ComfyUI LongCat Avatar

This repository adapts the official Avatar 1.5 pipeline to ComfyUI. It focuses on CUDA inference, Whisper-large-v3 audio conditioning, required distill LoRA inference, single-audio and multi-audio avatar generation, single-file .safetensors DiT loading, official sharded DiT loading, official sharded INT8 DiT loading, and bounded automatic download of known official checkpoint assets.

<p align="center"> <a href="https://github.com/meituan-longcat/LongCat-Video">Official LongCat-Video Repo</a> | <a href="https://meigen-ai.github.io/LongCat-Video-Avatar-1.5-Page/">Official Avatar 1.5 Project Page</a> </p> <div align="center"> <video src="https://github.com/user-attachments/assets/dbad0a81-c961-4cef-9a18-09377de2397a" width="900"></video> </div>

Last Update

<details> <summary><strong>Desktop installation and workflow reliability refreshed in 0.2.5</strong></summary>

• Fixed fresh-install startup failures by removing the undeclared Loguru dependency and loading optional Triton-backed block-sparse attention only when selected.
• Aligned Python, dependency, and ComfyUI compatibility metadata while preserving the host-managed PyTorch and CUDA stack.
• Added a complete nine-node Registry inventory and versioned workflow attribution so missing workflows identify comfyui-longcat-avatar instead of an unknown pack.
• Verified all nine nodes and the example workflow on ComfyUI Core 0.22.3 / Frontend 1.43.18 and Core 0.27.1 / Frontend 1.45.20.

</details> <details> <summary><strong>Apple Silicon MLX testing branch</strong></summary>

A macOS inference branch, macOS-MLX, is available for Apple Silicon MLX testing. If you have a suitable Mac, please try it and share feedback through GitHub issues or pull requests.

</details>

Table of Contents

• Last Update
• Feature Status
• Installation
• Model Files
• Inference Weight Modes
• Model Source Boundaries
• Automatic Official Weight Download
• Nodes
• Attention Backends
• Audio Conditioning And Dual-Person Mode
• Generation Controls
• Avatar 1.5 Usage Tips
• Troubleshooting Desktop Installation
• License

Feature Status

| Capability | Status | | --- | --- | | Avatar 1.5 single audio ai2v | Supported | | Avatar 1.5 single audio at2v | Supported by sampler mode; the current ComfyUI node still requires an image socket in the graph | | Avatar 1.5 multi audio | Supported with ai2v only | | 480p and 720p generation | Supported | | Distill inference | Required for Avatar 1.5; sampler defaults are 8 steps, text CFG 1.0, audio CFG 1.0 | | Single-file DiT .safetensors | Supported from ComfyUI/models/diffusion_models/ | | Official sharded DiT | Supported for Avatar 1.5 base_model/ checkpoints | | Official sharded INT8 DiT | Supported for Avatar 1.5 base_model_int8/ checkpoints | | Manifest-backed official weight download | Supported for known official Avatar 1.5 sharded DiT assets and shared LongCat text encoder assets | | Selectable attention backends | Supported for auto, sdpa, flash_attn_2, flash_attn_3, xformers, and sageattn; sageattn_3 is exposed as a reserved option but currently fails fast because LongCat varlen cross-attention wiring is incomplete | | GGUF DiT | Not supported yet | | Avatar 1.0 | Not supported by this ComfyUI contract | | CPU or MPS inference | Not supported for the CUDA-only model path |

Installation

Install the custom node inside ComfyUI:

cd ComfyUI/custom_nodes
git clone https://github.com/rookiestar28/ComfyUI-LongCat-Avatar
cd ComfyUI-LongCat-Avatar
pip install -r requirements.txt

Use the Python environment that launches ComfyUI. The runtime path is CUDA-oriented and expects a compatible NVIDIA GPU plus a working CUDA PyTorch build already installed for ComfyUI. The default requirements.txt installs dependencies for the exposed LongCat Avatar nodes, including vocal extraction support, but intentionally does not install torch, torchvision, torchaudio, FlashAttention, xFormers, SageAttention, Streamlit, OpenAI SDK, or upstream demo/server-only packages, because replacing those packages can break an existing ComfyUI setup.

