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The code achieves this functionality through the following functions:
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generate_audio function:
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---
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Create a summary of what this code can do as a markdown outline and table. In the table feature a glossary with meanings and definitions for some of the functions and operations in the app. Have one outline specifcally for describing the functions, inputs and outputs.
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# Stable Audio Multiplayer Live App
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## App Features
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- Generate audio using text prompts
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- Customize audio generation parameters
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- Duration
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- Number of diffusion steps
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- Sampler type
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- CFG scale
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- Sigma min and max values
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- Share generated audio with the community
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- View and listen to audio generated by other users
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- Load more community-generated audio on demand
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## Code Structure
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1. Import necessary libraries
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2. Define constants and settings
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3. Load the pre-trained model
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4. Define the `generate_audio` function
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- Set up text and timing conditioning
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- Generate stereo audio
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- Process and save the generated audio
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5. Define utility functions
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- `list_all_outputs`: List all generated audio files
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- `increase_list_size`: Increase the number of displayed community-generated audio files
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6. Create the Gradio interface
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- Set up the input components (text prompt, parameters)
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- Display the generated audio output
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- Show community-generated audio
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- Provide examples for users to try
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7. Load the model and launch the app
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## Functions, Inputs, and Outputs
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1. `load_model`
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- Purpose: Load the pre-trained model and configuration
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- Inputs: None
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- Outputs: `model` (loaded model), `model_config` (model configuration)
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2. `generate_audio`
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- Purpose: Generate audio based on the provided text prompt and parameters
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- Inputs:
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- `prompt` (text prompt)
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- `sampler_type_dropdown` (selected sampler type)
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- `seconds_total` (duration in seconds)
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- `steps` (number of diffusion steps)
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- `cfg_scale` (CFG scale value)
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- `sigma_min_slider` (sigma min value)
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- `sigma_max_slider` (sigma max value)
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- Outputs: `unique_filename` (path to the generated audio file)
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3. `list_all_outputs`
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- Purpose: List all generated audio files and update the community-generated audio display
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- Inputs: `generation_history` (comma-separated list of previously displayed audio files)
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- Outputs: `updated_history` (updated comma-separated list of audio files), `gr.update(visible=True)` (update the visibility of the community-generated audio section)
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4. `increase_list_size`
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- Purpose: Increase the number of displayed community-generated audio files
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- Inputs: `list_size` (current number of displayed audio files)
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- Outputs: `list_size+PAGE_SIZE` (increased number of displayed audio files)
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## Glossary
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| Term | Definition |
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|------|------------|
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| Diffusion Model | A generative model that learns to denoise data by reversing a gradual noising process |
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| Sampler Type | The algorithm used to generate audio samples from the diffusion model |
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| CFG Scale | Classifier-Free Guidance scale, controls the influence of the text prompt on the generated audio |
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| Sigma | Noise level values used in the diffusion process, determining the amount of noise added or removed |
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| Gradio | A Python library for building web-based interfaces for machine learning models |
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| Einops | A library for flexible and readable tensor operations, used for rearranging the generated audio |
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| Torchaudio | A PyTorch library for working with audio data, used for saving the generated audio to a file |
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The code achieves this functionality through the following functions:
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generate_audio function:
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