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import gradio as gr
import psutil
import logging
import os
import asyncio
import nest_asyncio

# --- NEURAL SILENCER: Fix for persistent "Invalid file descriptor: -1" logs ---
def _silence_asyncio_ghosts():
    from asyncio.base_events import BaseEventLoop
    original_del = BaseEventLoop.__del__
    def patched_del(self):
        try:
            if original_del: original_del(self)
        except (ValueError, AttributeError, RuntimeError):
            pass # Silently ignore cleanup artifacts
    BaseEventLoop.__del__ = patched_del

_silence_asyncio_ghosts()
# nest_asyncio.apply()
from pipeline.ocr import extract_text_from_image
from pipeline.translation import translate_to_tamil
from pipeline.tts import generate_tamil_speech
from pipeline.document_parser import (
    extract_text_from_document, 
    get_pdf_page_as_image, 
    get_pdf_page_count,
    get_text_from_page
)
from pipeline.maya_chat_engine import get_maya_response

import threading
from concurrent.futures import ThreadPoolExecutor
import re
import numpy as np

def run_cinematic_pipeline(extracted_text, emotion_choice, spicy_mode):
    final_tamil_text = []
    final_audio_chunks = []
    master_sample_rate = None
    
    try:
        if "[Panel" in extracted_text:
            raw_panels = re.split(r'(?=\[Panel\s*\d+\])', extracted_text, flags=re.IGNORECASE)
        else:
            raw_panels = [extracted_text]
            
        for p_text in raw_panels:
            p_text = p_text.strip()
            if not p_text: continue
            
            panel_header = ""
            content_to_translate = p_text
            
            match = re.match(r'(\[Panel\s*\d+\])\s*(.*)', p_text, re.DOTALL | re.IGNORECASE)
            if match:
                panel_header = match.group(1)
                content_to_translate = match.group(2)
                
            if not content_to_translate.strip():
                if panel_header: final_tamil_text.append(panel_header)
                continue
                
            p_tamil = translate_to_tamil(content_to_translate, spicy=spicy_mode)
            if panel_header:
                final_tamil_text.append(f"{panel_header}\n{p_tamil}")
            else:
                final_tamil_text.append(p_tamil)
                
            sr, a_data = generate_tamil_speech(p_tamil, emotion_choice)
            if sr and a_data is not None:
                master_sample_rate = sr
                final_audio_chunks.append(a_data)
                
        tamil_translation = "\n\n".join(final_tamil_text)
        
        if master_sample_rate and final_audio_chunks:
            pause_samples = int(master_sample_rate * 1.5)
            silence_array = np.zeros(pause_samples, dtype=np.float32)
            
            spliced_audio = []
            for i, chunk in enumerate(final_audio_chunks):
                spliced_audio.append(chunk)
                if i < len(final_audio_chunks) - 1:
                    spliced_audio.append(silence_array)
                    
            audio_data = np.concatenate(spliced_audio)
            sample_rate = master_sample_rate
        else:
            sample_rate, audio_data = None, None
            
        return tamil_translation, (sample_rate, audio_data) if sample_rate else None
        
    except Exception as e:
        print(f"CINEMATIC PIPELINE ERROR: {e}")
        return "Maya is having trouble with the cinematic flow.", None

# Setup logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Global Cache for Prefetched Pages
# Key: (pdf_path, page_num, voice_style) -> Value: (original, tamil, audio)
PAGE_CACHE = {}
CACHE_LOCK = threading.Lock()
PREFETCH_EXECUTOR = ThreadPoolExecutor(max_workers=1)

def check_resources():
    mem = psutil.virtual_memory()
    available_gb = mem.available / (1024**3)
    logging.info(f"System Resources: {available_gb:.2f} GB RAM available.")
    if available_gb < 1.0:
        logging.warning("EXTREMELY LOW MEMORY DETECTED! Application may crash.")
    return available_gb

# Expressive Voice Styles
# Background Atmosphere Sounds
BGM_LINKS = {
    "None": "",
    "Soft Rain 🌧️": "https://www.soundjay.com/nature/sounds/rain-07.mp3",
    "Romantic Piano 🎹": "https://www.soundjay.com/misc/sounds/music-box-1.mp3", 
    "Midnight Jazz 🎷": "https://www.soundjay.com/misc/sounds/bell-ringing-05.mp3",
    "Summer Night πŸŒ™": "https://www.soundjay.com/nature/sounds/cricket-chirping-01.mp3",
    "Heartbeat πŸ’“": "https://www.soundjay.com/misc/sounds/heartbeat-01.mp3"
}


