from flask import Flask, render_template, request, redirect, url_for, send_file
import os
from flask import session
from resume_parser import extract_resume_text
from matching_engine import calculate_similarity, get_top_job_matches
from scam_model import predict_scam
from skill_analyzer import analyze_skill_gap
from feedback_engine import generate_feedback
from skill_extractor import extract_skills
from warning_engine import detect_warnings

app = Flask(__name__)
app.config["UPLOAD_FOLDER"] = "uploads"


# ---------------- HOME ----------------
@app.route("/")
def index():
    return render_template("index.html")


# ---------------- PROCESS RESUME ----------------
@app.route("/process", methods=["POST"])
def process():
    resume_text = request.form.get("resume_text", "").strip()
    uploaded_file = request.files.get("resume_file")

    final_resume = ""

    if uploaded_file and uploaded_file.filename != "":
        filepath = os.path.join(app.config["UPLOAD_FOLDER"], uploaded_file.filename)
        uploaded_file.save(filepath)
        final_resume = extract_resume_text(filepath)

    elif resume_text:
        final_resume = resume_text

    else:
        return redirect(url_for("index"))

    return render_template("upload_jd.html", resume=final_resume)


# ---------------- ANALYZE ----------------
@app.route("/analyze", methods=["POST"])
def analyze():
    resume = request.form.get("resume", "").strip()
    jd = request.form.get("jd_text", "").strip()

    if not resume or not jd:
        return "Missing resume or job description", 400

    match_score = calculate_similarity(resume, jd)
    jobs = get_top_job_matches(resume)
    skills = extract_skills(resume)

    skill_data = analyze_skill_gap(resume, jd)
    if not isinstance(skill_data, dict):
        skill_data = {"matched": [], "missing": [], "match_ratio": 0}

    feedback = generate_feedback(resume, skill_data)

    return render_template(
        "result.html",
        match_score=match_score,
        jobs=jobs,
        skills=skills,
        resume=resume,
        jd=jd,
        skill_data=skill_data,
        feedback=feedback
    )


# ---------------- SCAM CHECKER ----------------
@app.route("/scam-checker")
def scam_checker():
    return render_template("scam_checker.html")


@app.route("/analyze-scam", methods=["POST"])
def analyze_scam():
    email = request.form.get("email", "")
    title = request.form.get("title", "")
    description = request.form.get("description", "")

    score, label = predict_scam(email, title, description)
    warnings = detect_warnings(email, title, description)

    return render_template(
        "scam_result.html",
        result=label,
        score=score,
        warnings=warnings
    )

# ---------------- DOWNLOAD REPORT ----------------
@app.route("/download-report", methods=["POST"])
def download_report():
    from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
    from reportlab.lib.styles import getSampleStyleSheet
    from flask import send_file, request

    pdf_path = "report.pdf"
    doc = SimpleDocTemplate(pdf_path)
    styles = getSampleStyleSheet()
    elements = []

    resume = request.form.get("resume", "")
    jd = request.form.get("jd_text", "")
    match_score = request.form.get("match_score", 0)

    elements.append(Paragraph("JobShield AI Report", styles["Title"]))
    elements.append(Spacer(1, 20))

    elements.append(Paragraph(f"<b>Match Score:</b> {match_score}%", styles["BodyText"]))
    elements.append(Spacer(1, 10))

    elements.append(Paragraph("<b>Resume Preview:</b>", styles["Heading2"]))
    elements.append(Paragraph(resume[:1000], styles["BodyText"]))

    elements.append(Spacer(1, 10))

    elements.append(Paragraph("<b>Job Description Preview:</b>", styles["Heading2"]))
    elements.append(Paragraph(jd[:1000], styles["BodyText"]))

    doc.build(elements)

    return send_file(pdf_path, as_attachment=True)


# ---------------- RUN ----------------
if __name__ == "__main__":
    os.makedirs(app.config["UPLOAD_FOLDER"], exist_ok=True)
    app.run(host="0.0.0.0", port=7860)
    
    
# from flask import Flask, render_template, request, redirect, url_for, send_file, session
# import os

# from resume_parser import extract_resume_text
# from matching_engine import calculate_similarity, get_top_job_matches
# from scam_model import predict_scam
# from skill_analyzer import analyze_skill_gap
# from feedback_engine import generate_feedback
# from skill_extractor import extract_skills
# from warning_engine import detect_warnings

