import streamlit as st
from utils.parser import parse_cv, extract_education_level, identify_cv_type
from utils.cv_scoring import calculate_cv_score
from utils.suggestions import (
    get_certification_suggestions,
    get_higher_education_suggestions,
    get_visa_recommendations,
    get_career_advice,
    get_job_listings,
)
from utils.visualizer import generate_timeline
from PIL import Image
from fpdf import FPDF
import matplotlib.pyplot as plt
import tempfile
import io

# ------------------ PDF Generation Function ------------------
def generate_pdf_report(cv_type, education_level, score, score_breakdown, certs, edu, visa, advice, jobs, fig):
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size=12)

    pdf.cell(200, 10, txt="CV Analysis Report", ln=True, align="C")
    pdf.ln(10)

    pdf.cell(200, 10, txt=f"CV Type: {cv_type}", ln=True)
    pdf.cell(200, 10, txt=f"Education Level: {education_level}", ln=True)
    pdf.cell(200, 10, txt=f"CV Score: {score}/100", ln=True)
    pdf.ln(5)

    pdf.set_font("Arial", style="B", size=12)
    pdf.cell(200, 10, txt="Score Breakdown:", ln=True)
    pdf.set_font("Arial", size=12)
    for k, v in score_breakdown.items():
        pdf.cell(200, 10, txt=f"- {k}: {v}", ln=True)
    pdf.ln(5)

    def add_list_to_pdf(title, items):
        pdf.set_font("Arial", style="B", size=12)
        pdf.cell(200, 10, txt=title, ln=True)
        pdf.set_font("Arial", size=12)
        if isinstance(items, list):
            for item in items:
                pdf.multi_cell(0, 10, f"- {item}")
        else:
            pdf.multi_cell(0, 10, str(items))
        pdf.ln(5)

    add_list_to_pdf("Certification Suggestions:", certs)
    add_list_to_pdf("Higher Education Suggestions:", edu)
    add_list_to_pdf("Visa Recommendations:", visa)
    add_list_to_pdf("Career Advice:", advice)
    add_list_to_pdf("Job Listings:", jobs)

    # Save the figure as an image and insert into PDF
    with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmpfile:
        fig.savefig(tmpfile.name, bbox_inches='tight')
        pdf.add_page()
        pdf.image(tmpfile.name, x=10, y=20, w=pdf.w - 20)

    return pdf

# ------------------ Streamlit App ------------------
st.title("Smart CV Analyzer & Career Roadmap")

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

if uploaded_file is not None:
    with open("temp_cv.pdf", "wb") as f:
        f.write(uploaded_file.getbuffer())

    parsed_text = parse_cv("temp_cv.pdf")
    education_level = extract_education_level(parsed_text)
    cv_type = identify_cv_type(parsed_text)
    score, score_breakdown = calculate_cv_score(parsed_text, education_level)

    st.header("CV Analysis Results")
    st.write(f"**CV Type:** {cv_type}")
    st.write(f"**Education Level:** {education_level}")
    st.write(f"### Overall CV Score: {score} / 100")
    st.write("### Score Breakdown:")
    for k, v in score_breakdown.items():
        st.write(f"- {k}: {v}")

    with st.expander("Certification Suggestions"):
        certs = get_certification_suggestions(parsed_text)
        st.write(certs)

    with st.expander("Higher Education Suggestions"):
        edu = get_higher_education_suggestions(parsed_text)
        st.write(edu)

    with st.expander("Visa Recommendations"):
        visa = get_visa_recommendations(parsed_text)
        st.write(visa)

    with st.expander("Career Advice"):
        advice = get_career_advice(parsed_text)
        st.write(advice)

    with st.expander("Job Listings"):
        jobs = get_job_listings(parsed_text)
        for job in jobs:
            st.write(f"- {job}")

    st.header("📈 Career Roadmap Timeline")
    fig = generate_timeline(cv_type, education_level, score)
    st.pyplot(fig)

    # --- PDF Download Button ---
    # --- PDF Download Button ---
    st.subheader("Download Report")

    # Generate the PDF as a string
    pdf_bytes = generate_pdf_report(cv_type, education_level, score, score_breakdown, certs, edu, visa, advice, jobs, fig).output(dest='S').encode('latin1')

    # Display a single download button
    st.download_button(
        label="📄 Download CV Analysis Report (PDF)",
        data=pdf_bytes,
        file_name="cv_analysis_report.pdf",
        mime="application/pdf"
    )