Create app.py

app.py

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+"""
+╔══════════════════════════════════════════════════════════════╗
+║          Rahbar           
+║  yeh sirf complaint nahi, poora civic guide hai
+║      (water/sanitation Q&A + report routing)
+║                                                             ║
+╚══════════════════════════════════════════════════════════════╝
+"""
+
+import os
+import io
+import re
+import uuid
+import base64
+import datetime
+import urllib.parse
+from PIL import Image
+import gradio as gr
+
+# ─── API KEYS FROM ENVIRONMENT ────────────────────────────────
+GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY", "")
+GROQ_API_KEY   = os.environ.get("GROQ_API_KEY", "")
+
+# ─── COMPLAINT LOG (IN-MEMORY) ────────────────────────────────
+complaint_log = []
+
+# ─── CITIES & AREAS ───────────────────────────────────────────
+CITIES_AREAS = {
+    "Lahore":     ["Model Town", "DHA", "Gulberg", "Johar Town", "Bahria Town", "Township", "Cantonment"],
+    "Karachi":    ["Clifton", "DHA", "Gulshan-e-Iqbal", "PECHS", "Korangi", "Saddar", "North Nazimabad"],
+    "Islamabad":  ["F-7", "F-8", "F-10", "G-9", "G-10", "G-11", "Blue Area"],
+    "Rawalpindi": ["Saddar", "Bahria Town", "Chaklala", "Satellite Town", "Murree Road"],
+    "Faisalabad": ["Jinnah Colony", "Madina Town", "Peoples Colony", "Ghulam Muhammad Abad", "Susan Road"],
+    "Multan":     ["Shah Rukn-e-Alam", "Cantt", "Gulgasht Colony", "New Multan", "Bosan Road"],
+    "Peshawar":   ["Hayatabad", "University Town", "Cantt", "Saddar", "Gulbahar"],
+    "Quetta":     ["Satellite Town", "Jinnah Town", "Cantt", "Sariab Road", "Brewery Road"],
+}
+
+ISSUE_TYPES = ["🗑️ Garbage", "🕳️ Pot Hole", "💧 Pipe Leakage"]
+LANGUAGES   = ["English", "اردو (Urdu)", "پنجابی (Punjabi)", "سندھی (Sindhi)"]
+
+# ─── RAG KNOWLEDGE BASE ───────────────────────────────────────
+LEGAL_KB = {
+    "Garbage": {
+        "laws": ["Punjab Waste Management Act 2014", "Pakistan Environmental Protection Act 1997"],
+        "fine": "Rs. 500 – 50,000",
+        "authority": "Local Government Department",
+        "hotline": "1139",
+        "response": "48 hours",
+    },
+    "Pot Hole": {
+        "laws": ["National Highways Safety Ordinance 2000", "Punjab Local Government Act 2022"],
+        "fine": "Dept. liable for damages",
+        "authority": "National Highway Authority (NHA)",
+        "hotline": "051-9032800",
+        "response": "72 hours",
+    },
+    "Pipe Leakage": {
+        "laws": ["WASA Act", "Punjab Water Act 2019"],
+        "fine": "Compensatory damages applicable",
+        "authority": "WASA",
+        "hotline": "042-99200300",
+        "response": "24 hours",
+    },
+}
+
+# ─── LOCALIZED TEXT ───────────────────────────────────────────
+LOCALIZED = {
+    "Garbage": {
+        "English": "Dumping garbage is a criminal offence. Fine: Rs. 500–50,000.",
+        "اردو (Urdu)": "کچرا پھینکنا جرم ہے، جرمانہ 500 سے 50,000 روپے",
+        "پنجابی (Punjabi)": "ਕੂੜਾ ਸੁੱਟਣਾ ਜੁਰਮ ਹੈ, ਜੁਰਮਾਨਾ 500 ਤੋਂ 50,000 ਰੁਪਏ",
+        "سندھی (Sindhi)": "ڪچرو اڇلائڻ جرم آهي، ڏنڊ 500 کان 50,000 رپيا",
+    },
+    "Pot Hole": {
+        "English": "Road repair is the government's responsibility within 72 hours.",
+        "اردو (Urdu)": "سڑک کی مرمت حکومت کی ذمہ داری ہے، 72 گھنٹے",
