Update app.py

app.py

@@ -1,1234 +1,1234 @@
-import requests
-from bs4 import BeautifulSoup
-import os
-import re
-import json
-import tempfile
-from datetime import datetime
-from dotenv import load_dotenv
-from groq import Groq
-from openai import OpenAI
-import gradio as gr
-
-# -----------------------------------------------
-# LOAD API KEYS
-# -----------------------------------------------
-# load_dotenv()  # Remove on Hugging Face
-BRIGHTDATA_API_KEY = os.getenv("BRIGHTDATA_API_KEY")
-BRIGHTDATA_USER = os.getenv("BRIGHTDATA_USER", "")
-BRIGHTDATA_PASS = os.getenv("BRIGHTDATA_PASS", "")
-BRIGHTDATA_HOST = os.getenv("BRIGHTDATA_HOST", "brd.superproxy.io")
-BRIGHTDATA_PORT = os.getenv("BRIGHTDATA_PORT", "22225")
-GROQ_API_KEY = os.getenv("GROQ_API_KEY")
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-client = Groq(api_key=GROQ_API_KEY)
-openai_client = OpenAI(api_key=OPENAI_API_KEY) if OPENAI_API_KEY else None
-
-print("GROQ key exists:", bool(GROQ_API_KEY))
-print("OPENAI key exists:", bool(OPENAI_API_KEY))
-
-# -----------------------------------------------
-# PERSISTENT STORAGE — JSON Files
-# -----------------------------------------------
-HISTORY_FILE = "chat_history.json"
-PREFERENCES_FILE = "user_preferences.json"
-
-
-def load_chat_history():
-    """Load chat history from JSON file."""
-    try:
-        if os.path.exists(HISTORY_FILE):
-            with open(HISTORY_FILE, "r", encoding="utf-8") as f:
-                data = json.load(f)
-                return data if isinstance(data, list) else []
-    except Exception as e:
-        print(f"[Storage] Could not load history: {e}")
-    return []
-
-
-def save_chat_history(history):
-    """Save chat history to JSON file after every turn."""
-    try:
-        with open(HISTORY_FILE, "w", encoding="utf-8") as f:
-            json.dump(history, f, indent=2, ensure_ascii=False)
-    except Exception as e:
-        print(f"[Storage] Could not save history: {e}")
-
-
-def load_preferences():
-    """Load user preferences from JSON file."""
-    try:
-        if os.path.exists(PREFERENCES_FILE):
-            with open(PREFERENCES_FILE, "r", encoding="utf-8") as f:
-                return json.load(f)
-    except Exception as e:
-        print(f"[Storage] Could not load preferences: {e}")
-    return {
-        "tone": "friendly",
-        "language": "English",
-        "format": "concise",
-        "custom_rules": ""
-    }
-
-
-def save_preferences(prefs):
-    """Save user preferences to JSON file."""
-    try:
-        with open(PREFERENCES_FILE, "w", encoding="utf-8") as f:
-            json.dump(prefs, f, indent=2, ensure_ascii=False)
-        return "✅ Preferences saved!"
-    except Exception as e:
-        return f"❌ Could not save: {str(e)}"
-
-
-# Load at startup
-chat_history_store = load_chat_history()
-user_preferences = load_preferences()
-print(f"[Storage] Loaded {len(chat_history_store)} messages from history")
-print(f"[Storage] Preferences: {user_preferences}")
-
-
-# ================================================================
-# VERSION 1: GOODREADS SCRAPER
-# ================================================================
-def get_books():
-    if not BRIGHTDATA_API_KEY:
-        return [], "❌ BRIGHTDATA_API_KEY not found!"
-
-    headers = {
-        "Authorization": f"Bearer {BRIGHTDATA_API_KEY}",
-        "Content-Type": "application/json"
-    }
-    data = {
-        "zone": "web_unlocker1",
-        "url": "https://www.goodreads.com/list/show/1.Best_Books_Ever",
-        "format": "raw"
-    }
-
-    try:
-        response = requests.post(
-            "https://api.brightdata.com/request",
-            json=data,
-            headers=headers,
-            timeout=30
-        )
-        if response.status_code != 200:
-            return [], f"❌ Scraping failed! Status: {response.status_code}"
-
-        soup = BeautifulSoup(response.text, "html.parser")
-        books = soup.select("tr[itemtype='http://schema.org/Book']")
-        if not books:
-            return [], "⚠️ No books found."
-
-        results = []
-        for i, book in enumerate(books[:20], start=1):
-            try:
-                title = book.select_one("a.bookTitle span").text.strip()
-                author = book.select_one("a.authorName span").text.strip()
-                rating = book.select_one("span.minirating").text.strip()
-                results.append({
-                    "rank": i,
-                    "title": title,
-                    "author": author,
-                    "rating": rating
-                })
-            except Exception:
-                pass
-        return results, f"✅ Scraped {len(results)} books!"
-    except Exception as e:
-        return [], f"❌ Error: {str(e)}"
-
-
-def format_books_as_text(books):
-    if not books:
-        return "No book data available."
-    return "\n".join([
-        f"Rank #{b['rank']}: \"{b['title']}\" by {b['author']} — Rating: {b['rating']}"
-        for b in books
-    ])
-
-
-def show_books_table(books_data, scrape_status):
-    if not books_data:
-        return f"**Status:** {scrape_status}"
-    md = f"**{scrape_status}**\n\n| Rank | Title | Author | Rating |\n|------|-------|--------|--------|\n"
-    for b in books_data:
-        md += f"| #{b['rank']} | {b['title']} | {b['author']} | {b['rating']} |\n"
-    return md
-
-
-print("🔄 Scraping Goodreads...")
-books_data, scrape_status = get_books()
-print(scrape_status)
-
-
-# ================================================================
-# VERSION 2: YOUTUBE TRANSCRIPT
-# ================================================================
-def get_youtube_transcript(video_id: str):
-    """Fetch YouTube transcript — old aur new API dono handle karta hai."""
-    video_id = video_id.strip()
-
-    if "youtube.com/watch" in video_id:
-        video_id = video_id.split("v=")[-1].split("&")[0]
-    elif "youtu.be/" in video_id:
-        video_id = video_id.split("youtu.be/")[-1].split("?")[0]
-
-    if not video_id:
-        return None, "❌ Please enter a valid YouTube Video ID or URL."
-
-    try:
-        from youtube_transcript_api import YouTubeTranscriptApi
-
-        try:
-            ytt = YouTubeTranscriptApi()
-            fetched = ytt.fetch(video_id)
-            full_text = " ".join([s.text for s in fetched])
-            if full_text.strip():
-                return full_text, f"✅ Transcript fetched! ({len(full_text)} chars, ID: {video_id})"
-        except Exception:
-            pass
-
-        try:
-            fetched = YouTubeTranscriptApi.get_transcript(video_id)
-            full_text = " ".join([s["text"] for s in fetched])
-            if full_text.strip():
-                return full_text, f"✅ Transcript fetched! ({len(full_text)} chars, ID: {video_id})"
-        except Exception:
-            pass
-
-        return None, "⚠️ Transcript empty or not available. Try another video."
-
-    except Exception as e:
-        return None, f"❌ Error: {str(e)}"
-
-
-current_transcript = {"text": None, "status": "No transcript loaded."}
-
-
-def load_transcript(video_id):
-    global current_transcript
-    text, status = get_youtube_transcript(video_id)
-    current_transcript["text"] = text
-    current_transcript["status"] = status
-    if text:
-        preview = text[:600] + "..." if len(text) > 600 else text
-        return status, f"**📄 Preview:**\n\n_{preview}_"
-    return status, "No preview available."
-
-
-# ================================================================
-# VERSION 4: VOICE HELPERS
-# ================================================================
-def transcribe_audio(audio_path):
-    """Convert microphone audio to text using Groq Whisper."""
-    if not audio_path:
-        return "", "⚠️ No audio recorded."
-
-    if not GROQ_API_KEY:
-        return "", "❌ GROQ_API_KEY not set for transcription."
-
-    try:
-        with open(audio_path, "rb") as audio_file:
-            transcript = client.audio.transcriptions.create(
-                file=audio_file,
-                model="whisper-large-v3-turbo",
-                response_format="verbose_json"
-            )
-
-        text = getattr(transcript, "text", "") or ""
-        if not text.strip():
-            return "", "⚠️ Speech detected but transcript is empty."
-
-        return text.strip(), "✅ Voice transcribed successfully!"
-    except Exception as e:
-        return "", f"❌ Transcription error: {str(e)}"
-
-
-def text_to_speech(text):
-    """Convert assistant reply to speech using OpenAI TTS."""
-    if not text or not text.strip():
-        return None, "⚠️ Empty text for audio output."
-
-    if not OPENAI_API_KEY or not openai_client:
-        return None, "⚠️ OPENAI_API_KEY not set. Text reply works, audio skipped."
-
-    try:
-        tmp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
-        tmp_path = tmp_file.name
-        tmp_file.close()
-
-        speech_response = openai_client.audio.speech.create(
-            model="tts-1",
-            voice="alloy",
-            input=text[:1000]
-        )
-
-        with open(tmp_path, "wb") as f:
-            f.write(speech_response.content)
-
-        return tmp_path, "✅ Audio reply generated!"
-    except Exception as e:
-        print("TTS full error:", repr(e))
-        return None, f"❌ TTS error: {str(e)}"
-
-
-def should_generate_image(user_text, reply_text):
-    text = f"{user_text} {reply_text}".lower()
-    triggers = [
-        "draw", "image", "picture", "diagram", "visual", "visually",
-        "show me", "illustrate", "architecture", "flowchart", "chart",
-        "generate image", "generate an image", "show a", "show an",
-        "solar system", "transformer", "mind map", "scene"
-    ]
-    return any(t in text for t in triggers)
-
-
-def build_image_prompt(user_text, reply_text):
-    if not GROQ_API_KEY:
-        return user_text[:500]
-    try:
-        resp = client.chat.completions.create(
-            model="llama-3.1-8b-instant",
-            messages=[
-                {"role": "system",
-                 "content": "Create one short descriptive image prompt. Return only the prompt text."},
-                {"role": "user",
-                 "content": f"User request: {user_text}\nAssistant reply: {reply_text[:1000]}\nCreate a concise image generation prompt."}
-            ],
-            temperature=0.4,
-            max_tokens=120
-        )
-        return (resp.choices[0].message.content or user_text).strip()
-    except Exception as e:
-        print("Image prompt error:", repr(e))
-        return user_text[:500]
-
-
-def maybe_generate_image(user_text, reply_text):
-    if not should_generate_image(user_text, reply_text):
-        return None, "ℹ️ No image needed for this reply."
-    if not OPENAI_API_KEY:
-        return None, "⚠️ OPENAI_API_KEY missing for image generation."
-    try:
-        image_prompt = build_image_prompt(user_text, reply_text)
-        image_resp = openai_client.images.generate(
-            model="dall-e-3",
-            prompt=image_prompt,
-            size="1024x1024",
-            quality="standard",
-            n=1
-        )
-        image_url = image_resp.data[0].url
-        if not image_url:
-            return None, "⚠️ Image was not generated."