# app = Flask(__name__)
# app.secret_key = "secret_key_change_this"
# app.config["UPLOAD_FOLDER"] = "uploads"


# # ---------------- HOME ----------------
# @app.route("/")
# def index():
#     return render_template("index.html")


# # ---------------- PROCESS RESUME ----------------
# @app.route('/process', methods=['POST'])
# def process():

#     resume_text = request.form.get("resume_text", "").strip()
#     uploaded_file = request.files.get("resume_file")

#     final_resume = ""

#     if uploaded_file and uploaded_file.filename != "":
#         filepath = os.path.join(app.config["UPLOAD_FOLDER"], uploaded_file.filename)
#         uploaded_file.save(filepath)
#         final_resume = extract_resume_text(filepath)

#     elif resume_text:
#         final_resume = resume_text

#     else:
#         return redirect(url_for("index"))

#     # store in session (IMPORTANT FIX)
#     session["resume"] = final_resume

#     return render_template("upload_jd.html", resume=final_resume)


# # ---------------- ANALYZE ----------------
# @app.route('/analyze', methods=['POST'])
# def analyze():

#     resume = request.form.get("resume", "").strip()
#     jd = request.form.get("jd_text", "").strip()

#     print("RESUME LENGTH:", len(resume))
#     print("JD LENGTH:", len(jd))

#     if not resume or not jd:
#         return "Missing resume or job description", 400

#     match_score = calculate_similarity(resume, jd)
#     jobs = get_top_job_matches(resume)
#     skills = extract_skills(resume)

#     skill_data = analyze_skill_gap(resume, jd)
#     if not isinstance(skill_data, dict):
#         skill_data = {"matched": [], "missing": [], "match_ratio": 0}

#     feedback = generate_feedback(resume, skill_data)

#     # store for PDF
#     session["match_score"] = match_score
#     session["resume"] = resume
#     session["jd"] = jd
#     session["skill_data"] = skill_data
#     session["feedback"] = feedback

#     return render_template(
#         "result.html",
#         match_score=match_score,
#         jobs=jobs,
#         skills=skills,
#         resume=resume[:300],
#         jd=jd[:300],
#         skill_data=skill_data,
#         feedback=feedback
#     )


# # ---------------- SCAM CHECKER ----------------
# @app.route('/scam-checker')
# def scam_checker():
#     return render_template("scam_checker.html")


# @app.route('/analyze-scam', methods=['POST'])
# def analyze_scam():

#     email = request.form.get("email", "")
#     title = request.form.get("title", "")
#     description = request.form.get("description", "")

#     score, label = predict_scam(email, title, description)
#     warnings = detect_warnings(email, title, description)

#     if label == "Scam":
#         precautions = [
#             "Do not pay money",
#             "Do not share bank details",
#             "Verify company website",
#             "Check LinkedIn presence",
#             "Be careful of urgency traps"
#         ]
#     elif label == "Medium Risk":
#         precautions = [
#             "Verify recruiter email",
#             "Check reviews",
#             "Avoid suspicious links"
#         ]
#     else:
#         precautions = ["Still verify company authenticity"]

#     return render_template(
#         "scam_result.html",
#         result=label,
#         score=score,
#         precautions=precautions,
#         warnings=warnings
#     )


# # ---------------- DOWNLOAD PDF REPORT ----------------
# @app.route('/download-report')
# def download_report():

#     from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
#     from reportlab.lib.styles import getSampleStyleSheet

#     pdf_path = os.path.join("/tmp", "report.pdf")

#     doc = SimpleDocTemplate(pdf_path)
#     styles = getSampleStyleSheet()
#     elements = []

#     match_score = session.get("match_score", 0)
#     resume = session.get("resume", "")
#     jd = session.get("jd", "")

#     skill_data = session.get("skill_data", {"matched": [], "missing": []})
#     feedback = session.get("feedback", [])

#     elements.append(Paragraph("JobShield AI Report", styles['Title']))
#     elements.append(Spacer(1, 20))

#     elements.append(Paragraph(f"<b>Match Score:</b> {match_score}%", styles['BodyText']))
#     elements.append(Spacer(1, 10))

