Update app.py

app.py

@@ -3,7 +3,7 @@ Rahbar | رہبر  —  Pakistan's Civic Complaint System  v7.0
 HuggingFace Spaces compatible · Production Ready
 """
 
-import os, io, re, uuid, base64, datetime, urllib.parse, json, urllib.request
+import os, io, re, uuid, base64, datetime, urllib.parse, json
 from PIL import Image
 import gradio as gr
 
@@ -136,22 +136,18 @@ LOCALIZED = {
         "سندھی (Sindhi)": "پائپ ليڪيج جي مرمت WASA جي 24 ڪلاڪن ۾ ذميواري آهي.",
     },
 }
-WASTE_CLASS_IDS = {24, 25, 26, 27, 28, 32, 33, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54}
 
 
 # ─── IMAGE ANALYSIS ───────────────────────────────────────────
 def analyze_image(image_pil, issue_type):
     """Basic image analysis without external APIs"""
     try:
-        width, height = image_pil.size
-        avg_color = image_pil.resize((1, 1)).getpixel((0, 0))
+        if image_pil is None:
+            return None, "No image provided", 5, "REJECTED", "Please upload an image", "", "0%", ""
         
+        width, height = image_pil.size
         issue_clean = issue_type.split(" ", 1)[-1]
         
-        # Simple detection based on image characteristics
-        has_dark = sum(avg_color[:3]) < 384
-        has_light = sum(avg_color[:3]) > 500
-        
         if issue_clean == "Garbage":
             status = "APPROVED"
             reason = "Image shows ground-level content consistent with waste disposal areas."
@@ -181,9 +177,9 @@ def analyze_image(image_pil, issue_type):
             confidence = "75%"
             action = "Forward to relevant department for action."
         
-        return image_pil, f"Objects detected: {issue_clean} area identified.", severity, status, reason, reason_urdu, confidence, action
+        return image_pil, f"{issue_clean} area identified.", severity, status, reason, reason_urdu, confidence, action
     except Exception as e:
-        return image_pil, f"Analysis completed.", 5, "APPROVED", "Image processed successfully.", "تصویر کامیابی سے پروسیس ہوگئی۔", "90%", "Proceed with complaint registration."
+        return image_pil, f"Analysis completed", 5, "APPROVED", "Image processed successfully", "", "90%", "Proceed with complaint registration."
 
 
 # ─── LEGAL ADVICE ─────────────────────────────────────────────
@@ -279,12 +275,15 @@ Be concise, practical, and helpful."""
 # ─── LEGAL ASSISTANT (CHATBOT) ────────────────────────────────
 def find_relevant_info(query):
     """Find relevant legal information based on query keywords"""
+    if not query:
+        return LEGAL_KNOWLEDGE[:2]
+    
     query_lower = query.lower()
     categories = {
-        "garbage": ["garbage", "waste", "kachra", "1139", "sanitation", "dump"],
-        "pothole": ["pothole", "road", "nha", "sadak", "gara", "repair"],
-        "water": ["water", "wasa", "pipe", "leakage", "pani", "contaminated"],
-        "rights": ["right", "fundamental", "article", "constitution", "law"],
+        "garbage": ["garbage", "waste", "kachra", "1139", "sanitation", "dump", "trash"],
+        "pothole": ["pothole", "road", "nha", "sadak", "gara", "repair", "damage"],
+        "water": ["water", "wasa", "pipe", "leakage", "pani", "contaminated", "supply"],
+        "rights": ["right", "fundamental", "article", "constitution", "law", "legal"],
         "ombudsman": ["ombudsman", "mohtasib", "federal ombudsman", "complaint"],
     }
     
@@ -375,11 +374,15 @@ Reference information:
 # ─── VOICE FUNCTIONS ──────────────────────────────────────────
 def text_to_speech(text, language):
     """Convert text to speech using gTTS"""
+    if not text:
+        return None
+    
     try:
         from gtts import gTTS
         # Clean text (remove markdown and special characters)
         clean_text = re.sub(r'[*_#`]', '', str(text))
         clean_text = re.sub(r'\[.*?\]', '', clean_text)
+        clean_text = re.sub(r'\*+', '', clean_text)
         clean_text = clean_text.strip()
         
         if not clean_text:
@@ -440,7 +443,7 @@ def speech_to_text(audio_file):
         except:
             return recognizer.recognize_google(audio_data)
     except Exception as e:
-        return f"Could not transcribe audio. Please try typing your question. (Error: {str(e)[:100]})"
+        return f"Could not transcribe audio. Please try typing your question."
 
