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import gradio as gr |
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import torch |
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import numpy as np |
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from diffusers import DiffusionPipeline |
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import random |
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import time |
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import os |
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from datetime import datetime, timedelta |
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import csv |
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import pandas as pd |
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import threading |
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from PIL import Image, ImageEnhance |
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from pathlib import Path |
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try: |
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import psutil |
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import platform |
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from transformers import Swin2SRForImageSuperResolution, Swin2SRImageProcessor |
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print("✅ Library tambahan (psutil, transformers) berhasil diimpor.") |
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except ImportError: |
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print("❌ Peringatan: Library 'psutil' atau 'transformers' tidak ditemukan. Fitur System Monitor & Upscaler tidak akan berfungsi.") |
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psutil = None |
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platform = None |
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Swin2SRForImageSuperResolution = None |
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Swin2SRImageProcessor = None |
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try: |
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import google.generativeai as genai |
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print("✅ Library 'google-generativeai' berhasil diimpor.") |
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except ImportError: |
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print("❌ Peringatan: Library 'google-generativeai' tidak ditemukan. Fitur Chatbot & Prompt Enhancer tidak akan berfungsi.") |
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genai = None |
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HEAD_HTML = """ |
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<head> |
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<meta charset="UTF-8"> |
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<meta name="viewport" content="width=device-width, initial-scale=1.0"> |
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<title>RenXploit's Creative AI Suite</title> |
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<link rel="preconnect" href="https: |
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin> |
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<link href="https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&family=Fira+Code:wght@500&display=swap" rel="stylesheet"> |
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<script> |
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function typewriterEffect(element, text, speed) { |
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let i = 0; |
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element.innerHTML = ""; |
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const cursor = document.createElement('span'); |
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cursor.className = 'typewriter-cursor'; |
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cursor.innerHTML = '|'; |
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element.appendChild(cursor); |
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function type() { |
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if (i < text.length) { |
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element.insertBefore(document.createTextNode(text.charAt(i)), cursor); |
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i++; |
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setTimeout(type, speed); |
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} else { |
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cursor.style.animation = 'blink 1s step-end infinite'; |
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} |
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} |
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type(); |
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} |
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document.addEventListener("DOMContentLoaded", function(event) { |
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const titleElement = document.querySelector('#main-title h1'); |
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if (titleElement) { |
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const titleText = "🚀 RenXploit's Creative AI Suite 🌌"; |
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titleElement.textContent = ""; |
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setTimeout(() => typewriterEffect(titleElement, titleText, 50), 500); |
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} |
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setInterval(() => { |
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const triggerButton = document.querySelector('#system-info-trigger-btn button'); |
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if (triggerButton) { |
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triggerButton.click(); |
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} |
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}, 5000); |
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}); |
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</script> |
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<style> |
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:root { --primary-color: |
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body, .gradio-container { font-family: var(--font-family-main); background-color: var(--background-color) !important; color: var(--text-color); } |
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h1, h2, h3 { color: |
