MCP Jobs Recommender Agent

import streamlit as st 
from src.helper import extract_text_from_pdf,ask_groq
from src.job_api import fetch_linkedin_jobs,fetch_naukri_jobs


st.set_page_config(page_title="Job Recommneder",layout="wide")
st.title("AI Job Recommender")
st.markdown("Upload your resume and get recommnedations based on your skills and experience from Linkedin and Naukri.")

uploaded_file = st.file_uploader("Upload your resume in pdf format", type=['pdf'])

if uploaded_file:
    with st.spinner("Extracting text from your resume..."):
        resume_text = extract_text_from_pdf(uploaded_file)
    
    with st.spinner("Summarizing your resume..."):
        summary = ask_groq(f"Summarize this resume highlighting the skills,education and experience:\n\n{resume_text}",max_tokens=500)

    with st.spinner("Finding skill gaps...."):
        gaps = ask_groq(f"Analyze this resume and highlight the missing skills, certifications and experience needed for better job opportunities:\n\n{resume_text}",max_tokens=400)

    with st.spinner("Creating future roadmap..."):
        roadmap = ask_groq(f"Based on this resume, suggest a future roadmap to improve this person's career prospects (Skill to learn, certifications needed, industry exposure):\n\n{resume_text}",max_tokens=400)
    
    st.markdown("---")
    st.header("Resume Summary")

    st.header("📑 Resume Summary")
    st.markdown(f"<div style='background-color: #000000; padding: 15px; border-radius: 10px; font-size:16px; color:white;'>{summary}</div>", unsafe_allow_html=True)

    st.markdown("---")
    st.header("🛠️ Skill Gaps & Missing Areas")
    st.markdown(f"<div style='background-color: #000000; padding: 15px; border-radius: 10px; font-size:16px; color:white;'>{gaps}</div>", unsafe_allow_html=True)

    st.markdown("---")
    st.header("🚀 Future Roadmap & Preparation Strategy")
    st.markdown(f"<div style='background-color: #000000; padding: 15px; border-radius: 10px; font-size:16px; color:white;'>{roadmap}</div>", unsafe_allow_html=True)

    st.success("✅ Analysis Completed Successfully!")

    
    if st.button("Get Job Recommendations"):
        with st.spinner("Fetching job recommendations...."):
            keywords = ask_groq(f"Based on this resume suggest the best job titles and keywords for searching jobs. Give a comma-seperated list only, no explanation.\n\nSummary: {summary}",
                                max_tokens=100)
            
            search_keywords_clean = keywords.replace("\n","").strip()
        
        st.success(f"Extracted Job keywords:{search_keywords_clean}")

        with st.spinner("Fetching jobs from Linkedin and Naukri..."):
            linkedin_jobs = fetch_linkedin_jobs(search_keywords_clean,rows=60)
            naukri_jobs = fetch_naukri_jobs(search_keywords_clean,rows=60)
        
        st.markdown("---")
        st.header("Top Linkedin Jobs")

        if linkedin_jobs:
            for job in linkedin_jobs:
                st.markdown(f"**{job.get('title')}** at *{job.get('companyName')}*")
                st.markdown(f"- 📍 {job.get('location')}")
                st.markdown(f"- 🔗 [View Job]({job.get('link')})")
                st.markdown("---")
        else:
            st.warning("No LinkedIn jobs found.")

        st.markdown("---")
        st.header("💼 Top Naukri Jobs (India)")

        if naukri_jobs:
            for job in naukri_jobs:
                st.markdown(f"**{job.get('title')}** at *{job.get('companyName')}*")
                st.markdown(f"- 📍 {job.get('location')}")
                st.markdown(f"- 🔗 [View Job]({job.get('url')})")
                st.markdown("---")
        else:
            st.warning("No Naukri jobs found.")