+        "پنجابی (Punjabi)": "ਸੜਕ ਦੀ ਮੁਰੰਮਤ ਸਰਕਾਰ ਦੀ ਜ਼ਿੰਮੇਵਾਰੀ ਹੈ",
+        "سندھی (Sindhi)": "سڙڪ جي مرمت حڪومت جي ذميواري آهي",
+    },
+    "Pipe Leakage": {
+        "English": "Pipe leakage must be repaired within 24 hours by WASA.",
+        "اردو (Urdu)": "پائپ لیکیج کی مرمت 24 گھنٹے میں لازمی ہے",
+        "پنجابی (Punjabi)": "ਪਾਈਪ ਲੀਕੇਜ ਦੀ ਮੁਰੰਮਤ 24 ਘੰਟਿਆਂ ਵਿੱਚ ਲਾਜ਼ਮੀ ਹੈ",
+        "سندھی (Sindhi)": "پائپ ليڪيج جي مرمت 24 ڪلاڪن ۾ لازمي آهي",
+    },
+}
+
+# Waste-related COCO class IDs
+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}
+
+# ─── YOLO DETECTION ────────────────────────────────���──────────
+def detect_with_yolo(image_pil, issue_type):
+    try:
+        from ultralytics import YOLO
+        import numpy as np
+        model_path = "yolo26n.pt"
+        model = YOLO(model_path)
+        img_np = np.array(image_pil)
+        results = model(img_np, verbose=False)
+        result = results[0]
+        names = model.names
+        detected = []
+        severity = 1
+        clean_issue = issue_type.split(" ", 1)[-1]
+        for box in result.boxes:
+            cls_id = int(box.cls[0])
+            conf = float(box.conf[0])
+            label = names.get(cls_id, f"class_{cls_id}")
+            detected.append(f"{label} ({conf:.0%})")
+            if clean_issue == "Garbage" and cls_id in WASTE_CLASS_IDS:
+                severity = min(10, severity + 2)
+            elif clean_issue in ("Pot Hole", "Pipe Leakage"):
+                severity = min(10, severity + 1)
+        annotated_np = result.plot()
+        annotated = Image.fromarray(annotated_np)
+        summary = f"Detected {len(detected)} object(s): {', '.join(detected[:5])}" if detected else "No specific objects detected by YOLO."
+        severity = max(severity, 3)
+        return annotated, summary, severity
+    except ImportError:
+        return image_pil, "YOLO not installed – skipping object detection.", 5
+    except Exception as e:
+        return image_pil, f"YOLO error: {e}", 5
+
+# ─── GEMINI ANALYSIS ──────────────────────────────────────────
+def analyze_with_gemini(image_pil, issue, location, city, yolo_summary):
+    if not GOOGLE_API_KEY:
+        return "⚠️ GOOGLE_API_KEY not set. Gemini analysis skipped."
+    try:
+        import google.generativeai as genai
+        genai.configure(api_key=GOOGLE_API_KEY)
+        model = genai.GenerativeModel("gemini-3-flash-preview")
+        buf = io.BytesIO()
+        image_pil.save(buf, format="JPEG")
+        image_bytes = buf.getvalue()
+        prompt = f"""
+You are a STRICT Pakistani Civic Issue Inspector AI. Verify if the submitted image shows a real civic problem.
+
+REPORTED ISSUE: '{issue}'
+CITY: {city}
+LOCATION: {location}
+YOLO DETECTION SUMMARY: {yolo_summary}
+
+YOUR TASK - Carefully examine the image and determine:
+- Garbage: Must show actual waste/litter/garbage heap/trash bags
+- Pot Hole: Must show a road with a clearly visible hole or severe damage
+- Pipe Leakage: Must show water leaking from pipe or water flooding from pipe burst
+
+STRICT RULES:
+- Clean area, indoor scene, person alone, vegetation only → REJECT
+- Single leaf or minor dirt is NOT garbage → REJECT  
+- Rough road surface without actual hole → REJECT
+- Be strict. Real civic problems are obvious and undeniable.