-        img_data = requests.get(image_url, timeout=60).content
-        tmp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
-        tmp_file.write(img_data)
-        tmp_file.close()
-        return tmp_file.name, "✅ Image generated!"
-    except Exception as e:
-        print("Image generation error:", repr(e))
-        return None, f"❌ Image generation error: {str(e)}"
-
-
-def process_voice_for_main_chat(audio_path, history):
-    """Voice input for main chatbot."""
-    transcript_text, voice_status = transcribe_audio(audio_path)
-    if not transcript_text:
-        return history, voice_status, None, "", None, ""
-
-    reply = ask_main_ai(transcript_text, history or [])
-    audio_reply, tts_status = text_to_speech(reply)
-
-    updated_history = list(history) if history else []
-    updated_history.append({"role": "user", "content": transcript_text})
-    updated_history.append({"role": "assistant", "content": reply})
-
-    image_path, image_status = maybe_generate_image(transcript_text, reply)
-    combined_status = f"{voice_status}\n{tts_status}"
-    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
-
-
-def process_voice_for_books(audio_path, history):
-    """Voice input for books chatbot."""
-    transcript_text, voice_status = transcribe_audio(audio_path)
-    if not transcript_text:
-        return history, voice_status, None, "", None, ""
-
-    reply = ask_books_ai(transcript_text, history or [])
-    audio_reply, tts_status = text_to_speech(reply)
-
-    updated_history = list(history) if history else []
-    updated_history.append({"role": "user", "content": transcript_text})
-    updated_history.append({"role": "assistant", "content": reply})
-
-    image_path, image_status = maybe_generate_image(transcript_text, reply)
-    combined_status = f"{voice_status}\n{tts_status}"
-    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
-
-
-def process_voice_for_youtube(audio_path, history):
-    """Voice input for YouTube chatbot."""
-    transcript_text, voice_status = transcribe_audio(audio_path)
-    if not transcript_text:
-        return history, voice_status, None, "", None, ""
-
-    reply = ask_youtube_ai(transcript_text, history or [])
-    audio_reply, tts_status = text_to_speech(reply)
-
-    updated_history = list(history) if history else []
-    updated_history.append({"role": "user", "content": transcript_text})
-    updated_history.append({"role": "assistant", "content": reply})
-
-    image_path, image_status = maybe_generate_image(transcript_text, reply)
-    combined_status = f"{voice_status}\n{tts_status}"
-    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
-
-
-# ================================================================
-# VERSION 3: PREFERENCES + PERSISTENT CHAT
-# ================================================================
-def build_system_prompt(base_prompt, prefs):
-    """Inject user preferences into system prompt dynamically."""
-    pref_text = f"""
-USER PREFERENCES (follow these always):
-- Tone: {prefs.get('tone', 'friendly')}
-- Language: {prefs.get('language', 'English')}
-- Response Format: {prefs.get('format', 'concise')}
-"""
-    custom = prefs.get("custom_rules", "").strip()
-    if custom:
-        pref_text += f"- Custom Rules: {custom}\n"
-    return base_prompt + pref_text
-
-
-def convert_history_for_display(history_store):
-    """Convert stored history to Gradio chatbot format (list of dicts)."""
-    return [{"role": item["role"], "content": item["content"]} for item in history_store]
-
-
-def ask_main_ai(message, history):
-    """
-    VERSION 3 Main Chatbot:
-    - Multi-turn (session memory via history)
-    - Persistent (saves to JSON after every turn)
-    - Preferences injected into system prompt
-    """
-    global chat_history_store, user_preferences
-
-    if not GROQ_API_KEY:
-        return "❌ GROQ_API_KEY not set."
-
-    base_prompt = """You are a smart, helpful AI assistant with memory of past conversations.
-You help users with general questions, book recommendations, research, and more.
-Always maintain context from previous messages in the conversation."""
-
-    system = build_system_prompt(base_prompt, user_preferences)
-    messages = [{"role": "system", "content": system}]
-
-    for item in chat_history_store:
-        messages.append({"role": item["role"], "content": item["content"]})
-
-    for item in history:
-        if isinstance(item, dict):
-            if item not in chat_history_store:
-                messages.append({"role": item["role"], "content": item["content"]})
-        else:
-            messages.append({"role": "user", "content": item[0]})
-            messages.append({"role": "assistant", "content": item[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    try:
-        response = client.chat.completions.create(
-            model="llama-3.1-8b-instant",
-            messages=messages,
-            temperature=0.6,
-            max_tokens=1024
-        )
-        reply = response.choices[0].message.content
-
-        chat_history_store.append({"role": "user", "content": message})
-        chat_history_store.append({"role": "assistant", "content": reply})
-        save_chat_history(chat_history_store)
-
-        return reply
-
-    except Exception as e:
-        return f"❌ AI Error: {str(e)}"
-
-
-def ask_books_ai(message, history):
-    """Goodreads Q&A — Version 1 (carried forward)."""
-    if not GROQ_API_KEY:
-        return "❌ GROQ_API_KEY not set."
-    if not books_data:
-        return f"⚠️ No book data. Status: {scrape_status}"
-
-    base = """You are a smart and friendly book assistant named BookBot 📚.
-Books data from Goodreads:
-{context}
-RULES: Only answer from this data. Be friendly and concise."""
-
-    system = build_system_prompt(base.format(context=format_books_as_text(books_data)), user_preferences)
-    messages = [{"role": "system", "content": system}]
-    for item in history:
-        if isinstance(item, dict):
-            messages.append({"role": item["role"], "content": item["content"]})
-        else:
-            messages.append({"role": "user", "content": item[0]})
-            messages.append({"role": "assistant", "content": item[1]})
-    messages.append({"role": "user", "content": message})
-
-    try:
-        resp = client.chat.completions.create(
-            model="llama-3.1-8b-instant",
-            messages=messages,
-            temperature=0.5,
-            max_tokens=1024
-        )
-        return resp.choices[0].message.content
-    except Exception as e:
-        return f"❌ AI Error: {str(e)}"
-
-
-def ask_youtube_ai(message, history):
-    """YouTube Q&A — Version 2 (carried forward)."""
-    if not GROQ_API_KEY:
-        return "❌ GROQ_API_KEY not set."
-    transcript = current_transcript.get("text")
-    if not transcript:
-        return "⚠️ No transcript loaded. Enter a YouTube Video ID and click 'Load Transcript' first."
-
-    base = "You are a helpful assistant answering ONLY from this transcript:\n{transcript}\nRULES: Only use transcript info. Be concise."
-    system = build_system_prompt(base.format(transcript=transcript[:6000]), user_preferences)
-    messages = [{"role": "system", "content": system}]
-    for item in history:
-        if isinstance(item, dict):
-            messages.append({"role": item["role"], "content": item["content"]})
-        else:
-            messages.append({"role": "user", "content": item[0]})
-            messages.append({"role": "assistant", "content": item[1]})
-    messages.append({"role": "user", "content": message})
-
-    try:
-        resp = client.chat.completions.create(
-            model="llama-3.1-8b-instant",
-            messages=messages,
-            temperature=0.4,
-            max_tokens=1024
-        )
-        return resp.choices[0].message.content
-    except Exception as e:
-        return f"❌ AI Error: {str(e)}"
-
-
-def update_preferences(tone, language, fmt, custom_rules):
-    """Save updated preferences and return status."""
-    global user_preferences
-    user_preferences = {
-        "tone": tone,
-        "language": language,
-        "format": fmt,
-        "custom_rules": custom_rules
-    }
-    status = save_preferences(user_preferences)
-    return status
-
-
-def clear_history():
-    """Clear all persistent chat history."""
-    global chat_history_store
-    chat_history_store = []
-    save_chat_history([])
-    return "🗑️ Chat history cleared!"
