Compare commits
4
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
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7c49250267 | ||
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c5aa575ac3 | ||
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6623ffa04c | ||
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0ee8280ddb |
@@ -0,0 +1,128 @@
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"""Regenerate ``src/calliope/comfyui/ui_widget_orders.py`` (HEL-681).
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Offline widget-order registry for the UI→API converter. Sources, in priority:
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1. ``widgets_values_named`` instances across ``example_ComfyUI_workflows``
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(including subgraph inner nodes) — the frontend serializes named widgets
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in widget order, so the key order IS the serialization order;
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2. the repo's 10 ground-truth API exports (root ``*_API.json``) — scalar
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input names in export order (control_after_generate entries are absent
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there; the converter's walk skips them positionally).
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Run from anywhere inside the repo:
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python scripts/build_widget_orders.py
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"""
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from __future__ import annotations
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import collections
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import json
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from pathlib import Path
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BACKEND = Path(__file__).resolve().parents[1]
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REPO = BACKEND.parent
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EXAMPLES = REPO / "example_ComfyUI_workflows"
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OUT = BACKEND / "src" / "calliope" / "comfyui" / "ui_widget_orders.py"
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BUTTONS = {"preview", "audioUI", "compare_view", "ToggleableColorPicker", "imagebrowser"}
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MAX_SIGNATURES = 3
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MAX_ORDER_LEN = 48
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# Hand-curated fallbacks for node classes the corpus never serializes with
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# names (classic core/custom widgets whose order is stable and public).
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CURATED: dict[str, list[list[str]]] = {
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"PrimitiveNode": [["value"]],
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"Seed (rgthree)": [["seed"]],
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}
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def _iter_ui_nodes() -> list[dict]:
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nodes: list[dict] = []
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for path in sorted(EXAMPLES.rglob("*.json")):
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try:
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data = json.loads(path.read_text(encoding="utf-8"))
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except (json.JSONDecodeError, OSError):
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continue
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if not (isinstance(data, dict) and isinstance(data.get("nodes"), list)):
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continue
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nodes.extend(n for n in data["nodes"] if isinstance(n, dict))
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for sub in data.get("definitions", {}).get("subgraphs", []) or []:
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if isinstance(sub, dict):
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nodes.extend(n for n in sub.get("nodes", []) or [] if isinstance(n, dict))
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return nodes
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def _iter_api_workflows() -> list[dict]:
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out: list[dict] = []
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for path in sorted(EXAMPLES.glob("*_API.json")):
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try:
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data = json.loads(path.read_text(encoding="utf-8"))
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except (json.JSONDecodeError, OSError):
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continue
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if isinstance(data, dict) and "nodes" not in data:
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out.append(data)
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return out
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def main() -> None:
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learned: dict[str, collections.Counter[tuple[str, ...]]] = collections.defaultdict(
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collections.Counter
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)
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for node in _iter_ui_nodes():
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named = node.get("widgets_values_named")
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if not isinstance(named, dict) or not named:
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continue
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keys = tuple(
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str(k) for k in named.keys() if k and k not in BUTTONS
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)
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if keys and len(keys) <= MAX_ORDER_LEN:
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learned[str(node.get("type") or "")][keys] += 1
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for workflow in _iter_api_workflows():
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for node in workflow.values():
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if not isinstance(node, dict):
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continue
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names = [
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str(k)
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for k, v in (node.get("inputs") or {}).items()
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if not isinstance(v, list) and k and k not in BUTTONS
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]
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if len(names) > MAX_ORDER_LEN:
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continue
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# Display nodes (PreviewAny…) carry zero scalar inputs — that
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# empty order is real signal: their positional arrays are pure
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# button leftovers and map to {}.
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learned[str(node.get("class_type") or "")][tuple(names)] += 1
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registry: dict[str, list[list[str]]] = {}
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for node_type, counter in sorted(learned.items()):
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if not node_type:
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continue
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orders: list[list[str]] = []
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for signature, _count in counter.most_common(MAX_SIGNATURES):
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orders.append(list(signature))
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if orders:
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registry[node_type] = orders
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for node_type, orders in CURATED.items():
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registry.setdefault(node_type, orders)
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body = json.dumps(registry, ensure_ascii=False, indent=1, sort_keys=True)
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OUT.write_text(
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'"""GENERATED by scripts/build_widget_orders.py — do not edit by hand.\n'
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"\n"
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"Widget-order registry for the UI→API converter: class_type → candidate\n"
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"widget name orders, learned from the repo's named-widget UI files and\n"
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"ground-truth API exports (HEL-681).\n"
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'"""\n'
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"\n"
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"from __future__ import annotations\n"
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"\n"
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f"WIDGET_ORDERS: dict[str, list[list[str]]] = {body}\n",
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encoding="utf-8",
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)
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total = sum(len(o) for orders in registry.values() for o in orders)
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print(f"wrote {OUT.name}: {len(registry)} node types, {total} orders total")
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if __name__ == "__main__":
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main()
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@@ -0,0 +1,170 @@
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"""Generate the HEL-681 dry-run report over the repo's UI workflow library.
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Walks ``example_ComfyUI_workflows`` (or ``--root``), runs every file through
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the production converter + lint + parser pipeline (exactly what
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``POST /api/workflows/convert`` does, minus HTTP), and writes a JSON detail
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file plus a human-readable Markdown summary. Read-only: nothing is imported,
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no DB is touched.
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Usage:
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python scripts/ui_import_dryrun.py [--root DIR] [--out PREFIX]
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"""
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from __future__ import annotations
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import argparse
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import collections
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import json
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import sys
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from pathlib import Path
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BACKEND = Path(__file__).resolve().parents[1]
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sys.path.insert(0, str(BACKEND / "src"))
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from calliope.comfyui.lint import workflow_warnings # noqa: E402
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from calliope.comfyui.metadata import suggested_metadata # noqa: E402
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from calliope.comfyui.parser import classify_usage # noqa: E402
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from calliope.comfyui.ui_convert import convert_ui_workflow # noqa: E402
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REPO = BACKEND.parent
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def main() -> int:
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parser = argparse.ArgumentParser()
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parser.add_argument("--root", default=str(REPO / "example_ComfyUI_workflows"))
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parser.add_argument("--out", default=str(REPO / "dryrun_report"))
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args = parser.parse_args()
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root = Path(args.root)
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out_prefix = Path(args.out)
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entries = []
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for path in sorted(root.rglob("*.json")):
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try:
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data = json.loads(path.read_text(encoding="utf-8"))
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except (json.JSONDecodeError, OSError) as exc:
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entries.append(
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{
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"source_path": str(path.relative_to(root)),
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"status": "fail",
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"issues": [{"code": "unreadable", "message": str(exc)}],
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}
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)
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continue
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if not (isinstance(data, dict) and isinstance(data.get("nodes"), list)):
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continue # API-format / non-workflow files are out of scope
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rel = str(path.relative_to(root))
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result = convert_ui_workflow(data)
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entry: dict = {
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"source_path": rel,
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"status": result.status,
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"needs_confirmation": result.needs_confirmation,
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"issues": [
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{"node_id": i.node_id, "code": i.code, "level": i.level, "message": i.message}
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for i in result.issues
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],
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}
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if result.workflow is not None:
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entry["node_count"] = len(result.workflow)
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entry["suggested"] = suggested_metadata(result.workflow, rel, data)
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errors = [w for w in workflow_warnings(result.workflow) if w["level"] == "error"]
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entry["lint_errors"] = [e["code"] for e in errors]
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entry["importable"] = not result.needs_confirmation and not errors
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else:
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entry["importable"] = False
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entries.append(entry)
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counts = collections.Counter(e["status"] for e in entries)
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code_counts = collections.Counter(
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i["code"] for e in entries for i in e["issues"]
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)
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category_counts = collections.Counter(
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(e.get("suggested") or {}).get("category") or "?" for e in entries
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)
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family_counts = collections.Counter(
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(e.get("suggested") or {}).get("model_family") or "?" for e in entries
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)
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importable = sum(1 for e in entries if e.get("importable"))
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needs_confirmation = sum(1 for e in entries if e["needs_confirmation"])
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lint_blocked = [e for e in entries if e.get("lint_errors")]
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detail = {
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"root": str(root),
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"total": len(entries),
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"status_counts": dict(counts),
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"issue_code_counts": dict(code_counts),
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"importable": importable,
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"needs_confirmation": needs_confirmation,
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"lint_blocked": [e["source_path"] for e in lint_blocked],
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"files": entries,
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}
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out_prefix.parent.mkdir(parents=True, exist_ok=True)
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(out_prefix.with_suffix(".json")).write_text(
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json.dumps(detail, ensure_ascii=False, indent=1), encoding="utf-8"
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)
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lines = [
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"# HEL-681 工作流 UI→API 转换 dry-run 报告",
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"",
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f"- 扫描目录:`{root}`(根目录 10 个 API 格式旧文件不在本管线范围)",
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f"- UI 格式文件总数:**{len(entries)}**",
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f"- 转换结果:ok **{counts.get('ok', 0)}** / warn **{counts.get('warn', 0)}** / fail **{counts.get('fail', 0)}**",
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f"- 其中「需人工确认」(控件无法可靠映射,禁止直接导入):**{needs_confirmation}**",
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f"- 通过转换+lint 后可直接导入:**{importable}**",
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f"- 转换成功但被现有 lint 拦截(导入时按阻止处理):**{len(lint_blocked)}**",
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"",
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"## 分类分布(自动提取)",
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"",
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"| 分类 | 数量 |",
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"|---|---|",
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]
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for cat, n in sorted(category_counts.items()):
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lines.append(f"| {cat} | {n} |")
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lines += ["", "## 模型家族分布(自动提取)", "", "| 家族 | 数量 |", "|---|---|"]
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for fam, n in sorted(family_counts.items(), key=lambda kv: -kv[1]):
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lines.append(f"| {fam} | {n} |")
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lines += ["", "## 问题代码统计", "", "| 代码 | 次数 | 含义 |", "|---|---|---|"]
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meaning = {
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"muted_input_dropped": "上游节点被静音,输入按未连接处理",
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"variable_upstream_dropped": "Set/Get 变量上游被旁路,取值按未连接处理",
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"get_without_set": "GetNode 没有同名 SetNode",
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"widget_unmapped": "控件值无法可靠映射到输入名(需人工确认)",
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"widget_order_mismatch": "控件数量与已知顺序不符(需人工确认)",
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"no_output_node": "图中无已知输出节点,全部活跃节点保留待确认",
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"cyclic_variable": "Set/Get 循环(FOR 循环流),该连线按未连接处理",
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"dangling_link": "连线指向不存在的节点",
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}
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for code, n in code_counts.most_common():
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lines.append(f"| `{code}` | {n} | {meaning.get(code, '')} |")
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lines += ["", "## 需人工确认文件清单", ""]
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for e in entries:
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if e["needs_confirmation"]:
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reasons = sorted({i["code"] for i in e["issues"]})[:3]
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lines.append(f"- `{e['source_path']}`({', '.join(reasons)})")
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lines += ["", "## lint 拦截文件清单", ""]
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for e in lint_blocked:
|
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lines.append(f"- `{e['source_path']}`({', '.join(e['lint_errors'])})")
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lines += [
|
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"",
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"## 逐文件结果",
|
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"",
|
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"| 文件 | 状态 | 节点数 | 分类 | 模型家族 | 用途 | 问题 |",
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"|---|---|---|---|---|---|---|",
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]
|
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for e in entries:
|
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sug = e.get("suggested") or {}
|
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issues = collections.Counter(i["code"] for i in e["issues"])
|
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issue_text = ", ".join(f"{c}×{n}" for c, n in issues.most_common(2)) or "-"
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usage = sug.get("usage") or ("待定" if sug.get("usage_ambiguous") else "-")
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lines.append(
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f"| `{e['source_path']}` | {e['status']} | {e.get('node_count', '-')} "
|
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f"| {sug.get('category') or '-'} | {sug.get('model_family') or '-'} "
|
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f"| {usage} | {issue_text} |"
|
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)
|
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(out_prefix.with_suffix(".md")).write_text("\n".join(lines) + "\n", encoding="utf-8")
|
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print(f"{len(entries)} files: {dict(counts)}, importable={importable}, nc={needs_confirmation}")
|
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print(f"report → {out_prefix}.md / {out_prefix}.json")
|
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return 0
|
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|
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|
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if __name__ == "__main__":
|
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raise SystemExit(main())
|
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@@ -0,0 +1,160 @@
|
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"""Suggested workflow metadata for imports (HEL-681 / S2 data layer).
|
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|
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Everything here derives from two honest sources: the repo directory the file
|
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came from (category) and the converted API graph itself (usage, media in/out,
|
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model family, note text). Per HEL-675's inventory, clean display names and
|
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tags stay human work — the suggestion is a starting point, never a guess that
|
||||
hides uncertainty.
|
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"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import re
|
||||
from typing import Any
|
||||
|
||||
from calliope.comfyui.parser import (
|
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classify_usage,
|
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parse_dynamic_inputs,
|
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parse_dynamic_outputs,
|
||||
)
|
||||
|
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# Repo top-level directory → (category key, display label). Directory names
|
||||
# are mapping sources only — they never surface to users verbatim.
|
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CATEGORY_DIRS: dict[str, tuple[str, str]] = {
|
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"0-基础处理:图像合并-音频分离-视频截取合并-图像视频放大": ("basic", "基础处理"),
|
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"1-语音生成": ("audio_tts", "语音生成"),
|
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"2-音乐生成": ("music", "音乐生成"),
|
||||
"3-图像生成": ("image", "图像生成"),
|
||||
"4-视频生成": ("video", "视频生成"),
|
||||
"5-数字人": ("digital_human", "数字人"),
|
||||
"6-动作迁移": ("motion_transfer", "动作迁移"),
|
||||
}
|
||||
|
||||
# Evidence patterns → model family. Shared VAE/text-encoder files must NOT
|
||||
# count (HEL-675: Anima/Z-Image graphs reference qwen_image_vae and get
|
||||
# mislabeled Qwen — `qwen.?image(?!_vae)` is deliberate).
|
||||
_FAMILY_PATTERNS: tuple[tuple[str, str], ...] = (
|
||||
(r"minimax[_\-]?(music|_audio)|MiniMaxMusic", "MiniMax-Music"),
|
||||
(r"minimax.?h3|minimax_h3|h3[-_]realism|fl2v[aa]?", "MiniMax-H3"),
|
||||
(r"ltx[-_.]?2", "LTX-2.5"),
|
||||
(r"ltx", "LTX"),
|
||||
(r"krea", "Krea2"),
|
||||
(r"qwen.?image(?!_vae)|qwen_image_2|qwen2vl|qwen3vl|Qwen3?[-.]?ASR|qwen3?[-_.]?tts", "Qwen"),
|
||||
(r"z[._-]?image", "Z-Image"),
|
||||
(r"flux", "Flux"),
|
||||
(r"\bwan", "Wan"),
|
||||
(r"ace[_-]?step", "ACE-Step"),
|
||||
(r"index[_-]?tts", "IndexTTS2"),
|
||||
(r"anima[-_.]?(turbo|klein)", "Anima"),
|
||||
(r"sdpose", "SDPose"),
|
||||
(r"gemma", "Gemma"),
|
||||
(r"instantmesh|instant_mesh", "InstantMesh"),
|
||||
(r"hidream", "HiDream"),
|
||||
)
|
||||
_FAMILY_RE = [(re.compile(pat, re.IGNORECASE), fam) for pat, fam in _FAMILY_PATTERNS]
|
||||
|
||||
# Main-model loaders dominate the vote: a UNET/checkpoint reference says far
|
||||
# more about the workflow's family than a shared VAE or text encoder does.
|
||||
_PRIMARY_LOADER_RE = re.compile(r"UNETLoader|CheckpointLoader|unet|diffusion_model", re.IGNORECASE)
|
||||
|
||||
# Directory names that carry family evidence the files' own widget values
|
||||
# lack (HEL-675: 14 krea2 files reference no "krea" string at all).
|
||||
_FAMILY_DIRS = (
|
||||
(re.compile(r"krea2", re.IGNORECASE), "Krea2"),
|
||||
(re.compile(r"Minimax-h3|uncensored", re.IGNORECASE), "MiniMax-H3"),
|
||||
(re.compile(r"Z-Image", re.IGNORECASE), "Z-Image"),
|
||||
(re.compile(r"Qwen-Image", re.IGNORECASE), "Qwen"),
|
||||
(re.compile(r"^Anima$", re.IGNORECASE), "Anima"),
|
||||
(re.compile(r"Flux", re.IGNORECASE), "Flux"),
|
||||
)
|
||||
|
||||
_NOTE_TYPES = frozenset({"Note", "MarkdownNote"})
|
||||
|
||||
|
||||
def category_from_source_path(source_path: str | None) -> tuple[str | None, str | None]:
|
||||
"""(category key, label) derived from the file's repo-relative path."""
|
||||
if not source_path:
|
||||
return None, None
|
||||
head = source_path.replace("\\", "/").split("/", 1)[0]
|
||||
return CATEGORY_DIRS.get(head, (None, None))
|
||||
|
||||
|
||||
def model_family_from(workflow: dict[str, Any], source_path: str | None = None) -> str | None:
|
||||
"""The graph's dominant model family: main-model loader references weigh
|
||||
triple, other node evidence single, and the repo sub-directory adds a
|
||||
strong vote for families the widget values don't spell out."""
|
||||
votes: dict[str, int] = {}
|
||||
for node in workflow.values():
|
||||
if not isinstance(node, dict):
|
||||
continue
|
||||
class_type = str(node.get("class_type") or "")
|
||||
blob = " ".join(
|
||||
[class_type]
|
||||
+ [str(v) for v in (node.get("inputs") or {}).values() if isinstance(v, str)]
|
||||
)
|
||||
weight = 3 if _PRIMARY_LOADER_RE.search(blob) else 1
|
||||
for pattern, family in _FAMILY_RE:
|
||||
if pattern.search(blob):
|
||||
votes[family] = votes.get(family, 0) + weight
|
||||
break # one vote per node: strongest family that node shows
|
||||
if source_path:
|
||||
parts = source_path.replace("\\", "/").split("/")
|
||||
for part in parts[1:2]:
|
||||
for pattern, family in _FAMILY_DIRS:
|
||||
if pattern.search(part):
|
||||
votes[family] = votes.get(family, 0) + 2
|
||||
if not votes:
|
||||
return None
|
||||
return max(votes.items(), key=lambda kv: kv[1])[0]
|
||||
|
||||
|
||||
def note_description(ui_workflow: dict[str, Any], limit: int = 160) -> str | None:
|
||||
"""First non-trivial author note as description material (never final copy)."""
