app.py(backup1)

import gradio as gr
import torch
import numpy as np
from diffusers import DiffusionPipeline
import random
import time
import os

try:
    import google.generativeai as genai
    print("✅ Library 'google-generativeai' berhasil diimpor.")
except ImportError:
    print("❌ Peringatan: Library 'google-generativeai' tidak ditemukan.")
    genai = None

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. Sistem rotasi aktif.")
            self.is_configured = True
        else:
            print("❌ PERINGATAN: Tidak ada API Key Gemini yang ditemukan di Secrets.")

    def chat(self, message, history):
        if not self.is_configured: return "Maaf, chatbot tidak terkonfigurasi."
        try:
            selected_key = random.choice(self.api_keys)
            genai.configure(api_key=selected_key)
            model = genai.GenerativeModel('gemini-2.5-flash')
            chat_session = model.start_chat(history=[])
            response = chat_session.send_message(message)
            return response.text
        except Exception as e:
            print(f"❌ Terjadi error pada salah satu API Key: {e}")
            return "Terjadi kesalahan saat menghubungi API Gemini. Silakan coba lagi."

gemini_bot = GeminiChat()

device = "cuda" if torch.cuda.is_available() else "cpu"
print(f"➡️ Menggunakan device untuk generator gambar: {device.upper()}")
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()
    
def generate_images(prompt, negative_prompt, steps, seed, num_images):
    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), gr.update(interactive=False), gr.update(visible=False)

    start_time = time.time()
    
    for i in range(20): # Loop singkat untuk animasi awal
        elapsed_time = time.time() - start_time
        loader_html_content = f"""
        <div class="loader-container">
            <div class="loader-bar"></div>
            <p class="loader-text">Mempersiapkan model... Waktu berlalu: {elapsed_time:.2f} detik</p>
        </div>
        """
        yield gr.update(), gr.update(value=loader_html_content), gr.update(), gr.update()
        time.sleep(0.1) # Jeda kecil untuk membuat animasi terlihat

    images, used_seed = generate_images(prompt, negative_prompt, steps, int(seed), int(num_images))
    end_time = time.time()
    
    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):
    print(f"Laporan Diterima:\nNama: {name}\nEmail: {email}\nPesan: {message}")
    return gr.update(value="✅ Terima kasih! Laporan Anda telah kami terima.", visible=True)

CUSTOM_CSS = """
.loader-container { border: 1px solid #333; border-radius: 8px; padding: 20px; background-color: #1a1a1a; text-align: center; overflow: hidden; position: relative; }
.loader-text { font-family: 'monospace'; font-size: 1.1em; color: #00ff99; text-shadow: 0 0 5px #00ff99; }
.loader-bar { position: absolute; top: 0; left: -10%; width: 10%; height: 100%; background: linear-gradient(90deg, transparent, rgba(0, 255, 153, 0.5), transparent); animation: scan 2s linear infinite; }
@keyframes scan { 0% { left: -10%; } 100% { left: 100%; } }
.footer { text-align: center; margin: 2rem auto; }
"""

with gr.Blocks(theme=gr.themes.Monochrome(), css=CUSTOM_CSS) as demo:
    gr.Markdown("# 🚀 RenXploit's Creative AI Suite 🌌\nSebuah platform lengkap untuk kreativitas Anda, ditenagai oleh AI.")
    
    with gr.Tabs():
        with gr.TabItem("🎨 Image Generator", id=0):
            with gr.Row(variant='panel'):
                with gr.Column(scale=1):
                    gr.Markdown("### 📝 Masukkan Perintah Anda")
                    prompt_input = gr.Textbox(label="Prompt", placeholder="Contoh: Cinematic photo, seekor rubah merah...", lines=3, info="Jadilah sangat spesifik! Semakin detail, semakin akurat hasilnya.")
                    negative_prompt_input = gr.Textbox(label="Prompt Negatif", placeholder="Contoh: blurry, low quality...", lines=2, info="Masukkan hal-hal yang TIDAK Anda inginkan di gambar.")
                    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")
                        with gr.Row():
                            seed_input = gr.Number(label="Seed", value=-1, precision=0, info="Gunakan -1 untuk acak.")
                            random_seed_btn = gr.Button("🎲 Acak")
                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)
        
        with gr.TabItem("💡 Panduan Prompting", id=1):
            gr.Markdown("## Cara Menjadi \"Art Director\" yang Hebat untuk AI\n...")
        with gr.TabItem("💬 Chat with AI", id=2):
            gr.Markdown("### 🤖 Asisten AI Flood\nTanyakan apa saja!")
            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, bubble_full_width=False, value=[[None, "Halo! Saya adalah asisten AI dari RenXploit. Ada yang bisa saya bantu?"]]))
        with gr.TabItem("📖 Blog & Updates", id=3):
            gr.Markdown("### Perkembangan Terbaru dari RenXploit's AI Suite\n...")
        with gr.TabItem("ℹ️ About & Support", id=4):
            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 ...")
            with gr.Accordion("Laporkan Masalah atau Beri Masukan"):
                report_name = gr.Textbox(label="Nama Anda")
                report_email = gr.Textbox(label="Email Anda")
                report_message = gr.Textbox(label="Pesan Anda", lines=5)
                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.launch()