app.py

import gradio as gr
from transformers import AutoProcessor, AutoModelForImageTextToText
import torch
from PIL import Image

# --- KONFIGURASI ALAM ---[new]
MODEL_PATH = "zai-org/GLM-OCR"

# 1. HUKUM KEKALAN HARDWARE
if torch.cuda.is_available():
    device = "cuda"
    dtype = torch.float16
else:
    device = "cpu"
    dtype = torch.float32

print(f"🚀 ENGINE STARTED: Device={device} | Dtype={dtype}")

# 2. INISIASI MODEL (RELOAD AMAN)
try:
    print("⏳ Menyiapkan Otak GLM...")
    
    # Processor
    processor = AutoProcessor.from_pretrained(
        MODEL_PATH, 
        trust_remote_code=True
    )
    
    # Model (Kita balik ke AutoModelForImageTextToText karena Library lu udh sukses load weights)
    model = AutoModelForImageTextToText.from_pretrained(
        MODEL_PATH,
        torch_dtype=dtype,
        trust_remote_code=True,
        low_cpu_mem_usage=True,
        device_map="auto"
    )
    
    model.eval()

except Exception as e:
    print(f"⚠️ Warning Model (Gas Terus): {e}")
    pass

# 3. LOGIKA EKSTRAKSI (INTELIJEN)
def proses_intelijen(image):
    if image is None:
        return "⚠️ Gambarnya mana Bos? Upload dulu."

    messages = [
        {
            "role": "user",
            "content": [
                {"type": "image", "image": image},
                {"type": "text", "text": "Text Recognition:"}
            ],
        }
    ]

    try:
        # IQ 1000: Tokenize=True adalah kunci biar tensor kebaca
        inputs = processor.apply_chat_template(
            messages,
            add_generation_prompt=True,
            tokenize=True, 
            return_dict=True,
            return_tensors="pt"
        ).to(model.device) # Paksa pindah ke device model

        with torch.no_grad():
            generated_ids = model.generate(
                **inputs, 
                max_new_tokens=2048, 
                do_sample=False
            )

        hasil = generated_ids[0][len(inputs["input_ids"][0]):]
        teks_final = processor.decode(hasil, skip_special_tokens=True)
        return teks_final

    except Exception as e:
        return f"🚨 SYSTEM CRITICAL FAILURE: {str(e)}"

# 4. ANTARMUKA (CLEAN VERSION - ANTI ERROR)
# CSS Kita masukin langsung ke head lewat method modern
css_custom = """
.container { max-width: 1200px; margin: auto; padding-top: 20px; }
h1 { text-align: center; color: #3b82f6; }
"""

with gr.Blocks(css=css_custom, title="GLM-OCR V-FINAL") as app:
    with gr.Column(elem_classes="container"):
        gr.Markdown("# 👁️ GLM-OCR ULTRA")
        gr.Markdown("Scanner Dokumen Tercerdas.")
        
        with gr.Row():
            with gr.Column(scale=1):
                input_img = gr.Image(type="pil", label="Upload Disini", height=450)
                scan_btn = gr.Button("🚀 START SCAN", variant="primary", size="lg")
            
            with gr.Column(scale=1):
                # INI PERBAIKANNYA BANG:
                # 1. Hapus 'show_copy_button=True' -> Penyebab Error.
                # 2. Hapus 'interactive=False' jika mau teksnya bisa dicopy manual.
                # Kita pakai settingan DEFAULT yang paling aman.
                output_txt = gr.Textbox(label="Hasil Teks", lines=24)
    
    scan_btn.click(fn=proses_intelijen, inputs=input_img, outputs=output_txt)

if __name__ == "__main__":
    app.launch()