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Update app.py
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app.py
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@@ -5,6 +5,8 @@ import gradio as gr
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import spaces
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import os
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import uuid
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# Importing the model-related functions
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from stable_audio_tools import get_pretrained_model
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@@ -16,6 +18,14 @@ def load_model():
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model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0")
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print("Model loaded successfully.")
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return model, model_config
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# Function to set up, generate, and process the audio
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@spaces.GPU(duration=60) # Allocate GPU only when this function is called
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@@ -77,10 +87,13 @@ def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
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# Save to file
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torchaudio.save(unique_filename, output, sample_rate)
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print(f"Audio saved: {unique_filename}")
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# Return the path to the generated audio file
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return unique_filename
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DESCRIPTION = "Welcome to Raptor APIs"
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import spaces
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import os
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import uuid
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import shutil
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import gzip
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# Importing the model-related functions
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from stable_audio_tools import get_pretrained_model
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model, model_config = get_pretrained_model("stabilityai/stable-audio-open-1.0")
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print("Model loaded successfully.")
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return model, model_config
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def compress_file(file_path):
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compressed_file_path = file_path + '.gz'
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with open(file_path, 'rb') as f_in:
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with gzip.open(compressed_file_path, 'wb') as f_out:
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shutil.copyfileobj(f_in, f_out)
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return compressed_file_path
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# Function to set up, generate, and process the audio
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@spaces.GPU(duration=60) # Allocate GPU only when this function is called
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# Save to file
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torchaudio.save(unique_filename, output, sample_rate)
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print(f"Audio saved: {unique_filename}")]
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compressed_filename = compress_file(unique_filename)
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return compressed_filename
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# # Return the path to the generated audio file
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# return unique_filename
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DESCRIPTION = "Welcome to Raptor APIs"
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