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32f837add1
Turn a text prompt into a petdex-spec spritesheet (8×9 grid of 192×208 cells), grounded so every animation row stays the same creature: - orchestrate: base drafts (distinct variation nudges) → per-row grounded generation → atlas compose; one image call per row, rows fan out in parallel. - atlas: frame-perfect registration in normalize_cells — 1-D cross-correlation of each frame's column-mass profile locks the body (robust to limbs/cape), one shared per-state scale, bottom-anchored; plus alpha-hole repair, gutter severing, and interior-seeded chroma-pocket clearing. - prompts: pixel-art-by-default style hints + registration constraints. - store: local pet write (register_local_pet), slugify/unique_slug, export_pet, slug-realigning rename_pet, createdBy provenance.
29 lines
882 B
Python
29 lines
882 B
Python
"""Pet generation — base-draft → hatch pipeline.
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Public surface used by the gateway RPCs, the CLI ``hermes pets generate``
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command, and tests:
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- :func:`generate_base_drafts` / :func:`hatch_pet` — the two-step flow.
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- :class:`HatchResult`, :class:`GenerationError`.
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- :mod:`atlas` — deterministic frame extraction + atlas composition/validation.
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Image generation is delegated to the active reference-capable
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:class:`~agent.image_gen_provider.ImageGenProvider` (OpenAI gpt-image-2 or Krea);
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atlas assembly is fully deterministic so it's testable without any API calls.
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"""
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from __future__ import annotations
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from agent.pet.generate.imagegen import GenerationError
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from agent.pet.generate.orchestrate import (
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HatchResult,
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generate_base_drafts,
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hatch_pet,
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)
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__all__ = [
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"GenerationError",
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"HatchResult",
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"generate_base_drafts",
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"hatch_pet",
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]
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