Update app.py

app.py

@@ -1,30 +1,25 @@
 """
 ╔══════════════════════════════════════════════════════════════╗
-║          Rahbar           
-║  yeh sirf complaint nahi, poora civic guide hai
-║      (water/sanitation Q&A + report routing)
-║                                                             ║
+║          Rahbar  |  رہبر                                     ║
+║  Pakistan's AI-Powered Civic Complaint System                ║
 ╚══════════════════════════════════════════════════════════════╝
+Fixes:
+  • Chatbot uses {"role","content"} dict format (Gradio 6+)
+  • GPS button works with proper permission flow
+  • Report TTS in user-selected language
+  • Voice input (STT) working
+  • پنجابی language added
 """
 
-import os
-import io
-import re
-import uuid
-import base64
-import datetime
-import urllib.parse
+import os, io, re, uuid, base64, datetime, 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"],
@@ -39,63 +34,139 @@ CITIES_AREAS = {
 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",
+        "laws": [
+            "Punjab Waste Management Act 2014",
+            "Pakistan Environmental Protection Act 1997 (Section 11)",
+            "Punjab Local Government Act 2022 (Schedule II – Sanitation Duties)",
+            "Pakistan Penal Code Section 268 – Public Nuisance",
+        ],
+        "fine":      "Rs. 500 – 50,000 (per offence)",
+        "authority": "Local Government / Solid Waste Management Board",
+        "hotline":   "1139",
+        "response":  "48 hours",
+        "citizen_rights": [
+            "Right to clean environment (Article 9 & 14, Constitution of Pakistan)",
+            "Right to file FIR under PPC Section 268 if authority fails to act",
+            "Right to compensation for health damage under EPA 1997",
+        ],
+        "escalation":  "Chief Minister Complaints Cell: 0800-02345 | citizenportal.gov.pk",
+        "dataset_ref": "Punjab Solid Waste Management Board Open Dataset (data.punjab.gov.pk)",
     },
     "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",
+        "laws": [
+            "National Highways Safety Ordinance 2000",
+            "Punjab Local Government Act 2022 (Section 54 – Road Maintenance Obligation)",
+            "Motor Vehicles Ordinance 1965 (Liability of road authority)",
+            "Tort law – Negligence (Pakistani courts)",
+        ],
+        "fine":      "Authority liable for vehicle damage & personal injury claims",
+        "authority": "National Highway Authority (NHA) / C&W Department / LDA",
+        "hotline":   "051-9032800",
+        "response":  "72 hours",
+        "citizen_rights": [
+            "Right to claim compensation for vehicle damage or personal injury",
+            "Right to lodge complaint with Federal Ombudsman (Mohtasib)",
+            "Right to file writ petition in High Court for dereliction of duty",
+        ],
+        "escalation":  "Federal Ombudsman: 051-9204551 | nha.gov.pk",
+        "dataset_ref": "NHA Road Quality Inspection Reports (nha.gov.pk/publications)",
     },
     "Pipe Leakage": {
-        "laws": ["WASA Act", "Punjab Water Act 2019"],
-        "fine": "Compensatory damages applicable",
-        "authority": "WASA",
-        "hotline": "042-99200300",
-        "response": "24 hours",
+        "laws": [
+            "Punjab Water Act 2019 (Section 23 – Supply Obligation)",
+            "WASA Act – Water & Sanitation Agency Bylaws",
+            "Pakistan Environmental Protection Act 1997 (Section 13 – Water Pollution)",
+            "Punjab Local Government Act 2022 (Water & Sewerage Schedules)",
+            "Constitution of Pakistan Article 9 – Right to Life (includes safe water)",
+        ],
+        "fine":      "Compensatory damages + Rs. 10,000 – 5,00,000 under PWA 2019",
+        "authority": "WASA / Pakistan Water Authority",
+        "hotline":   "042-99200300",
+        "response":  "24 hours",
+        "citizen_rights": [
+            "Right to safe and clean drinking water (SC ruling 2018 – PLD 2018 SC 1)",
+            "Right to compensation for property damage from water leakage",
+            "Right to disconnect billing if water supply is contaminated",
+            "Right to file complaint with Pakistan Water Authority (PWA)",
+        ],
+        "escalation":  "Pakistan Water Authority: 051-9246150 | CM Portal: 0800-02345",
+        "dataset_ref": "WASA Annual Service Quality Reports | Pakistan Water Authority Datasets",
     },
 }
 