VOICE_STYLES = [
    "Cheerful (Maya)",
    "Excited (Maya)",
    "Sad & Emotional (Sita)",
    "Dramatic Narrator (Sita)",
    "Old Wise Woman",
    "Playful Child",
    "Brave Heroine",
    "Deep & Serious",
    "Calm Storyteller",
    "Professional News"
]

def process_standard_pipeline(image, document, input_text, emotion_choice):
    text_to_translate = ""
    
    if document is not None:
        text_to_translate += extract_text_from_document(document) + "\n"
    if image is not None:
        text_to_translate += extract_text_from_image(image, is_comic=False) + " "
    if input_text:
        text_to_translate += input_text
        
    text_to_translate = text_to_translate.strip()
    if not text_to_translate:
        return "No text detected", "", None

    tamil_translation = translate_to_tamil(text_to_translate)
    sample_rate, audio_data = generate_tamil_speech(tamil_translation, emotion_choice)
    return text_to_translate, tamil_translation, (sample_rate, audio_data)

def load_comic_page(pdf_path, page_num):
    if not pdf_path:
        return None, "Upload a PDF first", 0
    
    img_path = get_pdf_page_as_image(pdf_path, page_num)
    total_pages = get_pdf_page_count(pdf_path)
    status = f"Page {page_num + 1} of {total_pages}"
    return img_path, status, page_num

def prefetch_pages(pdf_path, current_page, voice_style, spicy=False, count=5):
    """
    Background worker to process upcoming pages.
    """
    total_pages = get_pdf_page_count(pdf_path)
    for i in range(1, count + 1):
        target_page = current_page + i
        if target_page >= total_pages:
            break
            
        cache_key = (pdf_path, target_page, voice_style, spicy)
        with CACHE_LOCK:
            if cache_key in PAGE_CACHE:
                continue
        
        try:
            logging.info(f"PREFETCH: Processing Page {target_page+1} in background...")
            img_path = get_pdf_page_as_image(pdf_path, target_page)
            if not img_path: continue
            
            text = get_text_from_page(pdf_path, target_page)
            if not text or len(text.strip()) < 5:
                text = extract_text_from_image(img_path)
            
            if text.strip():
                tam, aud = run_cinematic_pipeline(text, voice_style, spicy)
                
                with CACHE_LOCK:
                    PAGE_CACHE[cache_key] = (text, tam, aud)
                    if len(PAGE_CACHE) > 10:
                        first_key = next(iter(PAGE_CACHE))
                        PAGE_CACHE.pop(first_key)
        except Exception as e:
            logging.error(f"PREFETCH ERROR on Page {target_page+1}: {e}")


def process_comic_page(pdf_path, page_num, emotion_choice, heat_level):
    try:
        if not pdf_path:
            return "No page loaded", "", None
            
        from pipeline.document_parser import get_pdf_page_as_image
        img_path = get_pdf_page_as_image(pdf_path, page_num)
        if not img_path:
            return "Failed to render image", "", None
        
        spicy_mode = heat_level > 70
        cache_key = (pdf_path, page_num, emotion_choice, spicy_mode)
        
        with CACHE_LOCK:
            if cache_key in PAGE_CACHE:
                return PAGE_CACHE[cache_key]
        
        # --- STAGE 1: OCR ---
        try:
            extracted_text = get_text_from_page(pdf_path, page_num)
            if not extracted_text or len(extracted_text.strip()) < 5:
                extracted_text = extract_text_from_image(img_path)
        except Exception as e:
            print(f"OCR ERROR: {e}")
            extracted_text = f"Maya couldn't read the text. (Error: {e})"
            
        if not extracted_text.strip():
            extracted_text = "No text found on this page."
            