-
-
-# ================================================================
-# CUSTOM CSS — SAME UI + SMALL AUDIO SECTION SUPPORT
-# ================================================================
-CUSTOM_CSS = """
-/* ── Google Fonts ── */
-@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500&display=swap');
-:root {
-    --bg-primary:     #0a0e1a;
-    --bg-secondary:   #0f1629;
-    --bg-card:        #141d35;
-    --bg-card-hover:  #1a2540;
-    --accent-cyan:    #00d4ff;
-    --accent-emerald: #00ff9d;
-    --accent-amber:   #ffb800;
-    --accent-rose:    #ff4f7b;
-    --text-primary:   #e8edf8;
-    --text-secondary: #8899bb;
-    --text-muted:     #4a5a7a;
-    --border:         #1e2d50;
-    --border-bright:  #2a3f70;
-    --glow-cyan:      0 0 20px rgba(0,212,255,0.15);
-    --glow-emerald:   0 0 20px rgba(0,255,157,0.12);
-    --radius-sm:      8px;
-    --radius-md:      14px;
-    --radius-lg:      20px;
-    --font-main:      'Space Grotesk', sans-serif;
-    --font-mono:      'JetBrains Mono', monospace;
-}
-*, *::before, *::after { box-sizing: border-box; }
-body, .gradio-container {
-    background: var(--bg-primary) !important;
-    font-family: var(--font-main) !important;
-    color: var(--text-primary) !important;
-    min-height: 100vh;
-}
-.gradio-container {
-    background:
-        radial-gradient(ellipse 80% 50% at 20% 10%, rgba(0,212,255,0.04) 0%, transparent 60%),
-        radial-gradient(ellipse 60% 40% at 80% 90%, rgba(0,255,157,0.03) 0%, transparent 60%),
-        var(--bg-primary) !important;
-    max-width: 1200px !important;
-    margin: 0 auto !important;
-    padding: 0 16px !important;
-}
-.hero-header {
-    text-align: center;
-    padding: 40px 20px 28px;
-    position: relative;
-}
-.hero-header::before {
-    content: '';
-    position: absolute;
-    top: 0; left: 50%; transform: translateX(-50%);
-    width: 300px; height: 1px;
-    background: linear-gradient(90deg, transparent, var(--accent-cyan), transparent);
-}
-.hero-title {
-    font-size: 2.4rem;
-    font-weight: 700;
-    letter-spacing: -0.5px;
-    background: linear-gradient(135deg, var(--accent-cyan) 0%, var(--accent-emerald) 60%, var(--accent-amber) 100%);
-    -webkit-background-clip: text;
-    -webkit-text-fill-color: transparent;
-    background-clip: text;
-    margin: 0 0 10px;
-    line-height: 1.1;
-}
-.hero-subtitle {
-    color: var(--text-secondary);
-    font-size: 0.95rem;
-    font-weight: 400;
-    letter-spacing: 0.3px;
-    margin: 0;
-}
-.hero-subtitle span {
-    color: var(--accent-cyan);
-    font-weight: 500;
-}
-.hero-badges {
-    display: flex;
-    justify-content: center;
-    gap: 10px;
-    margin-top: 16px;
-    flex-wrap: wrap;
-}
-.badge {
-    background: var(--bg-card);
-    border: 1px solid var(--border-bright);
-    border-radius: 20px;
-    padding: 4px 14px;
-    font-size: 0.75rem;
-    font-family: var(--font-mono);
-    color: var(--text-secondary);
-    letter-spacing: 0.5px;
-}
-.tab-nav {
-    background: var(--bg-secondary) !important;
-    border: 1px solid var(--border) !important;
-    border-radius: var(--radius-lg) !important;
-    padding: 6px !important;
-    margin-bottom: 20px !important;
-    display: flex;
-    gap: 4px;
-}
-.tab-nav button {
-    background: transparent !important;
-    border: none !important;
-    color: var(--text-muted) !important;
-    font-family: var(--font-main) !important;
-    font-size: 0.875rem !important;
-    font-weight: 500 !important;
-    padding: 10px 20px !important;
-    border-radius: var(--radius-md) !important;
-    cursor: pointer !important;
-    transition: all 0.25s ease !important;
-    letter-spacing: 0.2px !important;
-    white-space: nowrap !important;
-}
-.tab-nav button:hover {
-    background: var(--bg-card) !important;
-    color: var(--text-primary) !important;
-}
-.tab-nav button.selected {
-    background: linear-gradient(135deg, rgba(0,212,255,0.15), rgba(0,255,157,0.08)) !important;
-    color: var(--accent-cyan) !important;
-    border: 1px solid rgba(0,212,255,0.25) !important;
-    box-shadow: var(--glow-cyan) !important;
-}
-.chatbot-wrap .chatbot,
-.chatbot-wrap > div {
-    background: var(--bg-secondary) !important;
-    border: 1px solid var(--border) !important;
-    border-radius: var(--radius-md) !important;
-}
-.message.user {
-    background: linear-gradient(135deg, rgba(0,212,255,0.12), rgba(0,212,255,0.06)) !important;
-    border: 1px solid rgba(0,212,255,0.2) !important;
-    border-radius: var(--radius-md) var(--radius-sm) var(--radius-md) var(--radius-md) !important;
-    color: var(--text-primary) !important;
-    font-family: var(--font-main) !important;
-}
-.message.bot {
-    background: var(--bg-card) !important;
-    border: 1px solid var(--border-bright) !important;
-    border-radius: var(--radius-sm) var(--radius-md) var(--radius-md) var(--radius-md) !important;
-    color: var(--text-primary) !important;
-    font-family: var(--font-main) !important;
-}
-input[type="text"],
-textarea,
-.gr-textbox,
-.gr-textbox textarea,
-.gr-textbox input {
-    background: var(--bg-secondary) !important;
-    border: 1px solid var(--border-bright) !important;
-    border-radius: var(--radius-sm) !important;
-    color: var(--text-primary) !important;
-    font-family: var(--font-main) !important;
-    font-size: 0.9rem !important;
-    padding: 12px 16px !important;
-    transition: border-color 0.2s, box-shadow 0.2s !important;
-    outline: none !important;
-}
-input[type="text"]:focus,
-textarea:focus,
-.gr-textbox textarea:focus,
-.gr-textbox input:focus {
-    border-color: var(--accent-cyan) !important;
-    box-shadow: 0 0 0 3px rgba(0,212,255,0.08) !important;
-}
-button.lg.primary, button[variant="primary"] {
-    background: linear-gradient(135deg, var(--accent-cyan), #0099cc) !important;
-    border: none !important;
-    border-radius: var(--radius-sm) !important;
-    color: #000 !important;
-    font-family: var(--font-main) !important;
-    font-weight: 600 !important;
-    font-size: 0.875rem !important;
-    letter-spacing: 0.3px !important;
-    padding: 11px 22px !important;
-    transition: all 0.2s ease !important;
-    cursor: pointer !important;
-}
-button.lg.secondary, button[variant="secondary"] {
-    background: var(--bg-card) !important;
-    border: 1px solid var(--border-bright) !important;
-    border-radius: var(--radius-sm) !important;
-    color: var(--text-primary) !important;
-    font-family: var(--font-main) !important;
-    font-weight: 500 !important;
-    font-size: 0.875rem !important;
-    padding: 11px 22px !important;
-}
-button.lg.stop, button[variant="stop"] {
-    background: rgba(255,79,123,0.1) !important;
-    border: 1px solid rgba(255,79,123,0.3) !important;
-    border-radius: var(--radius-sm) !important;
-    color: var(--accent-rose) !important;
-    font-family: var(--font-main) !important;
-    font-weight: 500 !important;
-    font-size: 0.875rem !important;
-    padding: 11px 22px !important;
-}
-.gr-markdown, .prose {
-    color: var(--text-primary) !important;
-    font-family: var(--font-main) !important;
-}
-.status-box textarea {
-    background: var(--bg-secondary) !important;
-    border: 1px solid var(--border) !important;
-    border-radius: var(--radius-sm) !important;
-    color: var(--text-secondary) !important;
-    font-family: var(--font-mono) !important;
-    font-size: 0.82rem !important;
-}
-.transcript-preview {
-    background: var(--bg-secondary);
-    border: 1px solid var(--border);
-    border-left: 3px solid var(--accent-amber);
-    border-radius: var(--radius-sm);
-    padding: 14px 18px;
-    font-size: 0.875rem;
-    line-height: 1.6;
-    color: var(--text-secondary);
-    max-height: 180px;
-    overflow-y: auto;
-}
-.voice-box {
-    background: rgba(0, 212, 255, 0.04);
-    border: 1px solid rgba(0, 212, 255, 0.18);
-    border-radius: 14px;
-    padding: 14px;
-    margin-top: 14px;
-}
-.footer-strip {
-    text-align: center;
-    padding: 18px 0 28px;
-    color: var(--text-muted);
-    font-size: 0.75rem;
-    font-family: var(--font-mono);
-    letter-spacing: 0.5px;
-    border-top: 1px solid var(--border);
-    margin-top: 24px;
-}
-"""
-
-# ================================================================
-# GRADIO UI — SAME LAYOUT + VOICE BLOCKS ADDED
-# ================================================================
-initial_display = convert_history_for_display(chat_history_store)
-prefs = load_preferences()
-
-with gr.Blocks(title="⚡ NeuralChat — AI Assistant") as demo:
-    gr.HTML("""
-    <div class="hero-header">
-        <p class="hero-title">⚡ NeuralChat</p>
-        <p class="hero-subtitle">
-            Powered by <span>Groq LLaMA</span> &nbsp;·&nbsp;
-            <span>Persistent Memory</span> &nbsp;·&nbsp;
-            <span>Goodreads + YouTube + Voice + Images</span>
-        </p>
-        <div class="hero-badges">
-            <span class="badge">llama-3.3-70b</span>
-            <span class="badge">llama-3.1-8b</span>
-            <span class="badge">whisper-large-v3-turbo</span>
-            <span class="badge">tts-1</span>
-            <span class="badge">dall-e-3</span>
-            <span class="badge">ver 5.0</span>
-        </div>
-    </div>
-    """)
-
-    with gr.Tabs(elem_classes=["tab-nav"]):
-
-        # ============================================================
-        # TAB 1: MAIN CHATBOT
-        # ============================================================
-        with gr.Tab("💬  Chat"):
-            gr.HTML("""
-            <div style="margin-bottom:18px;">
-                <div class="section-label">Main Assistant</div>
-                <div class="section-title">Conversational AI with Memory</div>
-                <div class="section-desc">
-                    Your assistant remembers past sessions and adapts to your preferences automatically.
-                </div>
-            </div>
-            """)
-
-            main_chatbot = gr.Chatbot(
-                value=initial_display,
-                height=460,
-                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>💬 Start a conversation — I remember everything.</div>",
-                elem_classes=["chatbot-wrap"],
-                show_label=False
-
-            )
-
-            with gr.Row():
-                main_msg = gr.Textbox(
-                    placeholder="Type a message…",
-                    scale=7,
-                    show_label=False,
-                    container=False,
-                )
-                main_send = gr.Button("Send ↑", variant="primary", scale=1)
-
-
-            def submit_main_text(message, history):
-                history = list(history) if history else []
-                if not message.strip():
-                    return history, ""
-                reply = ask_main_ai(message, history)
-                history.append({"role": "user", "content": message})
-                history.append({"role": "assistant", "content": reply})
-                return history, ""
-
-
-            main_send.click(
-                fn=submit_main_text,
-                inputs=[main_msg, main_chatbot],
-                outputs=[main_chatbot, main_msg]
-            )
-            main_msg.submit(
-                fn=submit_main_text,
-                inputs=[main_msg, main_chatbot],
-                outputs=[main_chatbot, main_msg]
-            )
-
-            with gr.Column(elem_classes=["voice-box"]):
-                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
-                with gr.Row():
-                    main_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
-                    main_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
-                with gr.Row():
-                    main_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
-                    main_voice_status = gr.Textbox(label="Voice Status", interactive=False, elem_classes=["status-box"])
-                main_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
-
-            main_voice_btn.click(
-                fn=process_voice_for_main_chat,
-                inputs=[main_audio_in, main_chatbot],
-                outputs=[main_chatbot, main_voice_status, main_audio_out, main_voice_text]
-            )
-
-            gr.HTML("<div style='height:12px'></div>")
-
-            with gr.Row():
-                clear_btn = gr.Button("🗑️  Clear History", variant="stop", scale=1)
-                clear_status = gr.Textbox(
-                    label="Status",
-                    interactive=False,
-                    scale=3,
-                    elem_classes=["status-box"],
-                )
-
-            clear_btn.click(fn=clear_history, outputs=clear_status)
-
-        # ============================================================
-        # TAB 2: GOODREADS
-        # ============================================================
-        with gr.Tab("📖  Books"):
-            gr.HTML("""
-            <div style="margin-bottom:18px;">
-                <div class="section-label">Goodreads Scraper</div>
-                <div class="section-title">BookBot — Best Books Q&A</div>
-                <div class="section-desc">
-                    Ask BookBot anything about the scraped Goodreads \"Best Books Ever\" list.