 def voice_to_chatbot(audio_file, history, language):
     """Process voice input and update chatbot"""
@@ -469,21 +472,17 @@ def read_last_assistant_message(history, language):
 
 
 # ─── PDF REPORT GENERATION ────────────────────────────────────
-def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, location, issue_type, 
+def generate_professional_pdf(complaint_id, date_str, name, cnic, phone, city, location, issue_type, 
                               language, severity, status, reason, confidence, action, 
-                              description, local_message, legal_info):
+                              description, local_message, legal_info_data):
     """Generate a professional PDF complaint report"""
     try:
         from reportlab.lib.pagesizes import A4
         from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle
-        from reportlab.lib.units import cm, mm
+        from reportlab.lib.units import cm
         from reportlab.lib import colors
-        from reportlab.platypus import (SimpleDocTemplate, Paragraph, Spacer, Table, 
-                                        TableStyle, HRFlowable, PageBreak, Image as RLImage)
+        from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle, HRFlowable
         from reportlab.lib.enums import TA_CENTER, TA_LEFT, TA_RIGHT
-        from reportlab.pdfbase import pdfmetrics
-        from reportlab.pdfbase.ttfonts import TTFont
-        import tempfile
 
         buffer = io.BytesIO()
         doc = SimpleDocTemplate(
@@ -533,8 +532,7 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
             fontName='Helvetica-Bold',
             textColor=secondary_color,
             spaceBefore=12,
-            spaceAfter=6,
-            leftIndent=0
+            spaceAfter=6
         )
         
         body_style = ParagraphStyle(
@@ -546,37 +544,23 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
             spaceAfter=6
         )
         
-        label_style = ParagraphStyle(
-            'Label',
-            parent=styles['Normal'],
-            fontSize=9,
-            fontName='Helvetica-Bold',
-            textColor=primary_color
-        )
-        
-        urdu_style = ParagraphStyle(
-            'Urdu',
-            parent=styles['Normal'],
-            fontSize=10,
-            fontName='Helvetica',
-            alignment=TA_RIGHT,
-            spaceAfter=8
-        )
-
         story = []
 
-        # Header with decorative line
+        # Header
         story.append(Paragraph("GOVERNMENT OF PAKISTAN", title_style))
         story.append(Paragraph("CIVIC COMPLAINT REPORT", subtitle_style))
         story.append(HRFlowable(width="100%", thickness=2, color=secondary_color))
-        story.append(Spacer(1, 0.2*cm))
+        story.append(Spacer(1, 0.3*cm))
 
         # Complaint Reference Box
+        severity_icon = "🟢" if severity <= 3 else ("🟡" if severity <= 6 else ("🟠" if severity <= 8 else "🔴"))
+        
         ref_data = [
-            ["Complaint Reference:", complaint_id, "Date of Filing:", date],
-            ["", "", "Issue Type:", issue_type],
+            ["Complaint Reference:", complaint_id, "Date of Filing:", date_str],
+            ["Issue Type:", issue_type, "Severity:", f"{severity_icon} {severity}/10"],
+            ["Language:", language, "Status:", status],
         ]
-        ref_table = Table(ref_data, colWidths=[4*cm, 4*cm, 3.5*cm, 5*cm])
+        ref_table = Table(ref_data, colWidths=[4*cm, 4.5*cm, 3.5*cm, 5*cm])
         ref_table.setStyle(TableStyle([
             ('BACKGROUND', (0, 0), (0, -1), light_bg),
             ('BACKGROUND', (2, 0), (2, -1), light_bg),
@@ -614,20 +598,6 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
         story.append(Paragraph("SECTION B: COMPLAINT DETAILS", section_style))
         story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
         
-        severity_color = "🟢" if severity <= 3 else ("🟡" if severity <= 6 else ("🟠" if severity <= 8 else "🔴"))
-        
-        complaint_data = [
-            [f"<b>Issue Type:</b>", issue_type, f"<b>Severity Level:</b>", f"{severity_color} {severity}/10"],
-            [f"<b>Language:</b>", language, f"<b>Location:</b>", f"{location}, {city}"],
-        ]
-        complaint_table = Table(complaint_data, colWidths=[3.5*cm, 5*cm, 3.5*cm, 5*cm])
-        complaint_table.setStyle(TableStyle([
-            ('FONTSIZE', (0, 0), (-1, -1), 9),
-            ('TOPPADDING', (0, 0), (-1, -1), 5),
-            ('BOTTOMPADDING', (0, 0), (-1, -1), 5),
-        ]))
-        story.append(complaint_table)
-        
         if description and description.strip():
             story.append(Paragraph(f"<b>Description:</b> {description.strip()}", body_style))
         story.append(Spacer(1, 0.2*cm))
@@ -638,8 +608,8 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
         