#     elements.append(Paragraph("<b>Matched Skills:</b>", styles['Heading2']))
#     for skill in skill_data.get("matched", []):
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     elements.append(Paragraph("<b>Missing Skills:</b>", styles['Heading2']))
#     for skill in skill_data.get("missing", []):
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     elements.append(Paragraph("<b>Resume Feedback:</b>", styles['Heading2']))
#     for f in feedback:
#         elements.append(Paragraph(f"• {f}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     elements.append(Paragraph("<b>Resume Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(resume[:1000], styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     elements.append(Paragraph("<b>Job Description Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(jd[:1000], styles['BodyText']))

#     doc.build(elements)

#     return send_file(pdf_path, as_attachment=True)


# # ---------------- RUN ----------------
# if __name__ == "__main__":
#     os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
#     print("Starting JobShield AI...")
#     app.run(host="0.0.0.0", port=7860)







# from flask import Flask, render_template, request, redirect, url_for, send_file
# import os

# from resume_parser import extract_resume_text
# from matching_engine import calculate_similarity, get_top_job_matches
# from scam_model import predict_scam
# from skill_analyzer import analyze_skill_gap
# from feedback_engine import generate_feedback
# from skill_extractor import extract_skills
# from warning_engine import detect_warnings

# app = Flask(__name__)
# app.config["UPLOAD_FOLDER"] = "uploads"

# # ---------------- HOME ----------------
# @app.route("/")
# def index():
#     return render_template("index.html")


# # ---------------- PROCESS RESUME ----------------
# @app.route('/process', methods=['POST'])
# def process():

#     resume_text = request.form.get("resume_text", "").strip()
#     uploaded_file = request.files.get("resume_file")

#     final_resume = ""

#     # FILE INPUT
#     if uploaded_file and uploaded_file.filename != "":
#         filepath = os.path.join(app.config["UPLOAD_FOLDER"], uploaded_file.filename)
#         uploaded_file.save(filepath)
#         final_resume = extract_resume_text(filepath)

#     # TEXT INPUT
#     elif resume_text:
#         final_resume = resume_text

#     else:
#         return redirect(url_for("index"))

#     # PASS DIRECTLY TO JD PAGE (NO SESSION)
#     return render_template("upload_jd.html", resume=final_resume)


# # ---------------- ANALYZE ----------------
# @app.route('/analyze', methods=['POST'])
# def analyze():

#     resume = request.form.get("resume", "").strip()
#     jd = request.form.get("jd_text", "").strip()

#     print("RESUME LENGTH:", len(resume))
#     print("JD LENGTH:", len(jd))

#     if not resume or not jd:
#         return "Missing resume or job description", 400

#     match_score = calculate_similarity(resume, jd)
#     jobs = get_top_job_matches(resume)
#     skills = extract_skills(resume)

#     skill_data = analyze_skill_gap(resume, jd)
#     if not isinstance(skill_data, dict):
#         skill_data = {"matched": [], "missing": [], "match_ratio": 0}

#     feedback = generate_feedback(resume, skill_data)

#     return render_template(
#         "result.html",
#         match_score=match_score,
#         jobs=jobs,
#         skills=skills,
#         resume=resume[:300],
#         jd=jd[:300],
#         skill_data=skill_data,
#         feedback=feedback
#     )


# # ---------------- SCAM CHECKER ----------------
# @app.route('/scam-checker')
# def scam_checker():
#     return render_template("scam_checker.html")


# @app.route('/analyze-scam', methods=['POST'])
# def analyze_scam():

#     email = request.form.get("email", "")
#     title = request.form.get("title", "")
#     description = request.form.get("description", "")

#     score, label = predict_scam(email, title, description)
#     warnings = detect_warnings(email, title, description)

#     if label == "Scam":
#         precautions = [
#             "Do not pay money",
#             "Do not share bank details",
#             "Verify company website",
#             "Check LinkedIn presence",
#             "Be careful of urgency traps"
#         ]
#     elif label == "Medium Risk":
#         precautions = [
#             "Verify recruiter email",
#             "Check reviews",
#             "Avoid suspicious links"
#         ]
#     else:
#         precautions = ["Still verify company authenticity"]

#     return render_template(
#         "scam_result.html",
#         result=label,
#         score=score,
#         precautions=precautions,
#         warnings=warnings
#     )

# # ---------------- DOWNLOAD PDF REPORT ----------------
# @app.route('/download-report')
# def download_report():

#     from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
#     from reportlab.lib.styles import getSampleStyleSheet
#     from flask import send_file

