mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-09-21 03:01:27 -03:00
Will Miao
35b291ab19
ModelScope's model card is not just README.md: the author's summary (Description), the site-curated tags (OfficialTags), the internal architecture enums (VisionFoundation/SubVisionFoundation) and — per published version — the model filenames with that file's example images (coverImages) and trigger words all live in the model-detail API. AIGC repositories there frequently ship an auto-generated boilerplate README and put the only useful text in Description, so reading just the README yielded almost nothing. Add `ModelSource.fetch_model_card_context()` returning a new `ModelCardContext`, implemented by ModelScopeSource against the public (no API key) detail endpoint. Example images are matched to the model's basename through each version's `stats.fileList`, so every checkpoint in a collection repository gets its own images rather than a sibling's. Consume the context in the post-processor: * example images seed `civitai.images` and, being per-file, take priority in the preview fallback chain * the author summary becomes a paragraph in `modelDescription` and fills `civitai.description` when the LLM returns no short description * site-curated tags are always merged in, which also fixes the official `character-enhancement` being dropped by the prompt's no-hyphen rule * per-file trigger words are used before the repo-wide YAML `instance_prompt` * an explicitly stated strength range is recovered by regex so `usage_tips` is populated even without an LLM The prompt gains a Site-Provided Metadata section so the LLM can prefer the site's first-hand data over its own guesses.
76 lines
1.8 KiB
Python
76 lines
1.8 KiB
Python
"""External model-source providers (Hugging Face, ModelScope, TensorArt).
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This package is the single abstraction over "a site that hosts models and
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a model card". See :mod:`py.services.model_sources.base` for the provider
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protocol and :mod:`py.services.model_sources.registry` for the lookup and
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metadata-normalisation helpers used across the codebase.
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"""
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from __future__ import annotations
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from .base import (
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GROUP_PREFIXES,
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HTTP_TIMEOUT,
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ModelCardContext,
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ModelSource,
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ModelSourceError,
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SourceRef,
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USER_AGENT,
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clean_source_url,
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fetch_json,
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fetch_text,
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filter_weight_files,
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is_valid_source_id,
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)
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from .huggingface import HuggingFaceSource
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from .modelscope import ModelScopeSource
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from .registry import (
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LEGACY_HF_URL_FIELD,
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SOURCE_PLATFORM_FIELD,
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SOURCE_URL_FIELD,
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detect_source,
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downloadable_sources,
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get_download_source,
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get_source,
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get_source_platform,
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has_external_source,
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list_sources,
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normalize_metadata_source,
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resolve_source_ref,
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source_group_key,
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source_label,
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)
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from .tensorart import TensorArtSource
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__all__ = [
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"GROUP_PREFIXES",
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"HTTP_TIMEOUT",
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"LEGACY_HF_URL_FIELD",
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"ModelCardContext",
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"ModelSource",
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"ModelSourceError",
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"HuggingFaceSource",
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"ModelScopeSource",
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"SOURCE_PLATFORM_FIELD",
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"SOURCE_URL_FIELD",
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"SourceRef",
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"TensorArtSource",
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"USER_AGENT",
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"clean_source_url",
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"detect_source",
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"downloadable_sources",
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"fetch_json",
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"fetch_text",
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"filter_weight_files",
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"get_download_source",
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"get_source",
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"get_source_platform",
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"has_external_source",
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"is_valid_source_id",
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"list_sources",
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"normalize_metadata_source",
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"resolve_source_ref",
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"source_group_key",
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"source_label",
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]
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