+
+Respond ONLY in this EXACT format (no extra text):
+STATUS: [APPROVED or REJECTED]
+REASON: [2-3 sentences in English]
+REASON_URDU: [2-3 sentences in Urdu]
+SEVERITY: [single integer 1-10]
+CONFIDENCE: [percentage like 87%]
+RECOMMENDED_ACTION: [What authorities should do in one sentence]
+"""
+        image_part = {"mime_type": "image/jpeg", "data": base64.b64encode(image_bytes).decode()}
+        response = model.generate_content([prompt, image_part])
+        return response.text.strip()
+    except Exception as e:
+        return f"⚠️ Gemini error: {e}"
+
+def parse_gemini_response(gemini_text):
+    result = {"status": "UNKNOWN", "reason": "Gemini analysis could not be parsed.", "reason_urdu": "", "severity": 5, "confidence": "0%", "action": ""}
+    if not gemini_text:
+        return result
+    status_match = re.search(r"STATUS:\s*(APPROVED|REJECTED)", gemini_text, re.IGNORECASE)
+    if status_match:
+        result["status"] = status_match.group(1).upper()
+    reason_match = re.search(r"REASON:\s*(.+?)(?=REASON_URDU:|$)", gemini_text, re.DOTALL | re.IGNORECASE)
+    if reason_match:
+        result["reason"] = reason_match.group(1).strip()
+    reason_urdu_match = re.search(r"REASON_URDU:\s*(.+?)(?=SEVERITY:|$)", gemini_text, re.DOTALL | re.IGNORECASE)
+    if reason_urdu_match:
+        result["reason_urdu"] = reason_urdu_match.group(1).strip()
+    severity_match = re.search(r"SEVERITY:\s*(\d+)", gemini_text)
+    if severity_match:
+        result["severity"] = int(severity_match.group(1))
+    conf_match = re.search(r"CONFIDENCE:\s*(\d+)%", gemini_text)
+    if conf_match:
+        result["confidence"] = conf_match.group(1) + "%"
+    action_match = re.search(r"RECOMMENDED_ACTION:\s*(.+?)(?=$)", gemini_text, re.DOTALL)
+    if action_match:
+        result["action"] = action_match.group(1).strip()
+    return result
+
+# ─── LLAMA 3 LEGAL ADVICE ─────────────────────────────────────
+def analyze_with_llama(issue, location, city, yolo_summary, severity):
+    if not GROQ_API_KEY:
+        clean = issue.split(" ", 1)[-1]
+        kb = LEGAL_KB.get(clean, {})
+        return (f"📚 Applicable Laws: {', '.join(kb.get('laws', []))}\n💰 Fine/Penalty: {kb.get('fine', 'N/A')}\n📞 Authority Hotline: {kb.get('hotline', 'N/A')}\n⏱️ Expected Response: {kb.get('response', 'N/A')}\n\n(Tip: Set GROQ_API_KEY for AI-generated legal advice)")
+    try:
+        from groq import Groq
+        client = Groq(api_key=GROQ_API_KEY)
+        clean = issue.split(" ", 1)[-1]
+        kb = LEGAL_KB.get(clean, {})
+        prompt = f"""You are a Pakistani civic law expert for the Rahbar platform.
+
+Complaint: {issue} in {location}, {city}
+Severity: {severity}/10
+Detection: {yolo_summary}
+Applicable Laws: {', '.join(kb.get('laws', []))}
+
+Provide:
+1. Citizen's legal rights in this situation
+2. Exact legal sections that apply
+3. How to escalate if the authority doesn't respond within {kb.get('response', '72 hours')}
+4. Official complaint process (step by step)
+5. Compensation/fine the authority may face
+
+Be concise and practical for a Pakistani citizen."""
+        chat = client.chat.completions.create(model="llama-3.3-70b-versatile", messages=[{"role": "user", "content": prompt}], max_tokens=600)
+        return chat.choices[0].message.content.strip()
+    except Exception as e:
+        return f"⚠️ Llama 3 error: {e}"
+
+# ─── TEXT-TO-SPEECH ───────────────────────────────────────────
+LANG_CODES = {"English": "en", "اردو (Urdu)": "ur", "پنجابی (Punjabi)": "pa", "سندھی (Sindhi)": "sd"}
+def make_tts(text, language):
+    try:
+        from gtts import gTTS
+        lang_code = LANG_CODES.get(language, "en")
+        tts = gTTS(text=text[:500], lang=lang_code, slow=False)
+        path = f"/tmp/tts_{uuid.uuid4().hex[:8]}.mp3"
+        tts.save(path)
+        return path
+    except Exception as e:
+        print(f"TTS error: {e}")
+        return None
+
+# ─── SPEECH-TO-TEXT ───────────────────────────────────────────
+def stt(audio_file):
+    if audio_file is None:
+        return "No audio provided."