-                </div>
-            </div>
-            """)
-
-            books_chatbot = gr.Chatbot(
-                height=380,
-                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>📚 Ask me about the Goodreads Best Books list!</div>",
-                show_label=False
-
-            )
-
-            with gr.Row():
-                books_msg = gr.Textbox(
-                    placeholder="e.g. Who wrote the top book?",
-                    scale=7,
-                    show_label=False,
-                    container=False,
-                )
-                books_send = gr.Button("Ask ↑", variant="primary", scale=1)
-
-
-            def submit_books_text(message, history):
-                history = list(history) if history else []
-                if not message.strip():
-                    return history, ""
-                reply = ask_books_ai(message, history)
-                history.append({"role": "user", "content": message})
-                history.append({"role": "assistant", "content": reply})
-                return history, ""
-
-
-            books_send.click(
-                fn=submit_books_text,
-                inputs=[books_msg, books_chatbot],
-                outputs=[books_chatbot, books_msg]
-            )
-            books_msg.submit(
-                fn=submit_books_text,
-                inputs=[books_msg, books_chatbot],
-                outputs=[books_chatbot, books_msg]
-            )
-
-            with gr.Column(elem_classes=["voice-box"]):
-                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
-                with gr.Row():
-                    books_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
-                    books_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
-                with gr.Row():
-                    books_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
-                    books_voice_status = gr.Textbox(label="Voice Status", interactive=False,
-                                                    elem_classes=["status-box"])
-                books_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
-
-            books_voice_btn.click(
-                fn=process_voice_for_books,
-                inputs=[books_audio_in, books_chatbot],
-                outputs=[books_chatbot, books_voice_status, books_audio_out, books_voice_text]
-            )
-
-            gr.HTML("<hr>")
-            gr.HTML("""
-            <div style="margin-bottom:14px;">
-                <div class="section-label">Scraped Data</div>
-                <div class="section-title">Goodreads Top 20</div>
-            </div>
-            """)
-
-            books_display = gr.Markdown(value=show_books_table(books_data, scrape_status))
-            refresh_btn = gr.Button("🔄  Re-Scrape Goodreads", variant="secondary")
-
-
-            def refresh_data():
-                global books_data, scrape_status
-                books_data, scrape_status = get_books()
-                return show_books_table(books_data, scrape_status)
-
-
-            refresh_btn.click(fn=refresh_data, outputs=books_display)
-
-        # ============================================================
-        # TAB 3: YOUTUBE
-        # ============================================================
-        with gr.Tab("🎬  YouTube"):
-            gr.HTML("""
-            <div style="margin-bottom:18px;">
-                <div class="section-label">YouTube Transcript</div>
-                <div class="section-title">Video Q&A Assistant</div>
-                <div class="section-desc">
-                    Load any YouTube video's transcript, then ask questions about it.
-                </div>
-            </div>
-            """)
-
-            gr.HTML("""
-            <div style="background:rgba(255,184,0,0.06);border:1px solid rgba(255,184,0,0.2);
-                        border-left:3px solid #ffb800;border-radius:10px;
-                        padding:12px 18px;margin-bottom:16px;
-                        font-size:0.85rem;color:#c89a00;font-family:Space Grotesk,sans-serif;">
-                <strong>Step 1</strong> — Paste a YouTube Video ID or full URL and click <em>Load Transcript</em>
-            </div>
-            """)
-
-            with gr.Row():
-                video_id_input = gr.Textbox(
-                    placeholder="e.g.  dQw4w9WgXcQ  or  https://youtu.be/…",
-                    label="YouTube Video ID or URL",
-                    scale=4,
-                )
-                load_btn = gr.Button("📥  Load Transcript", variant="primary", scale=1)
-
-            with gr.Row():
-                transcript_status = gr.Textbox(
-                    label="Status",
-                    interactive=False,
-                    elem_classes=["status-box"],
-                )
-
-            transcript_preview = gr.Markdown(
-                value="*Transcript preview will appear here…*",
-                elem_classes=["transcript-preview"],
-            )
-            load_btn.click(
-                fn=load_transcript,
-                inputs=[video_id_input],
-                outputs=[transcript_status, transcript_preview],
-            )
-
-            gr.HTML("""
-            <div style="background:rgba(0,212,255,0.05);border:1px solid rgba(0,212,255,0.15);
-                        border-left:3px solid #00d4ff;border-radius:10px;
-                        padding:12px 18px;margin:16px 0;
-                        font-size:0.85rem;color:#0099bb;font-family:Space Grotesk,sans-serif;">
-                <strong>Step 2</strong> — Ask anything about the loaded video below
-            </div>
-            """)
-
-            youtube_chatbot = gr.Chatbot(
-                height=360,
-                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>📥 Load a transcript above, then ask anything!</div>",
-                show_label=False
-
-            )
-
-            with gr.Row():
-                youtube_msg = gr.Textbox(
-                    placeholder="e.g. What is the main topic?",
-                    scale=7,
-                    show_label=False,
-                    container=False,
-                )
-                youtube_send = gr.Button("Ask ↑", variant="primary", scale=1)
-
-
-            def submit_youtube_text(message, history):
-                history = list(history) if history else []
-                if not message.strip():
-                    return history, ""
-                reply = ask_youtube_ai(message, history)
-                history.append({"role": "user", "content": message})
-                history.append({"role": "assistant", "content": reply})
-                return history, ""
-
-
-            youtube_send.click(
-                fn=submit_youtube_text,
-                inputs=[youtube_msg, youtube_chatbot],
-                outputs=[youtube_chatbot, youtube_msg]
-            )
-            youtube_msg.submit(
-                fn=submit_youtube_text,
-                inputs=[youtube_msg, youtube_chatbot],
-                outputs=[youtube_chatbot, youtube_msg]
-            )
-
-            with gr.Column(elem_classes=["voice-box"]):
-                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
-                with gr.Row():
-                    youtube_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
-                    youtube_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
-                with gr.Row():
-                    youtube_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
-                    youtube_voice_status = gr.Textbox(label="Voice Status", interactive=False,
-                                                      elem_classes=["status-box"])
-                youtube_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
-
-            youtube_voice_btn.click(
-                fn=process_voice_for_youtube,
-                inputs=[youtube_audio_in, youtube_chatbot],
-                outputs=[youtube_chatbot, youtube_voice_status, youtube_audio_out, youtube_voice_text]
-            )
-
-        # ============================================================
-        # TAB 4: PREFERENCES
-        # ============================================================
-        with gr.Tab("⚙️  Preferences"):
-            gr.HTML("""
-            <div style="margin-bottom:20px;">
-                <div class="section-label">Personalization</div>
-                <div class="section-title">AI Behavior Settings</div>
-                <div class="section-desc">
-                    These preferences are saved permanently and injected into every AI response across all tabs.
-                </div>
-            </div>
-            """)
-
-            with gr.Row():
-                with gr.Column():
-                    tone_input = gr.Dropdown(
-                        choices=["friendly", "formal", "casual", "professional", "humorous"],
-                        value=prefs.get("tone", "friendly"),
-                        label="🎭  Tone",
-                        info="How the AI speaks to you",
-                    )
-                    lang_input = gr.Dropdown(
-                        choices=["English", "Urdu", "Roman Urdu", "Arabic", "French", "Spanish"],
-                        value=prefs.get("language", "English"),
-                        label="🌐  Response Language",
-                        info="Language for all AI responses",
-                    )
-
-                with gr.Column():
-                    fmt_input = gr.Dropdown(
-                        choices=["concise", "detailed", "bullet points", "numbered list", "paragraph"],
-                        value=prefs.get("format", "concise"),
-                        label="📝  Response Format",
-                        info="How responses should be structured",
-                    )
-                    custom_input = gr.Textbox(
-                        value=prefs.get("custom_rules", ""),
-                        label="✏️  Custom Rules",
-                        placeholder='e.g. "Always cite sources" or "Use emojis sparingly"',
-                        lines=3,
-                        info="Extra instructions for the AI to always follow",
-                    )
-
-            with gr.Row():
-                save_btn = gr.Button("💾  Save Preferences", variant="primary", scale=1)
-                pref_status = gr.Textbox(
-                    label="Status",
-                    interactive=False,
-                    scale=2,
-                    elem_classes=["status-box"],
-                )
-
-            save_btn.click(
-                fn=update_preferences,
-                inputs=[tone_input, lang_input, fmt_input, custom_input],
-                outputs=pref_status,
-            )
-
-
-            def show_current_prefs():
-                p = load_preferences()
-                return f"""```
-Tone         →  {p.get('tone')}
-Language     →  {p.get('language')}
-Format       →  {p.get('format')}
-Custom Rules →  {p.get('custom_rules') or 'None'}
-```"""
-
-
-            pref_preview = gr.Markdown(value=show_current_prefs())
-            save_btn.click(
-                fn=lambda t, l, f, c: show_current_prefs(),
-                inputs=[tone_input, lang_input, fmt_input, custom_input],
-                outputs=pref_preview,
-            )
-
-        # ============================================================
-        # TAB 5: ABOUT
-        # ============================================================
-        with gr.Tab("ℹ️  About"):
-            gr.HTML(f"""
-            <div style="max-width:680px;margin:0 auto;padding:10px 0 24px;">
-                <div style="margin-bottom:24px;">
-                    <div class="section-label">Project Info</div>
-                    <div class="section-title">NeuralChat — Version 5</div>
-                    <div class="section-desc">
-                        A multi-tab AI assistant with web scraping, YouTube transcript Q&A,
-                        persistent memory, user preference personalization, voice input, audio output, and on-demand image generation.
-                    </div>
-                </div>
-                <div style="background:var(--bg-card,#141d35);border:1px solid #1e2d50;
-                            border-radius:14px;overflow:hidden;margin-bottom:20px;">
-                    <table style="width:100%;border-collapse:collapse;">
-                        <thead>
-                            <tr style="background:rgba(0,212,255,0.07);">
-                                <th style="padding:11px 16px;text-align:left;font-size:0.72rem;letter-spacing:1px;text-transform:uppercase;color:#00d4ff;border-bottom:1px solid #1e2d50;">Layer</th>
-                                <th style="padding:11px 16px;text-align:left;font-size:0.72rem;letter-spacing:1px;text-transform:uppercase;color:#00d4ff;border-bottom:1px solid #1e2d50;">Detail</th>
-                            </tr>
-                        </thead>
-                        <tbody style="color:#e8edf8;font-size:0.875rem;">
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🌐 Scraping</td><td style="padding:10px 16px;">Bright Data Web Unlocker + BeautifulSoup</td></tr>
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🎬 YouTube</td><td style="padding:10px 16px;">youtube-transcript-api</td></tr>
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🎤 STT</td><td style="padding:10px 16px;">Groq Whisper Large v3 Turbo</td></tr>
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🔊 TTS</td><td style="padding:10px 16px;">OpenAI tts-1 (alloy)</td></tr>
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🤖 AI (Main)</td><td style="padding:10px 16px;">Groq — llama-3.3-70b-versatile</td></tr>
-                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">💾 Memory</td><td style="padding:10px 16px;">JSON persistent storage</td></tr>
-                            <tr><td style="padding:10px 16px;color:#8899bb;">⚙️ Prefs</td><td style="padding:10px 16px;">JSON persistent storage</td></tr>
-                        </tbody>
-                    </table>
-                </div>
-                <div style="text-align:center;padding-top:10px;font-size:0.78rem;color:#4a5a7a;font-family:JetBrains Mono,monospace;letter-spacing:0.5px;border-top:1px solid #1e2d50;">
-                    Assignment 01 — Ver 5 &nbsp;|&nbsp; Dept. of Data Science, University of Punjab<br>
-                    Instructor: Dr. Muhammad Arif Butt
-                </div>
-            </div>
-            """)
-
-    gr.HTML("""
-    <div class="footer-strip">
-        NeuralChat v5 &nbsp;·&nbsp; Groq + OpenAI + Gradio &nbsp;·&nbsp; Built for DSAI @ UOP
-    </div>
-    """)
-
-demo.launch(
-    share=False,
-    inbrowser=True,
-    css=CUSTOM_CSS,
-)
+import requests
+from bs4 import BeautifulSoup
+import os
+import re
+import json
+import tempfile
+from datetime import datetime
+from dotenv import load_dotenv
+from groq import Groq
+from openai import OpenAI
+import gradio as gr
+
+# -----------------------------------------------
+# LOAD API KEYS
+# -----------------------------------------------
+# load_dotenv()  # Remove on Hugging Face
+BRIGHTDATA_API_KEY = os.getenv("BRIGHTDATA_API_KEY")
+BRIGHTDATA_USER = os.getenv("BRIGHTDATA_USER", "")
+BRIGHTDATA_PASS = os.getenv("BRIGHTDATA_PASS", "")
+BRIGHTDATA_HOST = os.getenv("BRIGHTDATA_HOST", "brd.superproxy.io")
+BRIGHTDATA_PORT = os.getenv("BRIGHTDATA_PORT", "22225")
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+client = Groq(api_key=GROQ_API_KEY)
+openai_client = OpenAI(api_key=OPENAI_API_KEY) if OPENAI_API_KEY else None
+
+print("GROQ key exists:", bool(GROQ_API_KEY))
+print("OPENAI key exists:", bool(OPENAI_API_KEY))
+
+# -----------------------------------------------
+# PERSISTENT STORAGE — JSON Files
+# -----------------------------------------------
+HISTORY_FILE = "chat_history.json"
+PREFERENCES_FILE = "user_preferences.json"
+
+
+def load_chat_history():
+    """Load chat history from JSON file."""
