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| import streamlit as st | |
| from langchain_community.document_loaders import WebBaseLoader | |
| from chains import Chain | |
| # from portfolio import Portfolio | |
| from utils import clean_text, extract_text_from_pdf | |
| def create_streamlit_app(llm, clean_text): | |
| st.title("📧 Welcome to Cold E-Mail Generator") | |
| # PDF upload section | |
| uploaded_file = st.file_uploader("Upload your resume as PDF", type=["pdf"]) | |
| pdf_text = extract_text_from_pdf(uploaded_file) | |
| # if pdf_text: | |
| # st.text_area("Extracted Text", value=pdf_text, height=300) | |
| url_input = st.text_input("Enter the URL of Job Posting:", value="https://careers.myntra.com/job-detail/?id=7431200002") | |
| submit_button = st.button("Generate E-mail") | |
| if submit_button: | |
| try: | |
| loader = WebBaseLoader([url_input]) | |
| data = clean_text(loader.load().pop().page_content) # cleans any unnecessary garbage text | |
| jobs = llm.extract_jobs(data) # create json objects for the job | |
| for job in jobs: # this is for if one web page has multiple jobs | |
| # skills = job.get('skills', []) | |
| summarized_text = llm.summarize_pdf(pdf_text) | |
| # st.text_area(summarized_text) | |
| email = llm.write_mail(job, summarized_text) # write the email | |
| # st.code(email, language='markdown') | |
| st.text_area("Email is as follows", value=email, height=500) | |
| # st.code('hello') | |
| except Exception as e: | |
| st.error(f"An Error Occurred: {e}") | |
| if __name__ == "__main__": | |
| chain = Chain() | |
| # portfolio = Portfolio() | |
| st.set_page_config(layout="wide", page_title="Cold Email Generator", page_icon="📧") | |
| create_streamlit_app(chain, clean_text) | |