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# -- coding: utf-8 --
# --- IMPORT LIBRARY UTAMA & INTI ---

import gradio as gr
import torch
import numpy as np
from diffusers import DiffusionPipeline
import random
import time
import os
from datetime import datetime, timedelta # <-- KESALAHAN SUDAH DIPERBAIKI DI SINI
import csv
import pandas as pd
import threading
from PIL import Image, ImageEnhance
from pathlib import Path
import uuid # Library untuk ID unik chat
import urllib.parse
import json # Library baru untuk menyimpan data share
import string # Library baru untuk generate ID random

# --- LIBRARY BARU UNTUK FITUR UPGRADE ---

try:
    import psutil
    import platform
    from transformers import Swin2SRForImageSuperResolution, Swin2SRImageProcessor
    print("✅ Library tambahan (psutil, transformers) berhasil diimpor.")
except ImportError:
    print("❌ Peringatan: Library 'psutil' atau 'transformers' tidak ditemukan. Fitur System Monitor & Upscaler tidak akan berfungsi.")
    psutil = None
    platform = None
    Swin2SRForImageSuperResolution = None
    Swin2SRImageProcessor = None

try:
    import google.generativeai as genai
    print("✅ Library 'google-generativeai' berhasil diimpor.")
except ImportError:
    print("❌ Peringatan: Library 'google-generativeai' tidak ditemukan. Fitur Chatbot & Prompt Enhancer tidak akan berfungsi.")
    genai = None

# --- HEAD HTML & CSS (Tampilan Profesional dengan Upgrade untuk Chat) ---
HEAD_HTML = """
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>RenXploit's Creative AI Suite</title>
    <link rel="preconnect" href="https://fonts.googleapis.com">
    <link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
    <link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=Fira+Code:wght@500&display=swap" rel="stylesheet">
    <script>
        function typewriterEffect(element, text, speed) {
            let i = 0;
            element.innerHTML = ""; 
            const cursor = document.createElement('span');
            cursor.className = 'typewriter-cursor';
            cursor.innerHTML = '|';
            element.appendChild(cursor);
            function type() {
                if (i < text.length) {
                    element.insertBefore(document.createTextNode(text.charAt(i)), cursor);
                    i++;
                    setTimeout(type, speed);
                } else {
                    cursor.style.animation = 'blink 1s step-end infinite';
                }
            }
            type();
        }

        document.addEventListener("DOMContentLoaded", function(event) {
            const titleElement = document.querySelector('#main-title h1');
            if (titleElement) {
                const titleText = "🚀 RenXploit's Creative AI Suite 🌌";
                titleElement.textContent = "";
                setTimeout(() => typewriterEffect(titleElement, titleText, 50), 500);
            }
            
            setInterval(() => {
                const triggerButton = document.querySelector('#system-info-trigger-btn button');
                if (triggerButton) {
                    triggerButton.click();
                }
            }, 5000);
        });
    </script>
    <style>
        :root { --primary-color: #00aaff; --primary-hover-color: #0088cc; --background-color: #0d1117; --content-background-color: #161b22; --border-color: #30363d; --text-color: #c9d1d9; --text-muted-color: #8b949e; --font-family-main: 'Inter', sans-serif; --font-family-mono: 'Fira Code', monospace; --border-radius: 12px; --shadow-light: 0 4px 14px 0 rgba(0, 170, 255, 0.1); --shadow-strong: 0 6px 20px 0 rgba(0, 170, 255, 0.15); }
        body, .gradio-container { font-family: var(--font-family-main); background-color: var(--background-color) !important; color: var(--text-color); }
        h1, h2, h3 { color: #ffffff; font-weight: 600; }
        #main-title h1 { font-size: 2.5em !important; font-weight: 700 !important; text-align: center; padding: 2rem 1rem; color: #ffffff; background: linear-gradient(90deg, #00aaff, #00ffaa); -webkit-background-clip: text; -webkit-text-fill-color: transparent; display: inline-block; }
        #main-title .typewriter-cursor { color: var(--primary-color); font-weight: bold; }
        @keyframes blink { from, to { opacity: 1 } 50% { opacity: 0 } }
        #main-subtitle p { font-size: 1.2em !important; text-align: center; color: var(--text-muted-color); margin-top: -1.5rem !important; margin-bottom: 2rem !important; }
        .gradio-tabs { border: none !important; background-color: transparent !important; margin-bottom: 1.5rem; }
        .gradio-tabs > div[role="tablist"] { display: flex; justify-content: center; flex-wrap: wrap; gap: 10px; border-bottom: 2px solid var(--border-color); padding-bottom: 10px; }
        .gradio-tabs > div[role="tablist"] > button { background-color: transparent !important; color: var(--text-muted-color) !important; border: none !important; border-bottom: 3px solid transparent !important; font-size: 1.1em !important; font-weight: 600 !important; padding: 12px 20px !important; border-radius: 8px 8px 0 0 !important; transition: all 0.3s ease; }
        .gradio-tabs > div[role="tablist"] > button:hover { background-color: var(--content-background-color) !important; color: var(--primary-color) !important; }
        .gradio-tabs > div[role="tablist"] > button.selected { color: var(--primary-color) !important; border-bottom: 3px solid var(--primary-color) !important; background-color: var(--content-background-color) !important; }
        .tabitem { background-color: transparent !important; border: none !important; padding: 0 !important; }
        .gradio-row.panel, .gradio-accordion, .gradio-group { background-color: var(--content-background-color) !important; border: 1px solid var(--border-color) !important; border-radius: var(--border-radius) !important; padding: 24px !important; box-shadow: 0 4px 6px rgba(0,0,0,0.1); }
        .gradio-accordion { margin-top: 1rem; }
        .gradio-button.primary { background: linear-gradient(90deg, var(--primary-color), #00c6ff) !important; color: #ffffff !important; font-weight: 600 !important; font-size: 1.1em !important; border-radius: 8px !important; border: none !important; padding: 12px 24px !important; transition: all 0.3s ease; box-shadow: var(--shadow-light); }
        .gradio-button.primary:hover { transform: translateY(-2px); box-shadow: var(--shadow-strong); }
        .gradio-button.secondary { background-color: var(--content-background-color) !important; border: 1px solid var(--primary-color) !important; color: var(--primary-color) !important; transition: all 0.3s ease; }
        .gradio-button.secondary:hover { background-color: var(--primary-color) !important; color: #ffffff !important; }
        .gradio-textbox, .gradio-number, .gradio-image { background-color: var(--background-color) !important; border: 1px solid var(--border-color) !important; color: var(--text-color) !important; border-radius: 8px !important; }
        .gradio-textbox textarea, .gradio-number input { color: var(--text-color) !important; }
        .gradio-textbox:focus-within, .gradio-number:focus-within { border-color: var(--primary-color) !important; box-shadow: 0 0 0 2px rgba(0, 170, 255, 0.3); }
        div.info { color: var(--text-muted-color) !important; font-style: italic; }
        #gallery, #history_gallery { border-radius: var(--border-radius) !important; overflow: hidden; border: 1px solid var(--border-color); background-color: #010409; }
        #gallery .gallery-item, #history_gallery .gallery-item { transition: transform 0.3s ease, box-shadow 0.3s ease; }
        #gallery .gallery-item:hover, #history_gallery .gallery-item:hover { transform: scale(1.03); box-shadow: 0 8px 30px rgba(0, 170, 255, 0.3); }
        .loader-container { border: 1px solid var(--border-color); border-radius: var(--border-radius); padding: 30px; background: var(--content-background-color); text-align: center; overflow: hidden; }
        .loader-text { font-family: var(--font-family-mono); font-size: 1.1em; color: var(--primary-color); margin-bottom: 20px; }
        .loader-bar-container { height: 8px; background: var(--background-color); border-radius: 4px; overflow: hidden; }
        .loader-bar { width: 100%; height: 100%; background: linear-gradient(90deg, transparent, var(--primary-color), transparent); background-size: 200% 100%; animation: scan 2s linear infinite; }
        @keyframes scan { 0% { background-position: 200% 0; } 100% { background-position: -200% 0; } }
        #chatbot-container { display: flex; flex-direction: column; height: 70vh; max-height: 750px; }
        #chatbot-display { flex-grow: 1; overflow-y: auto; padding: 10px; border-bottom: 1px solid var(--border-color); }
        #chatbot-display .message { border-radius: 18px !important; padding: 12px 18px !important; box-shadow: none !important; max-width: 80%; }
        #chatbot-display .user { background-color: var(--primary-color) !important; color: white !important; align-self: flex-end; border-bottom-right-radius: 5px !important; }
        #chatbot-display .bot { background-color: var(--content-background-color) !important; border: 1px solid var(--border-color) !important; align-self: flex-start; border-bottom-left-radius: 5px !important; }
        #chat-history-sidebar { background-color: transparent !important; border: none !important; padding: 0 !important; box-shadow: none !important; }
        #chat-history-sidebar .gradio-radio > div { display: flex; flex-direction: column; gap: 8px; }
        #chat-history-sidebar .gradio-radio label { width: 100%; text-align: left; padding: 10px; border: 1px solid var(--border-color); border-radius: 8px; transition: all 0.2s ease; }
        #chat-history-sidebar .gradio-radio input:checked + label { border-color: var(--primary-color); background-color: rgba(0, 170, 255, 0.1); color: var(--primary-color); font-weight: 600; }
        .footer { text-align: center; margin: 2rem auto; padding: 1rem; color: var(--text-muted-color); border-top: 1px solid var(--border-color); }
        .footer b { color: var(--primary-color); }
    </style>
</head>
"""

