Step 6. Read from upstream's avatar demo rather than assumed, because almost nothing
carries over from the base model:

- avatar is a DIFFERENT pipeline class, LongCatVideoAvatarPipeline, with its own methods
  generate_at2v / generate_ai2v / generate_avc;
- it takes TWO guidance scales — text and audio — where the base pipeline takes one;
- its distilled pass is dmd_lora at 8 steps with lora_network_dim=128/alpha=64 and
  dit.enable_loras(["dmd"]), NOT cfg_step_lora at 16;
- use_int8 is a separate load_quantized_dit(subfolder="base_model_int8"), not a dtype;
- both INT8 and the DMD LoRA exist only for avatar-1.5, which also REQUIRES distilled
  sampling;
- the audio is librosa.load(sr=16000) then pipe.get_audio_embedding(...), and the encoder
  differs per family (chinese-wav2vec2-base for Avatar, whisper-large-v3 for Avatar-1.5).

Unsupported combinations are refused BEFORE loading, because the alternative is quietly
serving something that is not what was asked for: INT8 or DMD on anything but
avatar-1.5, avatar-1.5 without distilled sampling, a base-model mode on avatar weights or
the reverse, and GGUF, which needs ComfyUI's gguf loader and says so.

FP8 loads the DiT as float8_e4m3fn. Community layouts differ between publishers (Kijai's
scaled format is not a plain e4m3 dump), so a repo that needs its own loader fails with
that reason rather than producing noise.

Also: librosa is a real new dependency and went into requirements-longcat.txt, not only
into the code that imports it. And the avatar audio comes from the request's `audio_file`
field — `add_audio` is a BOOLEAN for the post-processing path, and using it would have
passed True into the base64 encoder.

35 new tests, 188 across the six LongCat suites.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_0182DhR1eFNPQyGmDrpHbedY