app.py

import gradio as gr
import subprocess
import json
import os
import requests
import urllib.parse
import time
from huggingface_hub import HfApi, InferenceClient

HF_TOKEN = os.getenv("HF_WRITE_TOKEN")
api = HfApi(token=HF_TOKEN)
DATASET_ID = "oviet711/render-factory"

def generate_ai_image(keyword, chunk_id):
    print(f"🎨 [TIER 1] Meminta Visual dari Pollinations: {keyword}")
    encoded_prompt = urllib.parse.quote(f"cinematic photography, ultra realistic, highly detailed, {keyword}, dark moody lighting, vertical")
    url = f"https://image.pollinations.ai/prompt/{encoded_prompt}?width=1080&height=1920&nologo=true"
    
    # TIER 1: Coba Pollinations AI
    for attempt in range(2):
        try:
            response = requests.get(url, stream=True, timeout=10)
            if response.status_code == 200:
                bg_filename = f"bg_{chunk_id}.png"
                with open(bg_filename, 'wb') as f:
                    for chunk in response.iter_content(1024):
                        f.write(chunk)
                return bg_filename
        except Exception as e:
            print(f"⚠️ Pollinations batuk (Percobaan {attempt+1}): {e}")
            time.sleep(1)
            
    # TIER 2: Jika Pollinations Mati, otomatis pakai Hugging Face FLUX
    print("🔄 [TIER 2] Beralih ke Hugging Face FLUX API...")
    try:
        client = InferenceClient(model="black-forest-labs/FLUX.1-schnell", token=HF_TOKEN)
        prompt = f"cinematic shot, photorealistic, vertical 9:16, {keyword}, dark and moody lighting, masterpiece"
        image = client.text_to_image(prompt)
        bg_filename = f"bg_{chunk_id}.png"
        image.save(bg_filename)
        return bg_filename
    except Exception as e:
        print(f"⚠️ TIER 2 Gagal (Server HF Penuh): {e}")
        
    # TIER 3: Jika semua gagal, return None (FFmpeg akan buat layar hitam)
    return None


# HAPUS BARIS INI: import spaces (di bagian atas file)
# HAPUS BARIS INI: @spaces.GPU

def render_worker(json_data):
    try:
        data = json.loads(json_data)
        chunk_id = data.get('chunk_id', '000')
        text = data.get('text', 'Teks kosong')
        keyword = data.get('keyword', 'fresh juice')
        
        # ... (Sisa kode di bawahnya tetap sama persis, jangan diubah) ...
        
        # LOGIKA DINAMIS: Kamera & Warna berganti berdasarkan ID potongan
        cid = int(chunk_id)
        
        # 1. Rotasi Efek Kamera (Zoompan)
        camera_effects = [
            "zoompan=z='min(zoom+0.0015,1.15)':d=500:s=1080x1920", # Maju perlahan ke tengah
            "zoompan=z='min(zoom+0.0015,1.15)':y='0':d=500:s=1080x1920", # Maju perlahan ke atas
            "zoompan=z='min(zoom+0.0015,1.15)':y='ih':d=500:s=1080x1920" # Maju perlahan ke bawah
        ]
        selected_camera = camera_effects[cid % len(camera_effects)]
        
        # 2. Rotasi Warna Subtitle (Format BGR: Kuning, Cyan, Putih)
        text_colors = ["&H00FFFF", "&HFFFF00", "&HFFFFFF"]
        selected_color = text_colors[cid % len(text_colors)]
        
        # Audio
        audio_file = f"audio_{chunk_id}.mp3"
        vtt_file = f"sub_{chunk_id}.vtt"
        subprocess.run([
            "edge-tts", "--voice", "id-ID-GadisNeural", "--rate", "+15%", 
            "--text", text, "--write-media", audio_file, "--write-subtitles", vtt_file
        ], check=True)
        
        # Visual
        bg_image = generate_ai_image(keyword, chunk_id)
        output_filename = f"chunk_{chunk_id}.mp4"
        
        if bg_image:
            cmd = [
                "ffmpeg", "-y",
                "-loop", "1", "-framerate", "30",
                "-i", bg_image,
                "-i", audio_file,
                # Memasukkan Kamera Dinamis dan Warna Dinamis!
                "-vf", f"scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920,setsar=1:1,{selected_camera},subtitles={vtt_file}:force_style='FontSize=20,PrimaryColour={selected_color},OutlineColour=&H000000,BorderStyle=1,Outline=2,Shadow=1,Alignment=2,MarginV=450'",
                "-c:v", "libx264", "-c:a", "aac",
                "-shortest", "-pix_fmt", "yuv420p", output_filename
            ]
        else:
            cmd = [
                "ffmpeg", "-y",
                "-f", "lavfi", "-i", "color=c=black:s=1080x1920:d=30",
                "-i", audio_file,
                "-vf", f"subtitles={vtt_file}:force_style='FontSize=20,PrimaryColour={selected_color},OutlineColour=&H000000,BorderStyle=1,Outline=2,Shadow=1,Alignment=2,MarginV=450'",
                "-c:v", "libx264", "-c:a", "aac",
                "-shortest", output_filename
            ]
            
        subprocess.run(cmd, check=True)
        
        api.upload_file(
            path_or_fileobj=output_filename, path_in_repo=f"chunks/{output_filename}",
            repo_id=DATASET_ID, repo_type="dataset"
        )
        return f"✅ SUKSES Chunk {chunk_id} (Efek Kamera: {cid%3})"
    except Exception as e:
        return f"❌ ERROR: {str(e)}"

demo = gr.Interface(fn=render_worker, inputs="text", outputs="text")
demo.launch()