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@keyframes blink { from, to { opacity: 1 } 50% { opacity: 0 } } |
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.gradio-tabs { border: none !important; background-color: transparent !important; margin-bottom: 1.5rem; } |
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.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; } |
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.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; } |
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.gradio-tabs > div[role="tablist"] > button:hover { background-color: var(--content-background-color) !important; color: var(--primary-color) !important; } |
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.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; } |
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.tabitem { background-color: transparent !important; border: none !important; padding: 0 !important; } |
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.gradio-row.panel, .gradio-accordion { 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); } |
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.gradio-accordion { margin-top: 1rem; } |
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.gradio-button.primary { background: linear-gradient(90deg, var(--primary-color), |
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.gradio-button.primary:hover { transform: translateY(-2px); box-shadow: var(--shadow-strong); } |
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.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; } |
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.gradio-button.secondary:hover { background-color: var(--primary-color) !important; color: |
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.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; } |
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.gradio-textbox textarea, .gradio-number input { color: var(--text-color) !important; } |
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.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); } |
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div.info { color: var(--text-muted-color) !important; font-style: italic; } |
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.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; } |
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.loader-text { font-family: var(--font-family-mono); font-size: 1.1em; color: var(--primary-color); margin-bottom: 20px; } |
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.loader-bar-container { height: 8px; background: var(--background-color); border-radius: 4px; overflow: hidden; } |
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.loader-bar { width: 100%; height: 100%; background: linear-gradient(90deg, transparent, var(--primary-color), transparent); background-size: 200% 100%; animation: scan 2s linear infinite; } |
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@keyframes scan { 0% { background-position: 200% 0; } 100% { background-position: -200% 0; } } |
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.gradio-chatbot .message { border-radius: 12px !important; box-shadow: none !important; } |
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.gradio-chatbot .user { background-color: var(--primary-color) !important; color: white !important; } |
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.gradio-chatbot .bot { background-color: var(--content-background-color) !important; border: 1px solid var(--border-color) !important; } |
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.footer { text-align: center; margin: 2rem auto; padding: 1rem; color: var(--text-muted-color); border-top: 1px solid var(--border-color); } |
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.footer b { color: var(--primary-color); } |
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</style> |
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</head> |
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""" |
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# --- PENGATURAN & LOGIC GLOBAL --- |
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VISITOR_LOG_FILE = "visitor_log.csv" |
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HISTORY_LOG_FILE = "generation_log.csv" |
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IMAGE_HISTORY_DIR = Path("generated_images") |
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file_lock = threading.Lock() |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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print(f"➡️ Menggunakan device: {device.upper()}") |
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# --- Inisialisasi File Log & Direktori --- |
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def initialize_environment(): |
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if not os.path.exists(VISITOR_LOG_FILE): |
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with file_lock: |
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if not os.path.exists(VISITOR_LOG_FILE): |
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with open(VISITOR_LOG_FILE, mode='w', newline='', encoding='utf-8') as f: |
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writer = csv.writer(f) |
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writer.writerow(["Timestamp", "IP Address", "User Agent"]) |
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print(f"✅ File log '{VISITOR_LOG_FILE}' berhasil dibuat.") |
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IMAGE_HISTORY_DIR.mkdir(exist_ok=True) |
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if not os.path.exists(HISTORY_LOG_FILE): |
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with file_lock: |
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if not os.path.exists(HISTORY_LOG_FILE): |
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with open(HISTORY_LOG_FILE, mode='w', newline='', encoding='utf-8') as f: |
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writer = csv.writer(f) |
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writer.writerow(["Timestamp", "Filename", "Prompt", "NegativePrompt", "Seed", "Steps"]) |
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print(f"✅ File log riwayat '{HISTORY_LOG_FILE}' dan direktori '{IMAGE_HISTORY_DIR}' siap.") |
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initialize_environment() |
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# --- PEMUATAN MODEL-MODEL AI --- |