#     pdf_path = "report.pdf"

#     doc = SimpleDocTemplate(pdf_path)

#     styles = getSampleStyleSheet()

#     elements = []

#     # DATA
#     match_score = session.get("match_score", 0)
#     resume = session.get("resume", "")                                        #resume = request.form.get("resume", "")
#     jd = session.get("jd", "")

#     skill_data = session.get("skill_data", {
#         "matched": [],
#         "missing": []
#     })

#     feedback = session.get("feedback", [])

#     # TITLE
#     elements.append(Paragraph("JobShield AI Report", styles['Title']))
#     elements.append(Spacer(1, 20))

#     # SCORE
#     elements.append(Paragraph(f"<b>Match Score:</b> {match_score}%", styles['BodyText']))
#     elements.append(Spacer(1, 10))

#     # MATCHED
#     elements.append(Paragraph("<b>Matched Skills:</b>", styles['Heading2']))

#     for skill in skill_data["matched"]:
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # MISSING
#     elements.append(Paragraph("<b>Missing Skills:</b>", styles['Heading2']))

#     for skill in skill_data["missing"]:
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # FEEDBACK
#     elements.append(Paragraph("<b>Resume Feedback:</b>", styles['Heading2']))

#     for f in feedback:
#         elements.append(Paragraph(f"• {f}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # RESUME
#     elements.append(Paragraph("<b>Resume Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(resume[:1000], styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # JD
#     elements.append(Paragraph("<b>Job Description Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(jd[:1000], styles['BodyText']))

#     # BUILD PDF
#     doc.build(elements)

#     return send_file(pdf_path, as_attachment=True)



# # ---------------- RUN ----------------
# if __name__ == "__main__":
#     os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
#     print("Starting JobShield AI...")
#     app.run(host="0.0.0.0", port=7860)



# from flask import Flask, render_template, request, redirect, url_for, session
# import os
# from resume_parser import extract_resume_text
# from matching_engine import calculate_similarity, get_top_job_matches
# from scam_model import predict_scam
# from skill_analyzer import analyze_skill_gap
# from feedback_engine import generate_feedback
# from skill_extractor import extract_skills
# from warning_engine import detect_warnings

# app = Flask(__name__)
# app.secret_key = "secret_key_change_this"

# app.config["UPLOAD_FOLDER"] = "uploads"


# # ---------------- HOME ----------------
# @app.route("/")
# def index():
#     session.clear()
#     return render_template("index.html")


# # ---------------- PROCESS RESUME ----------------
# @app.route('/process', methods=['POST'])
# def process():

#     resume_text = request.form.get("resume_text", "").strip()

#     uploaded_file = request.files.get("resume_file")

#     final_resume = ""

#     # FILE
#     if uploaded_file and uploaded_file.filename != "":
#         filepath = os.path.join(app.config["UPLOAD_FOLDER"], uploaded_file.filename)
#         uploaded_file.save(filepath)
#         final_resume = extract_resume_text(filepath)

#         session["uploaded_file"] = uploaded_file.filename

#     # TEXT
#     elif resume_text:
#         final_resume = resume_text
#         session.pop("uploaded_file", None)

#     else:
#         print("Resume text:", resume_text)
#         print("JD text:", jd_text)
#         print("Analyze route reached")
#         return redirect(url_for("index"))

#     # STORE RESUME
    
#     app.config["FULL_RESUME"] = final_resume

#     return render_template("upload_jd.html", resume=final_resume)


# # ---------------- JD PAGE ----------------
# @app.route('/upload_jd')
# def upload_jd():
#     return render_template("upload_jd.html")


# # ---------------- ANALYZE ----------------
# @app.route('/analyze', methods=['POST'])
# def analyze():

#     print("ANALYZE ROUTE HIT")
#     print("FORM DATA:", request.form)
#     print("SESSION:", session)
#     resume_text = session.get("resume")
#     print("RESUME:", resume_text)
#     jd_text = request.form.get("job_description")
#     print("JD:", jd_text)
    
#     jd = request.form.get("jd_text", "")
#     resume = request.form.get("resume", "")

#     if not jd.strip() or not resume.strip():
#         return "Missing resume or job description", 400

#     match_score = calculate_similarity(resume, jd)
#     jobs = get_top_job_matches(resume)
#     skills = extract_skills(resume)