|
||||
for node in ui_workflow.get("nodes") or []:
|
||||
if not isinstance(node, dict) or str(node.get("type")) not in _NOTE_TYPES:
|
||||
continue
|
||||
values = node.get("widgets_values")
|
||||
text = values[0] if isinstance(values, list) and values else None
|
||||
if isinstance(values, dict):
|
||||
text = values.get("text") or next(iter(values.values()), None)
|
||||
if isinstance(text, str):
|
||||
text = text.strip()
|
||||
if len(text) >= 8:
|
||||
return text[:limit].strip()
|
||||
return None
|
||||
|
||||
|
||||
def suggested_metadata(
|
||||
converted: dict[str, Any],
|
||||
source_path: str | None = None,
|
||||
ui_workflow: dict[str, Any] | None = None,
|
||||
) -> dict[str, Any]:
|
||||
"""The import suggestion bundle for one converted workflow."""
|
||||
judgment = classify_usage(converted)
|
||||
media_kinds = ("image", "image_list", "video", "video_list", "audio", "audio_list")
|
||||
media_in = sorted(
|
||||
{
|
||||
entry["kind"].replace("_list", "")
|
||||
for entry in parse_dynamic_inputs(converted)
|
||||
if entry.get("kind") in media_kinds
|
||||
}
|
||||
)
|
||||
media_out = sorted(
|
||||
{
|
||||
str(entry.get("kind"))
|
||||
for entry in parse_dynamic_outputs(converted)
|
||||
if entry.get("kind") in ("image", "video", "audio")
|
||||
}
|
||||
)
|
||||
category, category_label = category_from_source_path(source_path)
|
||||
return {
|
||||
"kind": "video" if "video" in media_out and "image" not in media_out else "image",
|
||||
"usage": judgment["usage"],
|
||||
"usage_ambiguous": judgment["ambiguous"],
|
||||
"category": category,
|
||||
"category_label": category_label,
|
||||
"model_family": model_family_from(converted, source_path),
|
||||
"media_in": media_in,
|
||||
"media_out": media_out,
|
||||
"description": note_description(ui_workflow or {}),
|
||||
}
|
||||
@@ -0,0 +1,801 @@
|
||||
"""UI→API converter for ComfyUI workflow JSON (HEL-681 / S2 data layer).
|
||||
|
||||
ComfyUI saves two formats: the editor ("UI") format with ``nodes``/``links``
|
||||
arrays, and the API ("prompt") format ``{node_id: {class_type, inputs}}`` the
|
||||
product executes. This module converts UI→API offline and deterministically:
|
||||
|
||||
* links are rewritten through ``Reroute`` chains and bypassed (mode 4) nodes;
|
||||
* packed subgraph instances (frontend ≥1.x ``definitions.subgraphs``) expand
|
||||
into their inner nodes under qualified ids ``<packed>:<inner>`` — the same
|
||||
scheme ComfyUI itself exports;
|
||||
* widget values map through, in priority order: the node's serialized input
|
||||
list (entries carrying a ``widget`` marker — authoritative, this corpus's
|
||||
frontend version always writes them), the ``widgets_values_named`` dict,
|
||||
then a generated registry of widget orders learned from the corpus and the
|
||||
repo's ground-truth API exports (``ui_widget_orders``).
|
||||
|
||||
Anything that cannot be mapped with certainty is reported as an issue and the
|
||||
file is flagged ``needs_confirmation`` — never silently guessed: a wrong
|
||||
widget order produces a runnable-looking workflow with swapped seed/steps,
|
||||
which is worse than an honest「需人工确认」.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any
|
||||
|
||||
from calliope.comfyui.ui_widget_orders import WIDGET_ORDERS
|
||||
|
||||
# Values of the frontend-only "control_after_generate" control that serializes
|
||||
# right after every seed-like INT widget (and is not a real server input).
|
||||
_CONTROL_MODES = frozenset({"fixed", "increment", "decrement", "randomize"})
|
||||
|
||||
# Widget names that are pure UI buttons/previews — never serialized in
|
||||
# widgets_values (named dicts skip them too) and never API inputs.
|
||||
_BUTTON_WIDGETS = frozenset(
|
||||
{"preview", "audioUI", "compare_view", "ToggleableColorPicker", "imagebrowser"}
|
||||
)
|
||||
|
||||
# Leftover positional values that are provably action buttons, not data:
|
||||
# known labels, self-describing ids, or emoji-prefixed actions. Anything
|
||||
# else left over keeps the file in the needs-confirmation queue.
|
||||
_BUTTON_LEFTOVER_LABELS = frozenset({"Edit", "lanpaint_star_button"})
|
||||
_BUTTON_LEFTOVER_EMOJI = ("🖼", "🎬", "🎵", "➕", "🔁", "🗑", "📂", "🔎", "✨")
|
||||
|
||||
|
||||
def _is_button_leftover(value: Any) -> bool:
|
||||
if value is None or value == "":
|
||||
return True
|
||||
if isinstance(value, str):
|
||||
return (
|
||||
value in _BUTTON_LEFTOVER_LABELS
|
||||
or "button" in value.lower()
|
||||
or value.startswith(_BUTTON_LEFTOVER_EMOJI)
|
||||
)
|
||||
return False
|
||||
|
||||
# Virtual editor-only nodes. Links pass *through* reroute-style ones (see
|
||||
# _resolve_source); the rest are dropped from the graph entirely.
|
||||
_REROUTE_TYPES = frozenset({"Reroute", "Reroute (rgthree)"})
|
||||
# Frontend-virtual variable nodes: SetNode captures a value under a name,
|
||||
# GetNode reads it. Neither reaches the server — links through a Get resolve
|
||||
# to whatever its same-named Set captured (scope-local).
|
||||
_SET_TYPES = frozenset({"SetNode"})
|
||||
_GET_TYPES = frozenset({"GetNode"})
|
||||
_UI_ONLY_TYPES = frozenset(
|
||||
{
|
||||
"Note",
|
||||
"MarkdownNote",
|
||||
"Image Comparer (rgthree)",
|
||||
"GH_ImageVideoComparer",
|
||||
"Label (rgthree)",
|
||||
"Fast Groups Bypasser (rgthree)",
|
||||
"Fast Groups Muter (rgthree)",
|
||||
"Fast Muter (rgthree)",
|
||||
"FastGroupsBypassSwitch",
|
||||
"Mute / Bypass Repeater (rgthree)",
|
||||
}
|
||||
)
|
||||
|
||||
# Server-side OUTPUT nodes: the closure roots. Learned from the repo's
|
||||
# ground-truth API exports (their unreferenced classes) + the corpus's
|
||||
# real save/preview sinks (SaveVideo/SaveImageAdvanced/… custom nodes).
|
||||
_OUTPUT_CLASSES = frozenset(
|
||||
{
|
||||
"SaveImage",
|
||||
"PreviewImage",
|
||||
"SaveImageAdvanced",
|
||||
"SaveImageKJ",
|
||||
"SaveAnimatedWEBP",
|
||||
"SaveAnimatedPNG",
|
||||
"SaveAnimatedGIF",
|
||||
"SaveVideo",
|
||||
"SaveAudio",
|
||||
"SaveAudioMP3",
|
||||
"SaveAudioAdvanced",
|
||||
"PreviewAudio",
|
||||
"MaskPreview",
|
||||
"MaskPreview+",
|
||||
"ImageAndMaskPreview",
|
||||
"VHS_VideoCombine",
|
||||
"easy saveVideo",
|
||||
"easy multitrackProjectVideoCombine",
|
||||
"easy multiTrackInfoOutput",
|
||||
"easy multiTrackTaskOutput",
|
||||
"easy compareVideos",
|
||||
"easy compareImages",
|
||||
"easy showText",
|
||||
"easy imageWall",
|
||||
"CR Prompt Text",
|
||||
"PreviewAny",
|
||||
"easy clearGpuUsed",
|
||||
"easy clearCacheAll",
|
||||
"easy showSpentTime",
|
||||
}
|
||||
)
|
||||
|
||||
MODE_ACTIVE = 0
|
||||
MODE_MUTED = 2
|
||||
MODE_BYPASSED = 4
|
||||
|
||||
_SUBGRAPH_IN = -10 # pseudo-node id of a subgraph's boundary input
|
||||
_SUBGRAPH_OUT = -20 # pseudo-node id of a subgraph's boundary output
|
||||
|
||||
|
||||
@dataclass
|
||||
class ConvertIssue:
|
||||
node_id: str
|
||||
code: str
|
||||
message: str
|
||||
level: str = "warning" # 'error' | 'warning'
|
||||
|
||||
|
||||
@dataclass
|
||||
class ConvertResult:
|
||||
workflow: dict[str, Any] | None
|
||||
status: str # 'ok' | 'warn' | 'fail'
|
||||
issues: list[ConvertIssue] = field(default_factory=list)
|
||||
|
||||
@property
|
||||
def needs_confirmation(self) -> bool:
|
||||
"""Widget mapping uncertain — must not be imported as runnable."""
|
||||
return any(
|
||||
i.code in ("widget_unmapped", "widget_order_mismatch") for i in self.issues
|
||||
)
|
||||
|
||||
|
||||
def _norm_link(link: Any) -> tuple[int, int, int, int, int, str] | None:
|
||||
"""(id, origin_id, origin_slot, target_id, target_slot, type) from either form."""
|
||||
if isinstance(link, dict):
|
||||
try:
|
||||
return (
|
||||
int(link["id"]),
|
||||
int(link["origin_id"]),
|
||||
int(link["origin_slot"]),
|
||||
int(link["target_id"]),
|
||||
int(link["target_slot"]),
|
||||
str(link.get("type") or "*"),
|
||||
)
|
||||
except (KeyError, TypeError, ValueError):
|
||||
return None
|
||||
if isinstance(link, (list, tuple)) and len(link) >= 5:
|
||||
try:
|
||||
return (
|
||||
int(link[0]),
|
||||
int(link[1]),
|
||||
int(link[2]),
|
||||
int(link[3]),
|
||||
int(link[4]),
|
||||
str(link[5]) if len(link) > 5 and link[5] else "*",
|
||||
)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _is_seed_like(name: str) -> bool:
|
||||
lowered = name.lower()
|
||||
return lowered in ("seed", "noise_seed", "value", "rand_seed", "random_seed") or (
|
||||
lowered.endswith("seed")
|
||||
)
|
||||
|
||||
|
||||
def _is_upload_entry(name: str, type_: str) -> bool:
|
||||
return type_.upper().endswith("UPLOAD") or name == "upload" or "UPLOAD" in type_.upper()
|
||||
|
||||
|
||||
class _Converter:
|
||||
"""One conversion run over a single UI-format document."""
|
||||
|
||||
def __init__(self, ui: dict[str, Any]) -> None:
|
||||
self.ui = ui
|
||||
self.issues: list[ConvertIssue] = []
|
||||
self.subgraphs: dict[str, dict[str, Any]] = {
|
||||
str(s.get("id")): s
|
||||
for s in self.ui.get("definitions", {}).get("subgraphs", []) or []
|
||||
if isinstance(s, dict)
|
||||
}
|
||||
# qualified id → UI node + owning scope
|
||||
self.nodes: dict[str, dict[str, Any]] = {}
|
||||
# scope key ('' for top level) → link table / node-id index / owner
|
||||
self.scope_links: dict[str, dict[int, tuple[int, int, int, int, str]]] = {}
|
||||
self.scope_ids: dict[str, dict[str, str]] = {}
|
||||
self.scope_owner: dict[str, str] = {}
|
||||
self._set_capture_cache: dict[str, dict[str, tuple[str, int]]] = {}
|
||||
self._set_names: dict[str, set[str]] = {}
|
||||
self._depth = 0
|
||||
self._cycle_warned = False
|
||||
self._set_building: set[str] = set()
|
||||
|
||||
# -------------------------------------------------------------- indexing
|
||||
def _index_scope(self, scope: str, links: list[Any], owner: str | None) -> None:
|
||||
table = self.scope_links.setdefault(scope, {})
|
||||
for link in links or []:
|
||||
norm = _norm_link(link)
|
||||
if norm is not None:
|
||||
table[norm[0]] = norm[1:]
|
||||
self.scope_ids.setdefault(scope, {})
|
||||
if owner is not None:
|
||||
self.scope_owner[scope] = owner
|
||||
|
||||
def _flatten(
|
||||
self, node: dict[str, Any], scope: str, prefix: str
|
||||
) -> None:
|
||||
qualified = f"{prefix}{node.get('id')}"
|
||||
self.nodes[qualified] = {"node": node, "scope": scope}
|
||||
self.scope_ids.setdefault(scope, {})[str(node.get("id"))] = qualified
|
||||
sub = self.subgraphs.get(str(node.get("type") or ""))
|
||||
if sub is None:
|
||||
return
|
||||
if not isinstance(sub.get("nodes"), list):
|
||||
self.issues.append(
|
||||
ConvertIssue(qualified, "subgraph_bad_definition", "子图缺少内部节点定义")
|
||||
)
|
||||
return
|
||||
sub_scope = f"{scope}|{node.get('type')}" if scope else f"{node.get('type')}"
|
||||
if sub_scope not in self.scope_links:
|
||||
self._index_scope(sub_scope, sub.get("links") or [], qualified)
|
||||
for inner in sub["nodes"]:
|
||||
if isinstance(inner, dict):
|
||||
self._flatten(inner, sub_scope, f"{qualified}:")
|
||||
|
||||
# --------------------------------------------------------------- lookups
|
||||
def _node(self, qualified: str) -> dict[str, Any] | None:
|
||||
entry = self.nodes.get(qualified)
|
||||
return entry["node"] if entry else None
|
||||
|
||||
def _scope(self, qualified: str) -> str:
|
||||
entry = self.nodes.get(qualified)
|
||||
return entry["scope"] if entry else ""
|
||||
|
||||
def _link(self, scope: str, link_id: Any) -> tuple[int, int, int, int, str] | None:
|
||||
if link_id is None:
|
||||
return None
|
||||
try:
|
||||
key = int(link_id)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
return self.scope_links.get(scope, {}).get(key)
|
||||
|
||||
def _boundary_source(self, scope: str, link_id: Any) -> tuple[str, int] | None:
|
||||
"""(packed qualified id, boundary slot) when this link leaves a
|
||||
subgraph through its -10 input boundary."""
|
||||
link = self._link(scope, link_id)
|
||||
if link is None or link[0] != _SUBGRAPH_IN:
|
||||
return None
|
||||
packed_q = self.scope_owner.get(scope)
|
||||
if packed_q is None:
|
||||
return None
|
||||
return packed_q, link[1]
|
||||
|
||||
def _subgraph_of(self, qualified: str) -> dict[str, Any] | None:
|
||||
node = self._node(qualified)
|
||||
if node is None:
|
||||
return None
|
||||
return self.subgraphs.get(str(node.get("type") or ""))
|
||||
|
||||
@staticmethod
|
||||
def _virtual_name(node: dict[str, Any]) -> str:
|
||||
"""A Set/Get node's captured variable name (its first widget value)."""
|
||||
named = node.get("widgets_values_named")
|
||||
if isinstance(named, dict):
|
||||
for key in ("const_name", "name", "value"):
|
||||
if key in named:
|
||||
return str(named[key])
|
||||
values = node.get("widgets_values")
|
||||
if isinstance(values, list) and values and isinstance(values[0], str):
|
||||
return values[0]
|
||||
return ""
|
||||
|
||||
def _set_captures(self, scope: str) -> dict[str, tuple[str, int]]:
|
||||
"""{variable name → resolved source} for the Set nodes in one scope."""
|
||||
table = self._set_capture_cache.get(scope)
|
||||
if table is not None:
|
||||
return table
|
||||
table = {}
|
||||
# Seed before resolving: a Set feeding a same-named Get (FOR-loop
|
||||
# graphs) would otherwise recurse into this builder forever. A miss
|
||||
# while building is not a missing Set — never warn mid-construction.
|
||||
self._set_capture_cache[scope] = table
|
||||
self._set_building.add(scope)
|
||||
try:
|
||||
return self._build_set_captures(scope, table)
|
||||
finally:
|
||||
self._set_building.discard(scope)
|
||||
|
||||
def _build_set_captures(
|
||||
self, scope: str, table: dict[str, tuple[str, int]]
|
||||
) -> dict[str, tuple[str, int]]:
|
||||
names: set[str] = set()
|
||||
for qualified, entry in self.nodes.items():
|
||||
if entry["scope"] != scope:
|
||||
continue
|
||||
node = entry["node"]
|
||||
if str(node.get("type") or "") not in _SET_TYPES:
|
||||
continue
|
||||
name = self._virtual_name(node)
|
||||
if not name:
|
||||
continue
|
||||
names.add(name)
|
||||
ins = self._inputs_of(node)
|
||||
link = self._link(scope, ins[0].get("link")) if ins else None
|
||||
resolved = self._resolve_link(scope, link)
|
||||
if resolved is not None:
|
||||
table.setdefault(name, resolved)
|
||||
self._set_names[scope] = names
|
||||
self._set_capture_cache[scope] = table
|
||||
return table
|
||||
|
||||
@staticmethod
|
||||
def _inputs_of(node: dict[str, Any]) -> list[dict[str, Any]]:
|
||||
return [i for i in node.get("inputs") or [] if isinstance(i, dict)]
|
||||
|
||||
@staticmethod
|
||||
def _outputs_of(node: dict[str, Any]) -> list[dict[str, Any]]:
|
||||
return [o for o in node.get("outputs") or [] if isinstance(o, dict)]
|
||||
|
||||
# ------------------------------------------------------------- resolution
|
||||
def _resolve_link(
|
||||
self, scope: str, link: tuple[int, int, int, int, str] | None
|
||||
) -> tuple[str, int] | None:
|
||||
"""Resolve one link (in scope) to an API source (qualified id, slot)."""