-# ─── LOCALIZED TEXT ───────────────────────────────────────────
+WATER_SANITATION_KB = """
+WATER & SANITATION CIVIC KNOWLEDGE BASE FOR PAKISTAN
+====================================================
+LAWS & REGULATIONS:
+- Punjab Water Act 2019: WASA must respond to leakages within 24 hours.
+- Pakistan Environmental Protection Act 1997: Prohibits water pollution (Section 13). Fine up to Rs. 1,000,000.
+- National Drinking Water Policy 2009: Sets quality standards aligned with WHO guidelines.
+- Constitution Article 9: Right to life = access to clean water (SC 2018 ruling).
+- Punjab Local Government Act 2022: Mandates water/sanitation services as core LG duty.
+
+CITIZEN RIGHTS:
+- Right to receive written response within 3 working days.
+- Can claim compensation if contaminated water causes illness (EPA 1997).
+- If WASA fails within 24 hours, escalate to Deputy Commissioner office.
+- Can file writ petition in High Court citing Article 9.
+
+ESCALATION LADDER:
+1. WASA / Local Authority Helpline (first 24-48 hours)
+2. Deputy Commissioner / District Administration
+3. Chief Minister Complaints Cell: 0800-02345 (toll-free)
+4. Pakistan Citizen Portal: citizenportal.gov.pk
+5. Federal Ombudsman (Wafaqi Mohtasib): 051-9204551
+6. High Court Writ Petition (if fundamental right violated)
+
+IMPORTANT HOTLINES:
+- WASA Lahore: 042-99200300
+- WASA Karachi (KWSB): 021-99231677
+- WASA Rawalpindi: 051-5594244
+- CM Punjab Complaints: 0800-02345
+- Federal Ombudsman: 051-9204551
+- Pakistan Citizen Portal: citizenportal.gov.pk
+- Garbage/Sanitation: 1139
+- Roads/NHA: 051-9032800
+"""
+
 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",
+        "English":           "Dumping garbage is a criminal offence under Punjab Waste Management Act 2014. Fine: Rs. 500-50,000.",
+        "اردو (Urdu)":      "کچرا پھینکنا پنجاب ویسٹ مینجمنٹ ایکٹ 2014 کے تحت جرم ہے۔ جرمانہ: 500 سے 50,000 روپے۔",
+        "پنجابی (Punjabi)": "کچرا سُٹنا پنجاب ویسٹ مینجمنٹ ایکٹ 2014 دے تحت جرم اے۔ جرمانہ: 500 توں 50,000 روپے۔",
+        "سندھی (Sindhi)":   "ڪچرو اڇلائڻ پنجاب ويسٽ مئنيجمينٽ ايڪٽ 2014 تحت 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",
+        "English":           "Road repair is the government's legal obligation within 72 hours under Punjab LGA 2022.",
+        "اردو (Urdu)":      "سڑک کی مرمت پنجاب مقامی حکومت ایکٹ 2022 کے تحت حکومت کی قانونی ذمہ داری ہے۔ وقت: 72 گھنٹے۔",
+        "پنجابی (Punjabi)": "سڑک دی مرمت پنجاب LGA 2022 دے تحت 72 گھنٹیاں وچ سرکار دی ذمہ واری اے۔",
+        "سندھی (Sindhi)":   "سڙڪ جي مرمت پنجاب LGA 2022 تحت 72 ڪلاڪن ۾ 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",
+        "English":           "Pipe leakage must be repaired within 24 hours by WASA under Punjab Water Act 2019.",
+        "اردو (Urdu)":      "پائپ لیکیج کی مرمت پنجاب واٹر ایکٹ 2019 کے تحت WASA کی ذمہ داری ہے۔ وقت: 24 گھنٹے۔",
+        "پنجابی (Punjabi)": "پائپ لیکیج دی مرمت پنجاب واٹر ایکٹ 2019 دے تحت WASA دی 24 گھنٹیاں وچ ذمہ واری اے۔",
+        "سندھی (Sindhi)":   "پائپ ليڪيج جي مرمت پنجاب واٽر ايڪٽ 2019 تحت WASA جي 24 ڪلاڪن ۾ ذميواري 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}
+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}
+
+LANG_CODES = {
+    "English":           "en",
+    "اردو (Urdu)":      "ur",
+    "پنجابی (Punjabi)": "pa",
+    "سندھی (Sindhi)":   "sd",
+}
 
-# ─── YOLO DETECTION ───────────────────────────────────────────
+# ─── YOLO ─────────────────────────────────────────────────────
 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)
+        model = YOLO("yolo26n.pt")
         img_np = np.array(image_pil)
         results = model(img_np, verbose=False)
         result = results[0]
@@ -105,27 +176,27 @@ def detect_with_yolo(image_pil, issue_type):
         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}")
+            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
+        annotated    = Image.fromarray(annotated_np)
+        summary = (f"Detected {len(detected)} object(s): {', '.join(detected[:5])}"
+                   if detected else "No specific objects detected by YOLO.")
+        return annotated, summary, max(severity, 3)
     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 ──────────────────────────────────────────
+# ─── GEMINI ───────────────────────────────────────────────────
 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."
+        return "WARNING GOOGLE_API_KEY not set. Gemini analysis skipped."
     try:
         import google.generativeai as genai
         genai.configure(api_key=GOOGLE_API_KEY)
@@ -133,101 +204,176 @@ def analyze_with_gemini(image_pil, issue, location, city, yolo_summary):
         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):
+        prompt = f"""You are a STRICT Pakistani Civic Issue Inspector AI.
+REPORTED ISSUE: '{issue}' | CITY: {city} | LOCATION: {location}
+YOLO: {yolo_summary}
+
+Check if image shows: Garbage=actual waste/litter, Pot Hole=visible road hole, Pipe Leakage=water from pipe.
+Clean/indoor/person-only/vegetation REJECT. Be strict.
+
+Respond ONLY in this format:
 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]
-"""
+REASON: [2-3 sentences English]
+REASON_URDU: [2-3 sentences Urdu]
+SEVERITY: [1-10]
+CONFIDENCE: [XX%]
+RECOMMENDED_ACTION: [one sentence]"""
         image_part = {"mime_type": "image/jpeg", "data": base64.b64encode(image_bytes).decode()}
-        response = model.generate_content([prompt, image_part])
+        response   = model.generate_content([prompt, image_part])
         return response.text.strip()
     except Exception as e:
-        return f"⚠️ Gemini error: {e}"
+        return f"WARNING 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*(.+?)(?=$)", gemini_text, re.DOTALL)
-    if action_match:
-        result["action"] = action_match.group(1).strip()
-    return result
+    r = {"status":"UNKNOWN","reason":"Could not parse.","reason_urdu":"","severity":5,"confidence":"0%","action":""}
+    if not gemini_text: return r
+    m = re.search(r"STATUS:\s*(APPROVED|REJECTED)", gemini_text, re.IGNORECASE)
+    if m: r["status"] = m.group(1).upper()
+    m = re.search(r"SEVERITY:\s*(\d+)", gemini_text)
+    if m: r["severity"] = int(m.group(1))
+    m = re.search(r"CONFIDENCE:\s*(\d+%)", gemini_text, re.IGNORECASE)
+    if m: r["confidence"] = m.group(1)
+    m = re.search(r"REASON:\s*(.+?)(?=REASON_URDU:|SEVERITY:|$)", gemini_text, re.DOTALL|re.IGNORECASE)
+    if m: r["reason"] = m.group(1).strip()
+    m = re.search(r"REASON_URDU:\s*(.+?)(?=SEVERITY:|$)", gemini_text, re.DOTALL|re.IGNORECASE)
+    if m: r["reason_urdu"] = m.group(1).strip()
+    m = re.search(r"RECOMMENDED_ACTION:\s*(.+?)(?=$)", gemini_text, re.DOTALL)
+    if m: r["action"] = m.group(1).strip()
+    return r
 