# --- PENGATURAN & LOGIC GLOBAL ---

VISITOR_LOG_FILE = "visitor_log.csv"
HISTORY_LOG_FILE = "generation_log.csv"
IMAGE_HISTORY_DIR = Path("generated_images")
SHARE_DATA_DIR = Path("shared_data")

file_lock = threading.Lock()
device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"➡️ Menggunakan device: {device.upper()}")

# --- Inisialisasi File Log & Direktori ---

def initialize_environment():
    if not os.path.exists(VISITOR_LOG_FILE):
        with file_lock:
            if not os.path.exists(VISITOR_LOG_FILE):
                with open(VISITOR_LOG_FILE, mode='w', newline='', encoding='utf-8') as f:
                    writer = csv.writer(f)
                    writer.writerow(["Timestamp", "IP Address", "User Agent"])
                print(f"✅ File log '{VISITOR_LOG_FILE}' berhasil dibuat.")

    IMAGE_HISTORY_DIR.mkdir(exist_ok=True)
    SHARE_DATA_DIR.mkdir(exist_ok=True) 
    if not os.path.exists(HISTORY_LOG_FILE):
        with file_lock:
            if not os.path.exists(HISTORY_LOG_FILE):
                with open(HISTORY_LOG_FILE, mode='w', newline='', encoding='utf-8') as f:
                    writer = csv.writer(f)
                    writer.writerow(["Timestamp", "Filename", "Prompt", "NegativePrompt", "Seed", "Steps"])
                print(f"✅ File log riwayat '{HISTORY_LOG_FILE}' dan direktori '{IMAGE_HISTORY_DIR}' siap.")

initialize_environment()

# --- PEMUATAN MODEL-MODEL AI ---
print("➡️ Memuat model SDXL-Turbo...")
pipe = DiffusionPipeline.from_pretrained(
    "stabilityai/sdxl-turbo", torch_dtype=torch.float16 if device == "cuda" else torch.float32,
    variant="fp16" if device == "cuda" else None, use_safetensors=True
).to(device)
if torch.cuda.is_available(): pipe.enable_xformers_memory_efficient_attention()
print("✅ Model SDXL-Turbo berhasil dimuat.")

upscaler_model = None
upscaler_processor = None
if Swin2SRForImageSuperResolution:
    try:
        print("➡️ Memuat model AI Upscaler (Swin2SR)...")
        upscaler_model = Swin2SRForImageSuperResolution.from_pretrained("caidas/swin2sr-realworld-sr-x4-64-bsrgan-psnr").to(device)
        upscaler_processor = Swin2SRImageProcessor.from_pretrained("caidas/swin2sr-realworld-sr-x4-64-bsrgan-psnr")
        print("✅ Model AI Upscaler berhasil dimuat.")
    except Exception as e:
        print(f"❌ Gagal memuat model Upscaler: {e}. Fitur upscale akan dinaktifkan.")

