Vito Sansevero
3ce9724f5f
The vocabulary fixture seeds own image categories on request
(image_categories: Landscapes on two images, Portraits on one image only).
mapVocabularyConcept maps D143 ("N positive prompts · M images", image-only
rows before Manage category), a model checked against the concept page with
those rows added at runtime, and mapVocabularyDialog takes the preview
sentence, so the Manage category preview is compared with D9 and D144's
images. The default fixture and mapping are unchanged.
272 lines
10 KiB
Python
272 lines
10 KiB
Python
"""Owned, deterministic vocabulary data for the native Tags & categories workflows.
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The six recipes are the approved concept's (docs/concepts/workspace/app.js:71-165)
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in concept order, so tag creation order and category first use match the mock.
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"""
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from __future__ import annotations
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from pathlib import Path
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from typing import TYPE_CHECKING
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from aiohttp import web
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from tests.browser.folder_trash import replace_folder
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if TYPE_CHECKING:
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from py.api import PromptManagerAPI
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CONCEPT_RECIPES = (
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{
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"title": "Alpine observatory",
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"category": "Landscapes",
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"tags": ["cinematic", "blue_hour", "architecture"],
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"positive": "A remote alpine observatory at blue hour, warm light through "
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"glass, dramatic mountain peaks, cinematic composition, atmospheric mist, "
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"fine detail",
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"negative": "blurry, low quality, low resolution",
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},
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{
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"title": "Quiet geometry",
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"category": "Architecture",
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"tags": ["minimal", "warm_light", "editorial"],
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"positive": "Monolithic sandstone pavilion in a vast desert, sweeping dunes, "
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"warm terracotta, late afternoon sun, architectural photography, quiet "
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"geometry",
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"negative": "plastic, harsh shadows, noise, watermark",
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},
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{
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"title": "Somewhere in the pines",
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"category": "Landscapes",
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"tags": ["forest", "mist", "peaceful"],
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"positive": "A quiet cedar cabin above a still forest lake, towering "
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"evergreens, soft morning mist, muted jade and moss, a small amber window, "
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"cinematic still",
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"negative": "oversaturated, blurry, low quality, text",
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},
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{
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"title": "After the rain",
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"category": "Environments",
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"tags": ["neon", "night", "cinematic"],
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"positive": "Rain-soaked city street at night, blue neon and rose "
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"reflections, deep perspective, cinematic science fiction, solitary "
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"architecture, detailed atmosphere",
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"negative": "blurry, low resolution, watermark, oversaturated",
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},
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{
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"title": "The long way home",
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"category": "Illustration",
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"tags": ["space", "minimal", "concept_art"],
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"positive": "An isolated lunar research outpost, a luminous planet above the "
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"horizon, sweeping pale terrain, quiet science fiction, finely detailed "
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"concept art",
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"negative": "blurry, low quality, watermark",
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},
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{
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"title": "Between sea and sky",
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"category": "Landscapes",
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"tags": ["coast", "soft_light", "peaceful"],
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"positive": "A solitary lighthouse on a rugged coastal cliff, sea mist, "
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"glints of morning light on turquoise water, atmospheric perspective, fine "
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"art landscape",
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"negative": "oversaturated, flat lighting, watermark, text",
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},
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)
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# #332 D143/D144 (opt-in, ``image_categories``): own image categories, one on
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# images only and one shared with prompts. Stored rows count whether or not the
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# files exist, so the keys name files the fixture never writes.
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IMAGE_CATEGORY_ROWS = (("Landscapes", 2), ("Portraits", 1))
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PAIR_ONLY_TAG = "pair_only_detail"
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ARCHIVED_ONLY_TAG = "archived_pair_detail"
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NEGATIVE_ONLY_TAG = "legacy_negative_detail"
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UNUSED_TAG = "unused_vocabulary"
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MAX_EXTRA_TAGS = 300
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MAX_EXTRA_CATEGORIES = 200
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_TABLES = (
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"saved_views",
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"image_favorites",
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"media_review_decisions",
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"media_review_items",
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"media_image_tags",
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"media_annotation_bytes",
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"media_annotation_files",
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"image_categories",
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"image_prompt_pairs",
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"prompt_pair_tags",
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"prompt_pairs",
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"generated_images",
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"prompt_tags",
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"tags",
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"prompt_library_state",
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"prompts",
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)
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# Every owner row a vocabulary command could touch, in a stable order, for
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# before/after comparisons; prompt text, pairs and images must never change.
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_SNAPSHOT = {
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"tags": "SELECT id, name FROM tags ORDER BY id",
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"prompt_tags": "SELECT prompt_id, tag_id FROM prompt_tags ORDER BY 1, 2",
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"prompt_pair_tags": "SELECT pair_id, tag_id FROM prompt_pair_tags ORDER BY 1, 2",
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"prompts": "SELECT id, text, category, tags, updated_at FROM prompts ORDER BY id",
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"prompt_pairs": "SELECT id, positive_prompt_id, negative_prompt_id, category,"
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" archived, updated_at FROM prompt_pairs ORDER BY id",
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"generated_images": "SELECT id, prompt_id, image_path FROM generated_images"
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" ORDER BY id",
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"image_prompt_pairs": "SELECT id, image_id, pair_id FROM image_prompt_pairs"
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" ORDER BY id",
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}
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def _seed_image_categories(api: PromptManagerAPI) -> dict:
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"""Own image category rows keyed as Images keys them; ``{value: count}``."""