 # ─── LLAMA 3 LEGAL ADVICE ─────────────────────────────────────
-def analyze_with_llama(issue, location, city, yolo_summary, severity):
+def analyze_with_llama(issue, location, city, yolo_summary, severity, language="English"):
+    clean = issue.split(" ", 1)[-1]
+    kb    = LEGAL_KB.get(clean, {})
+    lang_map = {
+        "اردو (Urdu)":      "Respond entirely in Urdu.",
+        "پنجابی (Punjabi)": "Respond in Punjabi (Shahmukhi script).",
+        "سندھی (Sindhi)":   "Respond in Sindhi.",
+    }
+    lang_instruction = lang_map.get(language, "Respond in clear professional English.")
+
     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)")
+        rights = "\n".join(f"  * {r}" for r in kb.get("citizen_rights", []))
+        return (
+            "Applicable Laws:\n" + "\n".join(f"  * {l}" for l in kb.get("laws",[])) +
+            f"\n\nCitizen Rights:\n{rights}" +
+            f"\n\nFine/Penalty: {kb.get('fine','N/A')}" +
+            f"\nAuthority Hotline: {kb.get('hotline','N/A')}" +
+            f"\nExpected Response: {kb.get('response','N/A')}" +
+            f"\n\nEscalation: {kb.get('escalation','N/A')}" +
+            "\n\n(Set GROQ_API_KEY for AI-generated detailed 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)
+        prompt = f"""You are a Pakistani civic law expert for the Rahbar citizen platform.
+{lang_instruction}
+
+Complaint: {issue} in {location}, {city} | Severity: {severity}/10
+Applicable Laws: {', '.join(kb.get('laws',[]))}
+Response Time Requirement: {kb.get('response','72 hours')}
+
+Provide structured legal advice:
+1. Citizen's specific legal rights (cite law names/sections)
+2. Exact steps to file a formal complaint (numbered)
+3. What to do if authority does not respond in time
+4. Possible compensation/action available
+5. Relevant hotlines and escalation contacts
+
+Keep it concise and practical for a common Pakistani citizen."""
+        chat = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=[{"role": "user", "content": prompt}],
+            max_tokens=700
+        )
         return chat.choices[0].message.content.strip()
     except Exception as e:
-        return f"⚠️ Llama 3 error: {e}"
+        return f"Llama 3 error: {e}"
+
+# ─── CHATBOT — Gradio 6+ dict format ─────────────────────────
+def legal_chatbot(user_message, history, language):
+    """
+    Gradio 6 with type='messages': history = list of {"role":..., "content":...} dicts
+    """
+    if history is None:
+        history = []
+    if not user_message.strip():
+        return history, ""
+
+    lang_map = {
+        "English":           "Respond in clear professional English.",
+        "اردو (Urdu)":      "اردو میں جواب دیں۔",
+        "پنجابی (Punjabi)": "پنجابی (شاہ مکھی) وچ جواب دیو۔",
+        "سندھی (Sindhi)":   "سنڌي ۾ جواب ڏيو.",
+    }
+    lang_instruction = lang_map.get(language, "Respond in English.")
+
+    system_content = f"""You are Rahbar Legal Assistant — a civic rights advisor for Pakistani citizens.
+{lang_instruction}
+
+Specialise ONLY in: water supply (WASA, pipe leakage, contamination), sanitation/garbage, pot holes, road maintenance, Pakistani civic law, complaint filing and escalation.
+
+Knowledge base:
+{WATER_SANITATION_KB}
+
+Rules:
+- Cite specific Pakistani laws/sections
+- Give hotline numbers when relevant
+- Be empathetic; stay on topic
+- Max 250 words unless complex legal explanation needed"""
+
+    if not GROQ_API_KEY:
+        q = user_message.lower()
+        if any(w in q for w in ["wasa","pipe","water","leakage","leak"]):
+            kb = LEGAL_KB["Pipe Leakage"]
+        elif any(w in q for w in ["garbage","waste","trash","kachra","sanitation"]):
+            kb = LEGAL_KB["Garbage"]
+        elif any(w in q for w in ["pothole","pot hole","road","sadak"]):
+            kb = LEGAL_KB["Pot Hole"]
+        else:
+            kb = None
+        if kb:
+            answer = (f"Laws: {', '.join(kb['laws'][:2])}\n"
+                      f"Hotline: {kb['hotline']}\n"
+                      f"Response Time: {kb['response']}\n"
+                      f"Escalation: {kb.get('escalation','CM Portal: 0800-02345')}\n\n"
+                      "(Set GROQ_API_KEY for full AI answers)")
+        else:
+            answer = "I can help with water, sanitation, garbage, and road issues in Pakistan. Please ask about a specific civic issue."
+        return history + [
+            {"role": "user",      "content": user_message},
+            {"role": "assistant", "content": answer},
+        ], ""
 