# --- KELAS UNTUK CHATBOT GEMINI ---
class GeminiChat:
    def __init__(self):
        self.api_keys = []
        self.is_configured = False
        if not genai: return

        i = 1
        while True:
            key = os.getenv(f"GEMINI_API_KEY_{i}")
            if key:
                self.api_keys.append(key)
                i += 1
            else:
                break
        
        if self.api_keys:
            print(f"✅ Berhasil memuat {len(self.api_keys)} API Key Gemini. Sistem rotasi aktif.")
            self.is_configured = True
        else:
            print("❌ PERINGATAN: Tidak ada API Key Gemini yang ditemukan. Fitur AI Chat & Prompt Enhancer tidak akan berfungsi.")

    def chat(self, message, history, system_prompt=None):
        if not self.is_configured:
            return "Maaf, fitur ini tidak terkonfigurasi karena tidak ada API Key."
        try:
            selected_key = random.choice(self.api_keys)
            genai.configure(api_key=selected_key)
            model = genai.GenerativeModel('gemini-2.5-flash')
            
            chat_history_for_api = []
            for user_msg, model_msg in history:
                if user_msg: chat_history_for_api.append({"role": "user", "parts": [user_msg]})
                if model_msg: chat_history_for_api.append({"role": "model", "parts": [model_msg]})
            
            chat_session = model.start_chat(history=chat_history_for_api)
            
            full_prompt = message
            if system_prompt and not history:
                full_prompt = f"{system_prompt}\n\nUser query: {message}"
                
            response = chat_session.send_message(full_prompt)
            return response.text
        except Exception as e:
            print(f"❌ Terjadi error pada API Key Gemini: {e}")
            return "Terjadi kesalahan saat menghubungi API AI. Mungkin salah satu API Key tidak valid atau ada masalah jaringan. Silakan coba lagi."

gemini_bot = GeminiChat()

# --- FUNGSI-FUNGSI INTI (GENERATOR & LAINNYA) ---
def log_visitor(request: gr.Request):
    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    ip_address = request.client.host if request else "N/A"
    user_agent = request.headers.get("user-agent", "Unknown") if request else "N/A"
    with file_lock:
        with open(VISITOR_LOG_FILE, mode='a', newline='', encoding='utf-8') as f:
            writer = csv.writer(f)
            writer.writerow([timestamp, ip_address, user_agent])
    print(f"✅ Pengunjung baru tercatat: IP {ip_address}")

def generate_images(prompt, negative_prompt, steps, seed, num_images):
    if not prompt:
        raise gr.Error("Prompt tidak boleh kosong!")
    if seed == -1:
        seed = random.randint(0, 2**32 - 1)
    generator = torch.manual_seed(seed)
    images = pipe(prompt=prompt, negative_prompt=negative_prompt, generator=generator, num_inference_steps=steps, guidance_scale=0.0, num_images_per_prompt=num_images).images
    return images, seed

def genie_wrapper(prompt, negative_prompt, steps, seed, num_images):
    yield gr.update(visible=False), gr.update(visible=True, value="<div class='loader-container'><div class='loader-text'>AI sedang melukis mahakarya Anda...</div><div class='loader-bar-container'><div class='loader-bar'></div></div></div>"), gr.update(interactive=False), gr.update(visible=False)

    start_time = time.time()
    images, used_seed = generate_images(prompt, negative_prompt, int(steps), int(seed), int(num_images))
    end_time = time.time()

    timestamp_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    for i, img in enumerate(images):
        filename = f"{int(time.time())}_{used_seed}_{i}.png"
        filepath = IMAGE_HISTORY_DIR / filename
        img.save(filepath)
        
        with file_lock:
            with open(HISTORY_LOG_FILE, mode='a', newline='', encoding='utf-8') as f:
                writer = csv.writer(f)
                writer.writerow([timestamp_str, filename, prompt, negative_prompt, used_seed, int(steps)])

    generation_time = end_time - start_time
    info_text = f"Seed yang digunakan: {used_seed}\nTotal waktu generasi: {generation_time:.2f} detik"
    yield gr.update(value=images, visible=True), gr.update(visible=False), gr.update(interactive=True), gr.update(value=info_text, visible=True)

def submit_report(name, email, message):
    if not name or not message:
        gr.Warning("Nama dan Pesan tidak boleh kosong!")
        return gr.update(visible=False)
    report_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
    report_content = f"--- Laporan Baru ({report_time}) ---\nNama: {name}\nEmail: {email}\nPesan: {message}\n\n"
    with open("reports.log", "a", encoding="utf-8") as f:
        f.write(report_content)
    print("✅ Laporan baru telah disimpan ke reports.log")
    return gr.update(value="✅ Terima kasih! Laporan Anda telah kami terima.", visible=True)

# --- FUNGSI VISITOR MONITOR ---
def update_visitor_monitor(time_filter: str):
    try:
        with file_lock:
            if not os.path.exists(VISITOR_LOG_FILE) or os.path.getsize(VISITOR_LOG_FILE) == 0:
                return "## 📈 0", pd.DataFrame({"Timestamp": [], "Total Pengunjung": []})
            
            column_names = ["Timestamp", "IP Address", "User Agent"]
            df = pd.read_csv(VISITOR_LOG_FILE, header=None, names=column_names)

            if not df.empty and df.iloc[0]['Timestamp'] == 'Timestamp':
                df = df.iloc[1:].reset_index(drop=True)
        
        if df.empty: return "## 📈 0", pd.DataFrame({"Timestamp": [], "Total Pengunjung": []})
        
        df['Timestamp'] = pd.to_datetime(df['Timestamp'], errors='coerce')
        df.dropna(subset=['Timestamp'], inplace=True)
        if df.empty: return "## 📈 0", pd.DataFrame({"Timestamp": [], "Total Pengunjung": []})

        total_overall_visitors = len(df)
        total_visitors_formatted = f"## 📈 {total_overall_visitors:,}"
        df['Total Pengunjung'] = np.arange(1, len(df) + 1)
        
        now = datetime.now()

        if time_filter == "1 Minggu Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(weeks=1)]
        elif time_filter == "2 Minggu Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(weeks=2)]
        elif time_filter == "3 Bulan Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(days=90)]
        else: df_plot = df
        
        if df_plot.empty: return total_visitors_formatted, pd.DataFrame({"Timestamp": [], "Total Pengunjung": []})
        
        return total_visitors_formatted, df_plot
    except Exception as e:
        error_message = f"Error saat memperbarui monitor: {e}"
        print(f"❌ {error_message}")
        return f"## ⚠️ Error: {e}", pd.DataFrame({"Error": [error_message]})