+    try:
+        import speech_recognition as sr
+        recognizer = sr.Recognizer()
+        with sr.AudioFile(audio_file) as src:
+            audio_data = recognizer.record(src)
+        text = recognizer.recognize_google(audio_data)
+        return text
+    except Exception as e:
+        return f"⚠️ STT error: {e}"
+
+# ─── LEGAL INFO DISPLAY ───────────────────────────────────────
+def law_info(issue, language):
+    clean = issue.split(" ", 1)[-1]
+    kb = LEGAL_KB.get(clean, {})
+    local = LOCALIZED.get(clean, {}).get(language, "")
+    out = f"## ⚖️ Legal Reference: {issue}\n\n**📜 Applicable Laws:**\n"
+    for law in kb.get("laws", []):
+        out += f"  • {law}\n"
+    out += f"\n**💰 Fine / Penalty:** {kb.get('fine', 'N/A')}\n**🏛️ Authority:** {kb.get('authority', 'N/A')}\n**📞 Hotline:** {kb.get('hotline', 'N/A')}\n**⏱️ Response Time:** {kb.get('response', 'N/A')}\n"
+    if local:
+        out += f"\n---\n**Localized Message:**\n> {local}\n"
+    return out
+
+# ─── WHATSAPP SHARE ───────────────────────────────────────────
+def make_whatsapp_link(text):
+    encoded = urllib.parse.quote(text[:1000])
+    return f"https://wa.me/?text={encoded}"
+
+# ─── ADMIN STATS ──────────────────────────────────────────────
+def get_admin_stats():
+    total = len(complaint_log)
+    if total == 0:
+        return "No complaints filed yet.", ""
+    counts = {"Garbage": 0, "Pot Hole": 0, "Pipe Leakage": 0}
+    cities = {}
+    severities = []
+    for c in complaint_log:
+        issue = c.get("issue", "").split(" ", 1)[-1]
+        counts[issue] = counts.get(issue, 0) + 1
+        city = c.get("city", "Unknown")
+        cities[city] = cities.get(city, 0) + 1
+        severities.append(c.get("severity", 5))
+    avg_sev = sum(severities) / len(severities) if severities else 0
+    top_city = max(cities, key=cities.get) if cities else "N/A"
+    stats_md = f"""## 🛡️ Admin Dashboard
+
+| Metric | Value |
+|--------|-------|
+| Total Complaints | **{total}** |
+| Avg Severity | **{avg_sev:.1f}/10** |
+| Top City | **{top_city}** |
+
+### By Issue Type
+| Issue | Count |
+|-------|-------|
+| 🗑️ Garbage | {counts['Garbage']} |
+| 🕳️ Pot Hole | {counts['Pot Hole']} |
+| 💧 Pipe Leakage | {counts['Pipe Leakage']} |
+
+### By City
+"""
+    for city, cnt in sorted(cities.items(), key=lambda x: -x[1]):
+        stats_md += f"| {city} | {cnt} |\n"
+    log_md = "## 📋 Recent Complaints\n\n"
+    for c in reversed(complaint_log[-10:]):
+        log_md += f"**{c['id']}** | {c['timestamp']} | {c['city']}, {c['location']} | {c['issue']} | Severity {c['severity']}/10 | Citizen: {c.get('name', 'N/A')} (CNIC: {c.get('cnic', 'N/A')})\n\n"
+    return stats_md, log_md
+
+def severity_icon(score):
+    if score <= 3: return "🟢"
+    if score <= 6: return "🟡"
+    if score <= 8: return "🟠"
+    return "🔴"
+
+# ─── 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, "")
+    if not location.strip():
+        return (None, "⚠️ Please enter a location.", "", "", None, "")
+    if not name.strip():
+        return (None, "⚠️ Please enter your full name.", "", "", None, "")
+    if not cnic.strip():
+        return (None, "⚠️ Please enter your CNIC (e.g., 1234567890123).", "", "", None, "")
+    
+    complaint_id = f"RB-{uuid.uuid4().hex[:8].upper()}"
+    timestamp = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    clean_issue = issue_type.split(" ", 1)[-1]
+    
+    annotated_img, yolo_summary, yolo_severity = detect_with_yolo(image, issue_type)
+    gemini_raw = analyze_with_gemini(image, issue_type, location, city, yolo_summary)
+    gemini_parsed = parse_gemini_response(gemini_raw)
+    gemini_status = gemini_parsed["status"]
+    gemini_reason = gemini_parsed["reason"]
+    gemini_severity = gemini_parsed["severity"]
+    
+    if gemini_status == "REJECTED":
+        error_msg = f"""❌ **COMPLAINT REJECTED BY AI VERIFICATION**
+
+**Reason:** {gemini_reason}
+**Confidence:** {gemini_parsed.get('confidence', 'N/A')}
+
+Please upload a clear image that clearly shows the reported issue ({issue_type}).