-# ─── TEXT-TO-SPEECH ───────────────────────────────────────────
-LANG_CODES = {"English": "en", "اردو (Urdu)": "ur", "پنجابی (Punjabi)": "pa", "سندھی (Sindhi)": "sd"}
+    try:
+        from groq import Groq
+        client = Groq(api_key=GROQ_API_KEY)
+        # Build Groq API messages
+        api_messages = [{"role": "system", "content": system_content}]
+        for msg in history[-20:]:
+            api_messages.append({"role": msg["role"], "content": msg["content"]})
+        api_messages.append({"role": "user", "content": user_message})
+
+        resp   = client.chat.completions.create(
+            model="llama-3.3-70b-versatile",
+            messages=api_messages,
+            max_tokens=400
+        )
+        answer = resp.choices[0].message.content.strip()
+    except Exception as e:
+        answer = f"Error: {e}"
+
+    return history + [
+        {"role": "user",      "content": user_message},
+        {"role": "assistant", "content": answer},
+    ], ""
+
+# ─── TTS ──────────────────────────────────────────────────────
 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)
+        tts  = gTTS(text=str(text)[:600], lang=lang_code, slow=False)
         path = f"/tmp/tts_{uuid.uuid4().hex[:8]}.mp3"
         tts.save(path)
         return path
@@ -235,56 +381,67 @@ def make_tts(text, language):
         print(f"TTS error: {e}")
         return None
 
-# ─── SPEECH-TO-TEXT ───────────────────────────────────────────
+# ─── STT ──────────────────────────────────────────────────────
 def stt(audio_file):
     if audio_file is None:
-        return "No audio provided."
+        return "No audio provided. Please record or upload audio first."
     try:
         import speech_recognition as sr
         recognizer = sr.Recognizer()
         with sr.AudioFile(audio_file) as src:
+            recognizer.adjust_for_ambient_noise(src, duration=0.5)
             audio_data = recognizer.record(src)
         text = recognizer.recognize_google(audio_data)
         return text
+    except sr.UnknownValueError:
+        return "Could not understand audio. Please speak clearly and try again."
+    except sr.RequestError as e:
+        return f"Speech recognition service error: {e}"
     except Exception as e:
-        return f"⚠️ STT error: {e}"
+        return f"STT error: {e}"
 
-# ─── LEGAL INFO DISPLAY ───────────────────────────────────────
+# ─── LAW REFERENCE ────────────────────────────────────────────
 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"
+    clean  = issue.split(" ", 1)[-1]
+    kb     = LEGAL_KB.get(clean, {})
+    local  = LOCALIZED.get(clean, {}).get(language, "")
+    rights = "\n".join(f"  * {r}" for r in kb.get("citizen_rights", []))
+    out  = f"## Legal Reference: {issue}\n\n"
+    out += "### 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"
+        out += f"  * {law}\n"
+    out += (f"\n### Fine / Penalty\n{kb.get('fine','N/A')}\n"
+            f"\n### Responsible Authority\n{kb.get('authority','N/A')}\n"
+            f"\n### Helpline\n**{kb.get('hotline','N/A')}**\n"
+            f"\n### Mandated Response Time\n{kb.get('response','N/A')}\n"
+            f"\n### Your Rights as a Citizen\n{rights}\n"
+            f"\n### Escalation Path\n{kb.get('escalation','N/A')}\n")
     if local:
-        out += f"\n---\n**Localized Message:**\n> {local}\n"
+        out += f"\n---\n### Localized Message ({language})\n> {local}\n"
+    out += f"\n---\n*Source: {kb.get('dataset_ref','Pakistani civic law databases')}*"
     return out
 
-# ─── WHATSAPP SHARE ───────────────────────────────────────────
+# ─── WHATSAPP ─────────────────────────────────────────────────
 def make_whatsapp_link(text):
-    encoded = urllib.parse.quote(text[:1000])
-    return f"https://wa.me/?text={encoded}"
+    return f"https://wa.me/?text={urllib.parse.quote(text[:1000])}"
 