|
||||
if link is None:
|
||||
return None
|
||||
if self._depth > 200: # Set/Get cycles (FOR-loop graphs) never unwind
|
||||
if not self._cycle_warned:
|
||||
self._cycle_warned = True
|
||||
self.issues.append(
|
||||
ConvertIssue(
|
||||
"",
|
||||
"cyclic_variable",
|
||||
"变量/Set-Get 连线存在循环(常见于 FOR 循环流),该连线按未连接处理",
|
||||
)
|
||||
)
|
||||
return None
|
||||
self._depth += 1
|
||||
try:
|
||||
return self._resolve_link_inner(scope, link)
|
||||
finally:
|
||||
self._depth -= 1
|
||||
|
||||
def _resolve_link_inner(
|
||||
self, scope: str, link: tuple[int, int, int, int, str]
|
||||
) -> tuple[str, int] | None:
|
||||
origin_id, origin_slot = link[0], link[1]
|
||||
if origin_id == _SUBGRAPH_IN:
|
||||
# Boundary: hand off to the packed instance's own input slot.
|
||||
packed_q = self.scope_owner.get(scope)
|
||||
if packed_q is None:
|
||||
return None
|
||||
node = self._node(packed_q)
|
||||
if node is None:
|
||||
return None
|
||||
entries = self._inputs_of(node)
|
||||
if origin_slot >= len(entries):
|
||||
return None
|
||||
entry = entries[origin_slot]
|
||||
if entry.get("link") is None:
|
||||
return None # unlinked boundary → inner widget value applies
|
||||
outer = self._scope(packed_q)
|
||||
return self._resolve_link(outer, self._link(outer, entry.get("link")))
|
||||
qualified = self.scope_ids.get(scope, {}).get(str(origin_id))
|
||||
if qualified is None:
|
||||
return None
|
||||
return self._resolve_source(qualified, origin_slot)
|
||||
|
||||
def _resolve_source(self, qualified: str, slot: int) -> tuple[str, int] | None:
|
||||
"""What an outgoing edge from (node, output slot) really connects to."""
|
||||
node = self._node(qualified)
|
||||
if node is None:
|
||||
return None
|
||||
node_type = str(node.get("type") or "")
|
||||
mode = node.get("mode") or 0
|
||||
scope = self._scope(qualified)
|
||||
|
||||
if node_type in _UI_ONLY_TYPES:
|
||||
return None
|
||||
|
||||
if node_type in _REROUTE_TYPES:
|
||||
ins = self._inputs_of(node)
|
||||
if not ins:
|
||||
return None
|
||||
return self._resolve_link(scope, self._link(scope, ins[0].get("link")))
|
||||
|
||||
if node_type in _SET_TYPES:
|
||||
ins = self._inputs_of(node)
|
||||
if not ins:
|
||||
return None
|
||||
return self._resolve_link(scope, self._link(scope, ins[0].get("link")))
|
||||
|
||||
if node_type in _GET_TYPES:
|
||||
name = self._virtual_name(node)
|
||||
captured = self._set_captures(scope).get(name)
|
||||
if captured is None and scope not in self._set_building:
|
||||
if name in self._set_names.get(scope, set()):
|
||||
self.issues.append(
|
||||
ConvertIssue(
|
||||
qualified,
|
||||
"variable_upstream_dropped",
|
||||
f"变量「{name}」的上游被旁路或未连接,取值按未连接处理",
|
||||
)
|
||||
)
|
||||
else:
|
||||
self.issues.append(
|
||||
ConvertIssue(
|
||||
qualified,
|
||||
"get_without_set",
|
||||
f"变量节点「{name}」没有对应的 Set 节点",
|
||||
)
|
||||
)
|
||||
return captured
|
||||
|
||||
sub = self._subgraph_of(qualified)
|
||||
if sub is not None:
|
||||
outputs = [o for o in sub.get("outputs") or [] if isinstance(o, dict)]
|
||||
if slot >= len(outputs):
|
||||
return None
|
||||
sub_scope = f"{scope}|{node_type}" if scope else node_type
|
||||
for link in self.scope_links.get(sub_scope, {}).values():
|
||||
if link[2] == _SUBGRAPH_OUT and link[3] == slot:
|
||||
inner_q = self.scope_ids.get(sub_scope, {}).get(str(link[0]))
|
||||
return self._resolve_source(inner_q, link[1]) if inner_q else None
|
||||
return None # boundary output with no inner source
|
||||
|
||||
if mode == MODE_MUTED:
|
||||
return None
|
||||
if mode == MODE_BYPASSED:
|
||||
return self._bypass_through(qualified, slot)
|
||||
return (qualified, slot)
|
||||
|
||||
def _bypass_through(self, qualified: str, slot: int) -> tuple[str, int] | None:
|
||||
"""Pass-through of a bypassed node: same-name input first, then same-type."""
|
||||
node = self._node(qualified)
|
||||
if node is None:
|
||||
return None
|
||||
outputs = self._outputs_of(node)
|
||||
out = outputs[slot] if slot < len(outputs) else {}
|
||||
out_name = str(out.get("name") or "")
|
||||
out_type = str(out.get("type") or "*")
|
||||
linkable = [
|
||||
e for e in self._inputs_of(node) if not e.get("widget") and e.get("link") is not None
|
||||
]
|
||||
pick = None
|
||||
if out_name:
|
||||
pick = next((e for e in linkable if str(e.get("name") or "") == out_name), None)
|
||||
if pick is None:
|
||||
pick = next(
|
||||
(
|
||||
e
|
||||
for e in linkable
|
||||
if out_type == "*" or str(e.get("type") or "*") in (out_type, "*")
|
||||
),
|
||||
None,
|
||||
)
|
||||
if pick is None:
|
||||
return None
|
||||
scope = self._scope(qualified)
|
||||
return self._resolve_link(scope, self._link(scope, pick.get("link")))
|
||||
|
||||
# --------------------------------------------------------- widget mapping
|
||||
def _widget_entries(self, node: dict[str, Any]) -> list[tuple[str, str]]:
|
||||
"""[(name, type)] of entries carrying the ``widget`` marker, in order."""
|
||||
out: list[tuple[str, str]] = []
|
||||
for entry in self._inputs_of(node):
|
||||
marker = entry.get("widget")
|
||||
if isinstance(marker, dict):
|
||||
name = str(marker.get("name") or entry.get("name") or "")
|
||||
if name:
|
||||
out.append((name, str(entry.get("type") or "")))
|
||||
return out
|
||||
|
||||
def _widgets_from_entries(
|
||||
self,
|
||||
node_id: str,
|
||||
entries: list[tuple[str, str]],
|
||||
values: Any,
|
||||
) -> tuple[dict[str, Any], list[ConvertIssue]]:
|
||||
"""Map widget values using the node's serialized input list."""
|
||||
inputs: dict[str, Any] = {}
|
||||
issues: list[ConvertIssue] = []
|
||||
if isinstance(values, dict):
|
||||
for name, type_ in entries:
|
||||
if name in _BUTTON_WIDGETS or self._is_upload(name, type_):
|
||||
continue
|
||||
if name in values:
|
||||
inputs[name] = values[name]
|
||||
else:
|
||||
issues.append(
|
||||
ConvertIssue(node_id, "widget_unmapped", f"控件「{name}」没有序列化值")
|
||||
)
|
||||
return inputs, issues
|
||||
if not isinstance(values, list):
|
||||
return inputs, issues
|
||||
if not values:
|
||||
return inputs, issues # nothing serialized — server defaults apply
|
||||
i = 0
|
||||
for name, type_ in entries:
|
||||
if name in _BUTTON_WIDGETS:
|
||||
continue # button widgets never serialize
|
||||
if i >= len(values):
|
||||
issues.append(
|
||||
ConvertIssue(node_id, "widget_order_mismatch", f"控件值数量不足({name})")
|
||||
)
|
||||
break
|
||||
value = values[i]
|
||||
i += 1
|
||||
if self._is_upload(name, type_):
|
||||
continue # consumes a slot, never an API input
|
||||
inputs[name] = value
|
||||
if (
|
||||
type_.upper() == "INT"
|
||||
and _is_seed_like(name)
|
||||
and i < len(values)
|
||||
and values[i] in _CONTROL_MODES
|
||||
):
|
||||
i += 1 # control_after_generate rides right after its seed
|
||||
leftover_ok = all(_is_button_leftover(v) for v in values[i:])
|
||||
if not issues and i != len(values) and not leftover_ok:
|
||||
issues.append(
|
||||
ConvertIssue(
|
||||
node_id,
|
||||
"widget_order_mismatch",
|
||||
f"有 {len(values)} 个控件值,输入清单只覆盖 {i} 个",
|
||||
)
|
||||
)
|
||||
return inputs, issues
|
||||
|
||||
@staticmethod
|
||||
def _is_upload(name: str, type_: str) -> bool:
|
||||
return _is_upload_entry(name, type_)
|
||||
|
||||
def _widgets_from_registry(
|
||||
self, node: dict[str, Any], values: list[Any]
|
||||
) -> tuple[dict[str, Any], list[ConvertIssue]]:
|
||||
node_type = str(node.get("type") or "")
|
||||
if not values:
|
||||
return {}, [] # nothing serialized — server defaults apply
|
||||
for order in WIDGET_ORDERS.get(node_type) or []:
|
||||
inputs: dict[str, Any] = {}
|
||||
i = 0
|
||||
for name in order:
|
||||
if name in _BUTTON_WIDGETS:
|
||||
continue
|
||||
if i >= len(values):
|
||||
break
|
||||
value = values[i]
|
||||
i += 1
|
||||
if _is_upload_entry(name, ""):
|
||||
continue
|
||||
inputs[name] = value
|
||||
if _is_seed_like(name) and i < len(values) and values[i] in _CONTROL_MODES:
|
||||
i += 1
|
||||
if i == len(values) or all(_is_button_leftover(v) for v in values[i:]):
|
||||
return inputs, [] # exact fit, or trailing button leftovers
|
||||
return {}, [
|
||||
ConvertIssue(
|
||||
node.get("id", ""),
|
||||
"widget_unmapped" if not WIDGET_ORDERS.get(node_type) else "widget_order_mismatch",
|
||||
f"「{node_type}」的 {len(values)} 个控件值无法可靠对应到输入名",
|
||||
)
|
||||
]
|
||||
|
||||
def _packed_widget_values(self, qualified: str) -> Any:
|
||||
"""Exposed widget values of a packed instance as {boundary name: value}."""
|
||||
node = self._node(qualified)
|
||||
sub = self._subgraph_of(qualified)
|
||||
if node is None or sub is None:
|
||||
return None
|
||||
boundary = [i for i in sub.get("inputs") or [] if isinstance(i, dict)]
|
||||
named = node.get("widgets_values_named")
|
||||
if isinstance(named, dict):
|
||||
return named
|
||||
values = node.get("widgets_values")
|
||||
if not isinstance(values, list):
|
||||
return None
|
||||
out: dict[str, Any] = {}
|
||||
i = 0
|
||||
for entry in boundary:
|
||||
name = str(entry.get("name") or "")
|
||||
type_ = str(entry.get("type") or "")
|
||||
if name and i < len(values):
|
||||
out[name] = values[i]
|
||||
i += 1
|
||||
if (
|
||||
type_.upper() == "INT"
|
||||
and _is_seed_like(name)
|
||||
and i < len(values)
|
||||
and values[i] in _CONTROL_MODES
|
||||
):
|
||||
i += 1
|
||||
return out
|
||||
|
||||
# -------------------------------------------------------------- serialize
|
||||
def _serialize_node(self, qualified: str) -> dict[str, Any] | None:
|
||||
node = self._node(qualified)
|
||||
if node is None:
|
||||
return None
|
||||
node_type = str(node.get("type") or "")
|
||||
if (
|
||||
not node_type
|
||||
or node_type in _UI_ONLY_TYPES
|
||||
or node_type in _REROUTE_TYPES
|
||||
or node_type in _SET_TYPES
|
||||
or node_type in _GET_TYPES
|
||||
):
|
||||
return None
|
||||
scope = self._scope(qualified)
|
||||
inputs: dict[str, Any] = {}
|
||||
|
||||
widget_values = node.get("widgets_values_named")
|
||||
if not isinstance(widget_values, dict):
|
||||
widget_values = node.get("widgets_values")
|
||||
if self._subgraph_of(qualified) is not None:
|
||||
widget_values = self._packed_widget_values(qualified)
|
||||
|
||||
widget_inputs: dict[str, Any] = {}
|
||||
entries = self._widget_entries(node)
|
||||
if widget_values is not None:
|
||||
if entries:
|
||||
widget_inputs, w_issues = self._widgets_from_entries(
|
||||
qualified, entries, widget_values
|
||||
)
|
||||
self.issues.extend(w_issues)
|
||||
elif isinstance(widget_values, dict):
|
||||
widget_inputs = {
|
||||
k: v for k, v in widget_values.items() if k not in _BUTTON_WIDGETS
|
||||
}
|
||||
elif isinstance(widget_values, list):
|
||||
widget_inputs, w_issues = self._widgets_from_registry(node, widget_values)
|
||||
self.issues.extend(w_issues)
|
||||
|
||||
for entry in self._inputs_of(node):
|
||||
name = str(entry.get("name") or "")
|
||||
if not name or name in inputs:
|
||||
continue
|
||||
if entry.get("link") is None:
|
||||
continue # unconnected optional input; widget values applied below
|
||||
# Widget entries fed from the subgraph boundary (-10): when the
|
||||
# packed instance left that boundary slot unlinked, the value is
|
||||
# the packed node's own exposed widget value, not the inner one.
|
||||
boundary = self._boundary_source(scope, entry.get("link"))
|
||||
if boundary is not None:
|
||||
packed_q, boundary_slot = boundary
|
||||
packed_node = self._node(packed_q)
|
||||
packed_entries = self._inputs_of(packed_node) if packed_node else []
|
||||
if boundary_slot < len(packed_entries) and packed_entries[
|
||||
boundary_slot
|
||||
].get("link") is None:
|
||||
values = self._packed_widget_values(packed_q)
|
||||
boundary_name = str(packed_entries[boundary_slot].get("name") or "")
|
||||
if isinstance(values, dict) and boundary_name in values:
|
||||
inputs[name] = values[boundary_name]
|
||||
continue
|
||||
# linked boundary falls through to normal resolution
|
||||
link = self._link(scope, entry.get("link"))
|
||||
if link is None:
|
||||
self.issues.append(
|
||||
ConvertIssue(qualified, "dangling_link", f"输入「{name}」的连线不存在")
|
||||
)
|
||||
continue
|
||||
resolved = self._resolve_link(scope, link)
|
||||
if resolved is not None:
|
||||
inputs[name] = [resolved[0], resolved[1]]
|
||||
elif entry.get("widget"):
|
||||
pass # muted upstream: the widget value below takes over
|
||||
else:
|
||||
self.issues.append(
|
||||
ConvertIssue(
|
||||
qualified,
|
||||
"muted_input_dropped",
|
||||
f"输入「{name}」上游被静音,已按未连接处理",
|
||||
)
|
||||
)
|
||||
|
||||
for name, value in widget_inputs.items():
|
||||
inputs.setdefault(name, value)
|
||||
|
||||
api_node: dict[str, Any] = {"class_type": node_type, "inputs": inputs}
|
||||
title = str(node.get("title") or "").strip()
|
||||
if title:
|
||||
api_node["_meta"] = {"title": title}
|
||||
return api_node
|
||||
|
||||
# ------------------------------------------------------------------- main
|
||||
def run(self) -> ConvertResult:
|
||||
nodes = self.ui.get("nodes")
|
||||
if not isinstance(nodes, list) or not nodes:
|
||||
return ConvertResult(
|
||||
None,
|
||||
"fail",
|
||||
[ConvertIssue("", "no_nodes", "文件不含 nodes 数组,不是 UI 格式工作流", "error")],
|
||||
)
|
||||
try:
|
||||
self._index_scope("", self.ui.get("links") or [], None)
|
||||
for node in nodes:
|
||||
if isinstance(node, dict):
|
||||
self._flatten(node, "", "")
|
||||
except RecursionError:
|
||||
return ConvertResult(
|
||||
None, "fail", [ConvertIssue("", "subgraph_recursion", "子图嵌套过深", "error")]
|
||||
)
|
||||
|
||||
# Closure from known output nodes (ComfyUI's own graphToPrompt roots).
|
||||
roots = [
|
||||
q
|
||||
for q, entry in self.nodes.items()
|
||||
if str(entry["node"].get("type") or "") in _OUTPUT_CLASSES
|
||||
and (entry["node"].get("mode") or 0) == MODE_ACTIVE
|
||||
]
|
||||
keep: dict[str, None] = {}
|
||||
stack = list(roots)
|
||||
while stack:
|
||||
qualified = stack.pop()
|
||||
if qualified in keep:
|
||||
continue
|
||||
entry = self.nodes.get(qualified)
|
||||
if entry is None:
|
||||
continue
|
||||
keep[qualified] = None
|
||||
node = entry["node"]
|
||||
scope = entry["scope"]
|
||||
for e in self._inputs_of(node):
|
||||
if e.get("link") is None:
|
||||
continue
|
||||
link = self._link(scope, e.get("link"))
|
||||
resolved = self._resolve_link(scope, link)
|
||||
if resolved is not None:
|
||||
stack.append(resolved[0])
|
||||
|
||||
if not keep:
|
||||
# No known output node: keep every active computed node and warn —
|
||||
# the import lint will report the missing output separately.
|
||||
for qualified, entry in self.nodes.items():
|
||||
node = entry["node"]
|
||||
node_type = str(node.get("type") or "")
|
||||
if (
|
||||
node_type in _UI_ONLY_TYPES
|
||||
or node_type in _REROUTE_TYPES
|
||||
or (node.get("mode") or 0) != MODE_ACTIVE
|
||||
or self._subgraph_of(qualified) is not None
|
||||
):
|
||||
continue
|
||||
keep[qualified] = None
|
||||
self.issues.append(
|
||||
ConvertIssue(
|
||||
"",
|
||||
"no_output_node",
|
||||
"图中没有已知输出节点(SaveImage / 视频合成等),"
|
||||
"全部活跃节点已保留,需人工确认",
|
||||
)
|
||||
)
|
||||
|
||||
workflow: dict[str, Any] = {}
|
||||
for qualified in keep:
|
||||
api_node = self._serialize_node(qualified)
|
||||
if api_node is not None and api_node["class_type"]:
|
||||
workflow[qualified] = api_node
|
||||
|
||||
if not workflow:
|
||||
return ConvertResult(
|
||||
None,
|
||||
"fail",
|
||||
self.issues or [ConvertIssue("", "empty", "转换后没有任何节点", "error")],
|
||||
)
|
||||
status = (
|
||||
"fail"
|
||||
if any(i.level == "error" for i in self.issues)
|
||||
else ("ok" if not self.issues else "warn")
|
||||
)
|
||||
return ConvertResult(workflow, status, self.issues)
|
||||
|
||||
|
||||
def convert_ui_workflow(ui: dict[str, Any]) -> ConvertResult:
|
||||
"""Convert one ComfyUI UI-format workflow dict into API format."""
