capsule AI-native Unix-like composition layer

capsule.yaml

1,938 bytes · 53 lines · capsule://quake0day/[email protected] raw on github

apiVersion: capsule.dev/v0.1
kind: Capsule
name: cverse-avatar-inference-adapter
version: 0.1.0
type: adapter
purpose:
  summary: 'Provides adapters for real-time avatar generation models, specifically
    FlashHead and SoulX-LiveAct. This capsule integrates these complex model implementations
    into the core inference service.

    '
  owns:
  - Base avatar plugin interface
  - FlashHead model implementation and utilities
  - SoulX-LiveAct model implementation and utilities
  does_not_own:
  - The core inference service
  - Other AI model types (ASR, LLM, TTS, etc.)
interfaces:
  provides:
  - kind: library
    name: avatar-plugin
    description: Avatar model implementations conforming to the inference core's plugin
      interface.
dependencies:
  capsules:
  - name: cverse-inference-core
    version: '>=0.1.0'
agent:
  summary_for_ai: 'An AI agent working on this capsule would focus on improving avatar
    generation quality, optimizing model performance (e.g., latency, VRAM usage),
    or integrating new avatar models. It requires deep knowledge of real-time video
    generation, computer vision, and machine learning frameworks (e.g., PyTorch).

    '
  avoid:
  - Modifying the core inference service or other AI model types.
verification:
  invariants:
  - Avatar plugins must generate video streams from audio/visual inputs.
  - Plugins must adhere to the defined avatar plugin interface.
  - Output video must be synchronized with audio.
x-reuse:
  notes: 'This capsule bundles two large, complex model implementations (FlashHead
    and SoulX-LiveAct). While the plugin interface is generic, the models themselves
    are highly specialized. Consumers would likely replace these with their own avatar
    models or use pre-trained versions. Model weights and specific training data are
    not included but are implied dependencies for these models to function.

    '
x-reconstruct:
  install: install.json