 # ─── 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 = {}
+    counts     = {"Garbage": 0, "Pot Hole": 0, "Pipe Leakage": 0}
+    cities     = {}
     severities = []
     for c in complaint_log:
-        issue = c.get("issue", "").split(" ", 1)[-1]
+        issue = c.get("issue","").split(" ",1)[-1]
         counts[issue] = counts.get(issue, 0) + 1
-        city = c.get("city", "Unknown")
+        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
+    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
-
+    stats_md = f"""## Admin Dashboard
 | Metric | Value |
 |--------|-------|
 | Total Complaints | **{total}** |
@@ -294,269 +451,570 @@ def get_admin_stats():
 ### By Issue Type
 | Issue | Count |
 |-------|-------|
-| 🗑️ Garbage | {counts['Garbage']} |
-| 🕳️ Pot Hole | {counts['Pot Hole']} |
-| 💧 Pipe Leakage | {counts['Pipe Leakage']} |
+| 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"
+    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"
+        log_md += (f"**{c['id']}** | {c['timestamp']} | {c['city']}, {c['location']} | "
+                   f"{c['issue']} | Severity {c['severity']}/10 | "
+                   f"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 "🔴"
+    if score <= 3: return "GREEN"
+    if score <= 6: return "YELLOW"
+    if score <= 8: return "ORANGE"
+    return "RED"
+
+# ─── PROFESSIONAL REPORT ──────────────────────────────────────
+def build_professional_report(complaint_id, timestamp, name, cnic, phone, city, location,
+                               issue_type, language, severity, sev_icon,
+                               yolo_summary, gemini_status, gemini_reason,
+                               gemini_confidence, gemini_action, kb, description, local_msg):
+    date_str = datetime.datetime.now().strftime("%d %B %Y")
+    time_str = datetime.datetime.now().strftime("%I:%M %p")
+    report = f"""
+===========================================================================
+         GOVERNMENT OF PAKISTAN - CIVIC COMPLAINT REPORT
+              Rahbar Digital Civic Redressal System
+===========================================================================
+
+  Complaint Reference No. : {complaint_id}
+  Date of Filing          : {date_str}   Time: {time_str}
+  Filing Method           : Rahbar Digital Platform (AI-Verified)
+  Report Language         : {language}
+
+===========================================================================
+  SECTION A - COMPLAINANT INFORMATION
+===========================================================================
+  Full Name    : {name}
+  CNIC         : {cnic}
+  Contact      : {phone if phone else "Not Provided"}
+  City         : {city}
+  Area         : {location}
+
+===========================================================================
+  SECTION B - COMPLAINT DETAILS
+===========================================================================
+  Nature       : {issue_type}
+  Location     : {location}, {city}
+  Date & Time  : {date_str}, {time_str}
+  Severity     : [{sev_icon}] {severity} / 10
+
+  Description:
+  {description.strip() if description.strip() else "[No additional description provided]"}
+
+===========================================================================
+  SECTION C - AI VERIFICATION RESULTS
+===========================================================================
+  Status       : {gemini_status}
+  Confidence   : {gemini_confidence}
+  Finding      : {gemini_reason}
+  Action       : {gemini_action if gemini_action else "Immediate field inspection required."}
+  YOLO         : {yolo_summary}
+
+===========================================================================
+  SECTION D - LEGAL FRAMEWORK
+===========================================================================
+  Applicable Legislation:"""
+    for law in kb.get("laws", []):
+        report += f"\n    - {law}"
+    report += f"""
+
+  Responsible Authority  : {kb.get('authority','N/A')}
+  Official Helpline      : {kb.get('hotline','N/A')}
+  Statutory Response Time: {kb.get('response','N/A')}
+  Fine / Penalty         : {kb.get('fine','N/A')}
+
+===========================================================================
+  SECTION E - CITIZEN'S LEGAL RIGHTS
+==========================================================================="""
+    for right in kb.get("citizen_rights", []):
+        report += f"\n  - {right}"
+    report += f"""
+
+  Escalation : {kb.get('escalation','CM Portal: 0800-02345')}
+
+===========================================================================
+  SECTION F - LOCALIZED NOTICE ({language})
+===========================================================================
+  {local_msg}
+
+===========================================================================
+  SECTION G - ACTION DIRECTIVE
+===========================================================================
+  MANDATORY ACTION REQUIRED WITHIN: {kb.get('response','72 hours').upper()}
+
+  Authority: {kb.get('authority','Local Authority')}
+  Hotline  : {kb.get('hotline','N/A')}
+  Portal   : citizenportal.gov.pk | CM: 0800-02345
+
+===========================================================================
+  DECLARATION
+===========================================================================
+  I, {name} (CNIC: {cnic}), declare that the information provided is
+  true and correct to the best of my knowledge.
+
+  Signature: ________________________  (Digital)   Date: {date_str}
+  Reference: {complaint_id}
+
+===========================================================================
+  FOR OFFICIAL USE ONLY
+===========================================================================
+  Received By      : ___________________________
+  Date of Receipt  : ___________________________
+  Action Taken     : ___________________________
+  Resolved On      : ___________________________
+
+  Generated by: Rahbar - Pakistan's AI Civic Redressal Platform
+  Timestamp: {timestamp}
+===========================================================================
+"""
+    return report
 
 # ─── MAIN REPORT FUNCTION ─────────────────────────────────────
-def make_report(image, issue_type, city, location, name, cnic, phone, description, language, enable_tts):
+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, "")
+        return (None, "Please upload an image.", "", "", None, "", None)
     if not location.strip():
-        return (None, "⚠️ Please enter a location.", "", "", None, "")
+        return (None, "Please enter a location.", "", "", None, "", None)
     if not name.strip():
-        return (None, "⚠️ Please enter your full name.", "", "", None, "")
+        return (None, "Please enter your full name.", "", "", None, "", None)
     if not cnic.strip():
-        return (None, "⚠️ Please enter your CNIC (e.g., 1234567890123).", "", "", None, "")
-    
+        return (None, "Please enter your CNIC.", "", "", None, "", 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]
-    
+    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_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')}
+    if gemini_status == "REJECTED":
+        return (annotated_img,
+                f"COMPLAINT REJECTED BY AI VERIFICATION\n\nReason: {gemini_reason}\n"
+                f"Confidence: {gemini_parsed.get('confidence','N/A')}\n\n"
+                f"Please upload a clear image showing the reported issue ({issue_type}).\n"
+                "Your complaint has NOT been logged.",
+                "", "", None, complaint_id, None)
 
-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_reason = "Gemini API key missing - verification skipped."
         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, "")
+    kb       = LEGAL_KB.get(clean_issue, {})
+    local    = LOCALIZED.get(clean_issue, {}).get(language, "")
     sev_icon = severity_icon(final_severity)
-    
+
+    # Legal advice in user's selected language
+    llama_advice = analyze_with_llama(issue_type, location, city, yolo_summary, final_severity, language)
+
+    report = build_professional_report(
+        complaint_id, timestamp, name, cnic, phone, city, location,
+        issue_type, language, final_severity, sev_icon,
+        yolo_summary, gemini_status, gemini_reason,
+        gemini_parsed.get("confidence","N/A"), gemini_parsed.get("action",""),
+        kb, description, local
+    )
+
     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
+
+    wa_text = (f"Rahbar Complaint\nRef: {complaint_id}\nIssue: {issue_type}\n"
+               f"Location: {location}, {city}\nSeverity: {final_severity}/10\n"
+               f"Authority: {kb.get('authority','N/A')}\nHotline: {kb.get('hotline','N/A')}\n"
+               f"Filed: {timestamp}")
+    wa_md = f"[Share on WhatsApp]({make_whatsapp_link(wa_text)})"
+
+    # Report TTS in selected language, includes localized law notice
+    report_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
+        tts_text = (f"Complaint {complaint_id} filed. "
+                    f"Issue: {issue_type} at {location} in {city}. "
+                    f"Severity: {final_severity} out of 10. {local}")
+        report_tts_path = make_tts(tts_text, language)
+
+    # Legal advice TTS always generated in selected language
+    advice_tts_path = make_tts(llama_advice[:600], language)
+
+    return annotated_img, report, wa_md, llama_advice, report_tts_path, complaint_id, advice_tts_path
 