System prerequisites:

• Python 3.10 or newer. ComfyUI Desktop's managed Python 3.12 is supported.
• FFmpeg executable: required by LongCat Avatar Vocal Extract through audio-separator, and by video/audio mux helpers. This must be an ffmpeg command visible on the PATH used to launch ComfyUI; Python packages such as imageio-ffmpeg do not satisfy every subprocess lookup.

Install examples:

# Conda/Miniforge environment used to launch ComfyUI
conda install -c conda-forge ffmpeg

# macOS Homebrew
brew install ffmpeg

# Debian/Ubuntu
sudo apt-get install ffmpeg

Verify from the same terminal or service environment that starts ComfyUI:

ffmpeg -version

macOS/MPS inference is not supported in this release. Any MPS work must happen on a dedicated experimental branch and must not be merged into the public CUDA path until Apple Silicon smoke inference proves model loading, attention fallback, audio encoding, VAE encode/decode, and end-to-end timing.

Dependency groups:

| File | Use When | Notes | | --- | --- | --- | | requirements.txt | Default node install | Required Python packages for model loading, audio encoding, vocal extraction, and sampling. | | requirements-acceleration.txt | You want optional attention acceleration | Documentation-only examples for FlashAttention, xFormers, and SageAttention. Do not install blindly; choose versions manually that match your ComfyUI PyTorch/CUDA stack. |

Model Files

Use the normal ComfyUI model folders so the node dropdowns can find manually placed files.

Some official assets can be downloaded automatically from inside the nodes. Enable auto_download_missing_weights on (auto)Load LongCat Avatar Model for official sharded Avatar 1.5 DiT checkpoints, and enable auto_download_missing_text_encoder on LongCat Avatar Text Encode for the official shared LongCat-Video tokenizer/text encoder. VAE, Whisper, and the selectable distill LoRA still need to be placed in the normal ComfyUI model folders.

Required for normal Avatar 1.5 generation:

• ComfyUI/models/loras/ longcat-avatar-dmd_lora.safetensors

• ComfyUI/models/vae/ LongCat-Video-Avatar-vae.safetensors

• ComfyUI/models/audio_encoders/ whisper-large-v3.safetensors

Choose one DiT source:

• official_sharded: use auto_download_missing_weights or place the official sharded files under ComfyUI/models/longcat/LongCat-Video-Avatar-1.5/base_model/.
• official_int8_sharded: use auto_download_missing_weights or place the official INT8 sharded files under ComfyUI/models/longcat/LongCat-Video-Avatar-1.5/base_model_int8/.
• single_file_safetensors: place LongCat-Video-Avatar-1.5-int8.safetensors under ComfyUI/models/diffusion_models/.

Choose one text encoder source:

• Recommended native path: use auto_download_missing_text_encoder or place the shared official assets under ComfyUI/models/longcat/LongCat-Video/tokenizer/ and ComfyUI/models/longcat/LongCat-Video/text_encoder/.
• Existing fallback path: connect ComfyUI Load CLIP to LongCat Avatar Text Encode and place umt5_xxl_fp8_e4m3fn_scaled.safetensors under ComfyUI/models/clip/.

Optional vocal separation:

• ComfyUI/models/longcat/ Kim_Vocal_2.onnx

Official sharded checkpoint layouts:

• ComfyUI/models/longcat/LongCat-Video-Avatar-1.5/base_model/ config.json diffusion_pytorch_model.safetensors.index.json diffusion_pytorch_model-00001-of-00006.safetensors ...

• ComfyUI/models/longcat/LongCat-Video-Avatar-1.5/base_model_int8/ config.json quantization_config.json quantized_model.safetensors.index.json quantized_model-00001-of-00004.safetensors ...

Download sources:

• Avatar 1.5 official weights: https://huggingface.co/meituan-longcat/LongCat-Video-Avatar-1.5
• Shared LongCat-Video tokenizer/text encoder: https://huggingface.co/meituan-longcat/LongCat-Video
• Community INT8 merged DiT: https://huggingface.co/smthem/LongCat-Video-Avatar-1.5-merge
• UMT5 text encoder: https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/text_encoders
• Optional vocal separator: https://huggingface.co/seanghay/uvr_models/blob/main/Kim_Vocal_2.onnx

| Model file | Description | Download link | ComfyUI filename | | --- | --- | --- | --- | | Whisper-large-v3 | Avatar 1.5 audio encoder used by LongCat Avatar Whisper | Hugging Face | Download as model.safetensors, then rename to whisper-large-v3.safetensors under ComfyUI/models/audio_encoders/. | | Distill LoRA | Required Avatar 1.5 distillation LoRA for 8-step inference | Hugging Face | Keep as dmd_lora.safetensors or rename to longcat-avatar-dmd_lora.safetensors under ComfyUI/models/loras/. | | Kim_Vocal_2.onnx | Optional vocal separation model used by LongCat Avatar Vocal Model | Hugging Face | Keep as Kim_Vocal_2.onnx under ComfyUI/models/longcat/. |

