DemonGatanjieuandClaude Opus 5.5
5667fa2d9e
Types go by their usual names, base model chips narrow the list, the version stands apart from the name, and a model's versions are one card whose version opens the list to show another; a pick goes with it. The grouping, the families and the type names are the Models page's own. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
91 lines
5.4 KiB
Python
91 lines
5.4 KiB
Python
"""Everything the materials picker (web/modules/ui_ai_toolbox.js) lists besides node types, in
|
|
one answer (GET /anomalous/ai_toolbox?kind=all): combos with their cover and prompt, saved
|
|
workflows with their cover, tags and prompts, prompts (the saved ones, and the ones inside
|
|
combos and workflows, ids "combo:<name>" and "workflow:<name>"), and models with their cover and
|
|
what the Models page groups them by (`metadata`: its version page, its base model),
|
|
by the names and ids the AI's tools use, and what the ways are called, for a picked way's chip. Read in one
|
|
go and kept a few seconds, so the picker opens at once; node types come from the page's own node definitions. prompt_entries() also
|
|
gives get_toolbox the text of picked prompts."""
|
|
|
|
import threading
|
|
import time
|
|
|
|
from . import mcp_tools, reference_blocks
|
|
from .model_catalog import _collect_all_scan_models
|
|
from .notebooks import _list_notebooks
|
|
from .quick_index import compact_models
|
|
from .recipe_store import _list_recipes, get_recipes_dir
|
|
|
|
CACHE_SECONDS = 15
|
|
MAX_TEXT = 1500
|
|
MAX_THUMBNAIL = 60_000 # an inline thumbnail larger than this is left out; the cover asset or the default stands in
|
|
_cache = {"at": 0.0, "data": None}
|
|
_lock = threading.Lock()
|
|
|
|
|
|
def _join(texts, limit=MAX_TEXT):
|
|
text = "\n".join(str(item).strip() for item in texts or [] if str(item or "").strip())
|
|
return text if len(text) <= limit else text[:limit] + "…"
|
|
|
|
|
|
def _combos():
|
|
out = []
|
|
for note in _list_notebooks():
|
|
data = note.get("data") or {}
|
|
combo, loras = mcp_tools.combo_view(note)
|
|
out.append({"name": combo["name"], "model": combo["main_model"], "loras": loras[:12], "base": combo.get("base_model") or "",
|
|
"prompt": combo["prompt"], "structure": data.get("kind") == "nodes",
|
|
"cover": (data.get("mainModel") or {}).get("preview_url") or "" if isinstance(data.get("mainModel"), dict) else "",
|
|
"image": data.get("source_image") if isinstance(data.get("source_image"), dict) else None})
|
|
return out
|
|
|
|
|
|
def _workflows():
|
|
out = []
|
|
for recipe in _list_recipes(get_recipes_dir()):
|
|
data = recipe.get("data") or {}
|
|
params = data.get("params") if isinstance(data.get("params"), dict) else {}
|
|
thumbnail = data.get("thumbnail") if isinstance(data.get("thumbnail"), str) and len(data["thumbnail"]) <= MAX_THUMBNAIL else None
|
|
out.append({"name": data.get("name") or recipe["filename"], "filename": recipe["filename"], "tags": (data.get("tags") or [])[:8],
|
|
"notes": str(data.get("notes") or "")[:300], "partial": data.get("workflow_scope") == "partial",
|
|
"nodes": len(params.get("nodes") or []), "base": params.get("baseModel") or "",
|
|
"prompt": _join(params.get("promptPositive")), "negative": _join(params.get("promptNegative"), 600),
|
|
"cover_asset": (data.get("presentation") or {}).get("cover_asset_id"), "thumbnail": thumbnail,
|
|
"image": data.get("source_image") if isinstance(data.get("source_image"), dict) else None,
|
|
"saved": data.get("timestamp") or 0})
|
|
return out
|
|
|
|
|
|
def _models():
|
|
out = []
|
|
for model in compact_models(_collect_all_scan_models(1, 0).get("models") or []):
|
|
place = f"{model['subfolder']}/{model['filename']}" if model["subfolder"] else model["filename"]
|
|
out.append({"id": f"{model['type']}:{model['path_idx']}:{place}", "name": model["name"] or model["civitai_name"] or model["filename"],
|
|
"file": model["filename"], "type": model["type"], "base": model["base"], "words": model["words"],
|
|
"cover": model["preview_url"], "folder": model["subfolder"],
|
|
"metadata": {"model_id": model["page"], "version_id": model["version"], "version_name": model["version_name"],
|
|
"baseModel": model["base"], "base_guess": model["base_guess"]}})
|
|
return out
|
|
|
|
|
|
def prompt_entries(combos, workflows):
|
|
"""The prompts the picker lists: saved ones (id = name), then those of combos and workflows."""
|
|
entries = [{"id": prompt["name"], "name": prompt["name"], "source": "saved", "tags": prompt["tags"],
|
|
"positive": prompt["positive"], "negative": prompt["negative"]} for prompt in mcp_tools.saved_prompts()]
|
|
entries += [{"id": f"combo:{combo['name']}", "name": combo["name"], "source": "combo", "tags": [],
|
|
"positive": combo["prompt"], "negative": ""} for combo in combos if combo["prompt"]]
|
|
entries += [{"id": f"workflow:{flow['name']}", "name": flow["name"], "source": "workflow", "tags": flow["tags"],
|
|
"positive": flow["prompt"], "negative": flow["negative"]} for flow in workflows if flow["prompt"] or flow["negative"]]
|
|
return entries
|
|
|
|
|
|
def everything(fresh=False):
|
|
"""{combos, workflows, prompts, models, ways}, read at most every CACHE_SECONDS."""
|
|
with _lock:
|
|
if fresh or _cache["data"] is None or time.monotonic() - _cache["at"] > CACHE_SECONDS:
|
|
combos, workflows = _combos(), _workflows()
|
|
_cache.update(at=time.monotonic(), data={"combos": combos, "workflows": workflows,
|
|
"ways": {name: block["title"] for name, block in reference_blocks.BLOCKS.items()},
|
|
"prompts": prompt_entries(combos, workflows), "models": _models()})
|
|
return _cache["data"]
|