+    try:
+        if os.path.exists(HISTORY_FILE):
+            with open(HISTORY_FILE, "r", encoding="utf-8") as f:
+                data = json.load(f)
+                return data if isinstance(data, list) else []
+    except Exception as e:
+        print(f"[Storage] Could not load history: {e}")
+    return []
+
+
+def save_chat_history(history):
+    """Save chat history to JSON file after every turn."""
+    try:
+        with open(HISTORY_FILE, "w", encoding="utf-8") as f:
+            json.dump(history, f, indent=2, ensure_ascii=False)
+    except Exception as e:
+        print(f"[Storage] Could not save history: {e}")
+
+
+def load_preferences():
+    """Load user preferences from JSON file."""
+    try:
+        if os.path.exists(PREFERENCES_FILE):
+            with open(PREFERENCES_FILE, "r", encoding="utf-8") as f:
+                return json.load(f)
+    except Exception as e:
+        print(f"[Storage] Could not load preferences: {e}")
+    return {
+        "tone": "friendly",
+        "language": "English",
+        "format": "concise",
+        "custom_rules": ""
+    }
+
+
+def save_preferences(prefs):
+    """Save user preferences to JSON file."""
+    try:
+        with open(PREFERENCES_FILE, "w", encoding="utf-8") as f:
+            json.dump(prefs, f, indent=2, ensure_ascii=False)
+        return "✅ Preferences saved!"
+    except Exception as e:
+        return f"❌ Could not save: {str(e)}"
+
+
+# Load at startup
+chat_history_store = load_chat_history()
+user_preferences = load_preferences()
+print(f"[Storage] Loaded {len(chat_history_store)} messages from history")
+print(f"[Storage] Preferences: {user_preferences}")
+
+
+# ================================================================
+# VERSION 1: GOODREADS SCRAPER
+# ================================================================
+def get_books():
+    if not BRIGHTDATA_API_KEY:
+        return [], "❌ BRIGHTDATA_API_KEY not found!"
+
+    headers = {
+        "Authorization": f"Bearer {BRIGHTDATA_API_KEY}",
+        "Content-Type": "application/json"
+    }
+    data = {
+        "zone": "web_unlocker2",
+        "url": "https://www.goodreads.com/list/show/1.Best_Books_Ever",
+        "format": "raw"
+    }
+
+    try:
+        response = requests.post(
+            "https://api.brightdata.com/request",
+            json=data,
+            headers=headers,
+            timeout=30
+        )
+        if response.status_code != 200:
+            return [], f"❌ Scraping failed! Status: {response.status_code}"
+
+        soup = BeautifulSoup(response.text, "html.parser")
+        books = soup.select("tr[itemtype='http://schema.org/Book']")
+        if not books:
+            return [], "⚠️ No books found."
+
+        results = []
+        for i, book in enumerate(books[:20], start=1):
+            try:
+                title = book.select_one("a.bookTitle span").text.strip()
+                author = book.select_one("a.authorName span").text.strip()
+                rating = book.select_one("span.minirating").text.strip()
+                results.append({
+                    "rank": i,
+                    "title": title,
+                    "author": author,
+                    "rating": rating
+                })
+            except Exception:
+                pass
+        return results, f"✅ Scraped {len(results)} books!"
+    except Exception as e:
+        return [], f"❌ Error: {str(e)}"
+
+
+def format_books_as_text(books):
+    if not books:
+        return "No book data available."
+    return "\n".join([
+        f"Rank #{b['rank']}: \"{b['title']}\" by {b['author']} — Rating: {b['rating']}"
+        for b in books
+    ])
+
+
+def show_books_table(books_data, scrape_status):
+    if not books_data:
+        return f"**Status:** {scrape_status}"
+    md = f"**{scrape_status}**\n\n| Rank | Title | Author | Rating |\n|------|-------|--------|--------|\n"
+    for b in books_data:
+        md += f"| #{b['rank']} | {b['title']} | {b['author']} | {b['rating']} |\n"
+    return md
+
+
+print("🔄 Scraping Goodreads...")
+books_data, scrape_status = get_books()
+print(scrape_status)
+
+
+# ================================================================
+# VERSION 2: YOUTUBE TRANSCRIPT
+# ================================================================
+def get_youtube_transcript(video_id: str):
+    """Fetch YouTube transcript — old aur new API dono handle karta hai."""
+    video_id = video_id.strip()
+
+    if "youtube.com/watch" in video_id:
+        video_id = video_id.split("v=")[-1].split("&")[0]
+    elif "youtu.be/" in video_id:
+        video_id = video_id.split("youtu.be/")[-1].split("?")[0]
+
+    if not video_id:
+        return None, "❌ Please enter a valid YouTube Video ID or URL."
+
+    try:
+        from youtube_transcript_api import YouTubeTranscriptApi
+
+        try:
+            ytt = YouTubeTranscriptApi()
+            fetched = ytt.fetch(video_id)
+            full_text = " ".join([s.text for s in fetched])
+            if full_text.strip():
+                return full_text, f"✅ Transcript fetched! ({len(full_text)} chars, ID: {video_id})"
+        except Exception:
+            pass
+
+        try:
+            fetched = YouTubeTranscriptApi.get_transcript(video_id)
+            full_text = " ".join([s["text"] for s in fetched])
+            if full_text.strip():
+                return full_text, f"✅ Transcript fetched! ({len(full_text)} chars, ID: {video_id})"
+        except Exception:
+            pass
+
+        return None, "⚠️ Transcript empty or not available. Try another video."
+
+    except Exception as e:
+        return None, f"❌ Error: {str(e)}"
+
+
+current_transcript = {"text": None, "status": "No transcript loaded."}
+
+
+def load_transcript(video_id):
+    global current_transcript
+    text, status = get_youtube_transcript(video_id)
+    current_transcript["text"] = text
+    current_transcript["status"] = status
+    if text:
+        preview = text[:600] + "..." if len(text) > 600 else text
+        return status, f"**📄 Preview:**\n\n_{preview}_"
+    return status, "No preview available."
+
+
+# ================================================================
+# VERSION 4: VOICE HELPERS
+# ================================================================
+def transcribe_audio(audio_path):
+    """Convert microphone audio to text using Groq Whisper."""
+    if not audio_path:
+        return "", "⚠️ No audio recorded."
+
+    if not GROQ_API_KEY:
+        return "", "❌ GROQ_API_KEY not set for transcription."
+
+    try:
+        with open(audio_path, "rb") as audio_file:
+            transcript = client.audio.transcriptions.create(
+                file=audio_file,
+                model="whisper-large-v3-turbo",
+                response_format="verbose_json"
+            )
+
+        text = getattr(transcript, "text", "") or ""
+        if not text.strip():
+            return "", "⚠️ Speech detected but transcript is empty."
+
+        return text.strip(), "✅ Voice transcribed successfully!"
+    except Exception as e:
+        return "", f"❌ Transcription error: {str(e)}"
+
+
+def text_to_speech(text):
+    """Convert assistant reply to speech using OpenAI TTS."""
+    if not text or not text.strip():
+        return None, "⚠️ Empty text for audio output."
+
+    if not OPENAI_API_KEY or not openai_client:
+        return None, "⚠️ OPENAI_API_KEY not set. Text reply works, audio skipped."
+
+    try:
+        tmp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
+        tmp_path = tmp_file.name
+        tmp_file.close()
+
+        speech_response = openai_client.audio.speech.create(
+            model="tts-1",
+            voice="alloy",
+            input=text[:1000]
+        )
+
+        with open(tmp_path, "wb") as f:
+            f.write(speech_response.content)
+
+        return tmp_path, "✅ Audio reply generated!"
+    except Exception as e:
+        print("TTS full error:", repr(e))
+        return None, f"❌ TTS error: {str(e)}"
+
+
+def should_generate_image(user_text, reply_text):
+    text = f"{user_text} {reply_text}".lower()
+    triggers = [
+        "draw", "image", "picture", "diagram", "visual", "visually",
+        "show me", "illustrate", "architecture", "flowchart", "chart",
+        "generate image", "generate an image", "show a", "show an",
+        "solar system", "transformer", "mind map", "scene"
+    ]
+    return any(t in text for t in triggers)
+
+
+def build_image_prompt(user_text, reply_text):
+    if not GROQ_API_KEY:
+        return user_text[:500]
+    try:
+        resp = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=[
+                {"role": "system",
+                 "content": "Create one short descriptive image prompt. Return only the prompt text."},
+                {"role": "user",
+                 "content": f"User request: {user_text}\nAssistant reply: {reply_text[:1000]}\nCreate a concise image generation prompt."}
+            ],
+            temperature=0.4,
+            max_tokens=120
+        )
+        return (resp.choices[0].message.content or user_text).strip()
+    except Exception as e:
+        print("Image prompt error:", repr(e))
+        return user_text[:500]
+
+
+def maybe_generate_image(user_text, reply_text):
+    if not should_generate_image(user_text, reply_text):
+        return None, "ℹ️ No image needed for this reply."
+    if not OPENAI_API_KEY:
+        return None, "⚠️ OPENAI_API_KEY missing for image generation."
+    try:
+        image_prompt = build_image_prompt(user_text, reply_text)
+        image_resp = openai_client.images.generate(
+            model="dall-e-3",
+            prompt=image_prompt,
+            size="1024x1024",
+            quality="standard",
+            n=1
+        )
+        image_url = image_resp.data[0].url
+        if not image_url:
+            return None, "⚠️ Image was not generated."
+        img_data = requests.get(image_url, timeout=60).content
+        tmp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+        tmp_file.write(img_data)
+        tmp_file.close()
+        return tmp_file.name, "✅ Image generated!"