The VAE filename is selectable from the ComfyUI VAE dropdown; LongCat-Video-Avatar-vae.safetensors and LongCat_Avatar_1.5_vae.safetensors are both acceptable local filenames as long as the selected file is the Avatar 1.5 VAE.

Kim_Vocal_2.onnx is only needed when using the vocal separation nodes. The Python dependencies for those nodes are included in the default requirements.txt install.

Automatic download coverage:

• auto_download_missing_weights only applies to the official Avatar 1.5 sharded DiT checkpoint modes, described below.
• VAE is not included in the automatic download manifest. Keep LongCat-Video-Avatar-vae.safetensors in ComfyUI/models/vae/.
• The official manifest includes the upstream lora/dmd_lora.safetensors asset for checkpoint completeness, but the ComfyUI node still loads the selected distill LoRA from ComfyUI/models/loras/. Keep longcat-avatar-dmd_lora.safetensors in ComfyUI/models/loras/ so the LoRA dropdown can find it.
• The official UMT5 text encoder is shared with the base LongCat-Video model. LongCat Avatar Text Encode can auto-download the bounded tokenizer/* and text_encoder/* assets from meituan-longcat/LongCat-Video into ComfyUI/models/longcat/LongCat-Video/. Existing workflows with Load CLIP connected to LongCat Avatar Text Encode use the single-file UMT5 fallback path.

Inference Weight Modes

(auto)Load LongCat Avatar Model exposes three supported inference weight modes. The selected mode determines the DiT source automatically; there is no separate diffusion_models or official_checkpoint selector on the node.

| Mode | Auto-selected source | Expected files | | --- | --- | --- | | single_file_safetensors | LongCat-Video-Avatar-1.5-int8.safetensors | One .safetensors DiT file in ComfyUI/models/diffusion_models/ | | official_sharded | LongCat-Video-Avatar-1.5/base_model/diffusion_pytorch_model.safetensors.index.json | Official base_model/ index and all referenced shards | | official_int8_sharded | LongCat-Video-Avatar-1.5/base_model_int8/quantized_model.safetensors.index.json | Official base_model_int8/ index, quantization_config.json, and all referenced shards |

Single-file mode loads the default merged/community DiT filename from ComfyUI/models/diffusion_models/. Official sharded modes validate the checkpoint index JSON, required config files, and every shard referenced by the index before inference begins.

GGUF remains unsupported and is not exposed as a model-node selector.

Model Source Boundaries

The official sharded modes are the official checkpoint contract for this repository. They load the official Avatar 1.5 base_model/ or base_model_int8/ layouts from ComfyUI/models/longcat/ and validate the official index files before tensor loading.

Single-file .safetensors mode is for local or community-converted DiT files in ComfyUI/models/diffusion_models/. A converted single-file checkpoint can originate from official weights, but it is not the official sharded layout and is not treated as an official_sharded or official_int8_sharded source.

Third-party wrapper-specific conversions and scheduler names are engineering references only. They do not redefine this repository's tensor schema, checkpoint layout, scheduler semantics, or supported runtime modes. This repository does not require third-party wrapper conversion before use.

FP16, FP8, GGUF, and alternate scheduler controls are not accepted official runtime modes in this release. They remain unsupported or experimental until implemented with explicit compatibility checks, tests, and documentation.

Official runtime precision remains bf16 by default. Official INT8 support is selected through official_int8_sharded as a checkpoint/weight mode, not through a generic FP8 runtime switch. FP16, FP8, and GGUF are not runtime precision modes in this release.