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print("➡️ Memuat model SDXL-Turbo...") |
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pipe = DiffusionPipeline.from_pretrained( |
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"stabilityai/sdxl-turbo", torch_dtype=torch.float16 if device == "cuda" else torch.float32, |
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variant="fp16" if device == "cuda" else None, use_safetensors=True |
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).to(device) |
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if torch.cuda.is_available(): pipe.enable_xformers_memory_efficient_attention() |
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print("✅ Model SDXL-Turbo berhasil dimuat.") |
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upscaler_model = None |
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upscaler_processor = None |
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if Swin2SRForImageSuperResolution: |
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try: |
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print("➡️ Memuat model AI Upscaler (Swin2SR)...") |
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upscaler_model = Swin2SRForImageSuperResolution.from_pretrained("caidas/swin2sr-realworld-sr-x4-64-bsrgan-psnr").to(device) |
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upscaler_processor = Swin2SRImageProcessor.from_pretrained("caidas/swin2sr-realworld-sr-x4-64-bsrgan-psnr") |
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print("✅ Model AI Upscaler berhasil dimuat.") |
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except Exception as e: |
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print(f"❌ Gagal memuat model Upscaler: {e}. Fitur upscale akan dinonaktifkan.") |
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# --- KELAS UNTUK CHATBOT GEMINI --- |
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class GeminiChat: |
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def __init__(self): |
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self.api_keys = [] |
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self.is_configured = False |
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if not genai: return |
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i = 1 |
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while True: |
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key = os.getenv(f"GEMINI_API_KEY_{i}") |
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if key: |
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self.api_keys.append(key) |
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i += 1 |
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else: |
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break |
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if self.api_keys: |
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print(f"✅ Berhasil memuat {len(self.api_keys)} API Key Gemini. Sistem rotasi aktif.") |
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self.is_configured = True |
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else: |
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print("❌ PERINGATAN: Tidak ada API Key Gemini yang ditemukan. Fitur AI Chat & Prompt Enhancer tidak akan berfungsi.") |
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def chat(self, message, history, system_prompt=None): |
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if not self.is_configured: |
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return "Maaf, fitur ini tidak terkonfigurasi karena tidak ada API Key." |
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try: |
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selected_key = random.choice(self.api_keys) |
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genai.configure(api_key=selected_key) |
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model = genai.GenerativeModel('gemini-2.5-flash') |
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full_prompt = message |
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if system_prompt: |
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full_prompt = f"{system_prompt}\n\nUser query: {message}" |
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response = model.generate_content(full_prompt) |
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return response.text |
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except Exception as e: |
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print(f"❌ Terjadi error pada API Key Gemini: {e}") |
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return "Terjadi kesalahan saat menghubungi API AI. Mungkin salah satu API Key tidak valid atau ada masalah jaringan. Silakan coba lagi." |
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gemini_bot = GeminiChat() |
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# --- FUNGSI-FUNGSI INTI (GENERATOR & LAINNYA) --- |
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def log_visitor(request: gr.Request): |
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timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S") |
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ip_address = request.client.host if request else "N/A" |
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user_agent = request.headers.get("user-agent", "Unknown") if request else "N/A" |
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with file_lock: |
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with open(VISITOR_LOG_FILE, mode='a', newline='', encoding='utf-8') as f: |
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writer = csv.writer(f) |
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writer.writerow([timestamp, ip_address, user_agent]) |
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print(f"✅ Pengunjung baru tercatat: IP {ip_address}") |
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def generate_images(prompt, negative_prompt, steps, seed, num_images): |
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if not prompt: |
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raise gr.Error("Prompt tidak boleh kosong!") |
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if seed == -1: |
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seed = random.randint(0, 2**32 - 1) |
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generator = torch.manual_seed(seed) |
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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 |