# --- FUNGSI-FUNGSI FITUR BARU ---
def enhance_prompt(simple_prompt):
    if not simple_prompt:
        gr.Warning("Tolong masukkan ide Anda terlebih dahulu.")
        return ""
    if not gemini_bot.is_configured:
        gr.Error("Fitur Prompt Enhancer tidak aktif karena API Key Gemini tidak diatur.")
        return "Fitur tidak aktif."
    
    system_instruction = (
        "Anda adalah seorang ahli prompt engineering untuk model AI text-to-image seperti Stable Diffusion. "
        "Tugas Anda adalah mengubah ide sederhana dari pengguna menjadi prompt yang kaya, deskriptif, dan artistik. "
        "Fokus pada detail visual: subjek, setting, pencahayaan, gaya seni, komposisi, dan kualitas. "
        "Hasilkan HANYA prompt-nya saja dalam format teks panjang, tanpa penjelasan atau kalimat pembuka/penutup."
    )
    yield "🧠 AI sedang meracik prompt ajaib untuk Anda..."
    enhanced_prompt = gemini_bot.chat(simple_prompt, [], system_prompt=system_instruction)
    yield enhanced_prompt

def upscale_image(image_to_upscale, clarity_strength):
    if image_to_upscale is None: raise gr.Error("Silakan unggah gambar terlebih dahulu.")
    if upscaler_model is None or upscaler_processor is None: raise gr.Error("Fitur Upscaler tidak aktif karena model gagal dimuat.")
    
    yield None, "🚀 Memproses peningkatan resolusi 4x oleh AI..."
    try:
        with torch.no_grad():
            inputs = upscaler_processor(image_to_upscale, return_tensors="pt").to(device)
            outputs = upscaler_model(**inputs)
            output_image = outputs.reconstruction.data.squeeze().float().cpu().clamp_(0, 1).numpy()
            output_image = np.moveaxis(output_image, source=0, destination=-1)
            output_image = (output_image * 255.0).round().astype(np.uint8)
            final_image = Image.fromarray(output_image)
        
        if clarity_strength > 1.0:
            yield final_image, f"✨ Menerapkan peningkatan kejernihan (Strength: {clarity_strength:.2f})..."
            enhancer = ImageEnhance.Sharpness(final_image)
            final_image = enhancer.enhance(clarity_strength)

        yield final_image, f"✅ Gambar berhasil ditingkatkan! Resolusi akhir: {final_image.width}x{final_image.height}px."
    except Exception as e:
        print(f"❌ Error saat upscaling: {e}")
        yield None, f"⚠️ Terjadi error saat upscaling: {e}"

def update_system_info():
    if not psutil or not platform: return "Informasi sistem tidak tersedia (library psutil tidak ditemukan)."
    cpu_percent = psutil.cpu_percent(interval=None)
    ram = psutil.virtual_memory()
    gpu_info = "Tidak terdeteksi (PyTorch tidak menemukan CUDA)"
    if torch.cuda.is_available():
        gpu_name = torch.cuda.get_device_name(0)
        gpu_mem_used_gb = torch.cuda.memory_allocated(0) / (1024**3)
        gpu_mem_total_gb = torch.cuda.get_device_properties(0).total_memory / (1024**3)
        gpu_info = f"GPU: {gpu_name}\nVRAM Terpakai: {gpu_mem_used_gb:.2f} GB / {gpu_mem_total_gb:.2f} GB"

    sys_info = f"**Platform:** `{platform.system()} {platform.release()}`"
    return (f"**CPU Terpakai:** `{cpu_percent:.1f}%`\n"
            f"**RAM Terpakai:** `{ram.percent:.1f}% ({ram.used / (1024**3):.2f} GB / {ram.total / (1024**3):.2f} GB)`\n"
            f"{gpu_info}\n---\n{sys_info}")

# --- FUNGSI-FUNGSI UNTUK MENU BARU & FITUR SHARE (DIPERBAIKI TOTAL) ---

def generate_random_id(length=10):
    """Menghasilkan ID acak dari huruf dan angka."""
    return ''.join(random.choices(string.ascii_lowercase + string.digits, k=length))

def share_image_history(selected_index: int, history_df: pd.DataFrame, request: gr.Request):
    """Membuat URL share untuk detail gambar."""
    if selected_index is None or history_df.empty:
        gr.Warning("Pilih gambar terlebih dahulu sebelum membagikan.")
        return gr.update(visible=False)

    try:
        selected_row = history_df.iloc[selected_index]
        base_url = "https://floodd-ai2.hf.space/" 

        share_data = {
            'prompt': selected_row['Prompt'],
            'neg': selected_row.get('NegativePrompt', ''),
            'seed': int(selected_row['Seed']),
            'steps': int(selected_row['Steps'])
        }
        
        share_id = generate_random_id()
        with open(SHARE_DATA_DIR / f"image_{share_id}.json", 'w') as f:
            json.dump(share_data, f)
            
        share_url = f"{base_url}?share_image_id={share_id}"
        
        share_content = f"✅ **URL Share Berhasil Dibuat!**\nBagikan link ini untuk mengisi ulang generator:\n\n`{share_url}`"
        return gr.update(value=share_content, visible=True)

    except Exception as e:
        print(f"❌ Error saat membuat URL share gambar: {e}")
        return gr.update(value=f"⚠️ Gagal membuat URL: {e}", visible=True)


def share_chat_history(chat_id, all_chats_history, request: gr.Request):
    """Membuat URL share untuk riwayat obrolan."""
    if not chat_id or chat_id not in all_chats_history:
        gr.Warning("Pilih obrolan yang valid untuk dibagikan.")
        return gr.update(visible=False)

    try:
        chat_to_share = all_chats_history[chat_id]
        if not chat_to_share.get('history'):
            gr.Warning("Obrolan ini kosong dan tidak bisa dibagikan.")
            return gr.update(visible=False)
            
        base_url = "https://floodd-ai2.hf.space/" 

        with open(SHARE_DATA_DIR / f"chat_{chat_id}.json", 'w') as f:
            json.dump(chat_to_share, f)
            
        share_url = f"{base_url}?share_chat_id={chat_id}"
        
        share_content = f"✅ **URL Share Berhasil Dibuat!**\nBagikan link ini untuk melihat obrolan:\n\n`{share_url}`"
        return gr.update(value=share_content, visible=True)
    except Exception as e:
        print(f"❌ Error saat membuat URL share chat: {e}")
        return gr.update(value=f"⚠️ Gagal membuat URL: {e}", visible=True)
        