Automatic Official Weight Download

auto_download_missing_weights is available as an on/off toggle on (auto)Load LongCat Avatar Model. When enabled with official_sharded or official_int8_sharded, the node builds a fixed manifest for meituan-longcat/LongCat-Video-Avatar-1.5 and downloads missing official checkpoint assets under:

ComfyUI/models/longcat/LongCat-Video-Avatar-1.5/

The downloader is intentionally bounded:

• It is manifest-backed and limited to known official assets.
• It does not accept arbitrary URLs.
• It does not accept arbitrary repo IDs.
• It does not add a token text box; use normal Hugging Face local authentication when your environment requires gated access.
• It does not replace every ComfyUI model dropdown. VAE, Whisper, and the distill LoRA still need to be present in their normal ComfyUI model folders.
• It does not download the VAE into ComfyUI/models/vae/.
• It does not register the official repo's lora/dmd_lora.safetensors as a selectable LoRA in ComfyUI/models/loras/; place or copy the required distill LoRA there before loading the model node.

auto_download_missing_text_encoder is available on LongCat Avatar Text Encode. When enabled, it downloads only the shared base meituan-longcat/LongCat-Video tokenizer/* and text_encoder/* assets into:

ComfyUI/models/longcat/LongCat-Video/

LongCat Avatar Text Encode also exposes its own offload_device control for the native official path. The default is cpu so the native UMT5 text encoder weights do not consume VRAM; choose cuda only when you have enough headroom and want faster text encoding. If the clip input is connected, the node uses the existing ComfyUI Load CLIP single-file UMT5 fallback and does not load the native text encoder.

Broad manual checkpoint download:

hf download meituan-longcat/LongCat-Video-Avatar-1.5 --local-dir ComfyUI/models/longcat/LongCat-Video-Avatar-1.5

That command downloads the upstream repository layout more broadly than the node's bounded manifest. The node still requires VAE, Whisper, and selectable distill LoRA files to be placed in the normal ComfyUI model folders described above.

Nodes

| Node | Purpose | | --- | --- | | (auto)Load LongCat Avatar Model | Loads the DiT source selected by inference_weight_mode, VAE, and required Avatar 1.5 distill LoRA | | LongCat Avatar Whisper | Loads whisper-large-v3.safetensors from ComfyUI/models/audio_encoders/ | | LongCat Avatar Text Encode | Preferred official-first text node. Without clip, it uses the shared official LongCat-Video tokenizer and UMT5 text encoder; with clip, it uses the ComfyUI Load CLIP single-file fallback | | LongCat Avatar Audio Crop | Trims a ComfyUI audio input by start/end time, returns AUDIO, and provides an inline cropped-audio preview | | LongCat Avatar Audio Encode | Builds reusable full-clip single-audio or optional dual-audio conditioning | | LongCat Avatar Audio Window | Optionally slices reusable full-clip audio conditioning for explicit continuation windows | | LongCat Avatar Sampler | Generates frames in ai2v or at2v mode and can optionally mux audio into a saved video | | LongCat Avatar Vocal Model | Loads an optional ONNX vocal separation model from ComfyUI/models/longcat/ | | LongCat Avatar Vocal Extract | Extracts vocals from an input audio clip before audio conditioning |

Typical graph order:

1. Load the model with (auto)Load LongCat Avatar Model.
2. Prefer LongCat Avatar Text Encode without connecting clip for official prompt-conditioning parity. It can auto-download the shared base LongCat-Video tokenizer/text encoder assets when auto_download_missing_text_encoder is enabled.
3. Load Whisper with LongCat Avatar Whisper.
4. Existing Load CLIP + LongCat Avatar Text Encode graphs remain supported as the UMT5 single-file fallback path.
5. Optionally trim source audio with LongCat Avatar Audio Crop. Its Crop Preview button queues only this output node so you can crop and preview audio without running the downstream sampler/video nodes.
6. Encode audio with LongCat Avatar Audio Encode.
7. Generate with LongCat Avatar Sampler.

Attention Backends

(auto)Load LongCat Avatar Model includes an attention_mode selector:

| Mode | Behavior | | --- | --- | | auto | Preserves the attention flags from the selected LongCat checkpoint config. Official configs currently default to FlashAttention 2. If an optional backend from the config is unavailable, the runtime prints a warning and falls back to SDPA where supported. | | sdpa | Forces PyTorch scaled_dot_product_attention. This is the most portable fallback. | | flash_attn_2 | Forces FlashAttention 2. The loader raises a clear error if the optional package is unavailable in the ComfyUI Python environment. | | flash_attn_3 | Forces FlashAttention 3. The loader raises a clear error if the optional package is unavailable in the ComfyUI Python environment. | | xformers | Forces xFormers memory-efficient attention. The loader raises a clear error if xFormers is unavailable. | | sageattn | Forces SageAttention for DiT attention. The loader raises a clear error if SageAttention is unavailable. | | sageattn_3 | Reserved for SageAttention3 Blackwell kernels. It currently raises a clear error even when a candidate backend is present because LongCat text varlen cross-attention support is not fully wired; use sageattn instead. |

