44 lines
1.9 KiB
Markdown
44 lines
1.9 KiB
Markdown
# Sage_KSamplerAudioDecoder
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**KSampler + Audio Decoder**
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A specialized KSampler node designed for audio generation workflows. It performs sampling on latent audio data and automatically decodes it to audio format, outputting both the denoised latent and decoded audio.
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## Inputs
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### Required
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- **model** (MODEL): The model used for denoising the input latent
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- **sampler_info** (SAMPLER_INFO): Most of the KSampler options. Should be piped both here and to the Construct Metadata node
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- **positive** (CONDITIONING): The conditioning describing the attributes you want to include in the audio
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- **negative** (CONDITIONING): The conditioning describing the attributes you want to exclude from the audio
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- **latent_audio** (LATENT): The latent audio to denoise
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- **vae** (VAE): The VAE used for decoding the latent audio
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- **denoise** (FLOAT): The amount of denoising applied, lower values will maintain the structure of the initial audio allowing for audio to audio sampling (default: 1.0, range: 0.0-1.0)
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### Optional
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- **advanced_info** (ADV_SAMPLER_INFO): Optional. Adds in the options an advanced KSampler would have
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## Outputs
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- **LATENT**: The denoised latent
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- **AUDIO**: The decoded audio (44.1kHz sample rate with normalized waveform)
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## Usage
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This node is specifically designed for audio generation workflows using latent diffusion models. It combines the sampling and decoding steps into a single node for convenience.
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Key features:
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- Automatic audio normalization (scales by 5x standard deviation, minimum 1.0)
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- Fixed 44.1kHz sample rate output
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- Supports advanced sampling options when connected to Sage_AdvSamplerInfo
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- Works with the Sage_SamplerInfo node for consistent workflow integration
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## Notes
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- The audio output includes automatic normalization to prevent clipping
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- This node is optimized for audio generation workflows
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- Use with audio-specific VAE models for best results
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- The latent_audio input should come from audio-compatible latent sources
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