def handle_shared_url(request: gr.Request):
    """Fungsi ini berjalan saat aplikasi dimuat untuk memeriksa parameter URL."""
    # Mengembalikan tuple dengan panjang yang konsisten untuk semua return path
    default_chat_return = (gr.State.IDENTITY, None, [], gr.update(), gr.update())
    default_image_return = (gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY, gr.update())

    if not request:
        return default_chat_return, default_image_return

    params = request.query_params
    
    if 'share_chat_id' in params:
        chat_id = params['share_chat_id']
        filepath = SHARE_DATA_DIR / f"chat_{chat_id}.json"
        if filepath.exists():
            print(f"✅ Memuat chat dari URL share: {chat_id}")
            with open(filepath, 'r') as f:
                shared_chat_data = json.load(f)
            initial_chat_state = {chat_id: shared_chat_data}
            chat_return = (
                initial_chat_state, 
                chat_id, 
                shared_chat_data.get('history', []), 
                gr.update(choices=[shared_chat_data.get('title', 'Obrolan Dibagikan')], value=shared_chat_data.get('title', 'Obrolan Dibagikan')),
                gr.Tabs(selected=1)
            )
            return chat_return, default_image_return
        else:
            print(f"⚠️ ID share chat tidak ditemukan: {chat_id}")

    elif 'share_image_id' in params:
        image_id = params['share_image_id']
        filepath = SHARE_DATA_DIR / f"image_{image_id}.json"
        if filepath.exists():
            print(f"✅ Memuat detail gambar dari URL share: {image_id}")
            with open(filepath, 'r') as f:
                shared_image_data = json.load(f)
            image_return = (
                shared_image_data.get('prompt', ''),
                shared_image_data.get('neg', ''),
                shared_image_data.get('seed', -1),
                shared_image_data.get('steps', 2),
                gr.Tabs(selected=0)
            )
            return default_chat_return, image_return
        else:
            print(f"⚠️ ID share gambar tidak ditemukan: {image_id}")

    return default_chat_return, default_image_return


def load_history():
    try:
        with file_lock:
            if not os.path.exists(HISTORY_LOG_FILE):
                return [], pd.DataFrame(), "### 📂 Riwayat Kosong\nBelum ada gambar yang dihasilkan."
            df = pd.read_csv(HISTORY_LOG_FILE)

        if df.empty:
            return [], df, "### 📂 Riwayat Kosong\nBelum ada gambar yang dihasilkan."

        df_sorted = df.sort_values(by="Timestamp", ascending=False)
        image_paths = [str(IMAGE_HISTORY_DIR / fname) for fname in df_sorted['Filename'] if (IMAGE_HISTORY_DIR / fname).exists()]
        return image_paths, df_sorted, "### ⓘ Detail Gambar\nKlik pada sebuah gambar untuk melihat detailnya."
    except Exception as e:
        print(f"❌ Error memuat riwayat: {e}")
        return [], pd.DataFrame(), f"### ⚠️ Error\nTidak dapat memuat riwayat: {e}"

def show_history_details(evt: gr.SelectData, history_df: pd.DataFrame):
    if not evt.selected or history_df.empty:
        return "### ⓘ Detail Gambar\nKlik gambar untuk melihat detailnya.", gr.update(visible=False), gr.update(visible=False), None

    selected_index = evt.index
    selected_row = history_df.iloc[selected_index]
    details = f"""
    **Prompt:** `{selected_row['Prompt']}`
    **Negative Prompt:** `{selected_row.get('NegativePrompt', 'N/A')}`
    ---
    **Seed:** `{selected_row['Seed']}` | **Steps:** `{selected_row['Steps']}`
    **File:** `{selected_row['Filename']}` | **Dibuat:** `{selected_row['Timestamp']}`
    """
    return details, gr.update(visible=True), gr.update(visible=False), selected_index

def send_history_to_generator(selected_index: int, history_df: pd.DataFrame):
    if selected_index is None or history_df.empty: return gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
    selected_row = history_df.iloc[selected_index]
    return ( selected_row['Prompt'], selected_row.get('NegativePrompt', ''), selected_row['Seed'], selected_row['Steps'], gr.Tabs(selected=0) )

def send_history_to_editor(selected_index: int, history_df: pd.DataFrame):
    if selected_index is None or history_df.empty: return gr.update(), gr.update()
    selected_row = history_df.iloc[selected_index]
    image_path = str(IMAGE_HISTORY_DIR / selected_row['Filename'])
    return Image.open(image_path), gr.Tabs(selected=5)

def apply_image_edits(image, brightness, contrast, saturation, sharpness, filter_choice):
    if image is None: return None
    output_image = image.copy()
    if filter_choice == "Grayscale": output_image = output_image.convert("L").convert("RGB")
    elif filter_choice == "Sepia":
        pixels = output_image.load()
        width, height = output_image.size
        for y in range(height):
            for x in range(width):
                r, g, b = output_image.getpixel((x, y))
                tr, tg, tb = int(0.393*r + 0.769*g + 0.189*b), int(0.349*r + 0.686*g + 0.168*b), int(0.272*r + 0.534*g + 0.131*b)
                pixels[x, y] = (min(255, tr), min(255, tg), min(255, tb))
    
    enhancer = ImageEnhance.Brightness(output_image); output_image = enhancer.enhance(brightness)
    enhancer = ImageEnhance.Contrast(output_image); output_image = enhancer.enhance(contrast)
    enhancer = ImageEnhance.Color(output_image); output_image = enhancer.enhance(saturation)
    enhancer = ImageEnhance.Sharpness(output_image); output_image = enhancer.enhance(sharpness)
    return output_image
    