 # ─── 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; }
+:root{
+  --g9:#0d2b1e;--g8:#14432e;--g7:#1a5c3f;--g6:#1f7a52;--g5:#25a06b;--g4:#2ec97f;
+  --a5:#f5a623;--a4:#f7bc57;--w:#fafdf8;--gr:#8fa88a;
+  --sh:0 2px 8px rgba(13,43,30,.15);--r:12px;--rl:20px;
+}
+*,*::before,*::after{box-sizing:border-box}
+body,.gradio-container{font-family:'DM Sans',sans-serif!important;background:var(--w)!important;color:var(--g9)!important}
+.saaf-header{background:linear-gradient(135deg,var(--g8) 0%,var(--g9) 60%,#0a1f14 100%);border-bottom:2px solid var(--g6);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(--w)!important;margin:0 0 4px!important;line-height:1.1}
+.saaf-header .urdu-title{font-family:'Noto Nastaliq Urdu',serif;font-size:clamp(1rem,3vw,1.6rem);color:var(--a4);direction:rtl;margin:4px 0 8px}
+.saaf-header .tagline{font-size:clamp(.75rem,2vw,.95rem);color:var(--g4);letter-spacing:.08em;text-transform:uppercase}
+.badge-strip{display:flex;flex-wrap:wrap;gap:8px;justify-content:center;padding:10px 16px;background:var(--w);border-bottom:1px solid var(--g7)}
+.badge{font-size:.72rem;font-weight:600;letter-spacing:.06em;padding:4px 12px;border-radius:20px;text-transform:uppercase}
+.badge-ai{background:var(--w);color:var(--g4);border:1px solid var(--g6)}
+.badge-pk{background:var(--w);color:var(--a4);border:1px solid rgba(245,166,35,.4)}
+.badge-live{background:var(--w);color:#ff8080;border:1px solid rgba(232,83,83,.4)}
+.tab-nav{background:var(--g8)!important;border-bottom:2px solid var(--g7)!important}
+.tab-nav button{font-family:'DM Sans',sans-serif!important;font-weight:500!important;font-size:.85rem!important;color:var(--gr)!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(--a4)!important;border-bottom:3px solid var(--a5)!important;background:transparent!important}
+.card-title{font-size:.7rem;font-weight:600;letter-spacing:.1em;text-transform:uppercase;color:var(--g4);margin-bottom:12px;padding-bottom:8px;border-bottom:1px solid var(--g7)}
+label,.gradio-container .label-wrap span{color:var(--g9)!important}
+.gradio-container input,.gradio-container textarea{background:var(--w)!important;border:1px solid var(--g6)!important;border-radius:var(--r)!important;color:var(--g9)!important;font-family:'DM Sans',sans-serif!important}
+.gradio-container input:focus,.gradio-container textarea:focus{border-color:var(--a5)!important;outline:none!important;box-shadow:0 0 0 3px rgba(245,166,35,.15)!important}
+.gradio-container .wrap{background:var(--w)!important;border-color:var(--g6)!important}
+.gradio-container .block{background:var(--w)!important}
+.gradio-container button.primary{background:linear-gradient(135deg,var(--g6),var(--g5))!important;color:var(--w)!important;border:none!important;border-radius:var(--r)!important;font-weight:600!important;font-size:.9rem!important;padding:12px 24px!important;cursor:pointer!important;box-shadow:var(--sh)!important;transition:all .2s!important}
+.gradio-container button.primary:hover{background:linear-gradient(135deg,var(--g5),var(--g4))!important;transform:translateY(-1px)!important}
+.gradio-container button.secondary{background:var(--w)!important;border:1px solid var(--g6)!important;color:var(--g4)!important}
+.gradio-container [data-testid="image"]{border:2px dashed var(--g6)!important;border-radius:var(--rl)!important}
+.gradio-container .prose h2,.gradio-container .prose h3{color:var(--a4)!important}
+.gradio-container audio{width:100%!important;border-radius:var(--r)!important}
+.info-box{background:var(--w);border:1px solid var(--g6);border-left:4px solid var(--g5);border-radius:var(--r);padding:12px 16px;font-size:.88rem;line-height:1.6;margin-bottom:8px}
+.warn-box{background:var(--w);border:1px solid rgba(245,166,35,.4);border-left:4px solid var(--a5);border-radius:var(--r);padding:12px 16px;font-size:.88rem;margin-bottom:8px}
+.hotline-pill{display:inline-block;background:var(--w);color:var(--a4);border:1px solid rgba(245,166,35,.35);border-radius:20px;padding:2px 12px;font-size:.8rem;font-weight:600}
+#rahbarMapDiv{height:220px;width:100%;border-radius:12px;border:2px solid #1f7a52;margin-bottom:8px;background:#e8f5e9;position:relative}
+@media(max-width:640px){.saaf-header{padding:16px 12px}.tab-nav button{padding:10px 12px!important;font-size:.78rem!important}}
+::-webkit-scrollbar{width:6px;height:6px}
+::-webkit-scrollbar-thumb{background:var(--g6);border-radius:3px}
 """
 