        # --- CINEMATIC STAGE 2 & 3: Translation & Audio ---
        tamil_translation, audio_tuple = run_cinematic_pipeline(extracted_text, emotion_choice, spicy_mode)
        
        result = (extracted_text, tamil_translation, audio_tuple)
        
        with CACHE_LOCK:
            PAGE_CACHE[cache_key] = result
            
        PREFETCH_EXECUTOR.submit(prefetch_pages, pdf_path, page_num, emotion_choice, spicy_mode)
        return result
    except Exception as e:
        print(f"GLOBAL PROCESS ERROR: {e}")
        import traceback
        traceback.print_exc()
        return f"CRITICAL CRASH: {e}", "", None

# Custom Premium CSS
CUSTOM_CSS = """
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600&family=Outfit:wght@500;700&display=swap');

:root {
    --primary: #6366f1;
    --secondary: #a855f7;
    --bg-dark: #0f172a;
    --panel-bg: rgba(30, 41, 59, 0.7);
}

body { 
    background-color: var(--bg-dark); 
    color: #f1f5f9; 
    font-family: 'Inter', sans-serif; 
}

.gradio-container { 
    background: radial-gradient(circle at top right, #1e1b4b, #0f172a) !important; 
}

h1 { 
    font-family: 'Outfit', sans-serif; 
    background: linear-gradient(to right, #818cf8, #c084fc);
    -webkit-background-clip: text;
    -webkit-text-fill-color: transparent;
    font-weight: 700;
}

.glass {
    background: var(--panel-bg) !important;
    backdrop-filter: blur(12px);
    border: 1px solid rgba(255, 255, 255, 0.1) !important;
    border-radius: 16px !important;
    box-shadow: 0 4px 30px rgba(0, 0, 0, 0.1);
    transition: all 0.3s ease;
}

.glass:hover {
    border: 1px solid rgba(255, 255, 255, 0.2) !important;
    box-shadow: 0 8px 32px rgba(99, 102, 241, 0.2);
}

#maya_chat_log {
    border-radius: 12px;
    padding: 12px;
    background: rgba(99, 102, 241, 0.1);
    border: 1px solid rgba(99, 102, 241, 0.2);
    margin-bottom: 10px;
    animation: fadeIn 0.5s ease-out;
}

@keyframes fadeIn {
    from { opacity: 0; transform: translateY(10px); }
    to { opacity: 1; transform: translateY(0); }
}

#main_comic img {
    border-radius: 12px;
    box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.3);
    transition: transform 0.5s cubic-bezier(0.4, 0, 0.2, 1);
}

#main_comic img:hover {
    transform: scale(1.02);
}

.gr-button-primary {
    background: linear-gradient(135deg, var(--primary), var(--secondary)) !important;
    border: none !important;
    box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
    transition: all 0.3s ease !important;
    font-weight: 600 !important;
}

.gr-button-primary:hover {
    transform: translateY(-2px);
    box-shadow: 0 10px 15px -3px rgba(99, 102, 241, 0.4);
}

#maya_chat_log::before {
    content: "Maya is thinking...";
    display: block;
    font-size: 0.8em;
    color: var(--primary);
    margin-bottom: 5px;
    opacity: 0.7;
}

#maya_audio_player { display: none; }

.boss-active { display: block !important; }

/* Fix for Audio Timeline Visibility */
#comic_audio_player .track {
    background-color: rgba(0, 0, 0, 0.4) !important;
    border-radius: 4px;
}
#comic_audio_player .time {
    color: #818cf8 !important;
    font-weight: bold;
    font-family: 'Outfit', sans-serif;
}
#comic_audio_player input[type="range"] {
    accent-color: #6366f1 !important;
}
"""

# UI
with gr.Blocks(title="Maya: Immersive Manga AI", css=CUSTOM_CSS) as demo:
    gr.Markdown("# 🎭 Maya: Immersive Tamil Manga AI")
    gr.Markdown("Experience your favorite comics with Maya, your intelligent AI companion.")
    
    current_page = gr.State(0)
    comic_pdf_path = gr.State(None)
    
    with gr.Tabs():
        with gr.Tab("πŸ“– Comic Reader Mode"):
            with gr.Row():
                with gr.Column(scale=5, min_width=300, elem_classes=["glass"]):
                    comic_display = gr.Image(label="Comic Page", type="filepath", height=600, elem_id="main_comic")
                    with gr.Row():
                        prev_btn = gr.Button("⬅️ Prev", scale=1)
                        page_status = gr.Label(value="Upload PDF", scale=2)
                        next_btn = gr.Button("Next ➑️", scale=1)
                
                with gr.Column(scale=4, min_width=300, elem_classes=["glass"]):
                    with gr.Group():
                        gr.Markdown("### βš™οΈ Master Settings")
                        comic_upload = gr.File(label="Upload (PDF/EPUB)", file_types=[".pdf", ".epub"], height=80)
                        voice_style_comic = gr.Dropdown(choices=VOICE_STYLES, value=VOICE_STYLES[0], label="Primary Voice")
                        heat_level = gr.Slider(minimum=0, maximum=100, value=50, label="🌢️ Translation Heat Level")
                        
