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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.ChatCompletion.create(
model='gpt-3.5-turbo',
messages=[
{"role": "system", "content": "You are an email classifier."},
{"role": "user", "content": f"Classify the following email:\n\n{email_text}\n\nCategories: Spam, Work, Personal, Promotion, Other"}
]
)
return response['choices'][0]['message']['content'].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.')
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