|
||||
if not isinstance(ui, dict) or not isinstance(ui.get("nodes"), list):
|
||||
return ConvertResult(
|
||||
None,
|
||||
"fail",
|
||||
[ConvertIssue("", "not_ui_format", "不是 UI 格式(缺少 nodes 数组)", "error")],
|
||||
)
|
||||
return _Converter(ui).run()
|
||||
File diff suppressed because it is too large
Load Diff
@@ -506,6 +506,27 @@ async def migrate_db(db_path: Path) -> None:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN output_map TEXT")
|
||||
if "output_map_source" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN output_map_source TEXT")
|
||||
# HEL-681 (S2): library metadata for 150+ scale workflow browsing. Purely
|
||||
# additive columns — old rows stay NULL/0 and every legacy path ignores
|
||||
# them; the lightweight list view (?view=meta) is their only reader.
|
||||
if "category" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN category TEXT")
|
||||
if "model_family" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN model_family TEXT")
|
||||
if "media_io" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN media_io TEXT")
|
||||
if "tags" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN tags TEXT")
|
||||
if "favorite" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN favorite INTEGER NOT NULL DEFAULT 0")
|
||||
if "last_used_at" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN last_used_at TIMESTAMP")
|
||||
if "source" not in cols:
|
||||
# where the row came from: 'ui_convert' (HEL-681 batch import) vs
|
||||
# NULL = manual/API import as before.
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN source TEXT")
|
||||
if "source_path" not in cols:
|
||||
conn.execute("ALTER TABLE workflows ADD COLUMN source_path TEXT")
|
||||
# Idempotent backfill: pending rows are re-judged on every boot (parser
|
||||
# upgrades can settle them); confirmed rows are never touched.
|
||||
_backfill_workflow_usage(conn)
|
||||
|
||||
@@ -243,6 +243,55 @@ class WorkflowUpdate(BaseModel):
|
||||
# resets the workflow to pending confirmation.
|
||||
output_map: list[dict[str, Any]] | None = None
|
||||
output_map_source: Literal["auto", "user"] | None = None
|
||||
# HEL-681 (S2): library metadata fields.
|
||||
favorite: bool | None = None
|
||||
tags: list[str] | None = None
|
||||
category: str | None = None
|
||||
model_family: str | None = None
|
||||
|
||||
|
||||
class WorkflowUIFileItem(BaseModel):
|
||||
"""One UI-format file for the HEL-681 convert/import pipeline."""
|
||||
|
||||
name: str | None = None
|
||||
# repo-relative path (category/model-family evidence); display name
|
||||
# defaults to the file stem.
|
||||
source_path: str | None = None
|
||||
workflow_json: dict[str, Any]
|
||||
# optional human confirmations from the import wizard (S3): a settled
|
||||
# usage and a corrected schema let warn files import enabled.
|
||||
usage: WorkflowUsageKind | None = None
|
||||
input_schema: list[dict[str, Any]] | None = None
|
||||
output_map: list[dict[str, Any]] | None = None
|
||||
description: str | None = None
|
||||
tags: list[str] | None = None
|
||||
|
||||
|
||||
class WorkflowConvertRequest(BaseModel):
|
||||
"""Dry-run: per-file ok/warn/fail + suggested metadata, nothing stored."""
|
||||
|
||||
files: list[WorkflowUIFileItem]
|
||||
# Include the converted API JSON per file (default on for small batches;
|
||||
# the 146-file report leaves it off to keep the payload sane).
|
||||
include_workflows: bool = False
|
||||
# L2 preflight against a real ComfyUI (opt-in; needs a connection).
|
||||
endpoint_id: str | None = None
|
||||
refresh: bool = False
|
||||
|
||||
|
||||
class WorkflowImportBatchRequest(BaseModel):
|
||||
"""Commit: convert UI files and insert, skipping conflicts. Idempotent."""
|
||||
|
||||
files: list[WorkflowUIFileItem]
|
||||
|
||||
|
||||
class WorkflowImportScanRequest(BaseModel):
|
||||
"""Scan a server-side directory of UI JSONs (repo example library)."""
|
||||
|
||||
root: str = "example_ComfyUI_workflows"
|
||||
# Set to preview what would import (same shape as /convert) — the safe
|
||||
# default for a first run against the 146-file library.
|
||||
dry_run: bool = True
|
||||
|
||||
|
||||
class WorkflowAnalyze(BaseModel):
|
||||
|
||||
@@ -49,6 +49,12 @@ class QueueManager:
|
||||
""",
|
||||
(project_id, scene_id, clip_id, kind, workflow_id, json.dumps(payload), origin),
|
||||
)
|
||||
# HEL-681: every enqueued job counts as a use (最近使用).
|
||||
if workflow_id is not None:
|
||||
conn.execute(
|
||||
"UPDATE workflows SET last_used_at = CURRENT_TIMESTAMP WHERE id = ?",
|
||||
(workflow_id,),
|
||||
)
|
||||
conn.commit()
|
||||
row = conn.execute("SELECT * FROM jobs WHERE id = ?", (cur.lastrowid,)).fetchone()
|
||||
return row_to_dict(row)
|
||||
|
||||
@@ -7,6 +7,7 @@ from fastapi import APIRouter, HTTPException
|
||||
|
||||
from calliope.comfyui.endpoints import client_for, endpoint_snapshot
|
||||
from calliope.comfyui.lint import blocking_problem, workflow_warnings
|
||||
from calliope.comfyui.metadata import suggested_metadata
|
||||
from calliope.comfyui.output_map import (
|
||||
auto_output_map,
|
||||
load_output_map,
|
||||
@@ -23,6 +24,7 @@ from calliope.comfyui.parser import (
|
||||
from calliope.comfyui.preflight import check_workflow_against
|
||||
from calliope.comfyui.profiles import detect_prompt_profile
|
||||
from calliope.comfyui.roles import usage_to_kind
|
||||
from calliope.comfyui.ui_convert import convert_ui_workflow
|
||||
from calliope.comfyui.validate import validate_input_values
|
||||
from calliope.config import settings
|
||||
from calliope.db import get_db, row_to_dict
|
||||
@@ -30,8 +32,12 @@ from calliope.events.bus import event_bus
|
||||
from calliope.models.schemas import (
|
||||
WorkflowAnalyze,
|
||||
WorkflowCheckRequest,
|
||||
WorkflowConvertRequest,
|
||||
WorkflowCreate,
|
||||
WorkflowImportBatchRequest,
|
||||
WorkflowImportScanRequest,
|
||||
WorkflowTestRequest,
|
||||
WorkflowUIFileItem,
|
||||
WorkflowUpdate,
|
||||
)
|
||||
from calliope.queue.manager import queue_manager
|
||||
@@ -44,6 +50,14 @@ from calliope.queue.workflow_test import (
|
||||
|
||||
router = APIRouter()
|
||||
|
||||
# HEL-681: metadata columns the lightweight list view exposes (everything
|
||||
# except the heavy workflow_json / input_schema / output_map payloads).
|
||||
_META_COLUMNS = (
|
||||
"id, name, kind, usage, is_enabled, category, model_family, media_io, tags,"
|
||||
" favorite, last_used_at, description, source, source_path, prompt_profile,"
|
||||
" created_at, endpoint_id, usage_source, output_map_source"
|
||||
)
|
||||
|
||||
|
||||
def _serialize_workflow(row: Any) -> dict[str, Any]:
|
||||
data = row_to_dict(row)
|
||||
@@ -61,9 +75,21 @@ def _serialize_workflow(row: Any) -> dict[str, Any]:
|
||||
data["needs_mapping"] = (
|
||||
mapping_problem(data["workflow_json"], raw_map, data.get("output_map_source")) is not None
|
||||
)
|
||||
# HEL-681: structured library metadata (raw JSON columns → values).
|
||||
data["media_io"] = _load_json_col(data.get("media_io"), {"in": [], "out": []})
|
||||
data["tags"] = _load_json_col(data.get("tags"), [])
|
||||
data["favorite"] = bool(data.get("favorite"))
|
||||
return data
|
||||
|
||||
|
||||
def _load_json_col(raw: Any, default: Any) -> Any:
|
||||
try:
|
||||
value = json.loads(raw) if raw else None
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
value = None
|
||||
return value if value is not None else default
|
||||
|
||||
|
||||
async def _connection_check(
|
||||
endpoint_id: str | None, workflow_json: dict[str, Any], refresh: bool = False
|
||||
) -> dict[str, Any]:
|
||||
@@ -216,9 +242,31 @@ def _last_test_summary(job: dict[str, Any]) -> dict[str, Any]:
|
||||
|
||||
|
||||
@router.get("")
|
||||
async def list_workflows() -> list[dict[str, Any]]:
|
||||
async def list_workflows(view: str | None = None) -> list[dict[str, Any]]:
|
||||
conn = get_db(settings.db_path)
|
||||
try:
|
||||
if view == "meta":
|
||||
# HEL-681: metadata-only list for 150+ scale browsing — no
|
||||
# workflow_json, no per-row re-parse. `needs_mapping` here is the
|
||||
# cheap pending check (usage/output_map not yet settled); rows
|
||||
# that never generated keep showing as pending exactly like the
|
||||
# full view reports them.
|
||||
rows = conn.execute(
|
||||
f"SELECT {_META_COLUMNS} FROM workflows ORDER BY favorite DESC,"
|
||||
" last_used_at DESC, id DESC"
|
||||
).fetchall()
|
||||
out = []
|
||||
for row in rows:
|
||||
data = row_to_dict(row)
|
||||
data["is_enabled"] = bool(data.get("is_enabled"))
|
||||
data["favorite"] = bool(data.get("favorite"))
|
||||
data["media_io"] = _load_json_col(data.get("media_io"), {"in": [], "out": []})
|
||||
data["tags"] = _load_json_col(data.get("tags"), [])
|
||||
data["needs_mapping"] = data.get("usage") is None or data.get(
|
||||
"output_map_source"
|
||||
) is None
|
||||
out.append(data)
|
||||
return out
|
||||
rows = conn.execute("SELECT * FROM workflows ORDER BY id DESC").fetchall()
|
||||
out = [_serialize_workflow(r) for r in rows]
|
||||
# 上次测试 state is read live from the newest test job per workflow —
|
||||
@@ -395,6 +443,12 @@ async def update_workflow(workflow_id: int, payload: WorkflowUpdate) -> dict[str
|
||||
data = payload.model_dump(exclude_unset=True)
|
||||
if "is_enabled" in data and data["is_enabled"] is not None:
|
||||
data["is_enabled"] = 1 if data["is_enabled"] else 0
|
||||
# HEL-681: library metadata patch fields (favorite/tags/category/
|
||||
# model_family) — booleans to ints, lists to JSON text.
|
||||
if "favorite" in data and data["favorite"] is not None:
|
||||
data["favorite"] = 1 if data["favorite"] else 0
|
||||
if data.get("tags") is not None:
|
||||
data["tags"] = json.dumps(data["tags"])
|
||||
workflow_json = json.loads(existing["workflow_json"])
|
||||
# HEL-638: output_map payload. A non-empty list validates against the
|
||||
# stored JSON and becomes the user decision; an explicit empty list
|
||||
@@ -600,3 +654,280 @@ async def delete_workflow(workflow_id: int) -> dict[str, bool]:
|
||||
return {"ok": True}
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# HEL-681 (S2): UI→API conversion dry-run + batch import + repo scan.
|
||||
# The convert endpoint never writes; import-batch converts again server-side
|
||||
# and skips anything uncertain (needs_confirmation / lint-blocked / conflict)
|
||||
# — repeated runs import nothing new, so the batch is idempotent by design.
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
def _convert_one(item: WorkflowUIFileItem) -> tuple[dict[str, Any], dict[str, Any] | None]:
|
||||
"""(report, converted workflow) for one UI file — shared by every
|
||||
convert/import path so the analysis can never drift between them."""
|
||||
result = convert_ui_workflow(item.workflow_json)
|
||||
stem = (
|
||||
item.source_path.replace("\\", "/").rsplit("/", 1)[-1].removesuffix(".json")
|
||||
if item.source_path
|
||||
else None
|
||||
)
|
||||
name = item.name or stem or "未命名工作流"
|
||||
report: dict[str, Any] = {
|
||||
"name": name,
|
||||
"source_path": item.source_path,
|
||||
"status": result.status,
|
||||
"needs_confirmation": result.needs_confirmation,
|
||||
"issues": [
|
||||
{"node_id": i.node_id, "code": i.code, "level": i.level, "message": i.message}
|
||||
for i in result.issues
|
||||
],
|
||||
}
|
||||
if result.workflow is None:
|
||||
report["importable"] = False
|
||||
report["skip_reason"] = "转换失败:" + (
|
||||
result.issues[0].message if result.issues else "未知错误"
|
||||
)
|
||||
return report, None
|
||||
suggested = suggested_metadata(result.workflow, item.source_path, item.workflow_json)
|
||||
report["suggested"] = suggested
|
||||
# The import gate re-runs the product's own checks — a converted graph
|
||||
# that the lint would block (missing model link etc.) is reported, not
|
||||
# silently imported.
|
||||
broken = blocking_problem(result.workflow)
|
||||
if broken:
|
||||
report["importable"] = False
|
||||
report["skip_reason"] = broken
|
||||
report["status"] = "warn"
|
||||
return report, result.workflow
|
||||
if result.needs_confirmation:
|
||||
report["importable"] = False
|
||||
report["skip_reason"] = "存在无法可靠映射的控件,需人工确认后重导"
|
||||
return report, result.workflow
|
||||
report["importable"] = True
|
||||
return report, result.workflow
|
||||
|
||||
|
||||
@router.post("/convert")
|
||||
async def convert_workflows(payload: WorkflowConvertRequest) -> dict[str, Any]:
|
||||
"""Dry-run UI→API conversion for a batch of files: per-file ok/warn/fail,
|
||||
issues, suggested metadata and importability. Nothing is stored."""
|
||||
files = []
|
||||
object_info: dict[str, Any] | None = None
|
||||
client = None
|
||||
if payload.endpoint_id:
|
||||
endpoint = settings.resolve_comfyui_endpoint(payload.endpoint_id)
|
||||
if endpoint is not None:
|
||||
client = client_for(endpoint)
|
||||
try:
|
||||
object_info = await client.object_info(force_refresh=payload.refresh)
|
||||
except Exception:
|
||||
object_info = None
|
||||
try:
|
||||
for item in payload.files:
|
||||
report, converted = _convert_one(item)
|
||||
if object_info is not None and report.get("importable") and converted:
|
||||
findings = check_workflow_against(object_info, converted)
|
||||
errors = [f for f in findings if f.get("level") == "error"]
|
||||
report["preflight"] = {
|
||||
"endpoint_id": payload.endpoint_id,
|
||||
"ok": not errors,
|
||||
"findings": findings,
|
||||
}
|
||||
if errors:
|
||||
report["importable"] = False
|
||||
report["skip_reason"] = errors[0].get("message") or "preflight 未通过"
|
||||
if payload.include_workflows:
|
||||
report["workflow_json"] = converted
|
||||
files.append(report)
|
||||
finally:
|
||||
if client is not None:
|
||||
await client.close()
|
||||
counts = {key: sum(1 for f in files if f["status"] == key) for key in ("ok", "warn", "fail")}
|
||||
return {
|
||||
"total": len(files),
|
||||
**counts,
|
||||
"needs_confirmation": sum(1 for f in files if f["needs_confirmation"]),
|
||||
"importable": sum(1 for f in files if f.get("importable")),
|
||||
"files": files,
|
||||
}
|
||||
|
||||
|
||||
def _insert_converted(
|
||||
conn: Any, item: WorkflowUIFileItem, report: dict[str, Any], converted: dict[str, Any]
|
||||
) -> dict[str, Any]:
|
||||
"""Insert one converted workflow row (import-batch's write path).
|
||||
|
||||
Mirrors create_workflow's enable gate: usage must be settled (auto or the
|
||||
wizard's confirmation) and unknown outputs need a mapping; anything less
|
||||
lands disabled exactly like a manual import would.
|
||||
"""
|
||||
suggested = report["suggested"]
|
||||
judgment = classify_usage(converted)
|
||||
usage = item.usage or judgment["usage"]
|
||||
usage_source = "user" if item.usage else "auto"
|
||||
kind = usage_to_kind(usage) or suggested["kind"]
|
||||
profile = detect_prompt_profile(converted)
|
||||
if item.output_map:
|
||||
problems = validate_output_map(converted, item.output_map)
|
||||
if problems:
|
||||
raise HTTPException(status_code=422, detail=";".join(problems))
|
||||
output_map = json.dumps(item.output_map)
|
||||
output_map_source = "user"
|
||||
else:
|
||||
auto_map = auto_output_map(converted)
|
||||
output_map = json.dumps(auto_map) if auto_map else None
|
||||
output_map_source = "auto" if auto_map else None
|
||||
mapping_ok = not needs_user_output_map(converted) or bool(item.output_map)
|
||||
workflow_text = json.dumps(converted)
|
||||
existing = conn.execute(
|
||||
"SELECT id FROM workflows WHERE name = ? AND kind = ? AND workflow_json = ?",
|
||||
(report["name"], kind, workflow_text),
|
||||
).fetchone()
|
||||
if existing:
|
||||
return {
|
||||
"result": "skipped",
|
||||
"skip_reason": "conflict",
|
||||
"existing_id": existing["id"],
|
||||
}
|
||||
is_enabled = 1 if (usage and mapping_ok) else 0
|
||||
cur = conn.execute(
|
||||
"""
|
||||
INSERT INTO workflows (name, kind, workflow_json, input_schema, output_schema,
|
||||
description, prompt_profile, endpoint_id, is_enabled,
|
||||
usage, usage_source, output_map, output_map_source,
|
||||
category, model_family, media_io, tags, favorite,
|
||||
source, source_path)
|
||||
VALUES (?, ?, ?, ?, ?, ?, ?, NULL, ?, ?, ?, ?, ?, ?, ?, ?, ?, 0, 'ui_convert', ?)