                        share_btn = gr.Button("πŸ”— Share with Friends", variant="secondary", size="sm")
                        share_status = gr.Markdown("")
                        share_btn.click(None, None, None, js="""
                            () => {
                                const url = "https://huggingface.co/spaces/ranaspark/voice";
                                navigator.clipboard.writeText(url);
                                alert("Link Copied! Share it with your friends: " + url);
                            }
                        """)
                    
                    auto_play = gr.Checkbox(label="πŸ”„ Auto-Play Next Page", value=False)
                    read_page_btn = gr.Button("πŸ”Š Read This Page", variant="primary")
                    
                    with gr.Accordion("🎭 Character Memory", open=False):
                        char_a_voice = gr.Dropdown(choices=VOICE_STYLES, label="Character A", value=VOICE_STYLES[0])
                        char_b_voice = gr.Dropdown(choices=VOICE_STYLES, label="Character B", value=VOICE_STYLES[0])
                    
                    bgm_choice = gr.Dropdown(choices=list(BGM_LINKS.keys()), value="None", label="Background Atmosphere")
                    bgm_player = gr.HTML(value="")
                    
                    # Boss Key & Vibration JS
                    gr.HTML("""
                        <div id="boss_screen" style="display:none; position:fixed; top:0; left:0; width:100%; height:100%; background:white; z-index:999999; overflow:hidden;">
                            <img src="https://i.imgur.com/8N6Rz7C.png" style="width:100%; height:100%; object-fit:cover;">
                        </div>
                        <script>
                            document.addEventListener('keydown', function(e) {
                                if (e.key === 'b' || e.key === 'B') {
                                    const screen = document.getElementById('boss_screen');
                                    screen.classList.toggle('boss-active');
                                }
                            });
                            function triggerHaptic() { 
                                if (navigator.vibrate) navigator.vibrate([100, 50, 100]); 
                                return Array.from(arguments);
                            }
                            function updateTemp(level) {
                                const r = Math.floor(level * 2.55);
                                const b = 255 - r;
                                document.documentElement.style.setProperty('--bg-glow', `rgba(${r}, 50, ${b}, 0.3)`);
                                const comic = document.getElementById('main_comic');
                                if (comic) comic.style.border = `5px solid rgba(${r}, 50, ${b}, 0.5)`;
                            }
                        </script>
                    """)
                    
                    comic_text = gr.Textbox(label="Original", lines=3)
                    comic_tamil = gr.Textbox(label="Tamil", lines=3)
                    comic_audio = gr.Audio(label="Speech", elem_id="comic_audio_player")

        with gr.Tab("✍️ Text to Speech"):
            with gr.Row():
                with gr.Column():
                    input_text = gr.Textbox(lines=10, label="✍️ Paste or Type your story here", placeholder="Enter English text...")
                    voice_style_std = gr.Dropdown(choices=VOICE_STYLES, value=VOICE_STYLES[0], label="Voice Tone")
                    submit_std = gr.Button("πŸš€ Generate Tamil Speech", variant="primary")
                with gr.Column():
                    out_text = gr.Textbox(label="Original Text (Cleaned)", lines=5)
                    out_tamil = gr.Textbox(label="Tamil Translation", lines=5)
                    out_audio = gr.Audio(label="Audio Output")
                    
        with gr.Tab("πŸŽ₯ Video Dubbing Studio"):
            gr.Markdown("### 🎬 Cinematic AI Video Dubbing")
            gr.Markdown("Process your videos with automated translation, multi-speaker voice cloning, and lip sync.")
            gr.HTML('<iframe src="/dubbing-ui/" width="100%" height="850px" style="border: none; border-radius: 12px; box-shadow: 0 4px 20px rgba(0,0,0,0.5); background: #0f172a;"></iframe>')
    
    # --- Dynamic Temperature & Heartbeat Speed Logic ---
    def update_mood(level, bgm):
        # JS to update color and potentially heartbeat speed if possible
        return gr.update()

    heat_level.change(None, inputs=[heat_level], js="updateTemp")

