Create app.py

app.py

@@ -0,0 +1,93 @@
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+# --- 1. Clone the VibeVoice Repository ---
+repo_dir = "VibeVoice"
+if not os.path.exists(repo_dir):
+    print("Cloning the VibeVoice repository...")
+    try:
+        subprocess.run(
+            ["git", "clone", "https://github.com/microsoft/VibeVoice.git"],
+            check=True,
+            capture_output=True,
+            text=True
+        )
+        print("Repository cloned successfully.")
+    except subprocess.CalledProcessError as e:
+        print(f"Error cloning repository: {e.stderr}")
+        sys.exit(1)
+else:
+    print("Repository already exists. Skipping clone.")
+
+# --- 2. Install the Package ---
+os.chdir(repo_dir)
+print(f"Changed directory to: {os.getcwd()}")
+
+print("Installing the VibeVoice package...")
+try:
+    subprocess.run(
+        [sys.executable, "-m", "pip", "install", "-e", "."],
+        check=True,
+        capture_output=True,
+        text=True
+    )
+    print("Package installed successfully.")
+except subprocess.CalledProcessError as e:
+    print(f"Error installing package: {e.stderr}")
+    sys.exit(1)
+
+# --- 3. Modify the demo script for CPU execution (Robust Method) ---
+demo_script_path = Path("demo/gradio_demo.py")
+print(f"Modifying {demo_script_path} for CPU execution...")
+
+try:
+    # Read the entire file content
+    file_content = demo_script_path.read_text()
+
+    # Define the original GPU-specific model loading block
+    original_block = """        self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
+            self.model_path,
+            torch_dtype=torch.bfloat16,
+            device_map='cuda',
+            attn_implementation="flash_attention_2",
+        )"""
+
+    # Define the new CPU-compatible block
+    replacement_block = """        self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
+            self.model_path,
+            torch_dtype=torch.float32,  # Use float32 for CPU
+            device_map="cpu",
+        )"""
+
+    # Replace the entire block
+    if original_block in file_content:
+        modified_content = file_content.replace(original_block, replacement_block)
+        
+        # Write the modified content back to the file
+        demo_script_path.write_text(modified_content)
+        print("Script modified successfully.")
+    else:
+        print("Warning: GPU-specific model loading block not found. The script might have been updated. Proceeding without modification.")
+
+except Exception as e:
+    print(f"An error occurred while modifying the script: {e}")
+    sys.exit(1)
+
+
+# --- 4. Launch the Gradio Demo ---
+model_id = "microsoft/VibeVoice-1.5B"
+
+# Construct the command as specified in the README
+command = [
+    "python",
+    str(demo_script_path),
+    "--model_path",
+    model_id,
+    "--share"
+]
+
+print(f"Launching Gradio demo with command: {' '.join(command)}")
+# This command will start the Gradio server
+subprocess.run(command)