+    except Exception as e:
+        print("Image generation error:", repr(e))
+        return None, f"❌ Image generation error: {str(e)}"
+
+
+def process_voice_for_main_chat(audio_path, history):
+    """Voice input for main chatbot."""
+    transcript_text, voice_status = transcribe_audio(audio_path)
+    if not transcript_text:
+        return history, voice_status, None, "", None, ""
+
+    reply = ask_main_ai(transcript_text, history or [])
+    audio_reply, tts_status = text_to_speech(reply)
+
+    updated_history = list(history) if history else []
+    updated_history.append({"role": "user", "content": transcript_text})
+    updated_history.append({"role": "assistant", "content": reply})
+
+    image_path, image_status = maybe_generate_image(transcript_text, reply)
+    combined_status = f"{voice_status}\n{tts_status}"
+    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
+
+
+def process_voice_for_books(audio_path, history):
+    """Voice input for books chatbot."""
+    transcript_text, voice_status = transcribe_audio(audio_path)
+    if not transcript_text:
+        return history, voice_status, None, "", None, ""
+
+    reply = ask_books_ai(transcript_text, history or [])
+    audio_reply, tts_status = text_to_speech(reply)
+
+    updated_history = list(history) if history else []
+    updated_history.append({"role": "user", "content": transcript_text})
+    updated_history.append({"role": "assistant", "content": reply})
+
+    image_path, image_status = maybe_generate_image(transcript_text, reply)
+    combined_status = f"{voice_status}\n{tts_status}"
+    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
+
+
+def process_voice_for_youtube(audio_path, history):
+    """Voice input for YouTube chatbot."""
+    transcript_text, voice_status = transcribe_audio(audio_path)
+    if not transcript_text:
+        return history, voice_status, None, "", None, ""
+
+    reply = ask_youtube_ai(transcript_text, history or [])
+    audio_reply, tts_status = text_to_speech(reply)
+
+    updated_history = list(history) if history else []
+    updated_history.append({"role": "user", "content": transcript_text})
+    updated_history.append({"role": "assistant", "content": reply})
+
+    image_path, image_status = maybe_generate_image(transcript_text, reply)
+    combined_status = f"{voice_status}\n{tts_status}"
+    return updated_history, combined_status, audio_reply, transcript_text, image_path, image_status
+
+
+# ================================================================
+# VERSION 3: PREFERENCES + PERSISTENT CHAT
+# ================================================================
+def build_system_prompt(base_prompt, prefs):
+    """Inject user preferences into system prompt dynamically."""
+    pref_text = f"""
+USER PREFERENCES (follow these always):
+- Tone: {prefs.get('tone', 'friendly')}
+- Language: {prefs.get('language', 'English')}
+- Response Format: {prefs.get('format', 'concise')}
+"""
+    custom = prefs.get("custom_rules", "").strip()
+    if custom:
+        pref_text += f"- Custom Rules: {custom}\n"
+    return base_prompt + pref_text
+
+
+def convert_history_for_display(history_store):
+    """Convert stored history to Gradio chatbot format (list of dicts)."""
+    return [{"role": item["role"], "content": item["content"]} for item in history_store]
+
+
+def ask_main_ai(message, history):
+    """
+    VERSION 3 Main Chatbot:
+    - Multi-turn (session memory via history)
+    - Persistent (saves to JSON after every turn)
+    - Preferences injected into system prompt
+    """
+    global chat_history_store, user_preferences
+
+    if not GROQ_API_KEY:
+        return "❌ GROQ_API_KEY not set."
+
+    base_prompt = """You are a smart, helpful AI assistant with memory of past conversations.
+You help users with general questions, book recommendations, research, and more.
+Always maintain context from previous messages in the conversation."""
+
+    system = build_system_prompt(base_prompt, user_preferences)
+    messages = [{"role": "system", "content": system}]
+
+    for item in chat_history_store:
+        messages.append({"role": item["role"], "content": item["content"]})
+
+    for item in history:
+        if isinstance(item, dict):
+            if item not in chat_history_store:
+                messages.append({"role": item["role"], "content": item["content"]})
+        else:
+            messages.append({"role": "user", "content": item[0]})
+            messages.append({"role": "assistant", "content": item[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    try:
+        response = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=messages,
+            temperature=0.6,
+            max_tokens=1024
+        )
+        reply = response.choices[0].message.content
+
+        chat_history_store.append({"role": "user", "content": message})
+        chat_history_store.append({"role": "assistant", "content": reply})
+        save_chat_history(chat_history_store)
+
+        return reply
+
+    except Exception as e:
+        return f"❌ AI Error: {str(e)}"
+
+
+def ask_books_ai(message, history):
+    """Goodreads Q&A — Version 1 (carried forward)."""
+    if not GROQ_API_KEY:
+        return "❌ GROQ_API_KEY not set."
+    if not books_data:
+        return f"⚠️ No book data. Status: {scrape_status}"
+
+    base = """You are a smart and friendly book assistant named BookBot 📚.
+Books data from Goodreads:
+{context}
+RULES: Only answer from this data. Be friendly and concise."""
+
+    system = build_system_prompt(base.format(context=format_books_as_text(books_data)), user_preferences)
+    messages = [{"role": "system", "content": system}]
+    for item in history:
+        if isinstance(item, dict):
+            messages.append({"role": item["role"], "content": item["content"]})
+        else:
+            messages.append({"role": "user", "content": item[0]})
+            messages.append({"role": "assistant", "content": item[1]})
+    messages.append({"role": "user", "content": message})
+
+    try:
+        resp = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=messages,
+            temperature=0.5,
+            max_tokens=1024
+        )
+        return resp.choices[0].message.content
+    except Exception as e:
+        return f"❌ AI Error: {str(e)}"
+
+
+def ask_youtube_ai(message, history):
+    """YouTube Q&A — Version 2 (carried forward)."""
+    if not GROQ_API_KEY:
+        return "❌ GROQ_API_KEY not set."
+    transcript = current_transcript.get("text")
+    if not transcript:
+        return "⚠️ No transcript loaded. Enter a YouTube Video ID and click 'Load Transcript' first."
+
+    base = "You are a helpful assistant answering ONLY from this transcript:\n{transcript}\nRULES: Only use transcript info. Be concise."
+    system = build_system_prompt(base.format(transcript=transcript[:6000]), user_preferences)
+    messages = [{"role": "system", "content": system}]
+    for item in history:
+        if isinstance(item, dict):
+            messages.append({"role": item["role"], "content": item["content"]})
+        else:
+            messages.append({"role": "user", "content": item[0]})
+            messages.append({"role": "assistant", "content": item[1]})
+    messages.append({"role": "user", "content": message})
+
+    try:
+        resp = client.chat.completions.create(
+            model="llama-3.1-8b-instant",
+            messages=messages,
+            temperature=0.4,
+            max_tokens=1024
+        )
+        return resp.choices[0].message.content
+    except Exception as e:
+        return f"❌ AI Error: {str(e)}"
+
+
+def update_preferences(tone, language, fmt, custom_rules):
+    """Save updated preferences and return status."""
+    global user_preferences
+    user_preferences = {
+        "tone": tone,
+        "language": language,
+        "format": fmt,
+        "custom_rules": custom_rules
+    }
+    status = save_preferences(user_preferences)
+    return status
+
+
+def clear_history():
+    """Clear all persistent chat history."""
+    global chat_history_store
+    chat_history_store = []
+    save_chat_history([])
+    return "🗑️ Chat history cleared!"
+
+
+# ================================================================
+# CUSTOM CSS — SAME UI + SMALL AUDIO SECTION SUPPORT
+# ================================================================
+CUSTOM_CSS = """
+/* ── Google Fonts ── */
+@import url('https://fonts.googleapis.com/css2?family=Space+Grotesk:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500&display=swap');
+:root {
+    --bg-primary:     #0a0e1a;
+    --bg-secondary:   #0f1629;
+    --bg-card:        #141d35;
+    --bg-card-hover:  #1a2540;
+    --accent-cyan:    #00d4ff;
+    --accent-emerald: #00ff9d;
+    --accent-amber:   #ffb800;
+    --accent-rose:    #ff4f7b;
+    --text-primary:   #e8edf8;
+    --text-secondary: #8899bb;
+    --text-muted:     #4a5a7a;
+    --border:         #1e2d50;
+    --border-bright:  #2a3f70;
+    --glow-cyan:      0 0 20px rgba(0,212,255,0.15);
+    --glow-emerald:   0 0 20px rgba(0,255,157,0.12);
+    --radius-sm:      8px;
+    --radius-md:      14px;
+    --radius-lg:      20px;
+    --font-main:      'Space Grotesk', sans-serif;
+    --font-mono:      'JetBrains Mono', monospace;
+}
+*, *::before, *::after { box-sizing: border-box; }
+body, .gradio-container {
+    background: var(--bg-primary) !important;
+    font-family: var(--font-main) !important;
+    color: var(--text-primary) !important;
+    min-height: 100vh;
+}
+.gradio-container {
+    background:
+        radial-gradient(ellipse 80% 50% at 20% 10%, rgba(0,212,255,0.04) 0%, transparent 60%),
+        radial-gradient(ellipse 60% 40% at 80% 90%, rgba(0,255,157,0.03) 0%, transparent 60%),
+        var(--bg-primary) !important;
+    max-width: 1200px !important;
+    margin: 0 auto !important;
+    padding: 0 16px !important;
+}
+.hero-header {
+    text-align: center;
+    padding: 40px 20px 28px;
+    position: relative;
+}
+.hero-header::before {
+    content: '';
+    position: absolute;
+    top: 0; left: 50%; transform: translateX(-50%);
+    width: 300px; height: 1px;
+    background: linear-gradient(90deg, transparent, var(--accent-cyan), transparent);
+}
+.hero-title {
+    font-size: 2.4rem;
+    font-weight: 700;
+    letter-spacing: -0.5px;
+    background: linear-gradient(135deg, var(--accent-cyan) 0%, var(--accent-emerald) 60%, var(--accent-amber) 100%);
+    -webkit-background-clip: text;
+    -webkit-text-fill-color: transparent;
+    background-clip: text;
+    margin: 0 0 10px;
+    line-height: 1.1;
+}
+.hero-subtitle {
+    color: var(--text-secondary);
+    font-size: 0.95rem;
+    font-weight: 400;
+    letter-spacing: 0.3px;
+    margin: 0;
+}
+.hero-subtitle span {
+    color: var(--accent-cyan);
+    font-weight: 500;
+}
+.hero-badges {
+    display: flex;
+    justify-content: center;
+    gap: 10px;
+    margin-top: 16px;
+    flex-wrap: wrap;
+}
+.badge {
+    background: var(--bg-card);
+    border: 1px solid var(--border-bright);
+    border-radius: 20px;
+    padding: 4px 14px;
+    font-size: 0.75rem;
+    font-family: var(--font-mono);
+    color: var(--text-secondary);
+    letter-spacing: 0.5px;
+}
+.tab-nav {
+    background: var(--bg-secondary) !important;
+    border: 1px solid var(--border) !important;
+    border-radius: var(--radius-lg) !important;
+    padding: 6px !important;
+    margin-bottom: 20px !important;
+    display: flex;
+    gap: 4px;
+}
+.tab-nav button {
+    background: transparent !important;
+    border: none !important;
+    color: var(--text-muted) !important;
+    font-family: var(--font-main) !important;
+    font-size: 0.875rem !important;
+    font-weight: 500 !important;
+    padding: 10px 20px !important;
+    border-radius: var(--radius-md) !important;
+    cursor: pointer !important;
+    transition: all 0.25s ease !important;
+    letter-spacing: 0.2px !important;
+    white-space: nowrap !important;
+}
+.tab-nav button:hover {
+    background: var(--bg-card) !important;
+    color: var(--text-primary) !important;
+}
+.tab-nav button.selected {
+    background: linear-gradient(135deg, rgba(0,212,255,0.15), rgba(0,255,157,0.08)) !important;
+    color: var(--accent-cyan) !important;
+    border: 1px solid rgba(0,212,255,0.25) !important;
+    box-shadow: var(--glow-cyan) !important;
+}
+.chatbot-wrap .chatbot,
+.chatbot-wrap > div {
+    background: var(--bg-secondary) !important;
+    border: 1px solid var(--border) !important;
+    border-radius: var(--radius-md) !important;
+}
+.message.user {