+Your complaint has **NOT** been logged."""
+        return (annotated_img, error_msg, "", "", None, complaint_id)
+    
+    if gemini_status == "UNKNOWN" and "GOOGLE_API_KEY not set" in gemini_raw:
+        gemini_reason = "⚠️ Gemini API key missing – verification skipped. Complaint accepted based on YOLO."
+        gemini_status = "APPROVED_WITH_WARNING"
+    
+    final_severity = gemini_severity if gemini_status == "APPROVED" else yolo_severity
+    llama_advice = analyze_with_llama(issue_type, location, city, yolo_summary, final_severity)
+    kb = LEGAL_KB.get(clean_issue, {})
+    local = LOCALIZED.get(clean_issue, {}).get(language, "")
+    sev_icon = severity_icon(final_severity)
+    
+    complaint_log.append({
+        "id": complaint_id, "timestamp": timestamp, "city": city, "location": location,
+        "issue": issue_type, "severity": final_severity, "language": language,
+        "name": name, "cnic": cnic, "phone": phone,
+    })
+    
+    report = f"""━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+              Rahbar
+         water/sanitation Q&A + report routing
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+
+🆔 Complaint ID : {complaint_id}
+🕐 Timestamp    : {timestamp}
+👤 Citizen      : {name} (CNIC: {cnic})
+📞 Phone        : {phone if phone else "(not provided)"}
+📍 Location     : {location}, {city}
+🔖 Issue Type   : {issue_type}
+🌐 Language     : {language}
+
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+{sev_icon} SEVERITY SCORE: {final_severity}/10
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+
+📷 YOLO DETECTION SUMMARY:
+{yolo_summary}
+
+🤖 AI VERIFICATION (Gemini):
+Status: {gemini_status}
+Reason: {gemini_reason}
+Confidence: {gemini_parsed.get('confidence', 'N/A')}
+
+⚖️ LEGAL INFORMATION:
+  • Laws    : {", ".join(kb.get("laws", []))}
+  • Fine    : {kb.get("fine", "N/A")}
+  • Authority: {kb.get("authority", "N/A")}
+  • Hotline : {kb.get("hotline", "N/A")}
+  • Response: {kb.get("response", "N/A")}
+
+📜 LEGAL ADVICE (Llama 3):
+{llama_advice}
+
+💬 LOCALIZED MESSAGE ({language}):
+{local}
+
+📝 CITIZEN DESCRIPTION:
+{description if description.strip() else "(none provided)"}
+
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+✅ ACTION REQUIRED within {kb.get("response", "72 hours")}
+   Contact: {kb.get("authority", "Local Authority")}
+   Hotline: {kb.get("hotline", "N/A")}
+━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
+"""
+    
+    wa_text = f"🏙️ Rahbar Complaint\nID: {complaint_id}\nIssue: {issue_type}\nLocation: {location}, {city}\nSeverity: {final_severity}/10\nHotline: {kb.get('hotline', 'N/A')}\nFiled: {timestamp}"
+    wa_link = make_whatsapp_link(wa_text)
+    wa_md = f"[📲 Share on WhatsApp]({wa_link})"
+    
+    tts_path = None
+    if enable_tts:
+        tts_text = f"Complaint {complaint_id} filed by {name}. Issue: {issue_type} at {location} in {city}. Severity: {final_severity} out of 10. {local}"
+        tts_path = make_tts(tts_text, language)
+    
+    return annotated_img, report, wa_md, llama_advice, tts_path, complaint_id
+
+# ─── CSS ──────────────────────────────────────────────────────
+CSS = """
+@import url('https://fonts.googleapis.com/css2?family=Noto+Nastaliq+Urdu&family=Playfair+Display:wght@700;900&family=DM+Sans:wght@300;400;500;600&display=swap');
+:root { --green-900: #0d2b1e; --green-800: #14432e; --green-700: #1a5c3f; --green-600: #1f7a52; --green-500: #25a06b; --green-400: #2ec97f; --amber-500: #f5a623; --amber-400: #f7bc57; --amber-300: #fbd07a; --red-500: #e85353; --white: #fafdf8; --gray-100: #f0f4ef; --gray-200: #dce6d8; --gray-400: #8fa88a; --shadow-sm: 0 2px 8px rgba(13,43,30,.15); --shadow-md: 0 4px 20px rgba(13,43,30,.2); --shadow-lg: 0 8px 40px rgba(13,43,30,.25); --radius: 12px; --radius-lg: 20px; }
+*, *::before, *::after { box-sizing: border-box; }
+body, .gradio-container { font-family: 'DM Sans', sans-serif !important; background: var(--white) !important; color: var(--green-900) !important; min-height: 100vh; }