# --- FUNGSI LOGIC CHATBOT BARU ---
def add_new_chat(all_chats_history):
    new_chat_id = str(uuid.uuid4())
    all_chats_history[new_chat_id] = {
        "title": "Percakapan Baru",
        "history": [(None, "Halo! Saya Flood, asisten AI dari RenXploit. Ada yang bisa saya bantu?")]
    }
    history_titles = [info['title'] for info in all_chats_history.values()]
    new_title = all_chats_history[new_chat_id]['title']
    
    return all_chats_history, new_chat_id, all_chats_history[new_chat_id]['history'], gr.update(choices=history_titles, value=new_title)

def handle_user_message(user_message, chat_id, all_chats_history):
    if not chat_id or chat_id not in all_chats_history:
        all_chats_history, chat_id, current_history, _ = add_new_chat({})
    
    current_history = all_chats_history[chat_id]['history']
    
    if len(current_history) == 1 and current_history[0][0] is None:
        current_history = []
        
    current_history.append((user_message, None))
    all_chats_history[chat_id]['history'] = current_history
    
    if len(current_history) == 1:
        new_title = user_message[:30] + '...' if len(user_message) > 30 else user_message
        all_chats_history[chat_id]['title'] = new_title
    
    history_titles = [info['title'] for info in all_chats_history.values()]
    
    yield all_chats_history, current_history, gr.update(choices=history_titles, value=all_chats_history[chat_id]['title']), gr.update(value=""), gr.update(visible=False)

    bot_response = gemini_bot.chat(user_message, [h for h in current_history if h[0] is not None])
    current_history[-1] = (user_message, bot_response)
    all_chats_history[chat_id]['history'] = current_history
    
    yield all_chats_history, current_history, gr.update(), gr.update(), gr.update(visible=True)

def switch_chat(selected_title, all_chats_history):
    if not selected_title: return None, [], gr.update(visible=False)
    
    selected_id = None
    for chat_id, info in all_chats_history.items():
        if info['title'] == selected_title:
            selected_id = chat_id
            break
            
    if selected_id:
        return selected_id, all_chats_history[selected_id]['history'], gr.update(visible=True)
    return None, [], gr.update(visible=False)
    

# --- ANTARMUKA PENGGUNA (GRADIO UI) ---

with gr.Blocks(theme=gr.themes.Base(), head=HEAD_HTML) as demo:
    gr.Markdown("# 🚀 RenXploit's Creative AI Suite 🌌", elem_id="main-title")
    gr.Markdown("Sebuah platform lengkap untuk kreativitas Anda, ditenagai oleh AI.", elem_id="main-subtitle")

    chat_history_state = gr.State({})
    current_chat_id_state = gr.State(None)
    selected_history_index_state = gr.State(None)
    
    with gr.Tabs() as tabs:
        with gr.TabItem("🎨 Image Generator", id=0):
            with gr.Row(variant='panel', equal_height=False):
                with gr.Column(scale=1):
                    gr.Markdown("### 📝 **Masukan Perintah Anda**")
                    prompt_input = gr.Textbox(label="Prompt", placeholder="Contoh: Cinematic photo, seekor rubah merah...", lines=3, info="Jadilah sangat spesifik! Atau gunakan Prompt Enhancer.")
                    negative_prompt_input = gr.Textbox(label="Prompt Negatif", placeholder="Contoh: blurry, low quality, bad hands...", lines=2, info="Hal-hal yang TIDAK Anda inginkan.")
                    num_images_slider = gr.Slider(minimum=1, maximum=8, value=2, step=1, label="Jumlah Gambar")
                    generate_btn = gr.Button("✨ Hasilkan Gambar!", variant="primary")
                    with gr.Accordion("⚙️ Opsi Lanjutan", open=False):
                        steps_slider = gr.Slider(minimum=1, maximum=5, value=2, step=1, label="Langkah Iterasi (Kualitas vs Kecepatan)")
                        with gr.Row():
                            seed_input = gr.Number(label="Seed", value=-1, precision=0, info="Gunakan -1 untuk acak.")
                            random_seed_btn = gr.Button("🎲 Acak", variant="secondary")
                with gr.Column(scale=2):
                    gr.Markdown("### 🖼️ **Hasil Generasi**")
                    output_gallery = gr.Gallery(label="Hasil Gambar", show_label=False, elem_id="gallery", columns=2, object_fit="contain", height="auto")
                    loader_html = gr.HTML(visible=False)
                    info_box = gr.Textbox(label="Informasi Generasi", visible=False, interactive=False, lines=2)
        
        with gr.TabItem("💬 Chat with AI", id=1):
            with gr.Row(variant='panel'):
                with gr.Column(scale=1, min_width=250) as sidebar:
                    gr.Markdown("### 🗂️ Riwayat Chat")
                    new_chat_btn = gr.Button("➕ Obrolan Baru", variant="primary")
                    with gr.Group(elem_id="chat-history-sidebar"):
                        chat_history_list = gr.Radio(label="Pilih Obrolan", choices=[], interactive=True)
                    with gr.Row(visible=False) as chat_action_buttons:
                         share_chat_btn = gr.Button("🔗 Bagikan Chat")
                    share_chat_output = gr.Textbox(label="URL untuk Dibagikan", lines=4, interactive=True, show_copy_button=True, visible=False)

                with gr.Column(scale=3):
                    gr.Markdown("### 🤖 **Asisten AI Flood**")
                    if not gemini_bot.is_configured:
                        gr.Warning("Fitur Chatbot dinonaktifkan. API Key Gemini tidak terkonfigurasi.")
                    else:
                        with gr.Column(elem_id="chatbot-container"):
                            chatbot_display = gr.Chatbot(elem_id="chatbot-display", label="Flood AI", bubble_full_width=False)
                            with gr.Row():
                                user_chat_input = gr.Textbox(show_label=False, placeholder="Ketik pesan Anda di sini...", scale=5)
                                send_chat_btn = gr.Button("Kirim", variant="secondary", scale=1)
        
        with gr.TabItem("✨ Prompt Enhancer", id=2):
            with gr.Row(variant='panel'):
                with gr.Column():
                    gr.Markdown("### 🪄 **Ubah Ide Jadi Prompt Ajaib**\nCukup tulis ide sederhana, dan biarkan AI menyempurnakannya menjadi prompt yang detail dan artistik.")
                    simple_prompt_input = gr.Textbox(label="Ide Sederhana Anda", placeholder="Contoh: seekor astronot di hutan alien", lines=3)
                    enhance_btn = gr.Button("Buat Prompt Ajaib!", variant="primary")
                    enhanced_prompt_output = gr.Textbox(label="Prompt yang Disempurnakan", lines=5, interactive=True, show_copy_button=True)
                    send_to_gen_btn = gr.Button("➡️ Kirim & Pindah ke Generator")

        with gr.TabItem("🚀 AI Image Upscaler", id=3):
            with gr.Row(variant='panel', equal_height=False):
                with gr.Column():
                    gr.Markdown("### **Tingkatkan Resolusi Gambar**\nUnggah gambar untuk meningkatkan kualitas dan ukurannya hingga 4x lipat menggunakan AI.")
                    image_to_upscale_input = gr.Image(type="pil", label="Unggah Gambar Anda di Sini")
                    clarity_slider = gr.Slider(minimum=1.0, maximum=3.0, value=1.0, step=0.1, label="Tingkat Peningkatan Kejernihan", info="Setelah di-upscale 4x, atur kejernihan gambar di sini. 1.0 = Tanpa efek.")
                    upscale_btn = gr.Button("Tingkatkan Resolusi!", variant="primary")
                with gr.Column():
                    gr.Markdown("### **Hasil Peningkatan Resolusi**")
                    upscaled_image_output = gr.Image(label="Gambar Hasil Upscale", interactive=False, show_download_button=True)
                    upscale_status_text = gr.Markdown("Status: Menunggu gambar...")