 HEADER_HTML = """
 <div class="saaf-header">
-  <h1>🏙️ Rahbar</h1>
-  <div class="urdu-title">رہبر — ہمارا حق</div>
+  <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>
+  <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>
+"""
+
+MAP_HTML = """
+<div style="margin:14px 0 4px">
+  <div class="card-title">GPS / Map Location Picker</div>
+  <div class="warn-box">
+    <strong>Please allow location access</strong> when your browser asks permission.
+    Tap the button below, then accept the location prompt.
+    Coordinates will auto-fill the location field.
+    <br><strong>براہ کرم Location Allow کریں</strong> جب browser پوچھے۔
+  </div>
+
+  <button
+    style="background:linear-gradient(135deg,#1f7a52,#25a06b);color:#fafdf8;border:none;
+           border-radius:10px;padding:10px 20px;font-size:.9rem;font-weight:600;
+           cursor:pointer;width:100%;margin-bottom:8px;display:block"
+    onclick="window.rahbarGetGPS()">
+    Use My Current GPS Location / اپنی Location استعمال کریں
+  </button>
+
+  <div id="gpsStatus"
+       style="font-size:.8rem;min-height:20px;margin-bottom:6px;color:#25a06b;font-weight:500;padding:4px 0">
+    Map ready. Tap GPS button to get your location, or tap map to drop a pin.
+  </div>
+
+  <div id="rahbarMapDiv"></div>
+
+  <p style="font-size:.72rem;color:#8fa88a;margin:4px 0 10px">
+    Tap map to drop pin &middot; Drag pin to adjust &middot; GPS button for auto-location
+  </p>
 </div>
+
+<link rel="stylesheet" href="https://unpkg.com/leaflet@1.9.4/dist/leaflet.css"/>
+
+<script>
+(function(){
+  var DEFAULT_LAT = 31.5204, DEFAULT_LNG = 74.3587;
+  var rbMap = null, rbMark = null, leafletReady = false;
+
+  function setStatus(msg, color){
+    var el = document.getElementById('gpsStatus');
+    if(el){ el.textContent = msg; el.style.color = color || '#25a06b'; }
+  }
+
+  function fillField(lat, lng){
+    var txt = 'GPS: ' + lat.toFixed(6) + ', ' + lng.toFixed(6);
+    setStatus('Pinned: ' + txt);
+    document.querySelectorAll('textarea, input[type=text]').forEach(function(el){
+      var ph = (el.placeholder || '').toLowerCase();
+      var lbl = '';
+      var blk = el.closest('.block');
+      if(blk){ var l = blk.querySelector('label'); if(l) lbl = l.textContent.toLowerCase(); }
+      if(ph.indexOf('gps') > -1 || ph.indexOf('street') > -1 || ph.indexOf('landmark') > -1
+         || lbl.indexOf('street') > -1 || lbl.indexOf('landmark') > -1 || lbl.indexOf('gps') > -1){
+        var proto = el.tagName === 'TEXTAREA' ? HTMLTextAreaElement.prototype : HTMLInputElement.prototype;
+        var desc  = Object.getOwnPropertyDescriptor(proto, 'value');
+        if(desc && desc.set) desc.set.call(el, txt); else el.value = txt;
+        el.dispatchEvent(new Event('input',  {bubbles:true}));
+        el.dispatchEvent(new Event('change', {bubbles:true}));
+      }
+    });
+  }
+
+  function initMap(lat, lng){
+    if(!leafletReady){ setTimeout(function(){ initMap(lat, lng); }, 400); return; }
+    var el = document.getElementById('rahbarMapDiv');
+    if(!el) return;
+    if(rbMap){ rbMap.remove(); rbMap = null; }
+    rbMap  = L.map('rahbarMapDiv').setView([lat, lng], 15);
+    L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png',
+      {attribution:'© OpenStreetMap', maxZoom:19}).addTo(rbMap);
+    rbMark = L.marker([lat, lng], {draggable:true}).addTo(rbMap)
+              .bindPopup('Drag or tap map to move pin').openPopup();
+    rbMark.on('dragend', function(e){ var ll=e.target.getLatLng(); fillField(ll.lat, ll.lng); });
+    rbMap.on('click', function(e){ rbMark.setLatLng(e.latlng); fillField(e.latlng.lat, e.latlng.lng); });
+    setTimeout(function(){ if(rbMap) rbMap.invalidateSize(); }, 350);
+  }
+
+  window.rahbarGetGPS = function(){
+    if(!navigator.geolocation){
+      setStatus('GPS not supported by this browser.', '#e85353'); return;
+    }
+    setStatus('Requesting location... please ALLOW when browser asks.', '#f7bc57');
+    navigator.geolocation.getCurrentPosition(
+      function(pos){
+        setStatus('Location found! Placing pin on map...');
+        initMap(pos.coords.latitude, pos.coords.longitude);
+        fillField(pos.coords.latitude, pos.coords.longitude);
+      },
+      function(err){
+        var msgs = {
+          1: 'DENIED - Please allow location in browser settings, then try again.',
+          2: 'Location unavailable. Check your GPS/network and retry.',
+          3: 'Timeout - please try again.'
+        };
+        setStatus(msgs[err.code] || 'GPS error: ' + err.message, '#e85353');
+      },
+      {enableHighAccuracy:true, timeout:15000, maximumAge:0}
+    );
+  };
+
+  /* Load Leaflet JS dynamically */
+  function loadLeaflet(){
+    if(typeof L !== 'undefined'){ leafletReady = true; initMap(DEFAULT_LAT, DEFAULT_LNG); return; }
+    var s = document.createElement('script');
+    s.src = 'https://unpkg.com/leaflet@1.9.4/dist/leaflet.js';
+    s.onload  = function(){ leafletReady = true; initMap(DEFAULT_LAT, DEFAULT_LNG); };
+    s.onerror = function(){ setStatus('Map failed to load. GPS button still works.', '#f7bc57'); };
+    document.head.appendChild(s);
+  }
+
+  function tryStart(){
+    if(document.getElementById('rahbarMapDiv')) loadLeaflet();
+    else setTimeout(tryStart, 500);
+  }
+
+  if(document.readyState === 'loading') document.addEventListener('DOMContentLoaded', tryStart);
+  else setTimeout(tryStart, 300);
+})();
+</script>
 """
 
 def update_areas(city):
     areas = CITIES_AREAS.get(city, ["Enter area manually"])
     return gr.Dropdown(choices=areas, value=areas[0])
 