SageAttention support is optional. Install and validate the package in the same Python environment that launches ComfyUI. The node uses lazy imports and does not require SageAttention for startup or CPU-only tests. At model load, the console prints the requested attention_mode, effective backend flags, and backend availability so slow SDPA fallback is visible.

Audio Conditioning And Dual-Person Mode

LongCat Avatar Audio Encode supports a single-person path and an optional two-person dialogue path.

For single-person generation, connect only audio. Leave left_audio disconnected.

For two-person dialogue generation, the audio inputs are assigned by the characters' visual positions in the input image or video frame:

| Input | Meaning | | --- | --- | | left_audio | Speech for the person on the left side of the image or video frame | | audio | Speech for the person on the right side of the image or video frame |

The left/right naming does not refer to stereo audio channels. It refers to where the people appear in the visual frame. In a two-person image, connect the left person's speech to left_audio and the right person's speech to audio.

audio_type controls how the two clips are combined:

| audio_type | Meaning | | --- | --- | | para | Parallel dialogue. The left and right clips are treated as simultaneous tracks and should have matching duration. | | add | Sequential dialogue. The left clip is placed before the right clip with silence-padding semantics. |

p_box optionally tells the node where the people are in the image. Use comma-separated bounding boxes in this order:

[left_y_min, left_x_min, left_y_max, left_x_max], [right_y_min, right_x_min, right_y_max, right_x_max]

Measure these coordinates on the original image connected to Load Image, not on the generated 480p/720p output. The pipeline builds masks from the original-image coordinates first, then resizes and center-crops the masks together with the image for inference.

To get the values, open the source image in an image editor or viewer that shows cursor coordinates, then record each person's bounding rectangle:

1. Read the top-left point as x_min, y_min.
2. Read the bottom-right point as x_max, y_max.
3. Enter the box in LongCat order: [y_min, x_min, y_max, x_max].

Example: if the left person covers x=120..430, y=80..760, and the right person covers x=520..820, y=90..770, enter:

[80, 120, 760, 430], [90, 520, 770, 820]

The first box maps to left_audio; the second box maps to audio. A third box may be provided for other/background people that should receive silent background conditioning:

[left_y_min, left_x_min, left_y_max, left_x_max], [right_y_min, right_x_min, right_y_max, right_x_max], [other_y_min, other_x_min, other_y_max, other_x_max]

If p_box is empty, the node still builds audio conditioning, but it does not provide explicit person-location boxes to the multi-person path.

