ComfyUI Extension: ComfyUI · Egregora Audio Super‑Resolution

Authored by lucasgattas

Created

Updated

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High‑quality music audio enhancement for ComfyUI: FlashSR super‑resolution + Fat Llama spectral enhancement (GPU & CPU).

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    README

    ComfyUI Egregora Audio Super Resolution

    A focused audio toolkit for ComfyUI: upscale, enhance, and evaluate audio quality with a clean, practical workflow. This pack is built for real-world use: minimal setup, clear node purposes, and tools to verify results.

    Project scope (what this is and is not)

    What it is:

    • A set of audio enhancement nodes (FlashSR + Fat Llama) plus evaluation tools (ABX, loudness, null tests).
    • Designed to help you improve low-quality audio and measure changes reliably.

    What it is not:

    • Not a magical "increase bitrate" tool. It enhances signal content and writes a new file at a chosen format/bitrate.
    • Not a replacement for professional mastering. Think of it as an audio cleanup/boost stage.

    Nodes overview (what each one does)

    1) Audio Super Resolution (FlashSR)

    Purpose: Diffusion-based upsampler aimed at musical content. It resamples internally to 48 kHz and can resample output back to your target rate.

    Best for:

    • Low to mid quality music or wideband content
    • Improving detail and clarity in band-limited audio

    Inputs:

    • audio (AUDIO)
    • lowpass_input (BOOL) gentle LPF before inference
    • output_sr (48000 / 44100 / 96000)

    Outputs:

    • One AUDIO buffer

    Use case:

    • Feed an audio file node -> FlashSR -> Preview Audio

    2) Spectral Enhance (Fat Llama GPU)

    Purpose: Iterative spectral enhancement using CuPy on GPU.

    Best for:

    • Noisy or compressed audio
    • Sharpening "sparkle" and spectral detail

    Inputs:

    • target_format (wav / flac)
    • max_iterations (higher = more aggressive, slower)
    • threshold_value (controls spectral gating)
    • target_bitrate_kbps (target write bitrate)
    • toggle_normalize (on by default)
    • toggle_autoscale (on by default)

    Outputs:

    • One AUDIO buffer

    Use case:

    • Audio -> Fat Llama GPU -> Preview

    3) Spectral Enhance (Fat Llama CPU/FFTW)

    Purpose: CPU fallback using FFTW. Same idea as GPU but slower.

    Use case:

    • When you don´t have CUDA/CuPy

    4) Enhance Extras

    Purpose: Denoise, dereverb, and codec tools you can chain in front of FlashSR or Fat Llama.

    Includes:

    • RNNoise Denoise
    • DeepFilterNet 2/3 Denoise
    • WPE Dereverb
    • DAC encode/decode

    5) Eval Pack

    Purpose: Measure loudness, distortion, and quality.

    Includes:

    • Loudness meter (LUFS approx)
    • Gain match (LUFS/RMS)
    • ABX preparation/judge
    • Spectral metrics (SI-SDR, LSD)
    • High quality resampler

    6) Null Test Suite

    Purpose: See exactly what changed between A and B by aligning and subtracting signals.

    Includes:

    • Alignment (GCC-PHAT)
    • Gain match
    • Null output and plots

    How to combine nodes (common workflows)

    Clean + enhance (recommended chain)

    1. Denoise/Dereverb (Extras)
    2. FlashSR (optional)
    3. Fat Llama (light pass)
    4. Eval Pack or Null Test to verify

    FlashSR only

    • Audio -> FlashSR -> Preview

    Fat Llama only

    • Audio -> Fat Llama -> Preview

    Installation

    1) Copy node pack

    Place this folder into:

    ComfyUI/custom_nodes/ComfyUI-Egregora-Audio-Super-Resolution

    Restart ComfyUI once.

    2) Install dependencies (recommended)

    Use ComfyUI´s embedded Python:

    python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-Egregora-Audio-Super-Resolution
equirements.txt
python_embeded\python.exe ComfyUI\custom_nodes\ComfyUI-Egregora-Audio-Super-Resolution\install.py

    Notes:

    • Torch/torchaudio are not installed here to avoid breaking ComfyUI.
    • On Windows, install.py installs NVIDIA CUDA runtime wheels for CuPy.

    FlashSR repo and weights

    The node auto-downloads the FlashSR inference repo on first use into deps/FlashSR_Inference/: https://github.com/jakeoneijk/FlashSR_Inference

    However, FlashSR model weights are not included in this pack due to licensing/redistribution limits. The weights page does not state a license — download at your own discretion.

    You must obtain the weights from the FlashSR authors or their official release and place them here: https://huggingface.co/datasets/jakeoneijk/FlashSR_weights

    ComfyUI/models/audio/flashsr/
  student_ldm.pth
  sr_vocoder.pth
  vae.pth

    Optional auto-download (if you host the weights in your own HF repo):

    set EGREGORA_FLASHSR_HF_REPO=yourname/flashsr-weights

    Troubleshooting (quick fixes)

    FlashSR import issues

    • The node auto-downloads deps/FlashSR_Inference/ on first use.
    • If it fails, delete the folder and retry:
    Remove-Item -Recurse -Force .\ComfyUI\custom_nodes\ComfyUI-Egregora-Audio-Super-Resolution\deps\FlashSR_Inference

    CuPy / CUDA root not detected (Fat Llama GPU)

    Run this in ComfyUI root:

    python_embeded\python.exe -m pip install -U nvidia-cuda-runtime-cu12 nvidia-cuda-nvrtc-cu12 nvidia-cublas-cu12 nvidia-cufft-cu12 nvidia-curand-cu12 nvidia-cusolver-cu12 nvidia-cusparse-cu12 cupy-cuda12x

    Numba needs NumPy 1.26 or less

    python_embeded\python.exe -m pip install "numpy<=1.26.4"

    License notes

    • FlashSR inference code and weights are from upstream authors; check their repo for license status.
    • Fat Llama packages are BSD-3-Clause (see PyPI).
    • This integration is MIT (see LICENSE).

    Changelog

    • v0.2.1

      • FlashSR auto-bootstrap and clearer diagnostics.
      • Fat Llama CUDA path detection fixes for portable installs.
      • Fat Llama output scaling aligned with upstream behavior.
      • NumPy pinned to <=1.26.4 for Numba compatibility.

    • v0.2.0 Added Enhance/Eval/Null toolsets; new installer + warmups.

    • v0.1.0 Initial release: FlashSR SR node, Fat Llama GPU/CPU.