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return images, seed |
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def genie_wrapper(prompt, negative_prompt, steps, seed, num_images): |
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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) |
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start_time = time.time() |
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images, used_seed = generate_images(prompt, negative_prompt, int(steps), int(seed), int(num_images)) |
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end_time = time.time() |
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timestamp_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S") |
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for i, img in enumerate(images): |
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filename = f"{int(time.time())}_{used_seed}_{i}.png" # Add seed to filename |
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filepath = IMAGE_HISTORY_DIR / filename |
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img.save(filepath) |
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with file_lock: |
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with open(HISTORY_LOG_FILE, mode='a', newline='', encoding='utf-8') as f: |
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writer = csv.writer(f) |
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writer.writerow([timestamp_str, filename, prompt, negative_prompt, used_seed, int(steps)]) |
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generation_time = end_time - start_time |
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info_text = f"Seed yang digunakan: {used_seed}\nTotal waktu generasi: {generation_time:.2f} detik" |
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yield gr.update(value=images, visible=True), gr.update(visible=False), gr.update(interactive=True), gr.update(value=info_text, visible=True) |
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def submit_report(name, email, message): |
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if not name or not message: |
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gr.Warning("Nama dan Pesan tidak boleh kosong!") |
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return gr.update(visible=False) |
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report_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S") |
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report_content = f"--- Laporan Baru ({report_time}) ---\nNama: {name}\nEmail: {email}\nPesan: {message}\n\n" |
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with open("reports.log", "a", encoding="utf-8") as f: |
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f.write(report_content) |
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print("✅ Laporan baru telah disimpan ke reports.log") |
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return gr.update(value="✅ Terima kasih! Laporan Anda telah kami terima.", visible=True) |
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def update_visitor_monitor(time_filter: str): |
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try: |
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with file_lock: |
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if not os.path.exists(VISITOR_LOG_FILE) or os.path.getsize(VISITOR_LOG_FILE) < 10: |
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return " |
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df = pd.read_csv(VISITOR_LOG_FILE) |
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if df.empty: return "## 📈 0", pd.DataFrame({"Timestamp": [], "Total Pengunjung": []}) |
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df['Timestamp'] = pd.to_datetime(df['Timestamp'], errors='coerce') |
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df.dropna(subset=['Timestamp'], inplace=True) |
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if df.empty: return "## 📈 0", pd.DataFrame({"Timestamp": [], "Total Pengunjung": []}) |
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total_overall_visitors = len(df) |
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total_visitors_formatted = f"## 📈 {total_overall_visitors:,}" |
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df['Total Pengunjung'] = np.arange(1, len(df) + 1) |
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now = pd.to_datetime('now', utc=True).tz_localize(None) |
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df['Timestamp'] = df['Timestamp'].dt.tz_localize(None) |
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if time_filter == "1 Minggu Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(weeks=1)] |
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elif time_filter == "2 Minggu Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(weeks=2)] |
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elif time_filter == "3 Bulan Terakhir": df_plot = df[df['Timestamp'] >= now - timedelta(days=90)] |
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else: df_plot = df |
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if df_plot.empty: return total_visitors_formatted, pd.DataFrame({"Timestamp": [], "Total Pengunjung": []}) |
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return total_visitors_formatted, df_plot |
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except Exception as e: |
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error_message = f"Error saat memperbarui monitor: {e}" |
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print(f"❌ {error_message}") |
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return f"## ⚠️ Error", pd.DataFrame({"Error": [error_message]}) |
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|
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def enhance_prompt(simple_prompt): |
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if not simple_prompt: |
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gr.Warning("Tolong masukkan ide Anda terlebih dahulu.") |
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return "" |
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|
if not gemini_bot.is_configured: |
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|
gr.Error("Fitur Prompt Enhancer tidak aktif karena API Key Gemini tidak diatur.") |
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return "Fitur tidak aktif." |
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|
|
|
|