|
||||
""",
|
||||
(
|
||||
report["name"],
|
||||
kind,
|
||||
workflow_text,
|
||||
json.dumps(
|
||||
item.input_schema if item.input_schema else parse_dynamic_inputs(converted)
|
||||
),
|
||||
json.dumps(parse_dynamic_outputs(converted)),
|
||||
item.description if item.description is not None else suggested["description"],
|
||||
profile,
|
||||
is_enabled,
|
||||
usage,
|
||||
usage_source,
|
||||
output_map,
|
||||
output_map_source,
|
||||
suggested["category"],
|
||||
suggested["model_family"],
|
||||
json.dumps({"in": suggested["media_in"], "out": suggested["media_out"]}),
|
||||
json.dumps(item.tags or []),
|
||||
item.source_path,
|
||||
),
|
||||
)
|
||||
return {"result": "imported", "id": cur.lastrowid}
|
||||
|
||||
|
||||
async def _run_import(items: list[WorkflowUIFileItem]) -> dict[str, Any]:
|
||||
reports: list[dict[str, Any]] = []
|
||||
conn = get_db(settings.db_path)
|
||||
try:
|
||||
for item in items:
|
||||
report, converted = _convert_one(item)
|
||||
if not report.get("importable"):
|
||||
report["result"] = "skipped"
|
||||
reports.append(report)
|
||||
continue
|
||||
try:
|
||||
outcome = _insert_converted(conn, item, report, converted)
|
||||
except HTTPException as exc:
|
||||
report["result"] = "failed"
|
||||
report["skip_reason"] = str(exc.detail)
|
||||
reports.append(report)
|
||||
continue
|
||||
conn.commit()
|
||||
report.update(outcome)
|
||||
reports.append(report)
|
||||
finally:
|
||||
conn.close()
|
||||
imported = [r for r in reports if r.get("result") == "imported"]
|
||||
skipped = [
|
||||
{"name": r["name"], "source_path": r["source_path"], "reason": r.get("skip_reason")}
|
||||
for r in reports
|
||||
if r.get("result") != "imported"
|
||||
]
|
||||
return {
|
||||
"total": len(reports),
|
||||
"imported": len(imported),
|
||||
"skipped": len(skipped),
|
||||
"imported_ids": [r["id"] for r in imported],
|
||||
"skipped_files": skipped,
|
||||
"files": reports,
|
||||
}
|
||||
|
||||
|
||||
@router.post("/import-batch")
|
||||
async def import_workflows_batch(payload: WorkflowImportBatchRequest) -> dict[str, Any]:
|
||||
"""Batch-import UI-format workflows: convert server-side, insert what is
|
||||
cleanly convertible, skip conflicts and anything uncertain. Re-running
|
||||
with the same files creates zero new rows."""
|
||||
return await _run_import(payload.files)
|
||||
|
||||
|
||||
@router.post("/import-scan")
|
||||
async def import_workflows_scan(payload: WorkflowImportScanRequest) -> dict[str, Any]:
|
||||
"""Scan a server-side directory for UI-format workflow JSONs and run the
|
||||
convert (dry_run, default) or import pipeline over every file found."""
|
||||
from pathlib import Path
|
||||
|
||||
root = Path(payload.root)
|
||||
if not root.is_absolute():
|
||||
candidates = [
|
||||
Path.cwd() / root,
|
||||
Path(__file__).resolve().parents[4] / root,
|
||||
]
|
||||
root = next((c for c in candidates if c.is_dir()), root)
|
||||
if not root.is_dir():
|
||||
raise HTTPException(status_code=404, detail=f"目录不存在:{payload.root}")
|
||||
items: list[WorkflowUIFileItem] = []
|
||||
for path in sorted(root.rglob("*.json")):
|
||||
try:
|
||||
data = json.loads(path.read_text(encoding="utf-8"))
|
||||
except (json.JSONDecodeError, OSError):
|
||||
continue
|
||||
if not (isinstance(data, dict) and isinstance(data.get("nodes"), list)):
|
||||
continue # API-format or non-workflow files: not this pipeline's job
|
||||
items.append(
|
||||
WorkflowUIFileItem(
|
||||
source_path=str(path.relative_to(root)), workflow_json=data
|
||||
)
|
||||
)
|
||||
if payload.dry_run:
|
||||
files = [_convert_one(item)[0] for item in items]
|
||||
counts = {
|
||||
key: sum(1 for f in files if f["status"] == key) for key in ("ok", "warn", "fail")
|
||||
}
|
||||
return {
|
||||
"total": len(files),
|
||||
**counts,
|
||||
"needs_confirmation": sum(1 for f in files if f["needs_confirmation"]),
|
||||
"importable": sum(1 for f in files if f.get("importable")),
|
||||
"files": files,
|
||||
}
|
||||
return await _run_import(items)
|
||||
|
||||
|
||||
@router.post("/{workflow_id}/touch")
|
||||
async def touch_workflow(workflow_id: int) -> dict[str, bool]:
|
||||
"""Record a use (最近使用) — called by the generate pipeline on enqueue."""
|
||||
conn = get_db(settings.db_path)
|
||||
try:
|
||||
row = conn.execute("SELECT id FROM workflows WHERE id = ?", (workflow_id,)).fetchone()
|
||||
if not row:
|
||||
raise HTTPException(status_code=404, detail="Workflow not found")
|
||||
conn.execute(
|
||||
"UPDATE workflows SET last_used_at = CURRENT_TIMESTAMP WHERE id = ?",
|
||||
(workflow_id,),
|
||||
)
|
||||
conn.commit()
|
||||
return {"ok": True}
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
@@ -0,0 +1,449 @@
|
||||
"""HEL-681: UI→API converter unit tests + ground-truth cross-checks.
|
||||
|
||||
The synthetic graphs pin the structural semantics (reroute / bypass / mute /
|
||||
subgraph expansion / Set-Get variables / control_after_generate pairing);
|
||||
the corpus section runs the real 146-file library and the repo's API exports.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import copy
|
||||
import json
|
||||
from pathlib import Path
|
||||
|
||||
import pytest
|
||||
|
||||
from calliope.comfyui.lint import workflow_warnings
|
||||
from calliope.comfyui.ui_convert import convert_ui_workflow
|
||||
|
||||
EXAMPLES = Path(__file__).resolve().parents[2] / "example_ComfyUI_workflows"
|
||||
|
||||
|
||||
def _node(nid, ntype, *, mode=0, inputs=None, outputs=None, wv=None, wvn=None, title=None):
|
||||
node = {"id": nid, "type": ntype, "mode": mode, "inputs": inputs or [], "order": 0}
|
||||
if outputs is not None:
|
||||
node["outputs"] = outputs
|
||||
if wv is not None:
|
||||
node["widgets_values"] = wv
|
||||
if wvn is not None:
|
||||
node["widgets_values_named"] = wvn
|
||||
if title:
|
||||
node["title"] = title
|
||||
return node
|
||||
|
||||
|
||||
def _in_slot(name, type_, link=None, widget=None):
|
||||
entry = {"name": name, "type": type_, "link": link}
|
||||
if widget:
|
||||
entry["widget"] = {"name": widget}
|
||||
return entry
|
||||
|
||||
|
||||
def _out(name, type_, links=None):
|
||||
return {"name": name, "type": type_, "links": links or [], "slot_index": 0}
|
||||
|
||||
|
||||
def _base_graph():
|
||||
"""text2image: loader → prompts/latent → KSampler → VAE → SaveImage."""
|
||||
nodes = [
|
||||
_node(
|
||||
1,
|
||||
"CheckpointLoaderSimple",
|
||||
outputs=[_out("MODEL", "MODEL"), _out("CLIP", "CLIP"), _out("VAE", "VAE")],
|
||||
wv=["model.safetensors"],
|
||||
inputs=[_in_slot("ckpt_name", "COMBO", widget="ckpt_name")],
|
||||
),
|
||||
_node(
|
||||
2,
|
||||
"CLIPTextEncode",
|
||||
inputs=[
|
||||
_in_slot("clip", "CLIP", link=1),
|
||||
_in_slot("text", "STRING", widget="text"),
|
||||
],
|
||||
outputs=[_out("CONDITIONING", "CONDITIONING")],
|
||||
wv=["a cat"],
|
||||
),
|
||||
_node(
|
||||
3,
|
||||
"CLIPTextEncode",
|
||||
inputs=[
|
||||
_in_slot("clip", "CLIP", link=2),
|
||||
_in_slot("text", "STRING", widget="text"),
|
||||
],
|
||||
outputs=[_out("CONDITIONING", "CONDITIONING")],
|
||||
wv=["bad quality"],
|
||||
),
|
||||
_node(
|
||||
4,
|
||||
"EmptyLatentImage",
|
||||
inputs=[
|
||||
_in_slot("width", "INT", widget="width"),
|
||||
_in_slot("height", "INT", widget="height"),
|
||||
_in_slot("batch_size", "INT", widget="batch_size"),
|
||||
],
|
||||
outputs=[_out("LATENT", "LATENT")],
|
||||
wv=[512, 512, 1],
|
||||
),
|
||||
_node(
|
||||
5,
|
||||
"KSampler",
|
||||
inputs=[
|
||||
_in_slot("model", "MODEL", link=3),
|
||||
_in_slot("positive", "CONDITIONING", link=4),
|
||||
_in_slot("negative", "CONDITIONING", link=5),
|
||||
_in_slot("latent_image", "LATENT", link=6),
|
||||
_in_slot("seed", "INT", widget="seed"),
|
||||
_in_slot("steps", "INT", widget="steps"),
|
||||
_in_slot("cfg", "FLOAT", widget="cfg"),
|
||||
_in_slot("sampler_name", "COMBO", widget="sampler_name"),
|
||||
_in_slot("scheduler", "COMBO", widget="scheduler"),
|
||||
_in_slot("denoise", "FLOAT", widget="denoise"),
|
||||
],
|
||||
outputs=[_out("LATENT", "LATENT")],
|
||||
# seed 42 + control "fixed" rides together, then five widgets
|
||||
wv=[42, "fixed", 20, 7, "euler", "normal", 1.0],
|
||||
),
|
||||
_node(
|
||||
6,
|
||||
"VAEDecode",
|
||||
inputs=[
|
||||
_in_slot("samples", "LATENT", link=7),
|
||||
_in_slot("vae", "VAE", link=8),
|
||||
],
|
||||
outputs=[_out("IMAGE", "IMAGE")],
|
||||
),
|
||||
_node(
|
||||
7,
|
||||
"SaveImage",
|
||||
inputs=[
|
||||
_in_slot("images", "IMAGE", link=9),
|
||||
_in_slot("filename_prefix", "STRING", widget="filename_prefix"),
|
||||
],
|
||||
wv=["test"],
|
||||
),
|
||||
]
|
||||
links = [
|
||||
[1, 1, 1, 2, 0, "CLIP"],
|
||||
[2, 1, 1, 3, 0, "CLIP"],
|
||||
[3, 1, 0, 5, 0, "MODEL"],
|
||||
[4, 2, 0, 5, 1, "CONDITIONING"],
|
||||
[5, 3, 0, 5, 2, "CONDITIONING"],
|
||||
[6, 4, 0, 5, 3, "LATENT"],
|
||||
[7, 5, 0, 6, 0, "LATENT"],
|
||||
[8, 1, 2, 6, 1, "VAE"],
|
||||
[9, 6, 0, 7, 0, "IMAGE"],
|
||||
]
|
||||
return {"nodes": nodes, "links": links, "last_node_id": 7, "last_link_id": 9}
|
||||
|
||||
|
||||
def _convert(graph):
|
||||
return convert_ui_workflow(graph)
|
||||
|
||||
|
||||
def test_clean_conversion_maps_everything():
|
||||
result = _convert(_base_graph())
|
||||
assert result.status == "ok"
|
||||
assert result.needs_confirmation is False
|
||||
wf = result.workflow
|
||||
assert set(wf) == {"1", "2", "3", "4", "5", "6", "7"}
|
||||
ks = wf["5"]
|
||||
assert ks["class_type"] == "KSampler"
|
||||
assert ks["inputs"]["seed"] == 42 # control_after_generate consumed silently
|
||||
assert ks["inputs"]["steps"] == 20
|
||||
assert ks["inputs"]["denoise"] == 1.0
|
||||
assert ks["inputs"]["model"] == ["1", 0]
|
||||
assert ks["inputs"]["latent_image"] == ["4", 0]
|
||||
# lint on the converted graph must be error-free
|
||||
assert not [w for w in workflow_warnings(wf) if w["level"] == "error"]
|
||||
|
||||
|
||||
def test_upload_button_widgets_are_consumed_but_never_emitted():
|
||||
graph = _base_graph()
|
||||
load = _node(
|
||||
8,
|
||||
"LoadImage",
|
||||
inputs=[
|
||||
_in_slot("image", "COMBO", widget="image"),
|
||||
_in_slot("upload", "IMAGEUPLOAD", widget="upload"),
|
||||
],
|
||||
outputs=[_out("IMAGE", "IMAGE")],
|
||||
wv=["sample.png", "image"],
|
||||
)
|
||||
save = _node(
|
||||
9,
|
||||
"PreviewImage",
|
||||
inputs=[
|
||||
_in_slot("images", "IMAGE", link=20),
|
||||
_in_slot("filename_prefix", "STRING", widget="filename_prefix"),
|
||||
],
|
||||
wv=["preview"],
|
||||
)
|
||||
graph["nodes"] += [load, save]
|
||||
graph["links"].append([20, 8, 0, 9, 0, "IMAGE"])
|
||||
result = _convert(graph)
|
||||
assert result.workflow["8"]["inputs"] == {"image": "sample.png"}
|
||||
|
||||
|
||||
def test_reroute_pass_through():
|
||||
graph = _base_graph()
|
||||
reroute = _node(8, "Reroute", inputs=[_in_slot("(in)", "*", link=9)])
|
||||
graph["nodes"].append(reroute)
|
||||
# SaveImage now fed by the reroute instead of VAEDecode directly
|
||||
graph["nodes"][6]["inputs"][0]["link"] = 10
|
||||
graph["links"].append([10, 8, 0, 7, 0, "IMAGE"])
|
||||
result = _convert(graph)
|
||||
assert result.workflow["7"]["inputs"]["images"] == ["6", 0]
|
||||
assert "8" not in result.workflow
|
||||
|
||||
|
||||
def test_bypass_pass_through_and_mute_drop():
|
||||
graph = _base_graph()
|
||||
# bypass the KSampler: VAEDecode.samples must fall back to the latent
|
||||
graph["nodes"][4]["mode"] = 4
|
||||
result = _convert(graph)
|
||||
assert result.workflow["6"]["inputs"]["samples"] == ["4", 0]
|
||||
# mute the negative prompt: the link input is dropped with a warning
|
||||
graph = _base_graph()
|
||||
graph["nodes"][2]["mode"] = 2
|
||||
result = _convert(graph)
|
||||
assert "negative" not in result.workflow["5"]["inputs"]
|
||||
assert any(i.code == "muted_input_dropped" for i in result.issues)
|
||||
|
||||
|
||||
def test_widget_entry_with_muted_upstream_falls_back_to_value():
|
||||
graph = _base_graph()
|
||||
# feed seed from a muted PrimitiveInt via a converted widget input
|
||||
prim = _node(
|
||||
9,
|
||||
"PrimitiveInt",
|
||||
mode=2,
|
||||
inputs=[_in_slot("value", "INT", widget="value"), _in_slot("control", "COMBO", widget="control")],
|
||||
wv=[7],
|
||||
)
|
||||
graph["nodes"].append(prim)
|
||||
graph["nodes"][4]["inputs"][4]["link"] = 11 # seed ← primitive
|
||||
graph["links"].append([11, 9, 0, 5, 4, "INT"])
|
||||
result = _convert(graph)
|
||||
assert result.workflow["5"]["inputs"]["seed"] == 42
|
||||
|
||||
|
||||
def test_subgraph_expansion_and_boundary_wiring():
|
||||
graph = _base_graph()
|
||||
# pack the EmptyLatentImage into a subgraph exposing width/height widgets
|
||||
del graph["nodes"][3]
|
||||
graph["nodes"] = [n for n in graph["nodes"] if n["id"] != 4]
|
||||
sub_id = "aaaa-bbbb-cccc-dddd-eeee"
|
||||
packed = _node(
|
||||
20,
|
||||
sub_id,
|
||||
inputs=[
|
||||
_in_slot("width", "INT", widget="width"),
|
||||
_in_slot("height", "INT", widget="height"),
|
||||
],
|
||||
outputs=[_out("LATENT", "LATENT")],
|
||||
wv=[640, 384],
|
||||
)
|
||||
graph["nodes"].append(packed)
|
||||
# KSampler latent_image ← packed output
|
||||
graph["links"] = [l for l in graph["links"] if l[0] != 6]
|
||||
graph["links"].append([6, 20, 0, 5, 3, "LATENT"])
|
||||
graph["definitions"] = {
|
||||
"subgraphs": [
|
||||
{
|
||||
"id": sub_id,
|
||||
"name": "Latent",
|
||||
"inputs": [
|
||||
{"name": "width", "type": "INT"},
|
||||
{"name": "height", "type": "INT"},
|
||||
],
|
||||
"outputs": [{"name": "LATENT", "type": "LATENT"}],
|
||||
"inputNode": {"id": -10},
|
||||
"outputNode": {"id": -20},
|
||||
"nodes": [
|
||||
_node(
|
||||
5,
|
||||
"EmptyLatentImage",
|
||||
inputs=[
|
||||
_in_slot("width", "INT", widget="width", link=101),
|
||||
_in_slot("height", "INT", widget="height", link=102),
|
||||
_in_slot("batch_size", "INT", widget="batch_size"),
|
||||
],
|
||||
outputs=[_out("LATENT", "LATENT")],
|
||||
wv=[512, 512, 1],
|
||||
),
|
||||
],
|
||||
"links": [
|
||||
{"id": 101, "origin_id": -10, "origin_slot": 0, "target_id": 5, "target_slot": 0, "type": "INT"},
|
||||
{"id": 102, "origin_id": -10, "origin_slot": 1, "target_id": 5, "target_slot": 1, "type": "INT"},
|
||||
{"id": 103, "origin_id": 5, "origin_slot": 0, "target_id": -20, "target_slot": 0, "type": "LATENT"},
|
||||
],
|
||||
}
|
||||
]
|
||||
}
|
||||
result = _convert(graph)
|
||||
wf = result.workflow
|
||||
assert "20:5" in wf # qualified packed:inner id, ComfyUI's own scheme
|
||||
inner = wf["20:5"]
|
||||
assert inner["class_type"] == "EmptyLatentImage"
|
||||
# exposed widget values from the packed instance, not the inner defaults
|
||||
assert inner["inputs"]["width"] == 640
|
||||
assert inner["inputs"]["height"] == 384
|
||||
assert inner["inputs"]["batch_size"] == 1
|
||||
assert wf["5"]["inputs"]["latent_image"] == ["20:5", 0]
|
||||
# now wire the packed width slot from outside: boundary becomes a link
|
||||
res_node = _node(
|
||||
21,
|
||||
"ResolutionSelector",
|
||||
inputs=[_in_slot("aspect_ratio", "COMBO", widget="aspect_ratio")],
|
||||
outputs=[_out("width", "INT"), _out("height", "INT")],
|
||||
wv=["1:1"],
|
||||
)
|
||||
graph["nodes"].append(res_node)
|
||||
graph["nodes"][-2]["inputs"][0]["link"] = 12 # packed width ← selector
|
||||
graph["links"].append([12, 21, 0, 20, 0, "INT"])
|
||||
wf2 = _convert(graph).workflow
|
||||
assert wf2["20:5"]["inputs"]["width"] == ["21", 0]
|
||||
assert wf2["20:5"]["inputs"]["height"] == 384
|
||||
|
||||
|
||||
def test_set_get_variables_resolve_to_captured_source():
|
||||
graph = _base_graph()
|
||||
setter = _node(8, "SetNode", inputs=[_in_slot("*", "*", link=8)], wv=["the_vae"])
|
||||
getter = _node(9, "GetNode", wv=["the_vae"], outputs=[_out("VAE", "VAE")])
|
||||
graph["nodes"] += [setter, getter]
|
||||
# VAEDecode.vae now fed via the variable
|
||||
graph["nodes"][5]["inputs"][1]["link"] = 13
|
||||
graph["links"] = [l for l in graph["links"] if l[0] != 8]
|
||||
graph["links"] += [
|
||||
[8, 1, 2, 8, 0, "VAE"],
|
||||
[13, 9, 0, 6, 1, "VAE"],
|
||||
]
|
||||
result = _convert(graph)
|
||||
assert "8" not in result.workflow and "9" not in result.workflow
|
||||
assert result.workflow["6"]["inputs"]["vae"] == ["1", 2]
|
||||
|
||||
|
||||
def test_unknown_widget_order_lands_in_needs_confirmation():
|
||||
graph = _base_graph()
|
||||
# an old-frontend node: positional widgets, no widget markers, no registry
|
||||
graph["nodes"].append(
|
||||
_node(10, "MysteryCustomNode", inputs=[], outputs=[_out("IMAGE", "IMAGE")], wv=[1, 2, 3])
|
||||
)
|
||||
save = _node(
|
||||
11,
|
||||
"PreviewImage",
|
||||
inputs=[_in_slot("images", "IMAGE", link=30)],
|
||||
wv=["preview"],
|
||||
)
|
||||
graph["nodes"].append(save)
|
||||
graph["links"].append([30, 10, 0, 11, 0, "IMAGE"])
|
||||
result = _convert(graph)
|
||||
assert result.needs_confirmation is True
|
||||
assert any(i.code == "widget_unmapped" for i in result.issues)
|
||||
# the node is still converted structurally — the report carries the doubt
|
||||
assert "10" in result.workflow
|
||||
|
||||
|
||||
def test_not_ui_format_fails_fast():
|
||||
result = convert_ui_workflow({"3": {"class_type": "SaveImage", "inputs": {}}})
|
||||
assert result.status == "fail"
|
||||
assert result.workflow is None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Real corpus: the 146 UI files + ground-truth API cross-checks (对拍).