Generation Controls

• resolution: 480p maps to 480x832 and 720p maps to 768x1280.
• steps: defaults to 8 for Avatar 1.5 DMD/distill inference; accepted range is 1 to 50. When the DMD/distill LoRA is active, the effective value is fixed to the official 8-step contract.
• text_guidance_scale: defaults to 1.0; accepted range is 1.0 to 10.0. It only affects non-DMD normal inference; Avatar 1.5 DMD/distill inference forces the effective text CFG to 1.0.
• audio_guidance_scale: defaults to 1.0; accepted range is 1.0 to 10.0. It only affects non-DMD normal inference; Avatar 1.5 DMD/distill inference forces the effective audio CFG to 1.0.
• LongCat Avatar Audio Encode computes num_segments automatically from the prepared input audio length and current save_fps. The first generated window is 93 frames; each continuation adds 80 new frames because the official window keeps 13 overlap frames. At 25 fps, an 18 second clip computes to 6 segments so generation covers the full audio. The sampler trims the generated segment envelope back to the source-audio frame count before returning image frames or muxing video.
• save_fps: defaults to 25. Treat 25 fps as the reliable Avatar 1.5 setting. Changing this value also changes audio-window segmentation and target output frame counts, but local validation showed non-25 fps values can make lip sync and motion timing unstable.
• ref_img_index: integer frame index for the reference image insertion/attention anchor used during continuation. It defaults to 10; official guidance commonly uses values in the 0 to 24 range for consistency.
• mask_frame_range: integer radius around ref_img_index where reference-frame attention is masked to reduce repeated motion. It defaults to 3; larger values may reduce repeated actions but can introduce artifacts.
• p_box: optional person boxes for LongCat Avatar Audio Encode; see Audio Conditioning And Dual-Person Mode for left/right audio mapping and coordinate order.
• block_num: integer memory-streaming control. 0 uses eager full DiT loading on CUDA and offloads the DiT back to CPU after generation. Values from 1 to 64 enable streaming prefetch mode with that block count.
• offload_device: VAE offload target used during denoising. cpu is the default and preserves the lower-VRAM behavior. cuda keeps the VAE resident on the active CUDA device to avoid VAE CPU/GPU transfers, but requires more VRAM.
• inference_weight_mode: choose single_file_safetensors, official_sharded, or official_int8_sharded; the node auto-selects the corresponding default DiT source.
• auto_download_missing_weights: on/off toggle for bounded official sharded checkpoint download when required files are missing.
• auto_download_missing_text_encoder: on/off toggle on text encode nodes for bounded shared base LongCat-Video tokenizer/text encoder download.
• LongCat Avatar Text Encode offload_device: chooses where the native official UMT5 text encoder is loaded for prompt encoding. cpu is the default to avoid loading the large text encoder into VRAM; cuda can be faster but needs substantially more VRAM. This is ignored when clip is connected for fallback.
• mux_audio_path: optional local audio file path used to mux audio into the generated video. Leave it empty to return only image frames and an empty video_path. When provided, the node saves a muxed .mp4 under the ComfyUI output directory using the built-in longcat_avatar filename prefix.
• debug_mode: when enabled on LongCat Avatar Sampler, prints detailed phase timing, CUDA synchronization, and memory counters around cache cleanup, runtime-plan setup, generation, cleanup, and video muxing.

Alternate scheduler controls are not exposed. Reference-wrapper scheduler names such as longcat_distill_euler are not adopted unless official Avatar 1.5 parity is proven with source comparison and tests.

Avatar 1.5 Usage Tips

| Tip | Repo-aligned guidance | | --- | --- | | Prompt detail | Use longer, descriptive prompts for better consistency. Include character appearance, speaking action, clothing, and scene context, for example: A young woman with long black hair is speaking and smiling, wearing a white blouse, sitting in a bright cafe. | | Reference frame controls | ref_img_index defaults to 10. Values in the 0 to 24 range are commonly used for consistency; 30 can be tried when repeated motion is visible. mask_frame_range defaults to 3; larger values may reduce repeated actions but can introduce artifacts. | | Resolution | The sampler supports 480p and 720p through the resolution control. In this ComfyUI node, 480p maps to 480x832 and 720p maps to 768x1280. | | Dual-audio mode | audio_type=para is for simultaneous two-person dialogue and requires equal prepared clip lengths. audio_type=add makes a sequential turn-taking track: left_audio first, then audio, with silence padding semantics. | | Avatar version | This ComfyUI package supports Avatar 1.5 only. Avatar 1.5 uses Whisper-large-v3 audio conditioning; Avatar 1.0/Wav2Vec2 is not a supported runtime path in this repo. | | Distill inference | Avatar 1.5 requires the DMD/distill LoRA. When the DMD LoRA is active, the effective sampler values are fixed to 8 steps, text CFG 1.0, and audio CFG 1.0; UI CFG inputs are accepted but do not affect inference. CFG tuning only applies to non-DMD normal inference. | | INT8 mode | INT8 is supported for Avatar 1.5 through official_int8_sharded or a compatible INT8 single-file DiT source. Use it when you want lower VRAM usage and have the required INT8 files available. |

Troubleshooting Desktop Installation

If ComfyUI Desktop reports the LongCat nodes as missing after installing Registry version 0.2.0, update the node pack to version 0.2.1 or later and fully restart ComfyUI. Version 0.2.0 omitted required fresh-install metadata and could fail before node registration; reinstalling current dependencies in the Python environment managed by ComfyUI Desktop and restarting clears that stale installation state.

The example workflow identifies this package as comfyui-longcat-avatar. When the package is absent, current ComfyUI frontends should group its missing nodes under that package name instead of an unknown pack. Model-file warnings are separate: follow Model Files after all LongCat node types are available.

License

This project is licensed under the MIT License.