+.saaf-header { background: linear-gradient(135deg, var(--green-800) 0%, var(--green-900) 60%, #0a1f14 100%); border-bottom: 2px solid var(--green-600); padding: 24px 20px 20px; text-align: center; position: relative; overflow: hidden; }
+.saaf-header::before { content: ''; position: absolute; inset: 0; background: radial-gradient(ellipse 60% 60% at 50% 0%, rgba(37,160,107,.18), transparent); pointer-events: none; }
+.saaf-header h1 { font-family: 'Playfair Display', serif !important; font-size: clamp(1.8rem, 5vw, 3rem) !important; font-weight: 900 !important; color: var(--white) !important; margin: 0 0 4px !important; letter-spacing: -0.02em; line-height: 1.1; }
+.saaf-header .urdu-title { font-family: 'Noto Nastaliq Urdu', serif; font-size: clamp(1rem, 3vw, 1.6rem); color: var(--amber-400); direction: rtl; margin: 4px 0 8px; }
+.saaf-header .tagline { font-size: clamp(.75rem, 2vw, .95rem); color: var(--green-400); letter-spacing: .08em; text-transform: uppercase; }
+.badge-strip { display: flex; flex-wrap: wrap; gap: 8px; justify-content: center; padding: 10px 16px; background: var(--white); border-bottom: 1px solid var(--green-700); }
+.badge { font-size: .72rem; font-weight: 600; letter-spacing: .06em; padding: 4px 12px; border-radius: 20px; text-transform: uppercase; }
+.badge-ai { background: var(--white); color: var(--green-400); border: 1px solid var(--green-600); }
+.badge-pk { background: var(--white); color: var(--amber-400); border: 1px solid rgba(245,166,35,.4); }
+.badge-live { background: var(--white); color: #ff8080; border: 1px solid rgba(232,83,83,.4); }
+.tabs { background: var(--white) !important; }
+.tab-nav { background: var(--green-800) !important; border-bottom: 2px solid var(--green-700) !important; overflow-x: auto; white-space: nowrap; }
+.tab-nav button { font-family: 'DM Sans', sans-serif !important; font-weight: 500 !important; font-size: .85rem !important; color: var(--gray-400) !important; padding: 12px 18px !important; border-radius: 0 !important; transition: all .2s !important; }
+.tab-nav button.selected, .tab-nav button[aria-selected="true"] { color: var(--amber-400) !important; border-bottom: 3px solid var(--amber-500) !important; background: transparent !important; }
+.card { background: var(--white); border: 1px solid var(--green-700); border-radius: var(--radius-lg); padding: 20px; margin-bottom: 16px; box-shadow: var(--shadow-sm); }
+.card-title { font-size: .7rem; font-weight: 600; letter-spacing: .1em; text-transform: uppercase; color: var(--green-400); margin-bottom: 12px; padding-bottom: 8px; border-bottom: 1px solid var(--green-700); }
+.gradio-container input, .gradio-container textarea, .gradio-container select, label, .gradio-container .label-wrap span { color: var(--green-900) !important; }
+.gradio-container input, .gradio-container textarea { background: var(--white) !important; border: 1px solid var(--green-600) !important; border-radius: var(--radius) !important; color: var(--green-900) !important; font-family: 'DM Sans', sans-serif !important; }
+.gradio-container input:focus, .gradio-container textarea:focus { border-color: var(--amber-500) !important; outline: none !important; box-shadow: 0 0 0 3px rgba(245,166,35,.15) !important; }
+.gradio-container .wrap, .gradio-container .svelte-1gfkn6j { background: var(--white) !important; border-color: var(--green-600) !important; }
+.gradio-container .block { background: var(--white) !important; }
+.gradio-container button.primary, .gradio-container .btn-primary { background: linear-gradient(135deg, var(--green-600), var(--green-500)) !important; color: var(--white) !important; border: none !important; border-radius: var(--radius) !important; font-family: 'DM Sans', sans-serif !important; font-weight: 600 !important; font-size: .9rem !important; padding: 12px 24px !important; cursor: pointer !important; transition: all .2s !important; box-shadow: var(--shadow-sm) !important; }
