Create app.py

app.py

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+import os
+import requests
+import subprocess
+import gradio as gr
+
+# Token Hugging Face từ biến môi trường
+hf_token = os.getenv("HF_TOKEN")
+
+# URLs cần tải
+app_url = "https://huggingface.co/datasets/ArrcttacsrjksX/Deffusion/resolve/main/RunModelAppp/App/sdRundeffusiononhuggingfacemaster-ac54e00"
+model_url = "https://huggingface.co/datasets/ArrcttacsrjksX/Deffusion/resolve/main/Model/realisticVisionV60B1_v51HyperVAE.safetensors"
+
+# Đường dẫn lưu file
+app_path = "sdRundeffusiononhuggingfacemaster-ac54e00"
+model_path = "realisticVisionV60B1_v51HyperVAE.safetensors"
+
+# Hàm tải file từ Hugging Face
+def download_file(url, output_path, token):
+    headers = {"Authorization": f"Bearer {token}"}
+    response = requests.get(url, headers=headers, stream=True)
+    response.raise_for_status()  # Kiểm tra lỗi
+    with open(output_path, "wb") as f:
+        for chunk in response.iter_content(chunk_size=8192):
+            f.write(chunk)
+    print(f"Downloaded: {output_path}")
+
+# Tải các file nếu chưa tồn tại
+if not os.path.exists(app_path):
+    download_file(app_url, app_path, hf_token)
+    subprocess.run(["chmod", "+x", app_path])  # Thay đổi quyền thực thi
+
+if not os.path.exists(model_path):
+    download_file(model_url, model_path, hf_token)
+
+# Hàm xử lý chạy ứng dụng
+def run_command(prompt, mode, height, width, steps, seed, init_image=None):
+    try:
+        # Lưu ảnh đầu vào nếu được cung cấp
+        init_image_path = None
+        if init_image:
+            init_image_path = "input_image.png"
+            init_image.save(init_image_path)
+
+        # Chạy lệnh
+        command = [
+            f"./{app_path}",
+            "-M", mode,
+            "-m", model_path,
+            "-p", prompt,
+            "-H", str(height),
+            "-W", str(width),
+            "--steps", str(steps),
+            "-s", str(seed),
+        ]
+        
+        # Thêm ảnh đầu vào nếu có
+        if mode == "img2img" and init_image_path:
+            command.extend(["-i", init_image_path])
+        
+        result = subprocess.run(command, capture_output=True, text=True)
+
+        # Kiểm tra kết quả và trả về
+        if result.returncode == 0:
+            output_path = "./output.png"  # Đường dẫn ảnh đầu ra mặc định
+            return output_path if os.path.exists(output_path) else "Output image not found."
+        else:
+            return f"Error: {result.stderr}"
+    except Exception as e:
+        return str(e)
+
+# Giao diện Gradio
+with gr.Blocks() as demo:
+    gr.Markdown("# Stable Diffusion Interface")
+    
+    # Cấu hình tham số
+    with gr.Row():
+        prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here", lines=2)
+        mode = gr.Radio(choices=["txt2img", "img2img"], value="txt2img", label="Mode")
+    
+    with gr.Row():
+        height = gr.Slider(128, 1024, value=512, step=64, label="Height (px)")
+        width = gr.Slider(128, 1024, value=512, step=64, label="Width (px)")
+    
+    with gr.Row():
+        steps = gr.Slider(1, 100, value=20, step=1, label="Steps")
+        seed = gr.Slider(-1, 10000, value=42, step=1, label="Seed (-1 for random)")
+    
+    init_image = gr.Image(label="Initial Image (for img2img mode, optional)", type="pil", optional=True)
+    output_path = gr.Textbox(label="Output Image Path or Logs", interactive=False)
+    run_button = gr.Button("Run")
+
+    # Kết nối hàm xử lý
+    run_button.click(
+        run_command,
+        inputs=[prompt, mode, height, width, steps, seed, init_image],
+        outputs=output_path,
+    )
+
+demo.launch()