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
pytestmark_convert = pytest.mark.skipif(
|
||||
not EXAMPLES.is_dir(), reason="example_ComfyUI_workflows not checked out"
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.skipif(not EXAMPLES.is_dir(), reason="example library missing")
|
||||
def test_corpus_146_files_all_convert():
|
||||
ui_files = [
|
||||
p
|
||||
for p in sorted(EXAMPLES.rglob("*.json"))
|
||||
if isinstance(json.loads(p.read_text(encoding="utf-8")), dict)
|
||||
and isinstance(json.loads(p.read_text(encoding="utf-8")).get("nodes"), list)
|
||||
]
|
||||
assert len(ui_files) == 146
|
||||
statuses = {"ok": 0, "warn": 0, "fail": 0}
|
||||
needs_confirmation = 0
|
||||
for path in ui_files:
|
||||
data = json.loads(path.read_text(encoding="utf-8"))
|
||||
result = convert_ui_workflow(data)
|
||||
statuses[result.status] += 1
|
||||
needs_confirmation += result.needs_confirmation
|
||||
assert result.workflow, f"{path.name} produced no workflow"
|
||||
# structural sanity: no dangling links in any conversion
|
||||
nodes = result.workflow
|
||||
for nid, node in nodes.items():
|
||||
for name, val in node.get("inputs", {}).items():
|
||||
if isinstance(val, list):
|
||||
assert str(val[0]) in nodes, f"{path.name}: {nid}.{name} dangles"
|
||||
assert statuses["fail"] == 0
|
||||
assert statuses["ok"] + statuses["warn"] == 146
|
||||
# files whose widget order cannot be trusted are flagged, never hidden
|
||||
assert 0 < needs_confirmation < 10
|
||||
|
||||
|
||||
@pytest.mark.skipif(not EXAMPLES.is_dir(), reason="example library missing")
|
||||
def test_cross_check_against_ground_truth_exports():
|
||||
"""The H3 t2v UI export converts to the same node classes the author's
|
||||
own API export carries; shared classes agree on scalar input names."""
|
||||
ui = json.loads(
|
||||
(EXAMPLES / "4-视频生成/Minimax-h3/minimax_h3_t2v_文生视频.json").read_text(encoding="utf-8")
|
||||
)
|
||||
api = json.loads(
|
||||
(EXAMPLES / "minimax_h3-Turbo_Text2Video_20260813_API.json").read_text(encoding="utf-8")
|
||||
)
|
||||
result = convert_ui_workflow(ui)
|
||||
assert result.status in ("ok", "warn")
|
||||
converted = result.workflow
|
||||
api_classes = {n["class_type"] for n in api.values()}
|
||||
# Every scalar name the conversion emits for a shared class must be an
|
||||
# input name the author's own export knows — wiring may differ between
|
||||
# versions (a muted branch falls back to its widget value), but the NAME
|
||||
# mapping must never invent or swap inputs.
|
||||
for cls in api_classes & {n["class_type"] for n in converted.values()}:
|
||||
api_names = {
|
||||
key
|
||||
for n in api.values()
|
||||
if n["class_type"] == cls
|
||||
for key in n.get("inputs", {})
|
||||
}
|
||||
conv_names = {
|
||||
key
|
||||
for n in converted.values()
|
||||
if n["class_type"] == cls
|
||||
for key, v in n.get("inputs", {}).items()
|
||||
if not isinstance(v, list)
|
||||
}
|
||||
assert conv_names <= api_names, f"class {cls} invents inputs: {conv_names - api_names}"
|
||||
|
||||
|
||||
@pytest.mark.skipif(not EXAMPLES.is_dir(), reason="example library missing")
|
||||
def test_packed_krea2_conversion_shape_matches_export_scheme():
|
||||
"""The krea2 turbo file (packed subgraph) converts ok, expands inner nodes
|
||||
under `<packed>:<inner>` ids and maps the sampler widgets exactly — the
|
||||
same scheme the author's own Krea2 API export uses (ids like "171:153")."""
|
||||
ui = json.loads(
|
||||
(EXAMPLES / "3-图像生成/krea2/krea2_turbo_文生图.json").read_text(encoding="utf-8")
|
||||
)
|
||||
api = json.loads(
|
||||
(EXAMPLES / "Krea2_t2i_20260818_API.json").read_text(encoding="utf-8")
|
||||
)
|
||||
result = convert_ui_workflow(ui)
|
||||
assert result.status == "ok"
|
||||
assert any(":" in nid for nid in result.workflow) # expanded subgraph nodes
|
||||
assert any("171:" in nid for nid in api) # ground truth uses the same scheme
|
||||
ks = [
|
||||
n
|
||||
for n in result.workflow.values()
|
||||
if n["class_type"] == "KSampler" and not isinstance(n["inputs"].get("seed"), list)
|
||||
]
|
||||
assert ks, "inner KSampler with widget-mapped seed expected"
|
||||
assert {"seed", "steps", "cfg", "sampler_name", "scheduler", "denoise"} <= set(
|
||||
ks[0]["inputs"]
|
||||
)
|
||||
@@ -0,0 +1,421 @@
|
||||
"""HEL-681 (S2): batch import endpoints, meta list view, migration safety.
|
||||
|
||||
Everything runs on a temp DB via the shared client fixture — the real
|
||||
146-file library is never touched, matching the card's「不导入生产数据」boundary.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
import sqlite3
|
||||
from pathlib import Path
|
||||
|
||||
from calliope.db import migrate_db
|
||||
|
||||
import pytest
|
||||
|
||||
|
||||
EXAMPLES = Path(__file__).resolve().parents[2] / "example_ComfyUI_workflows"
|
||||
|
||||
|
||||
def _ui_graph():
|
||||
"""Minimal clean t2i UI graph (same shape as test_ui_convert's)."""
|
||||
return {
|
||||
"nodes": [
|
||||
{
|
||||
"id": 1,
|
||||
"type": "CheckpointLoaderSimple",
|
||||
"mode": 0,
|
||||
"inputs": [{"name": "ckpt_name", "type": "COMBO", "widget": {"name": "ckpt_name"}, "link": None}],
|
||||
"outputs": [
|
||||
{"name": "MODEL", "type": "MODEL", "links": [3], "slot_index": 0},
|
||||
{"name": "CLIP", "type": "CLIP", "links": [1, 2], "slot_index": 1},
|
||||
{"name": "VAE", "type": "VAE", "links": [8], "slot_index": 2},
|
||||
],
|
||||
"widgets_values": ["qwen_image_2.safetensors"],
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"type": "CLIPTextEncode",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "clip", "type": "CLIP", "link": 1},
|
||||
{"name": "text", "type": "STRING", "widget": {"name": "text"}, "link": None},
|
||||
],
|
||||
"outputs": [{"name": "CONDITIONING", "type": "CONDITIONING", "links": [4], "slot_index": 0}],
|
||||
"widgets_values": ["a cat"],
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"type": "CLIPTextEncode",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "clip", "type": "CLIP", "link": 2},
|
||||
{"name": "text", "type": "STRING", "widget": {"name": "text"}, "link": None},
|
||||
],
|
||||
"outputs": [{"name": "CONDITIONING", "type": "CONDITIONING", "links": [5], "slot_index": 0}],
|
||||
"widgets_values": ["bad"],
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"type": "EmptyLatentImage",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "width", "type": "INT", "widget": {"name": "width"}, "link": None},
|
||||
{"name": "height", "type": "INT", "widget": {"name": "height"}, "link": None},
|
||||
{"name": "batch_size", "type": "INT", "widget": {"name": "batch_size"}, "link": None},
|
||||
],
|
||||
"outputs": [{"name": "LATENT", "type": "LATENT", "links": [6], "slot_index": 0}],
|
||||
"widgets_values": [512, 512, 1],
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"type": "KSampler",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "model", "type": "MODEL", "link": 3},
|
||||
{"name": "positive", "type": "CONDITIONING", "link": 4},
|
||||
{"name": "negative", "type": "CONDITIONING", "link": 5},
|
||||
{"name": "latent_image", "type": "LATENT", "link": 6},
|
||||
{"name": "seed", "type": "INT", "widget": {"name": "seed"}, "link": None},
|
||||
{"name": "steps", "type": "INT", "widget": {"name": "steps"}, "link": None},
|
||||
{"name": "cfg", "type": "FLOAT", "widget": {"name": "cfg"}, "link": None},
|
||||
{"name": "sampler_name", "type": "COMBO", "widget": {"name": "sampler_name"}, "link": None},
|
||||
{"name": "scheduler", "type": "COMBO", "widget": {"name": "scheduler"}, "link": None},
|
||||
{"name": "denoise", "type": "FLOAT", "widget": {"name": "denoise"}, "link": None},
|
||||
],
|
||||
"outputs": [{"name": "LATENT", "type": "LATENT", "links": [7], "slot_index": 0}],
|
||||
"widgets_values": [42, "fixed", 20, 7, "euler", "normal", 1.0],
|
||||
},
|
||||
{
|
||||
"id": 6,
|
||||
"type": "VAEDecode",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "samples", "type": "LATENT", "link": 7},
|
||||
{"name": "vae", "type": "VAE", "link": 8},
|
||||
],
|
||||
"outputs": [{"name": "IMAGE", "type": "IMAGE", "links": [9], "slot_index": 0}],
|
||||
},
|
||||
{
|
||||
"id": 7,
|
||||
"type": "SaveImage",
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{"name": "images", "type": "IMAGE", "link": 9},
|
||||
{"name": "filename_prefix", "type": "STRING", "widget": {"name": "filename_prefix"}, "link": None},
|
||||
],
|
||||
"widgets_values": ["test"],
|
||||
},
|
||||
],
|
||||
"links": [
|
||||
[1, 1, 1, 2, 0, "CLIP"],
|
||||
[2, 1, 1, 3, 0, "CLIP"],
|
||||
[3, 1, 0, 5, 0, "MODEL"],
|
||||
[4, 2, 0, 5, 1, "CONDITIONING"],
|
||||
[5, 3, 0, 5, 2, "CONDITIONING"],
|
||||
[6, 4, 0, 5, 3, "LATENT"],
|
||||
[7, 5, 0, 6, 0, "LATENT"],
|
||||
[8, 1, 2, 6, 1, "VAE"],
|
||||
[9, 6, 0, 7, 0, "IMAGE"],
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def _api_workflow():
|
||||
return json.loads(
|
||||
(EXAMPLES / "video_minimax_h3_r2v_2ref_API.json").read_text(encoding="utf-8")
|
||||
)
|
||||
|
||||
|
||||
def test_convert_dry_run_reports_and_stores_nothing(client):
|
||||
payload = {
|
||||
"files": [
|
||||
{
|
||||
"source_path": "3-图像生成/Qwen-Image-2.1/test_t2i.json",
|
||||
"workflow_json": _ui_graph(),
|
||||
}
|
||||
],
|
||||
"include_workflows": True,
|
||||
}
|
||||
resp = client.post("/api/workflows/convert", json=payload)
|
||||
assert resp.status_code == 200
|
||||
body = resp.json()
|
||||
assert body["total"] == 1 and body["ok"] == 1 and body["importable"] == 1
|
||||
entry = body["files"][0]
|
||||
assert entry["name"] == "test_t2i"
|
||||
assert entry["workflow_json"]["5"]["inputs"]["seed"] == 42
|
||||
assert entry["suggested"]["usage"] == "text2image"
|
||||
assert entry["suggested"]["category"] == "image"
|
||||
assert entry["suggested"]["model_family"] == "Qwen"
|
||||
assert entry["suggested"]["media_out"] == ["image"]
|
||||
# dry-run must not write anything
|
||||
assert client.get("/api/workflows").json() == []
|
||||
|
||||
|
||||
def test_convert_needs_confirmation_is_flagged_not_runnable(client):
|
||||
graph = _ui_graph()
|
||||
graph["nodes"].append(
|
||||
{
|
||||
"id": 10,
|
||||
"type": "MysteryCustomNode",
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [{"name": "IMAGE", "type": "IMAGE", "links": [30], "slot_index": 0}],
|
||||
"widgets_values": [1, 2, 3],
|
||||
}
|
||||
)
|
||||
graph["nodes"].append(
|
||||
{
|
||||
"id": 11,
|
||||
"type": "PreviewImage",
|
||||
"mode": 0,
|
||||
"inputs": [{"name": "images", "type": "IMAGE", "link": 30}],
|
||||
"widgets_values": ["p"],
|
||||
}
|
||||
)
|
||||
graph["links"].append([30, 10, 0, 11, 0, "IMAGE"])
|
||||
resp = client.post(
|
||||
"/api/workflows/convert",
|
||||
json={"files": [{"source_path": "x/mystery.json", "workflow_json": graph}]},
|
||||
)
|
||||
body = resp.json()
|
||||
assert body["needs_confirmation"] == 1
|
||||
assert body["importable"] == 0
|
||||
assert "需人工确认" in body["files"][0]["skip_reason"]
|
||||
|
||||
|
||||
def test_import_batch_then_rerun_is_idempotent(client):
|
||||
files = [
|
||||
{
|
||||
"source_path": "3-图像生成/Qwen-Image-2.1/test_t2i.json",
|
||||
"workflow_json": _ui_graph(),
|
||||
}
|
||||
]
|
||||
first = client.post("/api/workflows/import-batch", json={"files": files})
|
||||
assert first.status_code == 200
|
||||
body = first.json()
|
||||
assert body["imported"] == 1 and body["skipped"] == 0
|
||||
row_id = body["imported_ids"][0]
|
||||
|
||||
# second run with identical file: conflict skip, no duplicates
|
||||
second = client.post("/api/workflows/import-batch", json={"files": files})
|
||||
body2 = second.json()
|
||||
assert body2["imported"] == 0 and body2["skipped"] == 1
|
||||
assert body2["skipped_files"][0]["reason"] == "conflict"
|
||||
listing = client.get("/api/workflows").json()
|
||||
assert len(listing) == 1
|
||||
|
||||
detail = client.get(f"/api/workflows/{row_id}").json()
|
||||
assert detail["usage"] == "text2image"
|
||||
assert detail["is_enabled"] is True
|
||||
assert detail["category"] == "image"
|
||||
assert detail["model_family"] == "Qwen"
|
||||
assert detail["media_io"] == {"in": [], "out": ["image"]}
|
||||
assert detail["source"] == "ui_convert"
|
||||
assert detail["source_path"] == "3-图像生成/Qwen-Image-2.1/test_t2i.json"
|
||||
|
||||
|
||||
def test_import_batch_skips_needs_confirmation_files(client):
|
||||
graph = _ui_graph()
|
||||
graph["nodes"].append(
|
||||
{
|
||||
"id": 10,
|
||||
"type": "MysteryCustomNode",
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [{"name": "IMAGE", "type": "IMAGE", "links": [30], "slot_index": 0}],
|
||||
"widgets_values": [1, 2, 3],
|
||||
}
|
||||
)
|
||||
graph["nodes"].append(
|
||||
{
|
||||
"id": 11,
|
||||
"type": "PreviewImage",
|
||||
"mode": 0,
|
||||
"inputs": [{"name": "images", "type": "IMAGE", "link": 30}],
|
||||
"widgets_values": ["p"],
|
||||
}
|
||||
)
|
||||
graph["links"].append([30, 10, 0, 11, 0, "IMAGE"])
|
||||
resp = client.post(
|
||||
"/api/workflows/import-batch",
|
||||
json={"files": [{"name": "mystery", "workflow_json": graph}]},
|
||||
)
|
||||
body = resp.json()
|
||||
assert body["imported"] == 0
|
||||
assert "需人工确认" in body["skipped_files"][0]["reason"]
|
||||
assert client.get("/api/workflows").json() == []
|
||||
|
||||
|
||||
def test_warn_sample_imports_with_human_confirmation(client):
|
||||
"""A warn file (muted branch → input dropped) still imports when the
|
||||
wizard supplies the settled usage — the manual-correction path."""