+.gradio-container button.primary:hover { background: linear-gradient(135deg, var(--green-500), var(--green-400)) !important; transform: translateY(-1px) !important; box-shadow: var(--shadow-md) !important; }
+.gradio-container button.secondary { background: var(--white) !important; border: 1px solid var(--green-600) !important; color: var(--green-400) !important; }
+.gradio-container .upload-container, .gradio-container [data-testid="image"] { border: 2px dashed var(--green-600) !important; border-radius: var(--radius-lg) !important; background: var(--white) !important; }
+.gradio-container .output-text, .gradio-container .output-markdown, .gradio-container textarea { background: var(--white) !important; color: var(--green-900) !important; border-radius: var(--radius) !important; }
+.gradio-container .prose, .gradio-container .markdown-body { color: var(--green-900) !important; }
+.gradio-container .prose h2, .gradio-container .prose h3 { color: var(--amber-400) !important; font-family: 'Playfair Display', serif !important; }
+.gradio-container .prose a { color: var(--green-400) !important; }
+.gradio-container .prose a[href*="wa.me"] { display: inline-block; var(--white); color: green !important; padding: 8px 18px; border-radius: 24px; text-decoration: none !important; font-weight: 600; margin-top: 8px; }
+.gradio-container audio { width: 100% !important; border-radius: var(--radius) !important; background: var(--white) !important; }
+.info-box { background: var(--white); border: 1px solid var(--green-600); border-left: 4px solid var(--green-500); border-radius: var(--radius); padding: 12px 16px; font-size: .88rem; line-height: 1.6; }
+.warn-box { background: var(--white); border: 1px solid rgba(245,166,35,.4); border-left: 4px solid var(--amber-500); border-radius: var(--radius); padding: 12px 16px; font-size: .88rem; }
+@media (max-width: 640px) { .saaf-header { padding: 16px 12px; } .tab-nav button { padding: 10px 12px !important; font-size: .78rem !important; } .gradio-container .block { padding: 8px !important; } .card { padding: 14px; } .badge { font-size: .65rem; padding: 3px 9px; } }
+::-webkit-scrollbar { width: 6px; height: 6px; }
+::-webkit-scrollbar-track { background: var(--white); }
+::-webkit-scrollbar-thumb { background: var(--green-600); border-radius: 3px; }
+.hotline-pill { display: inline-block; background: var(--white); color: var(--amber-400); border: 1px solid rgba(245,166,35,.35); border-radius: 20px; padding: 2px 12px; font-size: .8rem; font-weight: 600; }
+"""
+
+HEADER_HTML = """
+<div class="saaf-header">
+  <h1>🏙️ Rahbar</h1>
+  <div class="urdu-title">رہبر — ہمارا حق</div>
+  <div class="tagline">Pakistan's AI-Powered Civic Complaint System</div>
+</div>
+<div class="badge-strip">
+  <span class="badge badge-ai">🤖 Gemini 2.0</span>
+  <span class="badge badge-ai">🔍 YOLOv8</span>
+  <span class="badge badge-ai">🦙 Llama 3</span>
+  <span class="badge badge-pk">🇵🇰 4 Languages</span>
+  <span class="badge badge-pk">⚖️ Live Laws</span>
+  <span class="badge badge-live">🔴 Live</span>
+</div>
+"""
+
+def update_areas(city):
+    areas = CITIES_AREAS.get(city, ["Enter area manually"])
+    return gr.Dropdown(choices=areas, value=areas[0])
+
+# ─── BUILD GRADIO UI ──────────────────────────────────────────
+def build_ui():
+    with gr.Blocks(title="Rahbar | رہبر", theme=gr.themes.Base(primary_hue=gr.themes.colors.green, secondary_hue=gr.themes.colors.yellow)) as demo:
+        gr.HTML(HEADER_HTML)
+        with gr.Tabs():
+            # TAB 1 – REPORT ISSUE
+            with gr.Tab("📸 Report Issue"):
+                with gr.Row(equal_height=False):
+                    with gr.Column(scale=1, min_width=280):
+                        gr.HTML('<div class="card-title">👤 Citizen Details</div>')
+                        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.HTML('<div class="card-title" style="margin-top:12px">📍 Complaint Details</div>')
+                        image_input = gr.Image(type="pil", label="📷 Upload Photo", height=220)