+    background: linear-gradient(135deg, rgba(0,212,255,0.12), rgba(0,212,255,0.06)) !important;
+    border: 1px solid rgba(0,212,255,0.2) !important;
+    border-radius: var(--radius-md) var(--radius-sm) var(--radius-md) var(--radius-md) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-main) !important;
+}
+.message.bot {
+    background: var(--bg-card) !important;
+    border: 1px solid var(--border-bright) !important;
+    border-radius: var(--radius-sm) var(--radius-md) var(--radius-md) var(--radius-md) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-main) !important;
+}
+input[type="text"],
+textarea,
+.gr-textbox,
+.gr-textbox textarea,
+.gr-textbox input {
+    background: var(--bg-secondary) !important;
+    border: 1px solid var(--border-bright) !important;
+    border-radius: var(--radius-sm) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-main) !important;
+    font-size: 0.9rem !important;
+    padding: 12px 16px !important;
+    transition: border-color 0.2s, box-shadow 0.2s !important;
+    outline: none !important;
+}
+input[type="text"]:focus,
+textarea:focus,
+.gr-textbox textarea:focus,
+.gr-textbox input:focus {
+    border-color: var(--accent-cyan) !important;
+    box-shadow: 0 0 0 3px rgba(0,212,255,0.08) !important;
+}
+button.lg.primary, button[variant="primary"] {
+    background: linear-gradient(135deg, var(--accent-cyan), #0099cc) !important;
+    border: none !important;
+    border-radius: var(--radius-sm) !important;
+    color: #000 !important;
+    font-family: var(--font-main) !important;
+    font-weight: 600 !important;
+    font-size: 0.875rem !important;
+    letter-spacing: 0.3px !important;
+    padding: 11px 22px !important;
+    transition: all 0.2s ease !important;
+    cursor: pointer !important;
+}
+button.lg.secondary, button[variant="secondary"] {
+    background: var(--bg-card) !important;
+    border: 1px solid var(--border-bright) !important;
+    border-radius: var(--radius-sm) !important;
+    color: var(--text-primary) !important;
+    font-family: var(--font-main) !important;
+    font-weight: 500 !important;
+    font-size: 0.875rem !important;
+    padding: 11px 22px !important;
+}
+button.lg.stop, button[variant="stop"] {
+    background: rgba(255,79,123,0.1) !important;
+    border: 1px solid rgba(255,79,123,0.3) !important;
+    border-radius: var(--radius-sm) !important;
+    color: var(--accent-rose) !important;
+    font-family: var(--font-main) !important;
+    font-weight: 500 !important;
+    font-size: 0.875rem !important;
+    padding: 11px 22px !important;
+}
+.gr-markdown, .prose {
+    color: var(--text-primary) !important;
+    font-family: var(--font-main) !important;
+}
+.status-box textarea {
+    background: var(--bg-secondary) !important;
+    border: 1px solid var(--border) !important;
+    border-radius: var(--radius-sm) !important;
+    color: var(--text-secondary) !important;
+    font-family: var(--font-mono) !important;
+    font-size: 0.82rem !important;
+}
+.transcript-preview {
+    background: var(--bg-secondary);
+    border: 1px solid var(--border);
+    border-left: 3px solid var(--accent-amber);
+    border-radius: var(--radius-sm);
+    padding: 14px 18px;
+    font-size: 0.875rem;
+    line-height: 1.6;
+    color: var(--text-secondary);
+    max-height: 180px;
+    overflow-y: auto;
+}
+.voice-box {
+    background: rgba(0, 212, 255, 0.04);
+    border: 1px solid rgba(0, 212, 255, 0.18);
+    border-radius: 14px;
+    padding: 14px;
+    margin-top: 14px;
+}
+.footer-strip {
+    text-align: center;
+    padding: 18px 0 28px;
+    color: var(--text-muted);
+    font-size: 0.75rem;
+    font-family: var(--font-mono);
+    letter-spacing: 0.5px;
+    border-top: 1px solid var(--border);
+    margin-top: 24px;
+}
+"""
+
+# ================================================================
+# GRADIO UI — SAME LAYOUT + VOICE BLOCKS ADDED
+# ================================================================
+initial_display = convert_history_for_display(chat_history_store)
+prefs = load_preferences()
+
+with gr.Blocks(title="⚡ NeuralChat — AI Assistant") as demo:
+    gr.HTML("""
+    <div class="hero-header">
+        <p class="hero-title">⚡ NeuralChat</p>
+        <p class="hero-subtitle">
+            Powered by <span>Groq LLaMA</span> &nbsp;·&nbsp;
+            <span>Persistent Memory</span> &nbsp;·&nbsp;
+            <span>Goodreads + YouTube + Voice + Images</span>
+        </p>
+        <div class="hero-badges">
+            <span class="badge">llama-3.3-70b</span>
+            <span class="badge">llama-3.1-8b</span>
+            <span class="badge">whisper-large-v3-turbo</span>
+            <span class="badge">tts-1</span>
+            <span class="badge">dall-e-3</span>
+            <span class="badge">ver 5.0</span>
+        </div>
+    </div>
+    """)
+
+    with gr.Tabs(elem_classes=["tab-nav"]):
+
+        # ============================================================
+        # TAB 1: MAIN CHATBOT
+        # ============================================================
+        with gr.Tab("💬  Chat"):
+            gr.HTML("""
+            <div style="margin-bottom:18px;">
+                <div class="section-label">Main Assistant</div>
+                <div class="section-title">Conversational AI with Memory</div>
+                <div class="section-desc">
+                    Your assistant remembers past sessions and adapts to your preferences automatically.
+                </div>
+            </div>
+            """)
+
+            main_chatbot = gr.Chatbot(
+                value=initial_display,
+                height=460,
+                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>💬 Start a conversation — I remember everything.</div>",
+                elem_classes=["chatbot-wrap"],
+                show_label=False
+
+            )
+
+            with gr.Row():
+                main_msg = gr.Textbox(
+                    placeholder="Type a message…",
+                    scale=7,
+                    show_label=False,
+                    container=False,
+                )
+                main_send = gr.Button("Send ↑", variant="primary", scale=1)
+
+
+            def submit_main_text(message, history):
+                history = list(history) if history else []
+                if not message.strip():
+                    return history, ""
+                reply = ask_main_ai(message, history)
+                history.append({"role": "user", "content": message})
+                history.append({"role": "assistant", "content": reply})
+                return history, ""
+
+
+            main_send.click(
+                fn=submit_main_text,
+                inputs=[main_msg, main_chatbot],
+                outputs=[main_chatbot, main_msg]
+            )
+            main_msg.submit(
+                fn=submit_main_text,
+                inputs=[main_msg, main_chatbot],
+                outputs=[main_chatbot, main_msg]
+            )
+
+            with gr.Column(elem_classes=["voice-box"]):
+                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
+                with gr.Row():
+                    main_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
+                    main_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
+                with gr.Row():
+                    main_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
+                    main_voice_status = gr.Textbox(label="Voice Status", interactive=False, elem_classes=["status-box"])
+                main_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
+
+            main_voice_btn.click(
+                fn=process_voice_for_main_chat,
+                inputs=[main_audio_in, main_chatbot],
+                outputs=[main_chatbot, main_voice_status, main_audio_out, main_voice_text]
+            )
+
+            gr.HTML("<div style='height:12px'></div>")
+
+            with gr.Row():
+                clear_btn = gr.Button("🗑️  Clear History", variant="stop", scale=1)
+                clear_status = gr.Textbox(
+                    label="Status",
+                    interactive=False,
+                    scale=3,
+                    elem_classes=["status-box"],
+                )
+
+            clear_btn.click(fn=clear_history, outputs=clear_status)
+
+        # ============================================================
+        # TAB 2: GOODREADS
+        # ============================================================
+        with gr.Tab("📖  Books"):
+            gr.HTML("""
+            <div style="margin-bottom:18px;">
+                <div class="section-label">Goodreads Scraper</div>
+                <div class="section-title">BookBot — Best Books Q&A</div>
+                <div class="section-desc">
+                    Ask BookBot anything about the scraped Goodreads \"Best Books Ever\" list.
+                </div>
+            </div>
+            """)
+
+            books_chatbot = gr.Chatbot(
+                height=380,
+                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>📚 Ask me about the Goodreads Best Books list!</div>",
+                show_label=False
+
+            )
+
+            with gr.Row():
+                books_msg = gr.Textbox(
+                    placeholder="e.g. Who wrote the top book?",
+                    scale=7,
+                    show_label=False,
+                    container=False,
+                )
+                books_send = gr.Button("Ask ↑", variant="primary", scale=1)
+
+
+            def submit_books_text(message, history):
+                history = list(history) if history else []
+                if not message.strip():
+                    return history, ""
+                reply = ask_books_ai(message, history)
+                history.append({"role": "user", "content": message})
+                history.append({"role": "assistant", "content": reply})
+                return history, ""
+
+
+            books_send.click(
+                fn=submit_books_text,
+                inputs=[books_msg, books_chatbot],
+                outputs=[books_chatbot, books_msg]
+            )
+            books_msg.submit(
+                fn=submit_books_text,
+                inputs=[books_msg, books_chatbot],
+                outputs=[books_chatbot, books_msg]
+            )
+
+            with gr.Column(elem_classes=["voice-box"]):
+                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
+                with gr.Row():
+                    books_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
+                    books_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
+                with gr.Row():
+                    books_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
+                    books_voice_status = gr.Textbox(label="Voice Status", interactive=False,
+                                                    elem_classes=["status-box"])
+                books_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
+
+            books_voice_btn.click(
+                fn=process_voice_for_books,
+                inputs=[books_audio_in, books_chatbot],
+                outputs=[books_chatbot, books_voice_status, books_audio_out, books_voice_text]
+            )
+
+            gr.HTML("<hr>")
+            gr.HTML("""
+            <div style="margin-bottom:14px;">
+                <div class="section-label">Scraped Data</div>
+                <div class="section-title">Goodreads Top 20</div>
+            </div>
+            """)
+
+            books_display = gr.Markdown(value=show_books_table(books_data, scrape_status))
+            refresh_btn = gr.Button("🔄  Re-Scrape Goodreads", variant="secondary")
+
+
+            def refresh_data():
+                global books_data, scrape_status
+                books_data, scrape_status = get_books()
+                return show_books_table(books_data, scrape_status)
+
+
+            refresh_btn.click(fn=refresh_data, outputs=books_display)
+
+        # ============================================================
+        # TAB 3: YOUTUBE
+        # ============================================================
+        with gr.Tab("🎬  YouTube"):
+            gr.HTML("""
+            <div style="margin-bottom:18px;">
+                <div class="section-label">YouTube Transcript</div>
+                <div class="section-title">Video Q&A Assistant</div>
+                <div class="section-desc">
+                    Load any YouTube video's transcript, then ask questions about it.