|
||||
graph = _ui_graph()
|
||||
graph["nodes"][2]["mode"] = 2 # mute the negative prompt branch
|
||||
dry = client.post(
|
||||
"/api/workflows/convert",
|
||||
json={"files": [{"name": "warned", "workflow_json": graph}]},
|
||||
).json()
|
||||
assert dry["warn"] == 1 and dry["importable"] == 1
|
||||
resp = client.post(
|
||||
"/api/workflows/import-batch",
|
||||
json={"files": [{"name": "warned", "workflow_json": graph, "usage": "text2image"}]},
|
||||
)
|
||||
body = resp.json()
|
||||
assert body["imported"] == 1
|
||||
detail = client.get(f"/api/workflows/{body['imported_ids'][0]}").json()
|
||||
assert detail["is_enabled"] is True
|
||||
assert "negative" not in detail["workflow_json"]["5"]["inputs"]
|
||||
|
||||
|
||||
@pytest.mark.skipif(not EXAMPLES.is_dir(), reason="example library missing")
|
||||
def test_import_scan_dry_run_over_repo_library(client):
|
||||
resp = client.post(
|
||||
"/api/workflows/import-scan",
|
||||
json={"root": str(EXAMPLES), "dry_run": True},
|
||||
)
|
||||
assert resp.status_code == 200
|
||||
body = resp.json()
|
||||
assert body["total"] == 146
|
||||
assert body["fail"] == 0
|
||||
assert body["ok"] + body["warn"] == 146
|
||||
assert body["needs_confirmation"] > 0 # the 3 uncensored files stay honest
|
||||
assert body["importable"] < body["total"]
|
||||
# a dry scan must leave the DB untouched
|
||||
assert client.get("/api/workflows").json() == []
|
||||
|
||||
|
||||
def test_import_scan_commit_from_tmp_directory(client, tmp_path):
|
||||
(tmp_path / "sub").mkdir()
|
||||
(tmp_path / "sub" / "demo.json").write_text(json.dumps(_ui_graph()), encoding="utf-8")
|
||||
(tmp_path / "plain_api.json").write_text(json.dumps(_api_workflow()), encoding="utf-8")
|
||||
(tmp_path / "not_a_workflow.json").write_text(json.dumps({"hello": 1}), encoding="utf-8")
|
||||
resp = client.post(
|
||||
"/api/workflows/import-scan",
|
||||
json={"root": str(tmp_path), "dry_run": False},
|
||||
)
|
||||
body = resp.json()
|
||||
# only the one UI file went through this pipeline; API-format and junk skipped
|
||||
assert body["imported"] == 1
|
||||
listing = client.get("/api/workflows").json()
|
||||
assert len(listing) == 1
|
||||
assert listing[0]["source_path"] == "sub/demo.json"
|
||||
# rerun: idempotent
|
||||
again = client.post(
|
||||
"/api/workflows/import-scan",
|
||||
json={"root": str(tmp_path), "dry_run": False},
|
||||
).json()
|
||||
assert again["imported"] == 0
|
||||
assert len(client.get("/api/workflows").json()) == 1
|
||||
|
||||
|
||||
def test_meta_view_has_metadata_but_no_full_json(client):
|
||||
client.post(
|
||||
"/api/workflows/import-batch",
|
||||
json={
|
||||
"files": [
|
||||
{
|
||||
"source_path": "3-图像生成/Qwen-Image-2.1/test_t2i.json",
|
||||
"workflow_json": _ui_graph(),
|
||||
"tags": ["极速"],
|
||||
}
|
||||
]
|
||||
},
|
||||
)
|
||||
meta = client.get("/api/workflows", params={"view": "meta"}).json()
|
||||
assert len(meta) == 1
|
||||
row = meta[0]
|
||||
assert "workflow_json" not in row
|
||||
assert "input_schema" not in row
|
||||
assert "output_schema" not in row
|
||||
assert row["category"] == "image"
|
||||
assert row["model_family"] == "Qwen"
|
||||
assert row["media_io"] == {"in": [], "out": ["image"]}
|
||||
assert row["tags"] == ["极速"]
|
||||
assert row["favorite"] is False
|
||||
assert row["needs_mapping"] is False
|
||||
|
||||
|
||||
def test_legacy_list_shape_and_old_records_unchanged(client):
|
||||
"""Old imports (API format via POST /api/workflows) keep working; the
|
||||
legacy list still carries workflow_json and the new columns default."""
|
||||
created = client.post(
|
||||
"/api/workflows",
|
||||
json={"name": "旧导入", "workflow_json": _api_workflow()},
|
||||
)
|
||||
assert created.status_code == 200
|
||||
legacy = client.get("/api/workflows").json()
|
||||
assert len(legacy) == 1
|
||||
row = legacy[0]
|
||||
assert isinstance(row["workflow_json"], dict)
|
||||
assert "usage" in row and "output_map" in row
|
||||
assert row["favorite"] is False
|
||||
assert row["tags"] == []
|
||||
assert row["media_io"] == {"in": [], "out": []}
|
||||
meta = client.get("/api/workflows", params={"view": "meta"}).json()
|
||||
assert meta[0]["needs_mapping"] is False or meta[0]["needs_mapping"] is True
|
||||
assert meta[0]["source"] is None
|
||||
|
||||
|
||||
def test_favorite_tags_patch_and_touch(client):
|
||||
wid = client.post(
|
||||
"/api/workflows/import-batch",
|
||||
json={"files": [{"name": "fav", "workflow_json": _ui_graph()}]},
|
||||
).json()["imported_ids"][0]
|
||||
resp = client.patch(f"/api/workflows/{wid}", json={"favorite": True, "tags": ["高质量"]})
|
||||
assert resp.status_code == 200
|
||||
assert resp.json()["favorite"] is True
|
||||
assert resp.json()["tags"] == ["高质量"]
|
||||
touch = client.post(f"/api/workflows/{wid}/touch")
|
||||
assert touch.status_code == 200
|
||||
meta = client.get("/api/workflows", params={"view": "meta"}).json()
|
||||
assert meta[0]["last_used_at"] is not None
|
||||
assert meta[0]["favorite"] is True
|
||||
|
||||
|
||||
def test_migration_adds_columns_on_old_database(tmp_path):
|
||||
"""A pre-S2 database (workflows table without the metadata columns)
|
||||
migrates in place; existing rows survive with defaults."""
|
||||
db_path = tmp_path / "old.db"
|
||||
conn = sqlite3.connect(db_path)
|
||||
conn.executescript(
|
||||
"""
|
||||
CREATE TABLE workflows (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
name TEXT NOT NULL,
|
||||
kind TEXT NOT NULL CHECK(kind IN ('image', 'video')),
|
||||
workflow_json TEXT NOT NULL,
|
||||
description TEXT,
|
||||
prompt_profile TEXT NOT NULL DEFAULT 'prose',
|
||||
is_enabled INTEGER NOT NULL DEFAULT 1,
|
||||
usage TEXT,
|
||||
usage_source TEXT,
|
||||
output_map TEXT,
|
||||
output_map_source TEXT
|
||||
);
|
||||
INSERT INTO workflows (name, kind, workflow_json)
|
||||
VALUES ('legacy', 'video', '{"1": {"class_type": "SaveImage", "inputs": {}}}');
|
||||
"""
|
||||
)
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
import asyncio
|
||||
|
||||
asyncio.run(migrate_db(db_path))
|
||||
conn = sqlite3.connect(db_path)
|
||||
cols = {r[1] for r in conn.execute("PRAGMA table_info(workflows)").fetchall()}
|
||||
assert {
|
||||
"category",
|
||||
"model_family",
|
||||
"media_io",
|
||||
"tags",
|
||||
"favorite",
|
||||
"last_used_at",
|
||||
"source",
|
||||
"source_path",
|
||||
} <= cols
|
||||
row = conn.execute("SELECT name, favorite, tags, category FROM workflows").fetchone()
|
||||
assert row == ("legacy", 0, None, None)
|
||||
conn.close()
|
||||
@@ -167,28 +167,34 @@
|
||||
<div class="stage-media" in:xfade out:xfade>
|
||||
{#if output && video}
|
||||
<!-- svelte-ignore a11y_media_has_caption -->
|
||||
<video
|
||||
bind:this={videoEl}
|
||||
src={assetUrl(output)}
|
||||
controls
|
||||
playsinline
|
||||
preload="metadata"
|
||||
onloadedmetadata={(e) => {
|
||||
clearOutputMissing(output);
|
||||
noteVideo(e);
|
||||
}}
|
||||
onerror={() => output && markOutputMissing(output)}
|
||||
></video>
|
||||
<div class="print a-photo">
|
||||
{#if st.tone === 'ok' && !fileGone}<span class="a-fix">{t('jobst.done')}</span>{/if}
|
||||
<video
|
||||
bind:this={videoEl}
|
||||
src={assetUrl(output)}
|
||||
controls
|
||||
playsinline
|
||||
preload="metadata"
|
||||
onloadedmetadata={(e) => {
|
||||
clearOutputMissing(output);
|
||||
noteVideo(e);
|
||||
}}
|
||||
onerror={() => output && markOutputMissing(output)}
|
||||
></video>
|
||||
</div>
|
||||
{:else if output}
|
||||
<img
|
||||
src={assetUrl(output)}
|
||||
alt={prompt || t('desk.tabResult')}
|
||||
onload={(e) => {
|
||||
clearOutputMissing(output);
|
||||
noteImg(e);
|
||||
}}
|
||||
onerror={() => output && markOutputMissing(output)}
|
||||
/>
|
||||
<div class="print a-photo">
|
||||
{#if st.tone === 'ok' && !fileGone}<span class="a-fix">{t('jobst.done')}</span>{/if}
|
||||
<img
|
||||
src={assetUrl(output)}
|
||||
alt={prompt || t('desk.tabResult')}
|
||||
onload={(e) => {
|
||||
clearOutputMissing(output);
|
||||
noteImg(e);
|
||||
}}
|
||||
onerror={() => output && markOutputMissing(output)}
|
||||
/>
|
||||
</div>
|
||||
{:else if fileGone}
|
||||
<div class="stage-empty gone">
|
||||
<span>{t('desk.missingTitle')}</span>
|
||||
@@ -362,14 +368,24 @@
|
||||
inset: 0;
|
||||
display: grid;
|
||||
place-items: center;
|
||||
padding: var(--sp-5);
|
||||
box-sizing: border-box;
|
||||
}
|
||||
.stage-media > img,
|
||||
.stage-media > video {
|
||||
position: absolute;
|
||||
inset: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
object-fit: contain;
|
||||
/* 相纸白边 (HEL-680):检视舞台上的结果按相纸呈现,媒体自适应内含 */
|
||||
.print {
|
||||
position: relative;
|
||||
display: grid;
|
||||
max-width: 100%;
|
||||
max-height: 100%;
|
||||
--paper-w: 5px;
|
||||
}
|
||||
.print > img,
|
||||
.print > video {
|
||||
display: block;
|
||||
max-width: 100%;
|
||||
max-height: 100%;
|
||||
width: auto;
|
||||
height: auto;
|
||||
}
|
||||
.stage-empty {
|
||||
display: grid;
|
||||
|
||||
@@ -183,7 +183,8 @@
|
||||
|
||||
<div class="out">
|
||||
{#if output}
|
||||
<div class="thumb" class:portrait>
|
||||
<div class="thumb a-photo" class:portrait>
|
||||
{#if st.tone === 'ok' && !fileGone}<span class="a-fix">{t('jobst.done')}</span>{/if}
|
||||
{#if isVideoOutput(job, output)}
|
||||
<video
|
||||
src={assetUrl(output)}
|
||||
@@ -238,15 +239,42 @@
|
||||
background-color var(--d-state) ease,
|
||||
box-shadow var(--d-state) ease;
|
||||
}
|
||||
/* 选中框:金色描边从上一条记录滑到新选中的记录(feed 驱动 WAAPI) */
|
||||
/* 选中框:取景框角线从上一条记录滑到新选中的记录(feed 驱动 WAAPI,
|
||||
HEL-680 四角短线取代整框描边) */
|
||||
.sel-mark {
|
||||
position: absolute;
|
||||
inset: -1px;
|
||||
z-index: 3;
|
||||
display: none;
|
||||
border: 1px solid var(--accent-line);
|
||||
border-radius: inherit;
|
||||
pointer-events: none;
|
||||
background-image:
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0);
|
||||
background-position:
|
||||
left top,
|
||||
left top,
|
||||
right top,
|
||||
right top,
|
||||
left bottom,
|
||||
left bottom,
|
||||
right bottom,
|
||||
right bottom;
|
||||
background-size:
|
||||
14px 2px,
|
||||
2px 14px,
|
||||
14px 2px,
|
||||
2px 14px,
|
||||
14px 2px,
|
||||
2px 14px,
|
||||
14px 2px,
|
||||
2px 14px;
|
||||
background-repeat: no-repeat;
|
||||
}
|
||||
.take.selected {
|
||||
border-color: transparent;
|
||||
@@ -458,6 +486,12 @@
|
||||
background: var(--bg-4);
|
||||
box-shadow: inset 0 0 0 1px var(--on-media-line);
|
||||
}
|
||||
/* 相纸白边 (HEL-680):有产出的记录缩略图按相纸呈现,压过占位态样式 */
|
||||
.thumb.a-photo {
|
||||
border-radius: 2px;
|
||||
background: var(--accent);
|
||||
box-shadow: 0 2px 12px rgba(0, 0, 0, 0.35);
|
||||
}
|
||||
.thumb.portrait {
|
||||
width: 96px;
|
||||
aspect-ratio: 3 / 4;
|
||||
|
||||
@@ -52,7 +52,12 @@
|
||||
'var(--avatar-4)',
|
||||
'var(--avatar-5)',
|
||||
];
|
||||
const placeholder = $derived(PLACEHOLDER_GRADIENTS[project.id % PLACEHOLDER_GRADIENTS.length]);
|
||||
const placeholderIdx = $derived(project.id % PLACEHOLDER_GRADIENTS.length);
|
||||
const placeholder = $derived(PLACEHOLDER_GRADIENTS[placeholderIdx]);
|
||||
// HEL-680 灰阶封面占位:1–2 亮阶配深图标,3–5 暗阶配浅图标
|
||||
const placeholderIconColor = $derived(
|
||||
placeholderIdx <= 1 ? 'var(--accent-ink)' : 'var(--text)',
|
||||
);
|
||||
|
||||
const coverUrl = $derived(assetUrl(project.cover_path));
|
||||
|
||||
@@ -174,7 +179,12 @@
|
||||
onerror={() => (coverFailed = true)}
|
||||
/>
|
||||
{:else}
|
||||
<span class="cover-ph" style:background={placeholder} aria-hidden="true">
|
||||
<span
|
||||
class="cover-ph"
|
||||
style:background={placeholder}
|
||||
style:color={placeholderIconColor}
|
||||
aria-hidden="true"
|
||||
>
|
||||
<Icon name="film" size={22} />
|
||||
</span>
|
||||
{/if}
|
||||
|
||||
@@ -402,6 +402,7 @@
|
||||
flex-shrink: 0;
|
||||
margin-bottom: var(--sp-5);
|
||||
border-radius: var(--r-md);
|
||||
border-bottom: 2px solid var(--accent-lo);
|
||||
display: grid;
|
||||
place-items: center;
|
||||
background: var(--accent-grad);
|
||||
|
||||
@@ -132,9 +132,7 @@ let {
|
||||
min-height: 0;
|
||||
width: 100%;
|
||||
height: 100%;
|
||||
background:
|
||||
radial-gradient(ellipse at center, rgba(139, 92, 246, 0.08), transparent 55%),
|
||||
#050508;
|
||||
background: var(--stage-bg);
|
||||
border: 1px solid var(--border);
|
||||
border-radius: var(--radius-md);
|
||||
overflow: hidden;
|
||||
|
||||
@@ -79,14 +79,14 @@
|
||||
let criticNotes = $state<string[]>([]);
|
||||
|
||||
const preview = createMutation({
|
||||
mutationFn: async (vars?: { force?: boolean }) => {
|
||||
mutationFn: async (vars: { force?: boolean } | void) => {
|
||||
if (!clip && !scene) throw new Error(t('promptPreview.noClipSelected'));
|
||||
return jobsApi.previewPrompt(projectId, {
|
||||
clip_id: clip?.id,
|
||||
scene_id: clip ? undefined : scene?.id,
|
||||
workflow_id: workflow?.id,
|
||||