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from py.api.images import image_category_key
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sources = list(api._get_all_output_dirs())
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for category, count in IMAGE_CATEGORY_ROWS:
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keys = [
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image_category_key(sources, str(Path(sources[0]) / f"{category}_{n}.png"))
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for n in range(count)
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]
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api.db.set_image_categories(keys, category)
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return dict(IMAGE_CATEGORY_ROWS)
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def seed_vocabulary(
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api: PromptManagerAPI,
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root: Path,
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extra_tags: int = 0,
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extra_categories: int = 0,
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image_categories: bool = False,
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) -> dict:
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"""Replace this server's disposable rows with the concept vocabulary."""
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db = api.db
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with db.model.get_connection() as conn:
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for table in _TABLES:
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conn.execute(f"DELETE FROM {table}")
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for name in ("output", "input"):
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replace_folder(root / name)
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epoch = db.get_execution_epoch()
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recipes = []
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for recipe in CONCEPT_RECIPES:
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receipt = db.create_library_recipe(
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recipe["positive"],
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recipe["negative"],
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expected_epoch=epoch,
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parent_metadata={
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"title": recipe["title"],
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"category": recipe["category"],
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"tags": list(recipe["tags"]),
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},
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)
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recipes.append(
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{"positive_id": receipt["positive"]["id"], "pair_id": receipt["pair"]["id"]}
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)
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first = CONCEPT_RECIPES[0]["positive"]
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# A tag carried only by an active saved pair counts its Library parent.
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db.save_prompt_pair(first, "grain, banding", tags=[PAIR_ONLY_TAG])
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# A tag carried only by an archived pair is hidden from Library Browse.
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archived = db.save_prompt_pair(
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CONCEPT_RECIPES[1]["positive"], "lens flare", tags=[ARCHIVED_ONLY_TAG]
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)
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db.archive_prompt_pair(archived, True)
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# A legacy tag on a negative-only component is never a Library parent.
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with db.model.get_connection() as conn:
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negative_id = conn.execute(
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"SELECT negative_prompt_id FROM prompt_pairs WHERE id=?",
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(recipes[2]["pair_id"],),
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).fetchone()[0]
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db.update_prompt_metadata(negative_id, tags=[NEGATIVE_ONLY_TAG])
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db.create_vocabulary_tag(UNUSED_TAG, expected_epoch=epoch)
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for number in range(extra_tags):
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db.create_vocabulary_tag(f"bulk_tag_{number:04}", expected_epoch=epoch)
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# Each extra category is carried by one minimal Library recipe, after the concept's.
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for number in range(extra_categories):
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db.create_library_recipe(
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f"Bulk category recipe {number:04}",
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"",
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expected_epoch=epoch,
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parent_metadata={
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"title": f"Bulk {number:04}",
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"category": f"bulk_category_{number:04}",
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},
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)
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images = _seed_image_categories(api) if image_categories else {}
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with db.model.get_connection() as conn:
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tags = [row[0] for row in conn.execute("SELECT name FROM tags ORDER BY id")]
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api.invalidate_gallery_cache()
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return {
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"epoch": epoch,
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"recipes": recipes,
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"archived_pair_id": archived,
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"negative_only_id": negative_id,
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"tags": tags,
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"pair_only_tag": PAIR_ONLY_TAG,
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"archived_only_tag": ARCHIVED_ONLY_TAG,
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"negative_only_tag": NEGATIVE_ONLY_TAG,
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"unused_tag": UNUSED_TAG,
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"image_categories": images,
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}
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def vocabulary_snapshot(api: PromptManagerAPI) -> dict:
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"""Plain rows of every vocabulary owner table."""
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with api.db.model.get_connection() as conn:
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return {
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name: [list(row) for row in conn.execute(query)]
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for name, query in _SNAPSHOT.items()
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}
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def register_vocabulary_commands(
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routes: web.RouteTableDef, api: PromptManagerAPI, root: Path
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) -> None:
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"""Register only fixed seed, snapshot and backup commands; no paths or SQL input."""
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@routes.post("/__test__/vocabulary/reset")
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async def reset(request: web.Request) -> web.Response:
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data = await request.json() if request.can_read_body else {}
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if not isinstance(data, dict) or set(data) - {
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"extra_tags",
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"extra_categories",
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"image_categories",
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}:
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raise web.HTTPBadRequest()
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images = data.get("image_categories", False)
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if not isinstance(images, bool):
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raise web.HTTPBadRequest()
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extra = data.get("extra_tags", 0)
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categories = data.get("extra_categories", 0)
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for value, limit in (
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(extra, MAX_EXTRA_TAGS),
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(categories, MAX_EXTRA_CATEGORIES),
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):
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if isinstance(value, bool) or not isinstance(value, int):
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raise web.HTTPBadRequest()
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if not 0 <= value <= limit:
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raise web.HTTPBadRequest()
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if request.query:
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raise web.HTTPBadRequest()
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manifest = await api._run_in_executor(
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seed_vocabulary, api, root, extra, categories, images
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)
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return web.json_response({"success": True, **manifest})
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@routes.get("/__test__/vocabulary/snapshot")
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async def snapshot(request: web.Request) -> web.Response:
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if request.query:
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raise web.HTTPBadRequest()
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rows = await api._run_in_executor(vocabulary_snapshot, api)
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return web.json_response(rows)
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@routes.get("/__test__/vocabulary/backup")
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async def backup(request: web.Request) -> web.Response:
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"""A database copy for the real restore route, which rotates the epoch."""
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if request.query:
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raise web.HTTPBadRequest()
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path = root / "owned-vocabulary-backup.db"
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created = await api._run_in_executor(api.db.model.backup_database, str(path))
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if not created:
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raise web.HTTPInternalServerError()
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return web.Response(
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body=path.read_bytes(), content_type="application/octet-stream"
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)
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