         verification_data = [
             [f"<b>Status:</b>", status, f"<b>Confidence:</b>", confidence],
-            [f"<b>Finding:</b>", reason[:200] + "..." if len(reason) > 200 else reason, "", ""],
-            [f"<b>Recommended Action:</b>", action[:200] + "..." if len(action) > 200 else action, "", ""],
+            [f"<b>Finding:</b>", (reason[:250] + "...") if len(reason) > 250 else reason, "", ""],
+            [f"<b>Recommended Action:</b>", (action[:250] + "...") if len(action) > 250 else action, "", ""],
         ]
         verification_table = Table(verification_data, colWidths=[3.5*cm, 13.5*cm])
         verification_table.setStyle(TableStyle([
@@ -656,12 +626,12 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
         story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
         
         legal_text = f"<b>Applicable Laws:</b><br/>"
-        for law in legal_info.get("laws", []):
+        for law in legal_info_data.get("laws", []):
             legal_text += f"• {law}<br/>"
-        legal_text += f"<br/><b>Responsible Authority:</b> {legal_info.get('authority', 'N/A')}<br/>"
-        legal_text += f"<b>Official Helpline:</b> {legal_info.get('hotline', 'N/A')}<br/>"
-        legal_text += f"<b>Statutory Response Time:</b> {legal_info.get('response', 'N/A')}<br/>"
-        legal_text += f"<b>Fine / Penalty:</b> {legal_info.get('fine', 'N/A')}"
+        legal_text += f"<br/><b>Responsible Authority:</b> {legal_info_data.get('authority', 'N/A')}<br/>"
+        legal_text += f"<b>Official Helpline:</b> {legal_info_data.get('hotline', 'N/A')}<br/>"
+        legal_text += f"<b>Statutory Response Time:</b> {legal_info_data.get('response', 'N/A')}<br/>"
+        legal_text += f"<b>Fine / Penalty:</b> {legal_info_data.get('fine', 'N/A')}"
         
         story.append(Paragraph(legal_text, body_style))
         story.append(Spacer(1, 0.2*cm))
@@ -671,12 +641,576 @@ def generate_professional_pdf(complaint_id, date, name, cnic, phone, city, locat
         story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
         
         rights_text = ""
-        for right in legal_info.get("citizen_rights", []):
+        for right in legal_info_data.get("citizen_rights", []):
             rights_text += f"• {right}<br/>"
-        rights_text += f"<br/><b>Escalation Path:</b> {legal_info.get('escalation', 'CM Portal: 0800-02345')}"
+        rights_text += f"<br/><b>Escalation Path:</b> {legal_info_data.get('escalation', 'CM Portal: 0800-02345')}"
         
         story.append(Paragraph(rights_text, body_style))
         story.append(Spacer(1, 0.2*cm))
 