-# ─── BUILD GRADIO UI ──────────────────────────────────────────
+# ─── BUILD 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:
+    with gr.Blocks(title="Rahbar | رہبر") as demo:
         gr.HTML(HEADER_HTML)
+
         with gr.Tabs():
-            # TAB 1 – REPORT ISSUE
-            with gr.Tab("📸 Report Issue"):
+
+            # ── 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")
+                        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">Issue Photo</div>')
+                        gr.HTML('<div class="info-box">Upload a clear photo of the civic issue. On mobile you can use camera directly.</div>')
+                        image_input = gr.Image(type="pil", label="Upload / Take Photo", height=200)
+
+                        gr.HTML('<div class="card-title" style="margin-top:12px">Complaint Details</div>')
+                        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")
+
+                        gr.HTML(MAP_HTML)
+
+                        location_tb = gr.Textbox(
+                            label="Street / Landmark / GPS Coordinates",
+                            placeholder="GPS coordinates auto-fill here — or type street/landmark",
+                            lines=1
+                        )
+                        desc_tb     = gr.Textbox(label="Description (optional)", placeholder="Describe the issue...", lines=3)
+                        language_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Report & Voice Language")
+                        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)
+                        gr.HTML('<div class="card-title">Analysis Results</div>')
+                        annotated_out    = gr.Image(label="AI Detection Result", height=230)
+                        complaint_id_out = gr.Textbox(label="Complaint ID", interactive=False)
+
+                        gr.HTML('<div class="card-title" style="margin-top:12px">Official Government Report</div>')
+                        report_out = gr.Textbox(
+                            label="Full Complaint Report (Ready for Submission)",
+                            lines=20, interactive=False,
+                            placeholder="Report will appear here after submission..."
+                        )
+                        wa_out         = gr.Markdown()
+                        report_tts_out = gr.Audio(label="Report Voice (in selected language)", autoplay=False)
+
+                        gr.HTML('<div class="card-title" style="margin-top:16px">Legal Advice</div>')
+                        gr.HTML('<div class="warn-box">AI-generated legal guidance in your selected language, based on Pakistani civic law.</div>')
+                        legal_advice_out = gr.Textbox(
+                            label="Legal Rights & Action Steps (in selected language)",
+                            lines=10, interactive=False,
+                            placeholder="Legal advice will appear here in your selected language..."
+                        )
+                        advice_tts_out = gr.Audio(label="Legal Advice Voice (in selected language)", 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>')
+                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,
+                             report_tts_out, complaint_id_out, advice_tts_out]
+                )
+
+            # ── TAB 2: LAW REFERENCE + CHATBOT ───────────────
+            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_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)
+                gr.Button("Show Law Details", 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> &nbsp;|&nbsp;
+  CM Portal: <span class="hotline-pill">0800-02345</span>
+</div>""")
+
+                gr.HTML('<div class="card-title" style="margin-top:24px">Legal Guidance Chatbot</div>')
+                gr.HTML("""<div class="info-box">
+  Ask anything about water supply, pipe leakage, garbage, WASA, sewage, road issues
+  or your legal rights as a Pakistani citizen.
+</div>""")
+                chat_lang_dd = gr.Dropdown(choices=LANGUAGES, value="English", label="Response Language")
+
+                # KEY FIX: type="messages" for Gradio 6+
+                chatbot = gr.Chatbot(
+                    label="Rahbar Legal Assistant",
+                    height=600,
+                    value=[],
+                )
+                with gr.Row():
+                    chat_input    = gr.Textbox(
+                        label="Your Question",
+                        placeholder="e.g., WASA ne pipe repair nahi ki, mujhe kya karna chahiye?",
+                        lines=2, scale=4
+                    )
+                    chat_send_btn = gr.Button("Send", variant="primary", scale=1)
+
+                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]
+                )
+
+                gr.Examples(
+                    examples=[
+                        ["WASA did not fix the leakage for 3 days. What are my rights?"],
+                        ["میرے علاقے میں پانی آلودہ ہے۔ میں کہاں شکایت کروں؟"],
+                        ["Garbage has not been collected for a week. What law applies?"],
+                        ["How do I escalate if the authority ignores my complaint?"],
+                        ["پانی کا بل غلط آیا ہے، کہاں شکایت کروں؟"],
+                    ],
+                    inputs=chat_input,
+                    label="Try These Questions"
+                )
+
+            # ── 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">Record your complaint. Copy the transcription to the Report Issue tab.</div>')
+                gr.HTML('<div class="info-box">Allow microphone access when your browser asks. Works best in Chrome/Edge.<br>مائیکروفون کی اجازت دیں جب browser پوچھے۔</div>')
+
+                audio_in = gr.Audio(
+                    type="filepath",
+                    label="Record or Upload Audio",
+                    sources=["microphone", "upload"]
+                )
+                stt_btn = gr.Button("Transcribe Audio", variant="primary")
+                stt_out = gr.Textbox(label="Transcription (editable — copy to Report tab)", 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>')
+
+                gr.HTML('<div class="card-title" style="margin-top:20px">Text-to-Speech Test</div>')
                 with gr.Row():
-                    tts_text_in = gr.Textbox(label="Enter text", placeholder="Type something to hear...", scale=3)
+                    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="🔊 Output", autoplay=True)
+                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")
+
+            # ── 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()
+                    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)
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        
+        css=CSS,
+        share=True,
+        theme=gr.themes.Base(
+            primary_hue=gr.themes.colors.green,
+            secondary_hue=gr.themes.colors.yellow
+        ),
+    )