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import gradio as gr
import requests
import os
from datetime import datetime # Import datetime for date validation
# Load Groq Cloud API key securely from environment variables
groq_api_key = os.getenv("GROQ_CLOUD_API_KEY")
# Scraping function to fetch user public data (for demo purposes, we will simulate this)
def fetch_public_data(name, dob, city):
# Simulate fetched bio data for demonstration purposes
bio = f"{name} is a software engineer from {city} with over 10 years of experience. Known for work in AI, cloud computing, and leadership in various engineering teams."
# Since we're asking the user to input their LinkedIn URL, we'll no longer scrape LinkedIn.
linkedin_profile = None
return bio, linkedin_profile
# Helper function to call Groq Cloud LLM API to generate and correct the email
def generate_and_correct_email(bio, company_name, role):
url = "https://api.groq.com/openai/v1/chat/completions" # Updated API URL for Groq Cloud
headers = {
"Authorization": f"Bearer {groq_api_key}", # Use the API key securely from environment
"Content-Type": "application/json",
}
# Updated prompt to ask the model to generate AND correct the email
prompt = f"""
Write a professional email applying for a {role} position at {company_name}. Use this bio: {bio}.
The email should include an introduction, relevant experience, skills, and a closing.
Ensure that the email is grammatically correct and formal.
"""
# Construct the data payload for the API request
data = {
"messages": [
{
"role": "user",
"content": prompt
}
],
"model": "llama3-8b-8192" # Use the appropriate model from Groq Cloud
}
response = requests.post(url, headers=headers, json=data)
if response.status_code == 200:
# Extract the generated email content from the API response
return response.json()["choices"][0]["message"]["content"].strip()
else:
# Print or log the error for debugging
print(f"Error: {response.status_code}, {response.text}")
return "Error generating email. Please check your API key or try again later."
# Function to validate the DOB format (DD-MM-YYYY)
def validate_dob(dob):
try:
# Attempt to parse the DOB to the expected format
datetime.strptime(dob, "%d-%m-%Y")
return True
except ValueError:
# Return False if the format is invalid
return False
# Main function to create the email and allow for saving, editing, or copying
def create_email(name, dob, city, company_name, role, email, phone, linkedin_profile):
# Validate the DOB format (DD-MM-YYYY)
if not validate_dob(dob):
return "Invalid Date of Birth format. Please use DD-MM-YYYY."
# Step 1: Fetch public data based on user info (no need to scrape LinkedIn anymore)
bio, _ = fetch_public_data(name, dob, city) # We'll use the provided LinkedIn URL
# Step 2: Generate the email using Groq Cloud LLM
generated_email = generate_and_correct_email(bio, company_name, role)
# Step 3: Add the user's email, phone number, and LinkedIn profile to the signature
signature = f"\n\nBest regards,\n{name}\nEmail: {email}\nPhone: {phone}\nLinkedIn: {linkedin_profile}"
# Return the final polished email with the signature
return generated_email + signature
# Define interface with Gradio
def gradio_ui():
# Define inputs
name_input = gr.Textbox(label="Name", placeholder="Enter your name")
dob_input = gr.Textbox(label="Date of Birth", placeholder="Enter your date of birth (DD-MM-YYYY)")
city_input = gr.Textbox(label="City", placeholder="Enter your city of residence")
company_name_input = gr.Textbox(label="Company Name", placeholder="Enter the name of the company you are applying to")
role_input = gr.Textbox(label="Role", placeholder="Enter the role you are applying for")
email_input = gr.Textbox(label="Email Address", placeholder="Enter your email address")
phone_input = gr.Textbox(label="Phone Number", placeholder="Enter your phone number")
linkedin_input = gr.Textbox(label="LinkedIn URL", placeholder="Enter your LinkedIn profile URL") # New input field for LinkedIn URL
# Define output for the generated email
email_output = gr.Textbox(label="Generated Email", placeholder="Your generated email will appear here", lines=10)
# Create the Gradio interface
demo = gr.Interface(
fn=create_email, # Function to call when the user submits
inputs=[name_input, dob_input, city_input, company_name_input, role_input, email_input, phone_input, linkedin_input],
outputs=[email_output],
title="Email Writing AI Agent",
description="Generate a professional email for a job application by providing your basic info.",
allow_flagging="never" # Disable flagging
)
# Launch the Gradio app
demo.launch()
# Start the Gradio app when running the script
if __name__ == "__main__":
gradio_ui()