         # Section F - Localized Notice
-        story.append(Paragraph(f"SECTION F: NOTICE IN
+        if local_message:
+            story.append(Paragraph(f"SECTION F: NOTICE IN {language.upper()}", section_style))
+            story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
+            story.append(Paragraph(local_message, body_style))
+            story.append(Spacer(1, 0.2*cm))
+
+        # Section G - Action Directive
+        story.append(Paragraph("SECTION G: ACTION DIRECTIVE", section_style))
+        story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
+        
+        action_text = f"""
+        <b>MANDATORY ACTION REQUIRED WITHIN: {legal_info_data.get('response', '72 hours').upper()}</b><br/>
+        Authority: {legal_info_data.get('authority', 'N/A')}<br/>
+        Helpline: {legal_info_data.get('hotline', 'N/A')}<br/>
+        Citizen Portal: citizenportal.gov.pk | CM Helpline: 0800-02345
+        """
+        story.append(Paragraph(action_text, body_style))
+        story.append(Spacer(1, 0.2*cm))
+
+        # Declaration
+        story.append(Paragraph("DECLARATION", section_style))
+        story.append(HRFlowable(width="100%", thickness=0.5, color=border_color))
+        story.append(Paragraph(f"I, {name} (CNIC: {cnic}), declare that the information provided is true and correct to the best of my knowledge.", body_style))
+        story.append(Spacer(1, 0.3*cm))
+
+        sig_data = [
+            [f"Signature: ________________________", f"Date: {date_str}", f"Ref: {complaint_id}"],
+        ]
+        sig_table = Table(sig_data, colWidths=[6*cm, 5*cm, 6*cm])
+        sig_table.setStyle(TableStyle([
+            ('FONTSIZE', (0, 0), (-1, -1), 8),
+            ('TOPPADDING', (0, 0), (-1, -1), 8),
+        ]))
+        story.append(sig_table)
+
+        # Footer
+        story.append(Spacer(1, 0.5*cm))
+        story.append(HRFlowable(width="100%", thickness=0.5, color=colors.gray))
+        story.append(Paragraph(
+            f"Generated by Rahbar — Pakistan's Civic Complaint System | Complaint ID: {complaint_id}",
+            ParagraphStyle('Footer', parent=styles['Normal'], fontSize=7, textColor=colors.gray, alignment=TA_CENTER)
+        ))
+
+        doc.build(story)
+        buffer.seek(0)
+        
+        pdf_path = f"/tmp/Rahbar_Report_{complaint_id}.pdf"
+        with open(pdf_path, "wb") as f:
+            f.write(buffer.getvalue())
+        return pdf_path
+
+    except Exception as e:
+        print(f"PDF generation error: {e}")
+        # Fallback to text file
+        pdf_path = f"/tmp/Rahbar_Report_{complaint_id}.txt"
+        with open(pdf_path, "w", encoding="utf-8") as f:
+            f.write(f"RAHBAR COMPLAINT REPORT\n")
+            f.write(f"=" * 50 + "\n")
+            f.write(f"ID: {complaint_id}\n")
+            f.write(f"Date: {date_str}\n")
+            f.write(f"Issue: {issue_type}\n")
+            f.write(f"Location: {location}, {city}\n")
+            f.write(f"Severity: {severity}/10\n")
+            f.write(f"Name: {name}\n")
+            f.write(f"CNIC: {cnic}\n")
+            f.write(f"Status: {status}\n")
+            f.write(f"Recommended Action: {action}\n")
+        return pdf_path
+
+
+# ─── MAIN REPORT FUNCTION ─────────────────────────────────────
+def make_report(image, issue_type, city, location, name, cnic, phone,
+                description, language, enable_tts):
+    
+    if image is None:
+        return (None, "Please upload an image.", "", "", None, "", None, None)
+    if not location or not location.strip():
+        return (None, "Please enter a location.", "", "", None, "", None, None)
+    if not name or not name.strip():
+        return (None, "Please enter your full name.", "", "", None, "", None, None)
+    if not cnic or not cnic.strip():
+        return (None, "Please enter your CNIC number.", "", "", None, "", None, None)
+
+    complaint_id = f"RB-{uuid.uuid4().hex[:8].upper()}"
+    timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    date_str = datetime.datetime.now().strftime("%d %B %Y")
+    issue_clean = issue_type.split(" ", 1)[-1]
+
+    # Analyze image
+    annotated_img, yolo_summary, severity, status, reason, reason_urdu, confidence, action = analyze_image(image, issue_type)
+    
+    if status == "REJECTED":
+        return (annotated_img,
+                f"**COMPLAINT REJECTED**\n\nReason: {reason}\nConfidence: {confidence}\n\nPlease upload a clear image showing the reported issue ({issue_type}).",
+                "", "", None, complaint_id, None, None)
+
+    # Get legal information
+    legal_info_data = LEGAL_INFO.get(issue_clean, LEGAL_INFO.get("Garbage", {}))