system_instruction = ( |
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"Anda adalah seorang ahli prompt engineering untuk model AI text-to-image seperti Stable Diffusion. " |
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|
"Tugas Anda adalah mengubah ide sederhana dari pengguna menjadi prompt yang kaya, deskriptif, dan artistik. " |
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"Fokus pada detail visual: subjek, setting, pencahayaan (cinematic lighting, soft light, dll), gaya seni (photorealistic, anime style, oil painting, dll), komposisi, dan kualitas (hyperdetailed, 4K, masterpiece, trending on artstation). " |
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"Hasilkan HANYA prompt-nya saja dalam format teks panjang, tanpa penjelasan atau kalimat pembuka/penutup." |
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) |
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yield "🧠 AI sedang meracik prompt ajaib untuk Anda..." |
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|
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: |
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|
raise gr.Error("Silakan unggah gambar terlebih dahulu.") |
|
|
if upscaler_model is None or upscaler_processor is None: |
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|
raise gr.Error("Fitur Upscaler tidak aktif karena model gagal dimuat. Periksa log saat startup.") |
|
|
|
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yield None, "🚀 Memproses peningkatan resolusi 4x oleh AI..." |
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|
try: |
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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) |
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|
output_image = (output_image * 255.0).round().astype(np.uint8) |
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|
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) |
|
|
|
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yield final_image, f"✅ Gambar berhasil ditingkatkan! Resolusi akhir: {final_image.width}x{final_image.height}px." |
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|
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}`\n**VRAM 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}") |
|
|
|
|
|
|
|
|
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 pada sebuah gambar untuk melihat detailnya.", gr.update(visible=False) |
|
|
|
|
|
selected_row = history_df.iloc[evt.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) |
|
|
|
|
|
def send_history_to_generator(evt: gr.SelectData, history_df: pd.DataFrame): |
|
|
if not evt.selected or history_df.empty: |
|
|
return gr.update(), gr.update(), gr.update(), gr.update(), gr.update() |
|
|
|
|
|
selected_row = history_df.iloc[evt.index] |
|
|
return ( |
|
|
selected_row['Prompt'], |
|
|
selected_row.get('NegativePrompt', ''), |
|
|
selected_row['Seed'], |
|
|
selected_row['Steps'], |
|
|
gr.Tabs(selected=0) |
|
|
) |
|
|
|
|
|
def send_history_to_editor(evt: gr.SelectData, history_df: pd.DataFrame): |
|
|
if not evt.selected or history_df.empty: |
|
|
return gr.update(), gr.update() |
|
|
|
|
|
selected_row = history_df.iloc[evt.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 |
|
|
|
|
|
|
|
|
|
|
|
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") |
|
|
|
|
|
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(): |
|
|
gr.Markdown("### 🤖 **Asisten AI Flood**") |
|
|
if not gemini_bot.is_configured: |
|
|
gr.Warning("Fitur Chatbot dinonaktifkan. API Key Gemini tidak terkonfigurasi.") |
|
|
else: |
|
|
gr.ChatInterface( |
|
|
gemini_bot.chat, |
|
|
chatbot=gr.Chatbot(height=500, label="Flood AI", value=[(None, "Halo! Saya adalah asisten AI dari RenXploit. Ada yang bisa saya bantu?")]), |
|
|
title=None, |
|
|
description="Tanyakan apa saja!", |
|
|
examples=["Apa itu SDXL-Turbo?", "Buatkan saya puisi tentang AI", "Jelaskan konsep lubang hitam dengan sederhana"], |
|
|
) |
|
|
|
|
|
|
|
|
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") |
|
|
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") |
|
|
|
|
|
|
|
|
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. Pengaturan ini ditentukan saat aplikasi dimulai berdasarkan ketersediaan GPU Anda.") |
|
|
|
|
|
|
|
|
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 |
|
|
- **v2.5 (Pembaruan Terkini):** Menambahkan **Galeri & Riwayat Generasi** dan **Image Editor** untuk pasca-produksi. |
|
|
- **v2.4:** Upscaler di-upgrade dengan kontrol kejernihan, Visitor Monitor diperbaiki, dan UI Settings diperjelas. |
|
|
- **v2.3:** Perbaikan bug kritis untuk kompatibilitas dengan berbagai versi Gradio. |
|
|
- **v2.2:** Perbaikan bug untuk kompatibilitas Gradio. |
|
|
- **v2.1:** Menambahkan **Prompt Enhancer**, **AI Image Upscaler**, dan **Live System Monitor**. |
|
|
- **v2.0:** Perombakan Desain Total. |
|
|
- **Rencana Berikutnya:** Menjajaki model generator gambar yang berbeda dan fitur Inpainting/Outpainting. Nantikan!""") |
|
|
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 yang dibuat untuk mengeksplorasi kemampuan AI generatif dalam sebuah antarmuka yang mudah digunakan dan profesional. |
|
|
Aplikasi ini terus dikembangkan dengan fitur-fitur baru untuk memberdayakan kreativitas Anda. |
|
|
|
|
|
Jika Anda memiliki masukan, menemukan bug, atau ingin berdiskusi, jangan ragu untuk menghubungi saya melalui website portofolio di: **[ngoprek.xyz/contact](https://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 yang Anda temui atau ide yang Anda miliki...") |
|
|
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") |
|
|
|
|
|
|
|
|
|
|
|
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]) |
|
|
report_btn.click(fn=submit_report, inputs=[report_name, report_email, report_message], outputs=[report_status]) |
|
|
|
|
|
|
|
|
demo.load(log_visitor, inputs=None, outputs=None) |
|
|
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]) |
|
|
|
|
|
|
|
|
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]) |
|
|
|
|
|
system_info_trigger_btn.click(fn=update_system_info, inputs=None, outputs=system_info_md) |
|
|
demo.load(fn=update_system_info, inputs=None, outputs=system_info_md) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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]) |
|
|
history_to_gen_btn.click(fn=send_history_to_generator, inputs=[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=[history_df_state], outputs=[editor_input_image, tabs]) |
|
|
|
|
|
|
|
|
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) |
|
|
|
|
|
|
|
|
if __name__ == "__main__": |
|
|
demo.launch(debug=True) |
