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")

# 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 get company information via Proxycurl Company API
def get_company_info(company_name):
    headers = {
        "Authorization": f"Bearer {proxycurl_api_key}",
    }
    url = f"https://nubela.co/proxycurl/api/v2/linkedin/company?company_name={company_name}"
    
    response = requests.get(url, headers=headers)
    
    if response.status_code == 200:
        data = response.json()
        company_info = data.get("description", "No detailed company info available.")
        return company_info
    else:
        return "Error: Unable to fetch company information."

# Placeholder for role description; could be enhanced to scrape or fetch real role data
def get_role_description(role_name, company_name):
    return f"The role of {role_name} at {company_name} involves..."

# 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, role_description):
    url = "https://api.groq.com/openai/v1/chat/completions"
    headers = {
        "Authorization": f"Bearer {groq_api_key}",
        "Content-Type": "application/json",
    }
    
    # New, detailed prompt to gather information about the company and role, and generate a compelling email
    prompt = f"""
    Write a professional and tailored email applying for the {role} position at {company_name}. 
    The candidate’s bio is: {bio}.
    
    The email should:
    - Be professional, engaging, and customized to the company's culture and the role’s requirements.
    - Include relevant company details: {company_info}. 
    - Highlight the candidate’s skills and experience, mapping them directly to the job requirements. The role description is: {role_description}.
    - Emphasize how the candidate’s background aligns with the company’s values and mission.
    - Attract the company's attention by focusing on how the candidate's background can bring value to the role and the company's future goals.
    - Use a tone that is persuasive but not overly promotional.
    - End with a strong call to action, encouraging the company to schedule an interview to discuss how the candidate can contribute to their success.

    Structure the email as follows:
    1. **Introduction**: Briefly introduce the candidate and state the role they are applying for.
    2. **Skills & Experience**: Creatively map the candidate’s skills and experience to the job's key requirements and how these will benefit the company.
    3. **Alignment with the Company**: Emphasize how the candidate’s background fits with the company's mission, values, and goals.
    4. **Call to Action**: Encourage the company to schedule an interview to further discuss the candidate’s fit for the role.
    
    The writing style should be professional, concise, and leave a strong, memorable impression on the company.
    """
    
    # 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."  # Default bio if no LinkedIn URL is provided
    
    # Step 2: Fetch company information and role description
    company_info = get_company_info(company_name)
    role_description = get_role_description(role, company_name)
    
    # Step 3: Generate the email using Groq Cloud LLM
    generated_email = generate_and_correct_email(bio, company_name, role, company_info, role_description)
    
    # 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()