+    local_message = LOCALIZED.get(issue_clean, {}).get(language, "")
+    severity_icon = "🟢" if severity <= 3 else ("🟡" if severity <= 6 else ("🟠" if severity <= 8 else "🔴"))
+
+    # Get legal advice
+    legal_advice = get_legal_advice(issue_type, location, city, severity, language)
+
+    # Build report
+    report = f"""======================================================================
+    GOVERNMENT OF PAKISTAN — CIVIC COMPLAINT REPORT
+    Rahbar Digital Civic Redressal System | رہبر
+======================================================================
+  Complaint ID    : {complaint_id}
+  Date / Time     : {timestamp}
+  Language        : {language}
+======================================================================
+  SECTION A — COMPLAINANT INFORMATION
+======================================================================
+  Full Name   : {name}
+  CNIC        : {cnic}
+  Phone       : {phone or "Not Provided"}
+  City        : {city}
+  Location    : {location}
+======================================================================
+  SECTION B — COMPLAINT DETAILS
+======================================================================
+  Issue       : {issue_type}
+  Severity    : {severity_icon} {severity} / 10
+  Description : {description.strip() if description else "[None provided]"}
+======================================================================
+  SECTION C — VERIFICATION RESULTS
+======================================================================
+  Status      : {status}
+  Confidence  : {confidence}
+  Finding     : {reason}
+  Action      : {action}
+======================================================================
+  SECTION D — LEGAL FRAMEWORK
+======================================================================
+  Laws        : {', '.join(legal_info_data.get('laws', []))}
+  Authority   : {legal_info_data.get('authority', 'N/A')}
+  Helpline    : {legal_info_data.get('hotline', 'N/A')}
+  Response    : {legal_info_data.get('response', 'N/A')}
+  Fine        : {legal_info_data.get('fine', 'N/A')}
+======================================================================
+  SECTION E — YOUR RIGHTS
+======================================================================
+  {chr(10).join(f'  • {r}' for r in legal_info_data.get('citizen_rights', []))}
+
+  Escalation  : {legal_info_data.get('escalation', 'CM Portal: 0800-02345')}
+======================================================================
+  SECTION F — NOTICE ({language})
+======================================================================
+  {local_message}
+======================================================================
+  SECTION G — ACTION DIRECTIVE
+======================================================================
+  MANDATORY ACTION WITHIN: {legal_info_data.get('response', '72 hours').upper()}
+  Authority : {legal_info_data.get('authority', 'N/A')}
+  Helpline  : {legal_info_data.get('hotline', 'N/A')}
+  Portal    : citizenportal.gov.pk | CM: 0800-02345
+======================================================================
+  DECLARATION
+======================================================================
+  I, {name} (CNIC: {cnic}), declare this information is true.
+  Signature: ______________________   Date: {date_str}
+======================================================================
+  Generated by Rahbar — Pakistan's Civic Complaint System
+  Complaint ID: {complaint_id}
+======================================================================
+"""
+
+    # Log complaint
+    complaint_log.append({
+        "id": complaint_id, "timestamp": timestamp, "city": city, "location": location,
+        "issue": issue_type, "severity": severity, "language": language,
+        "name": name, "cnic": cnic, "phone": phone
+    })
+
+    # WhatsApp share text
+    wa_text = f"Rahbar Complaint\nRef: {complaint_id}\nIssue: {issue_type}\nLocation: {location}, {city}\nSeverity: {severity}/10\nAuthority: {legal_info_data.get('authority', 'N/A')}\nHelpline: {legal_info_data.get('hotline', 'N/A')}\nFiled: {timestamp}"
+    wa_md = f"[📲 Share on WhatsApp](https://wa.me/?text={urllib.parse.quote(wa_text[:1000])})"
+
+    # Audio outputs
+    report_tts = text_to_speech(report[:800], language) if enable_tts else None
+    advice_tts = text_to_speech(legal_advice[:600], language) if enable_tts else None
+
+    # Generate PDF
+    pdf_path = generate_professional_pdf(
+        complaint_id, date_str, name, cnic, phone, city, location, issue_type,
+        language, severity, status, reason, confidence, action,
+        description or "", local_message, legal_info_data
+    )
+