        with gr.TabItem("🖼️ Galeri & Riwayat", id=4) as history_tab:
            with gr.Row(variant='panel'):
                with gr.Column(scale=2):
                    gr.Markdown("### **Galeri Hasil Generasi Anda**")
                    history_gallery = gr.Gallery(label="Riwayat Gambar", show_label=False, columns=4, object_fit="contain", height="auto", elem_id="history_gallery")
                    history_df_state = gr.State()
                with gr.Column(scale=1):
                    gr.Markdown("### **Detail & Aksi**")
                    history_details_md = gr.Markdown("### ⓘ Detail Gambar\nKlik pada sebuah gambar untuk melihat detailnya.")
                    refresh_history_btn = gr.Button("🔄 Segarkan Galeri", variant="secondary")
                    with gr.Row(visible=False) as history_action_buttons:
                        history_to_gen_btn = gr.Button("Kirim ke Generator")
                        history_to_editor_btn = gr.Button("Kirim ke Editor")
                        share_history_btn = gr.Button("🔗 Bagikan Detail")
                    share_history_output = gr.Textbox(label="URL untuk Dibagikan", lines=4, interactive=True, show_copy_button=True, visible=False)

        with gr.TabItem("🎨 Image Editor", id=5):
            with gr.Row(variant='panel'):
                with gr.Column(scale=1):
                    gr.Markdown("### **Toolkit Pasca-Produksi**")
                    editor_input_image = gr.Image(type="pil", label="Unggah Gambar atau Kirim dari Riwayat")
                    with gr.Accordion("Penyesuaian", open=True):
                        brightness_slider = gr.Slider(minimum=0.5, maximum=1.5, value=1.0, step=0.05, label="Kecerahan")
                        contrast_slider = gr.Slider(minimum=0.5, maximum=1.5, value=1.0, step=0.05, label="Kontras")
                        saturation_slider = gr.Slider(minimum=0.0, maximum=2.0, value=1.0, step=0.05, label="Saturasi Warna")
                        sharpness_slider = gr.Slider(minimum=0.0, maximum=3.0, value=1.0, step=0.1, label="Ketajaman")
                    with gr.Accordion("Filter Cepat", open=True):
                         filter_radio = gr.Radio(["None", "Grayscale", "Sepia"], label="Pilih Filter", value="None")
                with gr.Column(scale=1):
                    gr.Markdown("### **Hasil Editing**")
                    editor_output_image = gr.Image(label="Hasil Akhir", interactive=False, show_download_button=True)

        with gr.TabItem("📊 Visitor Monitor", id=6):
            with gr.Row(variant='panel'):
                with gr.Column():
                    gr.Markdown("### 📈 **Live Visitor Monitor**\nPantau jumlah total pengunjung aplikasi Anda secara real-time.")
                    with gr.Row():
                        with gr.Column(scale=3): visitor_count_display = gr.Markdown("## 📈 Memuat data...")
                        with gr.Column(scale=2):
                            time_filter_radio = gr.Radio(["Semua Waktu", "1 Minggu Terakhir", "2 Minggu Terakhir", "3 Bulan Terakhir"], label="Tampilkan data untuk", value="Semua Waktu")
                            refresh_btn = gr.Button("🔄 Segarkan Manual", variant="secondary")
                    visitor_plot = gr.LinePlot(x="Timestamp", y="Total Pengunjung", title="Grafik Pertumbuhan Pengunjung", tooltip=['Timestamp', 'Total Pengunjung'], height=500, interactive=True)

        with gr.TabItem("⚙️ System & Settings", id=7):
            with gr.Row(variant='panel'):
                with gr.Column():
                    gr.Markdown("### **Live System Monitor**")
                    system_info_md = gr.Markdown("Memuat info sistem...")
                    system_info_trigger_btn = gr.Button("Trigger System Info", visible=False, elem_id="system-info-trigger-btn")
                with gr.Column():
                    gr.Markdown("### **Pengaturan Aplikasi**")
                    with gr.Accordion("Kualitas Model", open=True):
                        gr.Radio(["FP16 (Cepat, Kualitas Baik)", "FP32 (Lambat, Kualitas Terbaik)"], 
                                 value="FP16 (Cepat, Kualitas Baik)" if device == "cuda" else "FP32 (Lambat, Kualitas Terbaik)",
                                 label="Presisi Model Generator", interactive=False, info="Terkunci. Ditentukan saat aplikasi dimulai.")

        with gr.TabItem("💡 Panduan Prompting", id=8):
            with gr.Row(variant='panel'): gr.Markdown("""## Cara Menjadi "Art Director" yang Hebat untuk AI...\n (Konten panduan Anda di sini)""")
        with gr.TabItem("📖 Blog & Updates", id=9):
            with gr.Row(variant='panel'): gr.Markdown("""### Perkembangan Terbaru dari RenXploit's AI Suite
v3.1 (Perbaikan Share URL): Mengimplementasikan sistem share berbasis URL Query Parameter yang fungsional. Kini URL share untuk chat dan gambar dapat dibuka dan menampilkan konten yang sesuai.
v3.0 (Perbaikan Kritis): Memperbaiki bug pada fitur Share URL dan Share Detail Galeri yang disebabkan oleh perbedaan versi Gradio dan logika event yang salah.
v2.8: Mengganti komponen `gr.Box` dengan `gr.Group` untuk kompatibilitas.
v2.7: Perombakan total UI Chatbot dengan fitur riwayat, new chat, dan share.""")
        with gr.TabItem("ℹ️ About & Support", id=10):
            with gr.Row(variant='panel'):
                with gr.Column():
                    gr.Markdown("### Tentang Proyek dan Dukungan")
                    with gr.Accordion("Tentang RenXploit's Creative AI Suite", open=True):
                        gr.Markdown("""
                        RenXploit's Creative AI Suite adalah proyek pribadi untuk mengeksplorasi AI generatif.
                        Hubungi saya melalui: ngoprek.xyz/contact
                        """)
                    with gr.Accordion("Laporkan Masalah atau Beri Masukan"):
                        report_name = gr.Textbox(label="Nama Anda")
                        report_email = gr.Textbox(label="Email Anda (Opsional)")
                        report_message = gr.Textbox(label="Pesan Anda", lines=5, placeholder="Jelaskan masalah atau ide Anda...")
                        report_btn = gr.Button("Kirim Laporan", variant="primary")
                        report_status = gr.Markdown(visible=False)

    gr.Markdown("---\n<div class='footer'><p>Dibuat dengan ❤️ oleh <b>RenXploit</b>.</p></div>", elem_classes="footer")

