DemonGatanjieuandClaude Opus 5.5
414e76c935
- header_words.py: modelspec.trigger_phrase, else the tags most training pictures share (ss_tag_frequency, generic ones left out); the scanner keeps them as anomalous_header_words when Civitai gives no trigger words, metadata gives headerWords, model search finds them. - model_kind: Flux Schnell told from Dev (no guidance_in), Z-Image from Lumina 2 (caption embedder width, a GGUF by parameter count); RULES 3 so kept header answers are read again. - api/model_guide.py + model_profiles.json: GET /anomalous/model_guide for the model details (example settings, header words, the text encoder and VAE a diffusion models file needs, found by name), and get_model's header_words and usage for the AI. - model_advice.example_settings gives the author's example settings as values; author_examples says them in words as before. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
102 lines
4.1 KiB
Python
102 lines
4.1 KiB
Python
"""What using a model takes besides its file, for the model details (GET /anomalous/model_guide)
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and the AI's get_model: the settings of its author's example pictures (model_advice), the words
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its own header suggests when Civitai gave no trigger words (header_words.py: kept by the scan,
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else read now), and, by its base model family (model_profiles.json), the files a drawing model
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loaded in parts needs beside it, with the one this ComfyUI has by that name, and notes for the AI.
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The page names a model by type, folder index, subfolder and file name, never by a path."""
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import asyncio
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import json
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import os
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import re
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import folder_paths
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from aiohttp import web
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from . import model_advice
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from .metadata import get_metadata
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from .model_constants import MODEL_EXTENSIONS
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from .path_utils import model_file_within, resolve_folder_subdir
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try:
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from ..header_words import of_file as header_words_of
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except ImportError: # loaded outside the package (tests)
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from header_words import of_file as header_words_of
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with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), "model_profiles.json"), encoding="utf-8") as _source:
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FAMILIES = json.load(_source)["families"]
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PART_FOLDERS = ("diffusion_models", "unet") # a checkpoint carries its text encoders and VAE
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def profile(base):
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"""The family whose marks start `base` (a base model name), else None."""
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lowered = str(base or "").strip().lower()
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return next((family for family in FAMILIES if lowered and lowered.startswith(tuple(family["marks"]))), None)
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def _plain(name):
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return re.sub(r"[^a-z0-9]", "", os.path.splitext(os.path.basename(name))[0].lower())
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def _found(part):
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"""The first file in the part's folder with one of its names in its own, "" when none."""
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try:
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listed = folder_paths.get_filename_list(part["folder"])
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except KeyError:
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return ""
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for name in listed:
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plain = _plain(name)
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if any(plain == wanted or (len(wanted) > 3 and wanted in plain) for wanted in part["names"]):
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return name
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return ""
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def parts(folder_type, base):
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"""[{"folder", "file", "found"}]: what a drawing model loaded in parts needs beside it; [] for others."""
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family = profile(base)
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if folder_type not in PART_FOLDERS or not family:
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return []
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return [{"folder": part["folder"], "file": part["file"], "found": _found(part)} for part in family.get("parts", [])]
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def words(path, folder_type, meta):
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"""What a LoRA's header suggests when Civitai gave no trigger words: kept by the scan, else read now."""
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if folder_type != "loras" or meta.get("trainedWords"):
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return []
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return list(meta.get("headerWords") or []) or header_words_of(path)
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def usage(folder_type, base):
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"""For the AI: the family's notes and the files it needs here, {} when nothing is known."""
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family = profile(base)
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if not family:
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return {}
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found = {"family": family["family"]}
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needed = parts(folder_type, base)
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if needed:
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found["needs"] = [f"{part['folder']}: {part['file']}" + (f" (here: {part['found']})" if part["found"] else " (none here by that name)")
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for part in needed]
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if family.get("notes"):
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found["notes"] = family["notes"]
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return found
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def guide(path, folder_type):
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meta = get_metadata(path)
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base = meta.get("baseModel") or meta.get("base_guess") or ""
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return {"examples": model_advice.example_settings(path, folder_type, meta.get("hash", "")),
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"words": words(path, folder_type, meta), "parts": parts(folder_type, base)}
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async def api_model_guide(request):
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query = request.query
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folder_type = query.get("type", "")
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try:
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_base, folder = resolve_folder_subdir(folder_type, int(query.get("path_idx", 0)), query.get("subfolder", ""))
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path = model_file_within(folder, query.get("filename", ""))
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except (ValueError, KeyError):
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return web.json_response({"error": "bad request"}, status=400)
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if not path.lower().endswith(MODEL_EXTENSIONS) or not os.path.isfile(path):
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return web.json_response({"error": "not found"}, status=404)
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return web.json_response(await asyncio.to_thread(guide, path, folder_type))
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