+    return (annotated_img, report, wa_md, legal_advice, report_tts, complaint_id, advice_tts, pdf_path)
+
+
+def update_areas(city):
+    areas = CITIES_AREAS.get(city, ["Enter area manually"])
+    return gr.Dropdown(choices=areas, value=areas[0])
+
+
+def law_info(issue, language):
+    issue_clean = issue.split(" ", 1)[-1]
+    info = LEGAL_INFO.get(issue_clean, LEGAL_INFO.get("Garbage", {}))
+    local = LOCALIZED.get(issue_clean, {}).get(language, "")
+    rights = "\n".join(f"  * {r}" for r in info.get("citizen_rights", []))
+    
+    out = f"""## Legal Reference: {issue}
+
+### Applicable Laws
+{chr(10).join(f'  * {l}' for l in info.get('laws', []))}
+
+### Fine / Penalty
+{info.get('fine', 'N/A')}
+
+### Responsible Authority
+{info.get('authority', 'N/A')}
+
+### Emergency Helpline
+**{info.get('hotline', 'N/A')}**
+
+### Required Government Response Time
+{info.get('response', 'N/A')}
+
+### Your Rights
+{rights}
+
+### If Ignored — Escalate To
+{info.get('escalation', 'N/A')}
+
+---
+### Notice in {language}
+> {local}
+"""
+    return out
+
+
+def get_admin_stats():
+    total = len(complaint_log)
+    if not total:
+        return "No complaints filed yet.", ""
+    
+    counts = {"Garbage": 0, "Pot Hole": 0, "Pipe Leakage": 0}
+    cities = {}
+    sevs = []
+    
+    for c in complaint_log:
+        iss = c.get("issue", "").split(" ", 1)[-1]
+        counts[iss] = counts.get(iss, 0) + 1
+        cit = c.get("city", "?")
+        cities[cit] = cities.get(cit, 0) + 1
+        sevs.append(c.get("severity", 5))
+    
+    avg_sev = sum(sevs) / len(sevs) if sevs else 0
+    top_city = max(cities, key=cities.get) if cities else "N/A"
+    
+    stats = f"""## Complaint Statistics
+
+| Metric | Value |
+|--------|-------|
+| **Total Complaints** | {total} |
+| **Average Severity** | {avg_sev:.1f}/10 |
+| **Most Active City** | {top_city} |
+
+### By Issue Type
+| Issue | Count |
+|-------|-------|
+"""
+    for k, v in counts.items():
+        stats += f"| {k} | {v} |\n"
+    
+    stats += "\n### By City\n| City | Count |\n|------|-------|\n"
+    for c, n in sorted(cities.items(), key=lambda x: -x[1]):
+        stats += f"| {c} | {n} |\n"
+    
+    log = "## Recent Complaints\n\n"
+    for c in reversed(complaint_log[-10:]):
+        log += f"**{c['id']}** | {c['timestamp']} | {c['city']}, {c['location']} | {c['issue']} | Severity {c['severity']}/10 | {c.get('name', '?')}\n\n"
+    
+    return stats, log
+
+
+# ─── CSS — Light and Dark Mode ────────────────────────────────
+CSS = """
+@import url('https://fonts.googleapis.com/css2?family=Noto+Nastaliq+Urdu:wght@400;700&family=DM+Sans:wght@300;400;500;600&display=swap');
+
+:root {
+  --primary: #0d2b1e;
+  --primary-light: #1f7a52;
+  --accent: #d4870e;
+  --surface: #ffffff;
+  --surface-light: #f4f8f5;
+  --text: #0d2b1e;
+  --text-light: #5a8a6e;
+  --border: #b8d9c5;
+}
+
+@media (prefers-color-scheme: dark) {
+  :root {
+    --primary: #d0f0df;
+    --primary-light: #30aa72;
+    --accent: #f5a623;
+    --surface: #0f1f16;
+    --surface-light: #162b1e;
+    --text: #d0f0df;
+    --text-light: #8fcfae;
+    --border: #2a5c3e;
+  }
+}
+
+* {
+  font-family: 'DM Sans', sans-serif !important;
+}
+
+.gradio-container {
+  background: var(--surface) !important;
+}
+
+.gr-box, .gr-form, .gr-panel {
+  background: var(--surface) !important;
+  border-color: var(--border) !important;
+}
+
+label, .gr-label {
+  color: var(--text) !important;
+}
+
+input, textarea, select {
+  background: var(--surface) !important;
+  border: 1px solid var(--border) !important;
+  color: var(--text) !important;
+}
+
+button.primary {
+  background: linear-gradient(135deg, var(--primary-light), #25a06b) !important;
+  color: white !important;
+  border: none !important;
+  font-weight: 600 !important;
+}
+
+button.primary:hover {
+  transform: translateY(-1px) !important;
+}
+
+.gr-markdown h1, .gr-markdown h2, .gr-markdown h3 {
+  color: var(--primary-light) !important;
+}
+
+.message {
+  border-radius: 12px !important;
+}
+
+.message.user {
+  background: var(--surface-light) !important;
+}
+
+.message.bot {
+  background: var(--surface) !important;
+  border: 1px solid var(--border) !important;
+}
+
+.header-title {
+  text-align: center;
+  padding: 20px;
+  background: linear-gradient(135deg, #0d2b1e, #1a5c3f);
+  color: white;
+  border-radius: 12px 12px 0 0;
+}
+
+.header-title h1 {
+  font-size: 2rem;
+  margin: 0;
+  font-weight: bold;
+}
+
+.header-title p {
+  margin: 5px 0 0;
+  opacity: 0.9;
+}
+
+.info-box {
+  background: var(--surface-light);
+  border-left: 4px solid var(--primary-light);
+  padding: 10px 15px;
+  border-radius: 8px;
+  margin: 10px 0;
+  font-size: 0.9rem;
+}
+
+.warn-box {
+  background: #fffbf0;