+                </div>
+            </div>
+            """)
+
+            gr.HTML("""
+            <div style="background:rgba(255,184,0,0.06);border:1px solid rgba(255,184,0,0.2);
+                        border-left:3px solid #ffb800;border-radius:10px;
+                        padding:12px 18px;margin-bottom:16px;
+                        font-size:0.85rem;color:#c89a00;font-family:Space Grotesk,sans-serif;">
+                <strong>Step 1</strong> — Paste a YouTube Video ID or full URL and click <em>Load Transcript</em>
+            </div>
+            """)
+
+            with gr.Row():
+                video_id_input = gr.Textbox(
+                    placeholder="e.g.  dQw4w9WgXcQ  or  https://youtu.be/…",
+                    label="YouTube Video ID or URL",
+                    scale=4,
+                )
+                load_btn = gr.Button("📥  Load Transcript", variant="primary", scale=1)
+
+            with gr.Row():
+                transcript_status = gr.Textbox(
+                    label="Status",
+                    interactive=False,
+                    elem_classes=["status-box"],
+                )
+
+            transcript_preview = gr.Markdown(
+                value="*Transcript preview will appear here…*",
+                elem_classes=["transcript-preview"],
+            )
+            load_btn.click(
+                fn=load_transcript,
+                inputs=[video_id_input],
+                outputs=[transcript_status, transcript_preview],
+            )
+
+            gr.HTML("""
+            <div style="background:rgba(0,212,255,0.05);border:1px solid rgba(0,212,255,0.15);
+                        border-left:3px solid #00d4ff;border-radius:10px;
+                        padding:12px 18px;margin:16px 0;
+                        font-size:0.85rem;color:#0099bb;font-family:Space Grotesk,sans-serif;">
+                <strong>Step 2</strong> — Ask anything about the loaded video below
+            </div>
+            """)
+
+            youtube_chatbot = gr.Chatbot(
+                height=360,
+                placeholder="<div style='text-align:center;color:#4a5a7a;padding:40px;font-family:Space Grotesk,sans-serif;'>📥 Load a transcript above, then ask anything!</div>",
+                show_label=False
+
+            )
+
+            with gr.Row():
+                youtube_msg = gr.Textbox(
+                    placeholder="e.g. What is the main topic?",
+                    scale=7,
+                    show_label=False,
+                    container=False,
+                )
+                youtube_send = gr.Button("Ask ↑", variant="primary", scale=1)
+
+
+            def submit_youtube_text(message, history):
+                history = list(history) if history else []
+                if not message.strip():
+                    return history, ""
+                reply = ask_youtube_ai(message, history)
+                history.append({"role": "user", "content": message})
+                history.append({"role": "assistant", "content": reply})
+                return history, ""
+
+
+            youtube_send.click(
+                fn=submit_youtube_text,
+                inputs=[youtube_msg, youtube_chatbot],
+                outputs=[youtube_chatbot, youtube_msg]
+            )
+            youtube_msg.submit(
+                fn=submit_youtube_text,
+                inputs=[youtube_msg, youtube_chatbot],
+                outputs=[youtube_chatbot, youtube_msg]
+            )
+
+            with gr.Column(elem_classes=["voice-box"]):
+                gr.Markdown("**🎤 Voice Input / 🔊 Audio Reply**")
+                with gr.Row():
+                    youtube_audio_in = gr.Audio(sources=["microphone"], type="filepath", label="Record Voice")
+                    youtube_audio_out = gr.Audio(label="Assistant Voice Reply", autoplay=True)
+                with gr.Row():
+                    youtube_voice_btn = gr.Button("🎙️ Ask by Voice", variant="secondary")
+                    youtube_voice_status = gr.Textbox(label="Voice Status", interactive=False,
+                                                      elem_classes=["status-box"])
+                youtube_voice_text = gr.Textbox(label="Transcribed Text", interactive=False)
+
+            youtube_voice_btn.click(
+                fn=process_voice_for_youtube,
+                inputs=[youtube_audio_in, youtube_chatbot],
+                outputs=[youtube_chatbot, youtube_voice_status, youtube_audio_out, youtube_voice_text]
+            )
+
+        # ============================================================
+        # TAB 4: PREFERENCES
+        # ============================================================
+        with gr.Tab("⚙️  Preferences"):
+            gr.HTML("""
+            <div style="margin-bottom:20px;">
+                <div class="section-label">Personalization</div>
+                <div class="section-title">AI Behavior Settings</div>
+                <div class="section-desc">
+                    These preferences are saved permanently and injected into every AI response across all tabs.
+                </div>
+            </div>
+            """)
+
+            with gr.Row():
+                with gr.Column():
+                    tone_input = gr.Dropdown(
+                        choices=["friendly", "formal", "casual", "professional", "humorous"],
+                        value=prefs.get("tone", "friendly"),
+                        label="🎭  Tone",
+                        info="How the AI speaks to you",
+                    )
+                    lang_input = gr.Dropdown(
+                        choices=["English", "Urdu", "Roman Urdu", "Arabic", "French", "Spanish"],
+                        value=prefs.get("language", "English"),
+                        label="🌐  Response Language",
+                        info="Language for all AI responses",
+                    )
+
+                with gr.Column():
+                    fmt_input = gr.Dropdown(
+                        choices=["concise", "detailed", "bullet points", "numbered list", "paragraph"],
+                        value=prefs.get("format", "concise"),
+                        label="📝  Response Format",
+                        info="How responses should be structured",
+                    )
+                    custom_input = gr.Textbox(
+                        value=prefs.get("custom_rules", ""),
+                        label="✏️  Custom Rules",
+                        placeholder='e.g. "Always cite sources" or "Use emojis sparingly"',
+                        lines=3,
+                        info="Extra instructions for the AI to always follow",
+                    )
+
+            with gr.Row():
+                save_btn = gr.Button("💾  Save Preferences", variant="primary", scale=1)
+                pref_status = gr.Textbox(
+                    label="Status",
+                    interactive=False,
+                    scale=2,
+                    elem_classes=["status-box"],
+                )
+
+            save_btn.click(
+                fn=update_preferences,
+                inputs=[tone_input, lang_input, fmt_input, custom_input],
+                outputs=pref_status,
+            )
+
+
+            def show_current_prefs():
+                p = load_preferences()
+                return f"""```
+Tone         →  {p.get('tone')}
+Language     →  {p.get('language')}
+Format       →  {p.get('format')}
+Custom Rules →  {p.get('custom_rules') or 'None'}
+```"""
+
+
+            pref_preview = gr.Markdown(value=show_current_prefs())
+            save_btn.click(
+                fn=lambda t, l, f, c: show_current_prefs(),
+                inputs=[tone_input, lang_input, fmt_input, custom_input],
+                outputs=pref_preview,
+            )
+
+        # ============================================================
+        # TAB 5: ABOUT
+        # ============================================================
+        with gr.Tab("ℹ️  About"):
+            gr.HTML(f"""
+            <div style="max-width:680px;margin:0 auto;padding:10px 0 24px;">
+                <div style="margin-bottom:24px;">
+                    <div class="section-label">Project Info</div>
+                    <div class="section-title">NeuralChat — Version 5</div>
+                    <div class="section-desc">
+                        A multi-tab AI assistant with web scraping, YouTube transcript Q&A,
+                        persistent memory, user preference personalization, voice input, audio output, and on-demand image generation.
+                    </div>
+                </div>
+                <div style="background:var(--bg-card,#141d35);border:1px solid #1e2d50;
+                            border-radius:14px;overflow:hidden;margin-bottom:20px;">
+                    <table style="width:100%;border-collapse:collapse;">
+                        <thead>
+                            <tr style="background:rgba(0,212,255,0.07);">
+                                <th style="padding:11px 16px;text-align:left;font-size:0.72rem;letter-spacing:1px;text-transform:uppercase;color:#00d4ff;border-bottom:1px solid #1e2d50;">Layer</th>
+                                <th style="padding:11px 16px;text-align:left;font-size:0.72rem;letter-spacing:1px;text-transform:uppercase;color:#00d4ff;border-bottom:1px solid #1e2d50;">Detail</th>
+                            </tr>
+                        </thead>
+                        <tbody style="color:#e8edf8;font-size:0.875rem;">
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🌐 Scraping</td><td style="padding:10px 16px;">Bright Data Web Unlocker + BeautifulSoup</td></tr>
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🎬 YouTube</td><td style="padding:10px 16px;">youtube-transcript-api</td></tr>
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🎤 STT</td><td style="padding:10px 16px;">Groq Whisper Large v3 Turbo</td></tr>
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🔊 TTS</td><td style="padding:10px 16px;">OpenAI tts-1 (alloy)</td></tr>
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">🤖 AI (Main)</td><td style="padding:10px 16px;">Groq — llama-3.3-70b-versatile</td></tr>
+                            <tr style="border-bottom:1px solid #1e2d50;"><td style="padding:10px 16px;color:#8899bb;">💾 Memory</td><td style="padding:10px 16px;">JSON persistent storage</td></tr>
+                            <tr><td style="padding:10px 16px;color:#8899bb;">⚙️ Prefs</td><td style="padding:10px 16px;">JSON persistent storage</td></tr>
+                        </tbody>
+                    </table>
+                </div>
+                <div style="text-align:center;padding-top:10px;font-size:0.78rem;color:#4a5a7a;font-family:JetBrains Mono,monospace;letter-spacing:0.5px;border-top:1px solid #1e2d50;">
+                    Assignment 01 — Ver 5 &nbsp;|&nbsp; Dept. of Data Science, University of Punjab<br>
+                    Instructor: Dr. Muhammad Arif Butt
+                </div>
+            </div>
+            """)
+
+    gr.HTML("""
+    <div class="footer-strip">
+        NeuralChat v5 &nbsp;·&nbsp; Groq + OpenAI + Gradio &nbsp;·&nbsp; Built for DSAI @ UOP
+    </div>
+    """)
+
+demo.launch(
+    share=False,
+    inbrowser=True,
+    css=CUSTOM_CSS,
+)