#     # SAFE CALL (ONLY IMPORTED FUNCTION)
#     skill_data = analyze_skill_gap(resume, jd)

#     # SAFE fallback (prevents Jinja crash)
#     if not isinstance(skill_data, dict):
#         skill_data = {"matched": [], "missing": [], "match_ratio": 0}

#     feedback = generate_feedback(resume, skill_data)
#     session["match_score"] = match_score
#     session["resume"] = resume
#     session["jd"] = jd
#     session["skill_data"] = skill_data
#     session["feedback"] = feedback

#     return render_template(
#         "result.html",
#         match_score=match_score,
#         jobs=jobs,
#         skills=skills,
#         resume=resume[:300],
#         jd=jd[:300],
#         skill_data=skill_data,
#         feedback=feedback
#     )
    

# # ---------------- RESULT PAGE ----------------
# @app.route("/result")
# def result():
#     return render_template(
#         "result.html",
#         match_score=0,
#         jobs=[],
#         skills=[],
#         skill_data={"matched": [], "missing": []},
#         resume="",
#         jd="", 
#         feedback=[]
#     )
    
# # ---------------- DOWNLOAD PDF REPORT ----------------
# @app.route('/download-report')
# def download_report():

#     from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
#     from reportlab.lib.styles import getSampleStyleSheet
#     from flask import send_file

#     pdf_path = "report.pdf"

#     doc = SimpleDocTemplate(pdf_path)

#     styles = getSampleStyleSheet()

#     elements = []

#     # DATA
#     match_score = session.get("match_score", 0)
#     resume = session.get("resume", "")                                        #resume = request.form.get("resume", "")
#     jd = session.get("jd", "")

#     skill_data = session.get("skill_data", {
#         "matched": [],
#         "missing": []
#     })

#     feedback = session.get("feedback", [])

#     # TITLE
#     elements.append(Paragraph("JobShield AI Report", styles['Title']))
#     elements.append(Spacer(1, 20))

#     # SCORE
#     elements.append(Paragraph(f"<b>Match Score:</b> {match_score}%", styles['BodyText']))
#     elements.append(Spacer(1, 10))

#     # MATCHED
#     elements.append(Paragraph("<b>Matched Skills:</b>", styles['Heading2']))

#     for skill in skill_data["matched"]:
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # MISSING
#     elements.append(Paragraph("<b>Missing Skills:</b>", styles['Heading2']))

#     for skill in skill_data["missing"]:
#         elements.append(Paragraph(f"• {skill}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # FEEDBACK
#     elements.append(Paragraph("<b>Resume Feedback:</b>", styles['Heading2']))

#     for f in feedback:
#         elements.append(Paragraph(f"• {f}", styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # RESUME
#     elements.append(Paragraph("<b>Resume Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(resume[:1000], styles['BodyText']))

#     elements.append(Spacer(1, 10))

#     # JD
#     elements.append(Paragraph("<b>Job Description Preview:</b>", styles['Heading2']))
#     elements.append(Paragraph(jd[:1000], styles['BodyText']))

#     # BUILD PDF
#     doc.build(elements)

#     return send_file(pdf_path, as_attachment=True)


# # ---------------- SCAM CHECKER ----------------
# @app.route('/scam-checker')
# def scam_checker():
#     return render_template("scam_checker.html")


# @app.route('/analyze-scam', methods=['POST'])
# def analyze_scam():

#     email = request.form.get("email", "")
#     title = request.form.get("title", "")
#     description = request.form.get("description", "")

#     score, label = predict_scam(email, title, description)
#     warnings = detect_warnings(email, title, description)

#     if label == "Scam":
#         precautions = [
#             "Do not pay money",
#             "Do not share bank details",
#             "Verify company website",
#             "Check LinkedIn presence",
#             "Be careful of urgency traps"
#         ]
#     elif label == "Medium Risk":
#         precautions = [
#             "Verify recruiter email",
#             "Check reviews",
#             "Avoid suspicious links"
#         ]
#     else:
#         precautions = [
#             "Still verify company authenticity"
#         ]

#     return render_template(
#         "scam_result.html",
#         result=label,
#         score=score,
#         precautions=precautions,
#         warnings=warnings
#     )


# # ---------------- RUN ----------------
# if __name__ == "__main__":
#     os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
#     print("Starting JobShield AI...")
#     app.run(host="0.0.0.0", port=7860)