    # --- PENANGANAN EVENT (EVENT HANDLERS DENGAN PERBAIKAN) ---
    
    # Kumpulan output untuk URL handler
    shared_chat_outputs = [chat_history_state, current_chat_id_state, chatbot_display, chat_history_list, tabs]
    shared_image_outputs = [prompt_input, negative_prompt_input, seed_input, steps_slider, tabs]

    @demo.load
    def process_url_and_init(request: gr.Request, current_chat_state):
        chat_return, image_return = handle_shared_url(request)

        # Cek apakah URL share chat diproses
        if chat_return[1] is not None: # Cek chat_id
            # Nilai-nilai ini akan mengisi komponen chat
            return chat_return + (gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY, gr.update())
        
        # Cek apakah URL share image diproses
        elif image_return[0] != gr.State.IDENTITY: # Cek prompt
            # Jika tidak ada share chat, inisialisasi chat default
            new_chat_state, new_chat_id, new_history, chat_list_update = add_new_chat({})
            return (new_chat_state, new_chat_id, new_history, chat_list_update, image_return[4]) + image_return[:-1]

        # Jika tidak ada URL share sama sekali, inisialisasi chat
        elif not current_chat_state:
            new_chat_state, new_chat_id, new_history, chat_list_update = add_new_chat({})
            return (new_chat_state, new_chat_id, new_history, chat_list_update, gr.update()) + (gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY, gr.State.IDENTITY)

        # Jika state sudah ada dan tidak ada URL, jangan lakukan apa-apa
        return (gr.State.IDENTITY,) * len(shared_chat_outputs + shared_image_outputs)

    demo.load(log_visitor, inputs=None, outputs=None)
    demo.load(fn=update_system_info, inputs=None, outputs=system_info_md)
    
    random_seed_btn.click(lambda: -1, outputs=seed_input)
    generate_btn.click(fn=genie_wrapper, inputs=[prompt_input, negative_prompt_input, steps_slider, seed_input, num_images_slider], outputs=[output_gallery, loader_html, generate_btn, info_box])
    
    new_chat_btn.click(fn=add_new_chat, inputs=[chat_history_state], outputs=[chat_history_state, current_chat_id_state, chatbot_display, chat_history_list])
    
    send_chat_btn.click(fn=handle_user_message, inputs=[user_chat_input, current_chat_id_state, chat_history_state], outputs=[chat_history_state, chatbot_display, chat_history_list, user_chat_input, chat_action_buttons])
    user_chat_input.submit(fn=handle_user_message, inputs=[user_chat_input, current_chat_id_state, chat_history_state], outputs=[chat_history_state, chatbot_display, chat_history_list, user_chat_input, chat_action_buttons])
    chat_history_list.change(fn=switch_chat, inputs=[chat_history_list, chat_history_state], outputs=[current_chat_id_state, chatbot_display, chat_action_buttons])
    
    share_chat_btn.click(fn=share_chat_history, inputs=[current_chat_id_state, chat_history_state], outputs=[share_chat_output])

    enhance_btn.click(fn=enhance_prompt, inputs=[simple_prompt_input], outputs=[enhanced_prompt_output])
    send_to_gen_btn.click(fn=lambda prompt: (prompt, gr.Tabs(selected=0)), inputs=[enhanced_prompt_output], outputs=[prompt_input, tabs])
    upscale_btn.click(fn=upscale_image, inputs=[image_to_upscale_input, clarity_slider], outputs=[upscaled_image_output, upscale_status_text])
    
    history_tab.select(fn=load_history, inputs=None, outputs=[history_gallery, history_df_state, history_details_md])
    refresh_history_btn.click(fn=load_history, inputs=None, outputs=[history_gallery, history_df_state, history_details_md])
    
    history_gallery.select(fn=show_history_details, inputs=[history_df_state], outputs=[history_details_md, history_action_buttons, share_history_output, selected_history_index_state])
    history_to_gen_btn.click(fn=send_history_to_generator, inputs=[selected_history_index_state, history_df_state], outputs=[prompt_input, negative_prompt_input, seed_input, steps_slider, tabs])
    history_to_editor_btn.click(fn=send_history_to_editor, inputs=[selected_history_index_state, history_df_state], outputs=[editor_input_image, tabs])
    
    share_history_btn.click(fn=share_image_history, inputs=[selected_history_index_state, history_df_state], outputs=[share_history_output])

    editor_inputs = [editor_input_image, brightness_slider, contrast_slider, saturation_slider, sharpness_slider, filter_radio]
    for slider in [brightness_slider, contrast_slider, saturation_slider, sharpness_slider]:
        slider.release(fn=apply_image_edits, inputs=editor_inputs, outputs=editor_output_image)
    filter_radio.change(fn=apply_image_edits, inputs=editor_inputs, outputs=editor_output_image)
    editor_input_image.change(fn=apply_image_edits, inputs=editor_inputs, outputs=editor_output_image)

    demo.load(fn=update_visitor_monitor, inputs=[time_filter_radio], outputs=[visitor_count_display, visitor_plot])
    refresh_btn.click(fn=update_visitor_monitor, inputs=[time_filter_radio], outputs=[visitor_count_display, visitor_plot])
    time_filter_radio.change(fn=update_visitor_monitor, inputs=[time_filter_radio], outputs=[visitor_count_display, visitor_plot])
    
    system_info_trigger_btn.click(fn=update_system_info, inputs=None, outputs=system_info_md)
    
    report_btn.click(fn=submit_report, inputs=[report_name, report_email, report_message], outputs=[report_status])

# --- Menjalankan Aplikasi ---

if __name__ == "__main__":
    demo.launch(debug=True)