Update app.py

app.py

@@ -1,78 +1,60 @@
 import streamlit as st
 from utils import (
+    detect_cv_field,
     get_skills_suggestions,
-    get_certification_recommendations,
-    get_scholarship_suggestions,
+    get_certifications,
+    get_scholarships,
     get_education_opportunities,
-    get_visa_pathways,
-    get_job_recommendations,
-    get_cv_score,
-    get_field_classification,
-    get_personalized_advice,
+    get_visa_opportunities,
 )
 
-st.set_page_config(page_title="Smart CV Analyzer & Career Roadmap", layout="wide")
+st.set_page_config(page_title="Universal Smart CV Analyzer", layout="wide")
 
-st.title("📄 Universal Smart CV Analyzer & 🌍 Career Roadmap Generator")
-st.markdown("Upload your CV and get a detailed analysis including personalized job suggestions, skill-building advice, education and visa guidance, and a tailored career roadmap.")
+st.title("📄 Universal Smart CV Analyzer & Career Roadmap Generator")
 
-uploaded_file = st.file_uploader("Upload your CV (.txt or .pdf)", type=["txt", "pdf"])
+uploaded_file = st.file_uploader("Upload your CV (TXT or PDF recommended)", type=["txt", "pdf"])
 
 if uploaded_file:
-    file_ext = uploaded_file.name.split('.')[-1]
-    if file_ext == "txt":
-        cv_text = uploaded_file.read().decode("utf-8")
-    elif file_ext == "pdf":
+    file_text = uploaded_file.read()
+    try:
+        text = file_text.decode("utf-8")
+    except UnicodeDecodeError:
         import PyPDF2
-        reader = PyPDF2.PdfReader(uploaded_file)
-        cv_text = "\n".join(page.extract_text() for page in reader.pages if page.extract_text())
-    else:
-        st.error("Unsupported file format.")
-        st.stop()
-
-    with st.spinner("Analyzing your CV..."):
-        score = get_cv_score(cv_text)
-        field = get_field_classification(cv_text)
-        skills = get_skills_suggestions(cv_text)
-        certs = get_certification_recommendations(cv_text)
-        scholarships = get_scholarship_suggestions(cv_text)
-        education = get_education_opportunities(cv_text)
-        visa = get_visa_pathways(cv_text, country="USA")
-        jobs = get_job_recommendations(cv_text, location="USA")
-        advice = get_personalized_advice(cv_text)
-
-    st.header("📊 CV Summary")
-    st.write(f"**Score:** {score}/100")
-    st.write(f"**Field/Domain:** {field}")
-
-    st.header("💡 Personalized Career Advice")
-    st.success(advice)
-
-    st.header("🧠 Recommended Skills to Learn")
-    for skill in skills:
-        st.markdown(f"- {skill}")
-
-    st.header("🎓 Recommended Certifications")
-    for cert in certs:
-        st.markdown(f"- {cert}")
-
-    st.header("🎯 Scholarship Opportunities")
-    for s in scholarships:
-        st.markdown(f"- {s}")
-
-    st.header("🏫 Education Paths")
-    for edu in education:
-        st.markdown(f"- {edu}")
-
-    st.header("🛂 Visa Pathways")
-    for v in visa:
-        st.markdown(f"- {v}")
-
-    st.header("💼 Job Opportunities (USA)")
-    for job in jobs:
-        st.subheader(job.get("title", "N/A"))
-        st.markdown(f"**Company:** {job.get('company', 'Unknown')}")
-        st.markdown(f"**Location:** {job.get('location', 'Unknown')}")
-        st.markdown(f"**Description:** {job.get('description', '')[:300]}...")
-        st.markdown(f"[Apply Here]({job.get('url', '#')})")
-        st.markdown("---")
+        pdf_reader = PyPDF2.PdfReader(uploaded_file)
+        text = ""
+        for page in pdf_reader.pages:
+            text += page.extract_text()
+
+    st.subheader("CV Summary")
+    st.write(text[:1000] + "...")
+
+    # --- Step 1: Identify field ---
+    field = detect_cv_field(text)
+    st.success(f"🧭 Detected Field: **{field.title()}**")
+
+    # --- Step 2: Personalized Suggestions ---
+    st.subheader("🔧 Recommended Skill Improvements")
+    skills = get_skills_suggestions(field)
+    st.write(skills)
+
+    st.subheader("📜 Relevant Certifications")
+    certs = get_certifications(field)
+    st.write(certs)
+
+    st.subheader("🎓 Scholarship Opportunities")
+    scholarships = get_scholarships(field)
+    st.write(scholarships)
+
+    st.subheader("🏫 Higher Education Opportunities")
+    education = get_education_opportunities(field)
+    st.write(education)
+
+    st.subheader("🌍 Suggested Visa Pathways")
+    visa_paths = get_visa_opportunities(field)
+    st.write(visa_paths)
+
+    # --- Final Counseling Advice ---
+    st.subheader("🧑‍💼 Career Counselor Advice")
+    st.markdown(f"""
+    Based on your background in **{field.title()}**, consider deepening your expertise in the top in-demand tools and seeking international opportunities through scholarships and visa-friendly countries. You may benefit from completing a few certifications like **{certs[0]}** and **{certs[1]}**. Keep your LinkedIn profile up to date and connect with professionals in this space.
+    """)