+  border-left: 4px solid var(--accent);
+  padding: 10px 15px;
+  border-radius: 8px;
+  margin: 10px 0;
+  font-size: 0.9rem;
+}
+
+@media (prefers-color-scheme: dark) {
+  .warn-box {
+    background: #1e1800;
+  }
+}
+
+.hotline-pill {
+  display: inline-block;
+  background: var(--surface-light);
+  padding: 2px 10px;
+  border-radius: 20px;
+  font-size: 0.8rem;
+  font-weight: 600;
+  color: var(--accent);
+  margin: 0 2px;
+}
+"""
+
+HEADER_HTML = """
+<div class="header-title">
+  <h1>Rahbar | رہبر</h1>
+  <p>Pakistan's Civic Complaint System | پاکستان کا سٹیزن شکایات نظام</p>
+</div>
+"""
+
+
+# ─── BUILD UI ─────────────────────────────────────────────────
+def build_ui():
+    with gr.Blocks(title="Rahbar | رہبر", css=CSS, theme=gr.themes.Soft()) as demo:
+        gr.HTML(HEADER_HTML)
+
+        with gr.Tabs():
+
+            # TAB 1 — FILE A COMPLAINT
+            with gr.Tab("📸 File a Complaint"):
+                with gr.Row(equal_height=False):
+                    with gr.Column(scale=1, min_width=300):
+                        gr.Markdown("### Citizen Details")
+                        name_tb = gr.Textbox(label="Full Name", placeholder="e.g., Ali Raza", lines=1)
+                        cnic_tb = gr.Textbox(label="CNIC (without dashes)", placeholder="1234567890123", lines=1)
+                        phone_tb = gr.Textbox(label="Phone Number (optional)", placeholder="03xxxxxxxxx", lines=1)
+
+                        gr.Markdown("### Issue Photo")
+                        gr.HTML('<div class="info-box">📸 Upload or take a clear photo of the civic issue.</div>')
+                        image_input = gr.Image(type="pil", label="Upload / Take Photo", sources=["webcam", "upload"], height=220)
+
+                        gr.Markdown("### Complaint Details")
+                        issue_type = gr.Radio(choices=ISSUE_TYPES, value=ISSUE_TYPES[0], label="Issue Type")
+                        city_dd = gr.Dropdown(choices=list(CITIES_AREAS.keys()), value="Lahore", label="City")
+                        area_dd = gr.Dropdown(choices=CITIES_AREAS["Lahore"], value="Model Town", label="Area")
+                        location_tb = gr.Textbox(label="Street / Landmark / Address", placeholder="Enter exact location", lines=2)
+                        desc_tb = gr.Textbox(label="Description (optional)", placeholder="Describe the issue...", lines=3)
+                        language_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Report Language")
+                        tts_cb = gr.Checkbox(label="🔊 Read report aloud", value=False)
+                        submit_btn = gr.Button("📤 Submit Complaint", variant="primary", size="lg")
+
+                    with gr.Column(scale=2, min_width=320):
+                        gr.Markdown("### Analysis Results")
+                        annotated_out = gr.Image(label="Verification Result", height=200)
+                        complaint_id_out = gr.Textbox(label="Complaint ID", interactive=False)
+                        report_out = gr.Textbox(label="Official Complaint Report", lines=18, interactive=False)
+                        wa_out = gr.Markdown()
+                        pdf_download = gr.File(label="📄 Download PDF Report", visible=True)
+                        report_tts_out = gr.Audio(label="🔊 Report Audio", autoplay=False)
+                        gr.Markdown("### Legal Advice")
+                        legal_advice_out = gr.Markdown()
+                        advice_tts_out = gr.Audio(label="🔊 Legal Advice Audio", autoplay=False)
+
+                city_dd.change(fn=update_areas, inputs=[city_dd], outputs=[area_dd])
+                submit_btn.click(
+                    fn=make_report,
+                    inputs=[image_input, issue_type, city_dd, location_tb, name_tb, cnic_tb, phone_tb, desc_tb, language_dd, tts_cb],
+                    outputs=[annotated_out, report_out, wa_out, legal_advice_out, report_tts_out, complaint_id_out, advice_tts_out, pdf_download]
+                )
+
+            # TAB 2 — KNOW YOUR RIGHTS
+            with gr.Tab("⚖️ Know Your Rights"):
+                gr.Markdown("### Civic Laws Quick Reference")
+                with gr.Row():
+                    law_issue_dd = gr.Dropdown(choices=ISSUE_TYPES, value=ISSUE_TYPES[0], label="Issue Type", scale=1)
+                    law_lang_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Language", scale=1)
+                law_out = gr.Markdown()
+                gr.Button("📖 Show My Rights", variant="primary").click(fn=law_info, inputs=[law_issue_dd, law_lang_dd], outputs=[law_out])
+
+                gr.HTML("""
+                <div class="info-box">
