Update app.py
Browse files
app.py
CHANGED
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@@ -2,7 +2,7 @@ import os
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import subprocess
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import sys
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from pathlib import Path
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# --- 1. Clone the VibeVoice Repository ---
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repo_dir = "VibeVoice"
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if not os.path.exists(repo_dir):
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@@ -23,17 +23,6 @@ else:
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os.chdir(repo_dir)
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print(f"Changed directory to: {os.getcwd()}")
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print("Installing bitsandbytes for potential quantization...")
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try:
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subprocess.run(
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[sys.executable, "-m", "pip", "install", "bitsandbytes"],
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check=True, capture_output=True, text=True
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)
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print("bitsandbytes installed successfully.")
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except subprocess.CalledProcessError as e:
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print(f"Error installing bitsandbytes: {e.stderr}")
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sys.exit(1)
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print("Installing the VibeVoice package in editable mode...")
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try:
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subprocess.run(
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@@ -57,10 +46,9 @@ try:
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modified_content = "import spaces\n" + modified_content
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# --- Patch 1: Prevent model loading at startup ---
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#
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# This stops the main CPU process from loading the heavyweight model.
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original_init_line = " self.load_model()"
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replacement_init_line = " # self.load_model() # Patched: Defer model loading
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if original_init_line in modified_content:
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modified_content = modified_content.replace(original_init_line, replacement_init_line)
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@@ -70,11 +58,11 @@ try:
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sys.exit(1)
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# --- Patch 2: Move model loading inside the generation function and add decorator ---
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# This ensures the model is loaded "just-in-time" on the GPU worker.
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original_method_signature = " def generate_podcast_streaming(self,"
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# Define the model loading code to be inserted.
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# We
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lazy_load_code = """
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# Patched: Lazy-load model and processor on the GPU worker
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if self.model is None or self.processor is None:
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@@ -82,7 +70,7 @@ try:
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self.processor = VibeVoiceProcessor.from_pretrained(self.model_path)
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self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
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self.model_path,
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device_map="auto",
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)
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self.model.eval()
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@@ -93,39 +81,27 @@ try:
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)
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self.model.set_ddpm_inference_steps(num_steps=self.inference_steps)
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print("Model and processor loaded successfully on GPU worker.")
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"""
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# We
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pre_method = modified_content[:method_start_index]
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method_signature_and_body = modified_content[method_start_index:]
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# Decorate the original signature
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decorated_signature = " @spaces.GPU(duration=120)\n" + original_method_signature
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method_signature_and_body = method_signature_and_body.replace(original_method_signature, decorated_signature)
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# Insert the lazy loading code after the signature line
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final_method = method_signature_and_body.replace("-> Iterator[tuple]:", "-> Iterator[tuple]:\n" + lazy_load_code, 1)
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modified_content = pre_method + final_method
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print("Successfully refactored generation method for lazy loading on GPU.")
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else:
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print(f"\033[91mError: Could not find '
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sys.exit(1)
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demo_script_path.write_text(modified_content)
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import subprocess
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import sys
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from pathlib import Path
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+
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# --- 1. Clone the VibeVoice Repository ---
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repo_dir = "VibeVoice"
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if not os.path.exists(repo_dir):
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os.chdir(repo_dir)
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print(f"Changed directory to: {os.getcwd()}")
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print("Installing the VibeVoice package in editable mode...")
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try:
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subprocess.run(
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modified_content = "import spaces\n" + modified_content
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# --- Patch 1: Prevent model loading at startup ---
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# Comment out self.load_model() in __init__ to avoid loading on the main CPU process.
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original_init_line = " self.load_model()"
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replacement_init_line = " # self.load_model() # Patched: Defer model loading\n self.model = None\n self.processor = None"
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if original_init_line in modified_content:
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modified_content = modified_content.replace(original_init_line, replacement_init_line)
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sys.exit(1)
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# --- Patch 2: Move model loading inside the generation function and add decorator ---
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# This ensures the model is loaded "just-in-time" on the GPU worker with proper precision.
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original_method_signature = " def generate_podcast_streaming(self,"
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# Define the model loading code to be inserted.
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# We use torch.bfloat16 for a balance of performance and quality.
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lazy_load_code = """
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# Patched: Lazy-load model and processor on the GPU worker
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if self.model is None or self.processor is None:
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self.processor = VibeVoiceProcessor.from_pretrained(self.model_path)
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self.model = VibeVoiceForConditionalGenerationInference.from_pretrained(
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self.model_path,
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torch_dtype=torch.bfloat16, # Use 16-bit precision for quality
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device_map="auto",
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)
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self.model.eval()
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)
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self.model.set_ddpm_inference_steps(num_steps=self.inference_steps)
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print("Model and processor loaded successfully on GPU worker.")
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"""
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# We need to find the full method signature to insert code into it.
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full_method_signature_line = None
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for line in modified_content.splitlines():
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if "def generate_podcast_streaming" in line:
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full_method_signature_line = line.strip()
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break
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if full_method_signature_line:
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# We find the end of the method signature to insert our code block.
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target_to_replace = full_method_signature_line + "\n"
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replacement_block = (
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" @spaces.GPU(duration=120)\n" +
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" " + full_method_signature_line + "\n" +
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lazy_load_code
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)
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modified_content = modified_content.replace(target_to_replace, replacement_block, 1)
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print("Successfully refactored generation method for lazy loading on GPU.")
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else:
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print(f"\033[91mError: Could not find full method signature for 'generate_podcast_streaming' to patch.\033[0m")
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sys.exit(1)
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demo_script_path.write_text(modified_content)
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