app.py

# app.py

import streamlit as st
from recommender import JobRecommender

def main():
    st.title("AI Job Recommender 🔍")
    st.markdown("Get personalized job recommendations using BERT AI and Jooble data.")
    
    # Your Jooble API key (replace with your actual API key)
    API_KEY = "11614a68-52db-4975-ad2b-c365991de2eb"
    recommender = JobRecommender(API_KEY)
    
    # User input fields
    keywords = st.text_input("Job Role", "Software Engineer")
    location = st.text_input("Location", "Remote")
    user_skills = st.text_area("Your Skills/Experience", 
                               "Python, Machine Learning, Software Development")
    
    if st.button("Get Recommendations"):
        with st.spinner("Fetching jobs and computing recommendations..."):
            recommender.refresh_job_data(keywords, location)
            recommendations = recommender.recommend_jobs(user_skills)
            
            if recommendations.empty:
                st.warning("No job recommendations found. Please try different keywords or location.")
            else:
                for idx, row in recommendations.iterrows():
                    st.subheader(row['title'])
                    st.caption(f"📍 {row.get('location', 'Location not specified')}")
                    st.markdown(f"**Company:** {row.get('company', 'Unknown company')}")
                    st.markdown(f"**Description:** {row['description'][:300]}...")
                    if 'link' in row and pd.notna(row['link']):
                        st.markdown(f"[Apply Here]({row['link']})")
                    st.divider()

if __name__ == "__main__":
    main()