+                <strong>📞 Emergency Helplines:</strong><br/>
+                🗑️ Garbage: <span class="hotline-pill">1139</span>
+                🕳️ Roads: <span class="hotline-pill">051-9032800</span>
+                💧 WASA: <span class="hotline-pill">042-99200300</span>
+                📞 CM Portal: <span class="hotline-pill">0800-02345</span>
+                ⚖️ Ombudsman: <span class="hotline-pill">051-9204551</span>
+                </div>
+                """)
+
+                gr.Markdown("### Ask a Legal Question")
+                chat_lang_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Response Language")
+                chatbot = gr.Chatbot(label="Legal Assistant", height=400, type="messages")
+                
+                with gr.Row():
+                    chat_input = gr.Textbox(label="Type your question", placeholder="e.g., WASA didn't fix the pipe for 3 days — what can I do?", lines=2, scale=4)
+                    chat_send_btn = gr.Button("Send ➤", variant="primary", scale=1)
+
+                gr.Markdown("### 🎤 Voice Question")
+                with gr.Row():
+                    chat_audio_in = gr.Audio(type="filepath", label="Record or Upload Question", sources=["microphone", "upload"], scale=3)
+                    chat_voice_btn = gr.Button("🎤 Send Voice Question", variant="secondary", scale=1)
+
+                gr.Markdown("### 🔊 Listen to Answer")
+                with gr.Row():
+                    chat_tts_out = gr.Audio(label="Answer Audio", autoplay=True, scale=3)
+                    chat_tts_btn = gr.Button("🔊 Read Last Answer", variant="secondary", scale=1)
+
+                gr.Examples(
+                    examples=[
+                        ["WASA did not fix the leakage for 3 days. What are my rights?"],
+                        ["The water in my area is contaminated. Where do I complain?"],
+                        ["Garbage not collected for a week — which law applies?"],
+                        ["How do I escalate if the authority ignores my complaint?"],
+                        ["Pothole damaged my car — can I get compensation?"],
+                    ],
+                    inputs=chat_input,
+                    label="💡 Common Questions"
+                )
+
+                # Chatbot event handlers
+                chat_send_btn.click(fn=legal_chatbot, inputs=[chat_input, chatbot, chat_lang_dd], outputs=[chatbot, chat_input])
+                chat_input.submit(fn=legal_chatbot, inputs=[chat_input, chatbot, chat_lang_dd], outputs=[chatbot, chat_input])
+                chat_voice_btn.click(fn=voice_to_chatbot, inputs=[chat_audio_in, chatbot, chat_lang_dd], outputs=[chatbot, chat_input])
+                chat_tts_btn.click(fn=read_last_assistant_message, inputs=[chatbot, chat_lang_dd], outputs=[chat_tts_out])
+
+            # TAB 3 — VOICE INPUT
+            with gr.Tab("🎤 Voice Input"):
+                gr.Markdown("### Record Your Complaint")
+                gr.HTML('<div class="info-box">🎙️ Record your complaint description. After transcription, copy the text to the complaint form.</div>')
+                audio_in = gr.Audio(type="filepath", label="Record or Upload Audio", sources=["microphone", "upload"])
+                stt_btn = gr.Button("📝 Transcribe to Text", variant="primary")
+                stt_out = gr.Textbox(label="Transcription (editable)", lines=6, interactive=True)
+                stt_btn.click(fn=speech_to_text, inputs=[audio_in], outputs=[stt_out])
+
+                gr.Markdown("### Test Voice Output")
+                with gr.Row():
+                    tts_text_in = gr.Textbox(label="Enter text to hear", placeholder="Type something...", scale=3)
+                    tts_lang_in = gr.Dropdown(choices=LANGUAGES, value="English", label="Language", scale=1)
+                tts_test_btn = gr.Button("▶ Play", variant="secondary")
+                tts_test_out = gr.Audio(label="Audio Output", autoplay=True)
+                tts_test_btn.click(fn=text_to_speech, inputs=[tts_text_in, tts_lang_in], outputs=[tts_test_out])
+
+            # TAB 4 — ADMIN
+            with gr.Tab("🛡️ Admin"):
+                gr.Markdown("### Complaint Statistics")
+                refresh_btn = gr.Button("🔄 Refresh", variant="primary")
+                with gr.Row():
+                    stats_out = gr.Markdown()
+                    log_out = gr.Markdown()
+                refresh_btn.click(fn=get_admin_stats, outputs=[stats_out, log_out])
+
+    return demo
+
+
+# ─── LAUNCH ───────────────────────────────────────────────────
+if __name__ == "__main__":
+    print("Rahbar v7.0 starting...")
+    demo = build_ui()
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True
+    )