response = openai.Completion.create(
        model='gpt-3.5-turbo-instruct',
        prompt=f'Classify the following email:\n\n{email_text}\n\nCategories: Spam, Work, Personal, Promotion, Other',
        max_tokens=50
    )
    return response.choices[0].text.strip()

# Streamlit interface
st.title('Email Classifier')
st.write('Enter the email text below and click "Classify" to determine its category.')

email_text = st.text_area('Email Text', height=300)

if st.button('Classify'):
    if email_text:
        category = classify_email(email_text)
        st.write(f'The email is classified as: **{category}**')
    else:
        st.write('Please enter some text to classify.')