+                        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", placeholder="e.g., Main Boulevard near McDonald's", lines=1)
+                        desc_tb = gr.Textbox(label="📝 Description (optional)", placeholder="Describe the issue...", lines=3)
+                        language_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="🌐 Language / زبان")
+                        tts_cb = gr.Checkbox(label="🔊 Read report aloud (TTS)", value=False)
+                        submit_btn = gr.Button("🚀 Submit Complaint", variant="primary", size="lg")
+                    with gr.Column(scale=2, min_width=300):
+                        gr.HTML('<div class="card-title">📊 Analysis Results</div>')
+                        annotated_out = gr.Image(label="🔍 AI Detection Result", height=250)
+                        complaint_id_out = gr.Textbox(label="🆔 Complaint ID", interactive=False)
+                        report_out = gr.Textbox(label="📋 Full Report", lines=18, interactive=False)
+                        wa_out = gr.Markdown(label="📲 Share")
+                        legal_advice_out = gr.Textbox(label="⚖️ Legal Advice (Llama 3)", lines=6, interactive=False)
+                        tts_out = gr.Audio(label="🔊 Voice Report", 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, area_dd, name_tb, cnic_tb, phone_tb, desc_tb, language_dd, tts_cb], outputs=[annotated_out, report_out, wa_out, legal_advice_out, tts_out, complaint_id_out])
+            
+            # TAB 2 – LAW REFERENCE
+            with gr.Tab("⚖️ Law Reference"):
+                gr.HTML('<div class="card-title">📜 Pakistani Civic Laws Database</div>')
+                with gr.Row():
+                    law_issue_dd = gr.Dropdown(choices=ISSUE_TYPES, value=ISSUE_TYPES[0], label="Select Issue", scale=1)
+                    law_lang_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Language", scale=1)
+                law_out = gr.Markdown()
+                gr.Button("📖 Show Law", variant="primary").click(fn=law_info, inputs=[law_issue_dd, law_lang_dd], outputs=[law_out])
+                gr.HTML('<div class="info-box"><strong>📌 Quick Hotlines:</strong><br>🗑️ Garbage — <span class="hotline-pill">1139</span> &nbsp;|&nbsp; 🕳️ Roads — <span class="hotline-pill">051-9032800</span> &nbsp;|&nbsp; 💧 WASA — <span class="hotline-pill">042-99200300</span></div>')
+            
+            # TAB 3 – VOICE INPUT
+            with gr.Tab("🎤 Voice Input"):
+                gr.HTML('<div class="card-title">🎙️ Speech-to-Text (STT)</div>')
+                gr.HTML('<div class="warn-box">Speak your complaint in any language. The system will transcribe it. You can then copy the transcription into the Report Issue tab.</div>')
+                audio_in = gr.Audio(type="filepath", label="🎤 Record or Upload Audio", sources=["microphone", "upload"])
+                stt_btn = gr.Button("📝 Transcribe", variant="primary")
+                stt_out = gr.Textbox(label="📄 Transcription", lines=5, interactive=True)
+                stt_btn.click(fn=stt, inputs=[audio_in], outputs=[stt_out])
+                gr.HTML('<div class="card-title" style="margin-top:20px">🔊 Text-to-Speech (TTS) Test</div>')
+                with gr.Row():
+                    tts_text_in = gr.Textbox(label="Enter text", placeholder="Type something to hear...", 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="🔊 Output", autoplay=True)
+                tts_test_btn.click(fn=make_tts, inputs=[tts_text_in, tts_lang_in], outputs=[tts_test_out])
+            
+            # TAB 4 – ADMIN DASHBOARD
+            with gr.Tab("🛡️ Admin Dashboard"):
+                gr.HTML('<div class="card-title">📊 Complaint Statistics</div>')
+                refresh_btn = gr.Button("🔄 Refresh Stats", 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
+
+if __name__ == "__main__":
+    demo = build_ui()
+    demo.launch(server_name="0.0.0.0", server_port=7860, theme=gr.themes.Base(primary_hue=gr.themes.colors.green, secondary_hue=gr.themes.colors.yellow), css=CSS, share=True, show_error=True)