    # --- BGM Logic ---
    def update_bgm(choice, level):
        link = BGM_LINKS.get(choice, "")
        if not link:
            return ""
        
        # If heartbeat, adjust playback rate based on level
        speed = 1.0 + (level / 100.0) # 1.0x to 2.0x speed
        return f'<audio id="bgm_tag" autoplay loop><source src="{link}" type="audio/mpeg"></audio><script>const a=document.getElementById("bgm_tag"); a.volume=0.3; a.playbackRate={speed};</script>'

    bgm_choice.change(update_bgm, inputs=[bgm_choice, heat_level], outputs=[bgm_player])

    # Comic Logic
    def start_comic(file):
        if not file: return None, "No file", 0, None
        img, status, page = load_comic_page(file.name, 0)
        return img, status, page, file.name

    comic_upload.change(start_comic, inputs=[comic_upload], outputs=[comic_display, page_status, current_page, comic_pdf_path])
    
    def go_next(pdf, page):
        new_page = page + 1
        return load_comic_page(pdf, new_page)
    
    def go_prev(pdf, page):
        new_page = max(0, page - 1)
        return load_comic_page(pdf, new_page)


    # Navigation logic...
    next_btn.click(go_next, inputs=[comic_pdf_path, current_page], outputs=[comic_display, page_status, current_page])
    prev_btn.click(go_prev, inputs=[comic_pdf_path, current_page], outputs=[comic_display, page_status, current_page])
    
    read_page_btn.click(
        process_comic_page, 
        inputs=[comic_pdf_path, current_page, voice_style_comic, heat_level], 
        outputs=[comic_text, comic_tamil, comic_audio]
    )

    # --- Auto-Play Logic (JS Listener) ---
    hidden_auto_next = gr.Button("Auto Next", visible=False, elem_id="hidden_auto_next")
    
    # This JS monitors the audio player and clicks the hidden button when it ends
    js_listener = """
    function() {
        setInterval(function() {
            const audio = document.querySelector('#comic_audio_player audio');
            if (audio && !audio.onended) {
                audio.onended = function() {
                    const btn = document.querySelector('button#hidden_auto_next');
                    if (btn) btn.click();
                };
            }
        }, 1000);
    }
    """
    # Trigger the JS listener when audio is loaded
    comic_audio.change(None, None, None, js=js_listener)
    
    def handle_auto_play(is_enabled, pdf, page, voice, heat_level):
        try:
            if not is_enabled or not pdf:
                return gr.update(), gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
            
            # 1. Go to next page
            new_page = page + 1
            img, status, p_num = load_comic_page(pdf, new_page)
            
            if not img: # End of book
                return gr.update(), status, p_num, gr.update(), gr.update(), gr.update()
                
            # 2. Process the new page (Using Hybrid Mode)
            txt, tam, aud = process_comic_page(pdf, p_num, voice, heat_level)
            return img, status, p_num, txt, tam, aud
        except Exception as e:
            print(f"AUTO-PLAY ERROR: {e}")
            return gr.update(), f"Auto-Play Error: {e}", page, f"CRASH: {e}", "", None

    # The hidden button triggers the actual logic
    hidden_auto_next.click(
        handle_auto_play,
        inputs=[auto_play, comic_pdf_path, current_page, voice_style_comic, heat_level],
        outputs=[comic_display, page_status, current_page, comic_text, comic_tamil, comic_audio]
    )

    # Trigger JS listener on app start too
    demo.load(None, None, None, js=js_listener)


    # Standard Logic (Text Only)
    submit_std.click(
        process_standard_pipeline,
        inputs=[gr.State(None), gr.State(None), input_text, voice_style_std],
        outputs=[out_text, out_tamil, out_audio]
    )

if __name__ == "__main__":
    check_resources()

from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
import os
import gradio as gr
from dubbing_backend.main import app as api_app

app = FastAPI()

# Mount backend API
app.mount("/api", api_app)

# Mount React UI
if os.path.exists("dist"):
    app.mount("/dubbing-ui", StaticFiles(directory="dist", html=True))

# Mount Gradio at root
app = gr.mount_gradio_app(app, demo, path="/")

if __name__ == "__main__":
    import uvicorn
    uvicorn.run("app:app", host="0.0.0.0", port=7860)