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import gradio as gr
import requests
import os
from bs4 import BeautifulSoup # For scraping company and role info
# Load API keys securely from environment variables
proxycurl_api_key = os.getenv("PROXYCURL_API_KEY") # Proxycurl API key
groq_api_key = os.getenv("GROQ_CLOUD_API_KEY") # Groq Cloud API key
class EmailAgent:
def __init__(self, linkedin_url, company_name, role, word_limit, user_name, email, phone, linkedin):
self.linkedin_url = linkedin_url
self.company_name = company_name
self.role = role
self.word_limit = word_limit
self.user_name = user_name
self.email = email
self.phone = phone
self.linkedin = linkedin
self.bio = None
self.skills = []
self.experiences = []
self.company_info = None
self.role_description = None
# Reason: Decide what information is needed and if we need to take additional steps
def reason_about_data(self):
print("Reasoning: Deciding what data we need...")
if not self.linkedin_url:
print("Warning: LinkedIn URL missing. Proceeding with default bio.")
if not self.company_name:
print("Warning: Company name missing. Proceeding with default company info.")
if not self.role:
print("Warning: Role missing. We will use general logic for the role.")
# Action: Fetch LinkedIn data via Proxycurl (acting based on reasoning)
def fetch_linkedin_data(self):
if not self.linkedin_url:
print("Action: No LinkedIn URL provided, using default bio.")
self.bio = "A professional with diverse experience."
self.skills = ["Adaptable", "Hardworking"]
self.experiences = ["Worked across various industries"]
else:
print("Action: Fetching LinkedIn data via Proxycurl.")
headers = {"Authorization": f"Bearer {proxycurl_api_key}"}
url = f"https://nubela.co/proxycurl/api/v2/linkedin?url={self.linkedin_url}"
response = requests.get(url, headers=headers)
if response.status_code == 200:
data = response.json()
self.bio = data.get("summary", "No bio available")
self.skills = data.get("skills", [])
self.experiences = data.get("experiences", [])
else:
print("Error: Unable to fetch LinkedIn profile. Using default bio.")
self.bio = "A professional with diverse experience."
self.skills = ["Adaptable", "Hardworking"]
self.experiences = ["Worked across various industries"]
# Action: Fetch company information via Proxycurl or use defaults
def fetch_company_info(self):
if not self.company_name:
print("Action: No company name provided, using default company info.")
self.company_info = "A leading company in its field, offering innovative solutions."
else:
print(f"Action: Fetching company info for {self.company_name}.")
headers = {"Authorization": f"Bearer {proxycurl_api_key}"}
url = f"https://nubela.co/proxycurl/api/v2/linkedin/company?company_name={self.company_name}"
response = requests.get(url, headers=headers)
if response.status_code == 200:
data = response.json()
self.company_info = data.get("description", "No detailed company info available.")
else:
print(f"Error: Unable to fetch company info for {self.company_name}. Using default info.")
self.company_info = "A leading company in its field, offering innovative solutions."
# Action: Scrape the company's website for role-specific information or use defaults
def scrape_role_from_website(self):
print(f"Action: Scraping role description from the company's website for {self.role}.")
if not self.company_name:
print("Error: No company name or URL provided for scraping.")
return False
# Try scraping the website for role descriptions
try:
response = requests.get(f"https://{self.company_name}.com/careers")
if response.status_code == 200:
soup = BeautifulSoup(response.text, 'html.parser')
role_descriptions = soup.find_all(string=lambda text: self.role.lower() in text.lower())
if role_descriptions:
self.role_description = role_descriptions[0]
print(f"Found role description: {self.role_description}")
return True
else:
print(f"No specific role description found on the website for {self.role}.")
return False
else:
print(f"Error: Unable to reach company's website at {self.company_name}.com.")
return False
except Exception as e:
print(f"Error during scraping: {e}")
return False
# Action: Use default logic for role description if no role is available
def use_default_role_description(self):
print(f"Action: Using default logic for the role of {self.role}.")
self.role_description = f"The role of {self.role} at {self.company_name} involves mentoring and leading teams in innovative technology solutions."
# Reflection: Check if we have enough data to generate the email
def reflect_on_data(self):
print("Reflection: Do we have enough data?")
if not self.bio or not self.skills or not self.company_info:
print("Warning: Some critical information is missing. Proceeding with default values.")
return True
# Final Action: Generate the email using Groq Cloud LLM based on gathered data
def generate_email(self):
print("Action: Generating the email with the gathered information.")
prompt = f"""
Write a professional email applying for the {self.role} position at {self.company_name}.
The candidate’s bio is: {self.bio}.
Focus on relevant skills and experiences from LinkedIn, such as {', '.join(self.skills)},
that directly align with the role of {self.role}.
Highlight only the skills and experiences that relate to leadership, mentoring, technology, and innovation.
The company info is: {self.company_info}.
The role involves: {self.role_description}.
End the email with this signature:
Best regards,
{self.user_name}
Email: {self.email}
Phone: {self.phone}
LinkedIn: {self.linkedin}
The email should not exceed {self.word_limit} words.
"""
url = "https://api.groq.com/openai/v1/chat/completions"
headers = {"Authorization": f"Bearer {groq_api_key}", "Content-Type": "application/json"}
data = {
"messages": [{"role": "user", "content": prompt}],
"model": "llama3-8b
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