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| import streamlit as st | |
| from langchain_groq import ChatGroq | |
| from langchain_core.prompts import PromptTemplate | |
| import fitz # PyMuPDF | |
| import requests | |
| from bs4 import BeautifulSoup | |
| # Initialize the LLM with your Groq API key | |
| llm = ChatGroq( | |
| temperature=0, | |
| groq_api_key='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', # Replace with your Groq API key | |
| model_name="llama-3.1-70b-versatile" | |
| ) | |
| # Function to extract text from a PDF file | |
| def extract_text_from_pdf(pdf_file): | |
| text = "" | |
| with fitz.open(stream=pdf_file.read(), filetype="pdf") as doc: | |
| for page in doc: | |
| text += page.get_text() | |
| return text | |
| # Function to extract the job description from a given URL | |
| def extract_job_description(job_link): | |
| try: | |
| response = requests.get(job_link) | |
| response.raise_for_status() | |
| soup = BeautifulSoup(response.text, 'html.parser') | |
| job_description = soup.get_text(separator='\n') | |
| return job_description.strip() | |
| except Exception as e: | |
| st.error(f"Error fetching job description: {e}") | |
| return "" | |
| # Function to extract requirements from the job description using ChatGroq | |
| def extract_requirements(job_description): | |
| prompt_text = f""" | |
| The following is a job description: | |
| {job_description} | |
| Extract the list of job requirements, qualifications, and skills from the job description. Provide them as a numbered list. | |
| Requirements: | |
| """ | |
| prompt = PromptTemplate.from_template(prompt_text) | |
| chain = prompt | llm | |
| response = chain.invoke({}) | |
| requirements = response.content.strip() | |
| return requirements | |
| # Function to generate an email using ChatGroq | |
| def generate_email(job_description, requirements, resume_text): | |
| prompt_text = f""" | |
| Given the following job description: | |
| {job_description} | |
| And the following extracted requirements: | |
| {requirements} | |
| And the following resume text: | |
| {resume_text} | |
| Write a cold email as Adithya S Nair, a recent graduate in Computer Science with a focus on Artificial Intelligence and Machine Learning. Highlight your relevant skills and experiences from the resume, emphasizing how you, as a fresher, can bring value to the client’s company. Mention key projects, internships, and any leadership experiences that align with the job description and requirements. Ensure the email is concise and professional. | |
| Email: | |
| """ | |
| prompt = PromptTemplate.from_template(prompt_text) | |
| chain = prompt | llm | |
| response = chain.invoke({}) | |
| email_text = response.content.strip() | |
| return email_text | |
| # Streamlit App | |
| def main(): | |
| st.title("Automated Email Generator") | |
| st.write(""" | |
| This application generates a personalized email based on a job posting and your resume. | |
| """) | |
| # Input fields | |
| job_link = st.text_input("Enter the job link:") | |
| uploaded_file = st.file_uploader("Upload your resume (PDF format):", type="pdf") | |
| if st.button("Generate Email"): | |
| if not job_link: | |
| st.error("Please enter a job link.") | |
| return | |
| if not uploaded_file: | |
| st.error("Please upload your resume.") | |
| return | |
| with st.spinner("Processing..."): | |
| # Extract job description | |
| job_description = extract_job_description(job_link) | |
| if not job_description: | |
| st.error("Failed to extract job description.") | |
| return | |
| # Extract requirements | |
| requirements = extract_requirements(job_description) | |
| if not requirements: | |
| st.error("Failed to extract requirements.") | |
| return | |
| # Extract resume text | |
| resume_text = extract_text_from_pdf(uploaded_file) | |
| if not resume_text: | |
| st.error("Failed to extract text from resume.") | |
| return | |
| # Generate email | |
| email_text = generate_email(job_description, requirements, resume_text) | |
| if email_text: | |
| st.subheader("Generated Email:") | |
| st.write(email_text) | |
| else: | |
| st.error("Failed to generate email.") | |
| if __name__ == "__main__": | |
| main() | |