app.py

import gradio as gr
import requests
import os

# Load API keys securely from environment variables
proxycurl_api_key = os.getenv("PROXYCURL_API_KEY")  # Add your Proxycurl API key to your environment variables
groq_api_key = os.getenv("GROQ_CLOUD_API_KEY")
serpapi_key = os.getenv("SERPAPI_API_KEY")  # Add your SerpAPI key to your environment variables

# Function to use Proxycurl API to get the LinkedIn profile data
def get_linkedin_profile_via_proxycurl(linkedin_profile_url):
    headers = {
        "Authorization": f"Bearer {proxycurl_api_key}",
    }
    url = f"https://nubela.co/proxycurl/api/v2/linkedin?url={linkedin_profile_url}"
    
    response = requests.get(url, headers=headers)
    
    if response.status_code == 200:
        data = response.json()
        bio = data.get("summary", "No bio available")
        return bio
    else:
        return "Error: Unable to fetch LinkedIn profile"

# Function to use SerpAPI to fetch company and role information
def get_company_and_role_info(company_name, role):
    query = f"{company_name} {role} job description"
    url = f"https://serpapi.com/search.json?engine=google&q={query}&api_key={serpapi_key}"
    
    response = requests.get(url)
    
    if response.status_code == 200:
        results = response.json()
        # Extract information about the company and role from the search results
        company_info = []
        for result in results.get("organic_results", []):
            if "linkedin.com" not in result.get("link", ""):
                company_info.append(result.get("snippet", ""))
        return "\n".join(company_info[:2])  # Limit to 2 top results
    else:
        return "Error fetching company and role information."

# Helper function to call Groq Cloud LLM API to generate and correct the email
def generate_and_correct_email(bio, company_name, role, company_info):
    url = "https://api.groq.com/openai/v1/chat/completions"
    headers = {
        "Authorization": f"Bearer {groq_api_key}",
        "Content-Type": "application/json",
    }
    
    # Updated prompt with a focus on professionalism, relevance, and creativity
    prompt = f"""
    Write a professional, concise, and compelling email applying for the {role} position at {company_name}. 
    Use this bio to highlight the candidate's skills and experience: {bio}.
    
    Additionally, here is some information about the company and the role:
    {company_info}
    
    The email should:
    - Be professional, creative, and tailored to the company and role.
    - Creatively emphasize the candidate’s key skills and experience, aligning them with the job's requirements.
    - Attract the company's attention by focusing on how the candidate's background can bring value to the role and company.
    - Be concise but engaging, leaving a strong impression on the recruiter.
    - Include a clear call to action, encouraging the company to interview the candidate.
    
    Structure the email as follows:
    1. **Introduction**: Briefly introduce the candidate and the role they are applying for.
    2. **Skills & Experience**: Creatively map the candidate’s skills and experience to the job's key requirements, focusing on relevance.
    3. **Value Proposition**: Highlight how the candidate’s experience will contribute to the company's success.
    4. **Call to Action**: Encourage the company to set up an interview to explore how the candidate can add value.
    """
    
    # Construct the data payload for the API request
    data = {
        "messages": [
            {
                "role": "user",
                "content": prompt
            }
        ],
        "model": "llama3-8b-8192"
    }
    
    response = requests.post(url, headers=headers, json=data)
    
    if response.status_code == 200:
        return response.json()["choices"][0]["message"]["content"].strip()
    else:
        print(f"Error: {response.status_code}, {response.text}")
        return "Error generating email. Please check your API key or try again later."

# Main function to create the email and allow for saving, editing, or copying
def create_email(name, company_name, role, email, phone, linkedin_profile_url):
    # Step 1: Fetch LinkedIn profile using Proxycurl API if LinkedIn URL is provided
    if linkedin_profile_url:
        bio = get_linkedin_profile_via_proxycurl(linkedin_profile_url)
    else:
        bio = f"{name} is a professional."
    
    # Step 2: Fetch company and role information using SerpAPI
    company_info = get_company_and_role_info(company_name, role)
    
    # Step 3: Generate the email using Groq Cloud LLM
    generated_email = generate_and_correct_email(bio, company_name, role, company_info)
    
    # Step 4: 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_url if linkedin_profile_url else 'Not provided'}"

    # Ensure the body doesn't include any redundant 'Best regards' and just append our signature
    if "Best regards" in generated_email:
        generated_email = generated_email.split("Best regards")[0].strip()

    # 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")
    
    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 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, 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()