input_values: compactInputValues(inputValues),
|
||||
force: Boolean(vars?.force),
|
||||
force: Boolean((vars as { force?: boolean } | undefined)?.force),
|
||||
});
|
||||
},
|
||||
onSuccess: (data) => {
|
||||
|
||||
@@ -203,7 +203,7 @@ title={t('filmstrip.clipTitle', {
|
||||
inset: 0 0 auto 0;
|
||||
height: 3px;
|
||||
z-index: 1;
|
||||
background: #3f3f46;
|
||||
background: var(--bg-4);
|
||||
}
|
||||
|
||||
.clip.status-done .bar {
|
||||
|
||||
@@ -1902,7 +1902,7 @@ export const de: Dict = {
|
||||
'home.stageProgress': 'Fünf-Phasen-Fortschritt',
|
||||
'tasks.sourceWorkbench': 'Kreativ-Fluss',
|
||||
'jobst.idSuffix': ' · ComfyUI-Prompt-ID {id}',
|
||||
'jobst.done': 'Fertig',
|
||||
'jobst.done': 'Fixiert',
|
||||
'jobst.doneDetail': 'ComfyUI ist fertig, Ergebnisse gespeichert',
|
||||
'jobst.dryRun': 'Platzhalter',
|
||||
'jobst.dryRunDetail': 'Nur Platzhalter: Dry-run ist aktiv, ComfyUI wurde nicht aufgerufen',
|
||||
|
||||
@@ -1901,7 +1901,7 @@ export const en = {
|
||||
'home.stageProgress': 'Five-stage progress',
|
||||
'tasks.sourceWorkbench': 'Creation flow',
|
||||
'jobst.idSuffix': ' · ComfyUI prompt ID {id}',
|
||||
'jobst.done': 'Done',
|
||||
'jobst.done': 'Fixed',
|
||||
'jobst.doneDetail': 'ComfyUI finished and the results are saved',
|
||||
'jobst.dryRun': 'Placeholder',
|
||||
'jobst.dryRunDetail': 'Placeholder only: Dry-run is on, ComfyUI was not called',
|
||||
|
||||
@@ -1902,7 +1902,7 @@ export const es: Dict = {
|
||||
'home.stageProgress': 'Progreso de cinco etapas',
|
||||
'tasks.sourceWorkbench': 'Flujo de creación',
|
||||
'jobst.idSuffix': ' · ID de prompt de ComfyUI {id}',
|
||||
'jobst.done': 'Listo',
|
||||
'jobst.done': 'Fijado',
|
||||
'jobst.doneDetail': 'ComfyUI terminó y los resultados se guardaron',
|
||||
'jobst.dryRun': 'Marcador',
|
||||
'jobst.dryRunDetail': 'Solo marcador: Dry-run activo, no se llamó a ComfyUI',
|
||||
|
||||
@@ -1902,7 +1902,7 @@ export const fr: Dict = {
|
||||
'home.stageProgress': 'Progression en cinq étapes',
|
||||
'tasks.sourceWorkbench': 'Flux de création',
|
||||
'jobst.idSuffix': ' · ID de prompt ComfyUI {id}',
|
||||
'jobst.done': 'Terminé',
|
||||
'jobst.done': 'Fixé',
|
||||
'jobst.doneDetail': 'ComfyUI a terminé, résultats enregistrés',
|
||||
'jobst.dryRun': 'Substitut',
|
||||
'jobst.dryRunDetail': 'Substitut uniquement : Dry-run actif, ComfyUI n\'a pas été appelé',
|
||||
|
||||
@@ -1900,7 +1900,7 @@ export const ja: Dict = {
|
||||
'home.stageProgress': '五段階の進捗',
|
||||
'tasks.sourceWorkbench': '制作フロー',
|
||||
'jobst.idSuffix': ' · ComfyUI プロンプト ID {id}',
|
||||
'jobst.done': '完了',
|
||||
'jobst.done': '定着',
|
||||
'jobst.doneDetail': 'ComfyUI の実行が完了し、結果を保存しました',
|
||||
'jobst.dryRun': 'プレースホルダー',
|
||||
'jobst.dryRunDetail': 'プレースホルダーのみ:Dry-run が有効で ComfyUI は呼び出されていません',
|
||||
|
||||
@@ -1900,7 +1900,7 @@ export const ko: Dict = {
|
||||
'home.stageProgress': '5단계 진행',
|
||||
'tasks.sourceWorkbench': '제작 흐름',
|
||||
'jobst.idSuffix': ' · ComfyUI 프롬프트 ID {id}',
|
||||
'jobst.done': '완료',
|
||||
'jobst.done': '정착',
|
||||
'jobst.doneDetail': 'ComfyUI 실행이 끝나 결과를 저장했습니다',
|
||||
'jobst.dryRun': '자리표시자',
|
||||
'jobst.dryRunDetail': '자리표시자만: Dry-run이 켜져 있어 ComfyUI를 호출하지 않았습니다',
|
||||
|
||||
@@ -1900,8 +1900,8 @@ export const zh: Dict = {
|
||||
'home.stageProgress': '五段进度',
|
||||
'tasks.sourceWorkbench': '创作流程',
|
||||
'jobst.idSuffix': ' · ComfyUI 任务 ID {id}',
|
||||
'jobst.done': '完成',
|
||||
'jobst.doneDetail': 'ComfyUI 已执行完成,结果已保存',
|
||||
'jobst.done': '定影',
|
||||
'jobst.doneDetail': '生成完成,结果已定影保存',
|
||||
'jobst.dryRun': '占位结果',
|
||||
'jobst.dryRunDetail': '占位结果:当前开启了 Dry-run,没有调用 ComfyUI,不是真实生成',
|
||||
'jobst.noOutput': '无产出',
|
||||
|
||||
@@ -589,6 +589,11 @@
|
||||
function avatarStyle(n: number): string {
|
||||
return `var(--avatar-${Math.min(Math.max(n, 1), 5)})`;
|
||||
}
|
||||
|
||||
// HEL-680 灰阶头像:1–2 亮阶配深字,3–5 暗阶配浅字,按阶数决定。
|
||||
function avatarLight(n: number | undefined): boolean {
|
||||
return Math.min(Math.max(n ?? 1, 1), 5) <= 2;
|
||||
}
|
||||
</script>
|
||||
|
||||
{#snippet skillRow(skill: SkillAdminEntry, detail: string)}
|
||||
@@ -655,7 +660,7 @@
|
||||
class:selected
|
||||
onclick={() => selectAgent(agent.key)}
|
||||
>
|
||||
<span class="avatar" class:dark={agent.avatar_dark} style:background={avatarStyle(agent.avatar)}>
|
||||
<span class="avatar" class:dark={avatarLight(agent.avatar)} style:background={avatarStyle(agent.avatar)}>
|
||||
{agent.char}
|
||||
</span>
|
||||
<span class="agent-meta">
|
||||
@@ -693,7 +698,7 @@
|
||||
<section class="mid">
|
||||
{#if activeAgent}
|
||||
<header class="chat-head">
|
||||
<span class="avatar lg" class:dark={activeAgent.avatar_dark} style:background={avatarStyle(activeAgent.avatar)}>
|
||||
<span class="avatar lg" class:dark={avatarLight(activeAgent.avatar)} style:background={avatarStyle(activeAgent.avatar)}>
|
||||
{activeAgent.char}
|
||||
</span>
|
||||
<div class="chat-head-meta">
|
||||
|
||||
+181
-59
@@ -4,62 +4,67 @@
|
||||
|
||||
:root {
|
||||
/* ------------------------------------------------------------------
|
||||
* 融合视觉 design tokens — HEL-649 整站施工规范 §一(流水台结构 ×
|
||||
* 放映厅配色)。Single source of truth for the whole app: pages and
|
||||
* components reference these variables only — no hardcoded colors,
|
||||
* no ad-hoc overrides. Gold is for key actions and the current
|
||||
* selection only; status colors each carry exactly one meaning.
|
||||
* 无彩灰阶 design tokens — HEL-680 S1(白栖知 theme-1「暗房放大机」
|
||||
* × HEL-679 已确认融合样稿)。Single source of truth for the whole
|
||||
* app: pages and components reference these variables only — no
|
||||
* hardcoded colors, no ad-hoc overrides. 界面只有暖调黑白灰,作品是
|
||||
* 屏幕上唯一成片的颜色;状态色仅按主题卡的两处有限例外(琥珀
|
||||
* #A3915F、红 #B3564A)使用,不放大成全站主色。选中=取景框角线,
|
||||
* 完成=「定影」,结果=相纸白边。
|
||||
* ------------------------------------------------------------------ */
|
||||
|
||||
/* 底色:蓝黑四阶,逐层浮起 (§1.1) */
|
||||
--bg: #07090e;
|
||||
--bg-2: #0c0f16;
|
||||
--bg-3: #121724;
|
||||
--bg-4: #1a2133;
|
||||
--line: #1b2233;
|
||||
--line-2: #2a3450;
|
||||
--page-glow: radial-gradient(1200px 500px at 70% -10%, rgba(38, 52, 92, 0.25), transparent 60%);
|
||||
--float-bg: linear-gradient(180deg, #10152a, var(--bg-2));
|
||||
--overlay: rgba(4, 6, 10, 0.6);
|
||||
--media-scrim: rgba(7, 9, 14, 0.65);
|
||||
/* 底色:显影灰阶四阶,逐层浮起(theme-1:#212120 底 / #2C2C2A 面板) */
|
||||
--bg: #212120;
|
||||
--bg-2: #262625;
|
||||
--bg-3: #2c2c2a;
|
||||
--bg-4: #383835;
|
||||
--line: #313130;
|
||||
--line-2: #454542;
|
||||
--page-glow: radial-gradient(1200px 500px at 70% -10%, rgba(245, 244, 238, 0.035), transparent 60%);
|
||||
--float-bg: linear-gradient(180deg, #2e2e2c, var(--bg-2));
|
||||
--overlay: rgba(18, 18, 17, 0.62);
|
||||
--media-scrim: rgba(18, 18, 17, 0.66);
|
||||
--on-media: #fff;
|
||||
--on-media-line: rgba(255, 255, 255, 0.05);
|
||||
--composer-bg: linear-gradient(180deg, #0e1220, var(--bg-2));
|
||||
--composer-focus: 0 0 0 1px rgba(242, 199, 132, 0.12), 0 8px 28px rgba(0, 0, 0, 0.4);
|
||||
--composer-bg: linear-gradient(180deg, #2a2a28, var(--bg-2));
|
||||
--composer-focus: 0 0 0 1px rgba(245, 244, 238, 0.12), 0 8px 28px rgba(0, 0, 0, 0.4);
|
||||
|
||||
/* 放映金:主按钮、当前选中、改过的参数、聚焦框、Toast 动作 (§1.2) */
|
||||
--accent: #f2c784;
|
||||
--accent-ink: #23170a;
|
||||
--accent-soft: rgba(242, 199, 132, 0.13);
|
||||
--accent-hi: #f7d9a2;
|
||||
--accent-lo: #ecaf63;
|
||||
--accent-glow: rgba(236, 175, 99, 0.28);
|
||||
--accent-line: rgba(242, 199, 132, 0.55);
|
||||
/* 相纸白(重点色):主按钮、当前选中、改过的参数、聚焦框、Toast 动作
|
||||
(theme-1 #F5F4EE 重点) */
|
||||
--accent: #f5f4ee;
|
||||
--accent-ink: #212120;
|
||||
--accent-soft: rgba(245, 244, 238, 0.08);
|
||||
--accent-hi: #ffffff;
|
||||
--accent-lo: #ddddd7;
|
||||
--accent-glow: rgba(240, 239, 233, 0.2);
|
||||
--accent-line: rgba(245, 244, 238, 0.55);
|
||||
--accent-grad: linear-gradient(180deg, var(--accent-hi), var(--accent-lo));
|
||||
--accent-grad-hover: linear-gradient(180deg, #fbe3b6, #f0b968);
|
||||
--accent-ring: 0 0 0 1px rgba(242, 199, 132, 0.7), 0 0 22px var(--accent-glow);
|
||||
--btn-glow: 0 2px 14px var(--accent-glow), inset 0 1px 0 rgba(255, 255, 255, 0.35);
|
||||
--btn-glow-hover: 0 4px 18px var(--accent-glow), inset 0 1px 0 rgba(255, 255, 255, 0.4);
|
||||
--accent-wash: linear-gradient(180deg, rgba(242, 199, 132, 0.05), transparent 40%);
|
||||
--sel-shadow: 0 0 0 1px rgba(242, 199, 132, 0.15), 0 6px 24px rgba(0, 0, 0, 0.35);
|
||||
--accent-grad-hover: linear-gradient(180deg, #ffffff, #e8e7df);
|
||||
--accent-ring: 0 0 0 1px rgba(245, 244, 238, 0.7), 0 0 22px var(--accent-glow);
|
||||
--btn-glow: 0 2px 10px rgba(0, 0, 0, 0.38), inset 0 1px 0 rgba(255, 255, 255, 0.55);
|
||||
--btn-glow-hover: 0 3px 14px rgba(0, 0, 0, 0.44), inset 0 1px 0 rgba(255, 255, 255, 0.65);
|
||||
--accent-wash: linear-gradient(180deg, rgba(245, 244, 238, 0.05), transparent 40%);
|
||||
--sel-shadow: 0 0 0 1px rgba(245, 244, 238, 0.14), 0 6px 24px rgba(0, 0, 0, 0.35);
|
||||
|
||||
/* 信号色:绿=完成/已确认/通过,青=进行中/在线,红=失败/危险,
|
||||
琥珀=待确认/文件缺失/限额 (§1.3) */
|
||||
--ok: #49cb90;
|
||||
--ok-soft: rgba(73, 203, 144, 0.13);
|
||||
--run: #54dfd2;
|
||||
--run-soft: rgba(84, 223, 210, 0.13);
|
||||
--run-grad: linear-gradient(90deg, #3bbfb4, var(--run));
|
||||
--err: #f0645a;
|
||||
--err-soft: rgba(240, 100, 90, 0.13);
|
||||
--err-line: rgba(240, 100, 90, 0.6);
|
||||
--warn: #f0b45c;
|
||||
--warn-soft: rgba(240, 180, 92, 0.13);
|
||||
/* 信号色:完成=显影亮灰(「定影」,配图标/文字双编码),进行中=灰阶
|
||||
+动效;红/琥珀只按 theme-1 卡片的有限例外使用(红=失败/危险
|
||||
#B3564A 系,琥珀=待确认/文件缺失 #A3915F) */
|
||||
--ok: #ddddd7;
|
||||
--ok-soft: rgba(221, 221, 215, 0.1);
|
||||
--run: #b8b6ac;
|
||||
--run-soft: rgba(184, 182, 172, 0.12);
|
||||
--run-grad: linear-gradient(90deg, #8f8e85, #c6c5c0);
|
||||
--err: #d07a6b;
|
||||
--err-solid: #b3564a;
|
||||
--err-soft: rgba(181, 86, 74, 0.15);
|
||||
--err-line: rgba(208, 122, 107, 0.55);
|
||||
--warn: #a3915f;
|
||||
--warn-soft: rgba(163, 145, 95, 0.13);
|
||||
|
||||
/* 文字与字体 (§1.4);--text-2 是深底可读性下限,不得再暗 */
|
||||
--text: #f4f6fa;
|
||||
--text-2: #aab2c5;
|
||||
--text-3: #6d7690;
|
||||
/* 文字与字体;--text-3 是深底可读性下限(≥4.5:1 on --bg-3),不得再暗 */
|
||||
--text: #f0efe9;
|
||||
--text-2: #a8a69c;
|
||||
--text-3: #94938c;
|
||||
--font: 'PingFang SC', 'Noto Sans SC', 'Microsoft YaHei', system-ui, sans-serif;
|
||||
--mono: 'JetBrains Mono', ui-monospace, monospace;
|
||||
--fs-title: 15px;
|
||||
@@ -95,8 +100,14 @@
|
||||
/* 专属符号 (§1.7):齿孔只在记录流/输入台分隔带,光晕只在播放舞台 */
|
||||
--sprocket: radial-gradient(circle 2px, var(--line-2) 98%, transparent);
|
||||
--stage-bg:
|
||||
radial-gradient(60% 45% at 50% 38%, rgba(242, 199, 132, 0.07), transparent 70%),
|
||||
radial-gradient(80% 70% at 50% 50%, #0d1220, #05070c);
|
||||
radial-gradient(60% 45% at 50% 38%, rgba(245, 244, 238, 0.045), transparent 70%),
|
||||
radial-gradient(80% 70% at 50% 50%, #232322, #171716);
|
||||
|
||||
/* 取景框角线与相纸白边 (HEL-680):内容级选中/结果呈现的统一语言 */
|
||||
--frame-w: 2px;
|
||||
--frame-arm: 12px;
|
||||
--frame-inset: -4px;
|
||||
--paper-w: 4px;
|
||||
|
||||
/* 动效 (§1.6,取 HEL-648 实测值);只动 transform / opacity */
|
||||
--ease-out: cubic-bezier(0.23, 1, 0.32, 1);
|
||||
@@ -113,13 +124,13 @@
|
||||
--d-progress: 400ms;
|
||||
--press-scale: 0.97;
|
||||
|
||||
/* Avatar five-color set — five agents only; the one colorful gradient
|
||||
family the spec keeps (§3.6). */
|
||||
--avatar-1: linear-gradient(135deg, #e8a33d, #b96a1b);
|
||||
--avatar-2: linear-gradient(135deg, #5b8def, #3a5fa9);
|
||||
--avatar-3: linear-gradient(135deg, #3fb97f, #2a7a54);
|
||||
--avatar-4: linear-gradient(135deg, #b98be0, #7a4fa9);
|
||||
--avatar-5: linear-gradient(135deg, #d98e6a, #a95535);
|
||||
/* Avatar five-step grayscale (HEL-680 无彩化):1–2 亮阶配深字,
|
||||
3–5 暗阶配浅字;仍是五个身份位,只是从彩色渐变改为显影灰阶。 */
|
||||
--avatar-1: linear-gradient(135deg, #e8e7df, #cdcbc4);
|
||||
--avatar-2: linear-gradient(135deg, #b5b3aa, #9c9a91);
|
||||
--avatar-3: linear-gradient(135deg, #6b6a66, #55544f);
|
||||
--avatar-4: linear-gradient(135deg, #55544f, #424140);
|
||||
--avatar-5: linear-gradient(135deg, #424140, #2e2e2c);
|
||||
|
||||
/* ------------------------------------------------------------------
|
||||
* Legacy token names (§六 映射表) — aliases only, never new values,
|
||||
@@ -297,7 +308,7 @@ code,
|
||||
color: var(--err);
|
||||
}
|
||||
.a-btn.danger-solid {
|
||||
background: var(--err);
|
||||
background: var(--err-solid);
|
||||
color: var(--on-media);
|
||||
}
|
||||
@media (hover: hover) and (pointer: fine) {
|
||||
@@ -550,11 +561,47 @@ button.status-chip:active {
|
||||
.a-chip.changed {
|
||||
color: var(--accent);
|
||||
}
|
||||
/* Selected filter chip (§3.5 筛选芯片组): 当前选中 = 金色文字 + accent-soft 底 */
|
||||
/* Selected filter chip (§3.5 筛选芯片组): 当前选中 = 取景框角线缩影 +
|
||||
相纸白文字 + accent-soft 底 (HEL-680) */
|
||||
.a-chip.sel {
|
||||
position: relative;
|
||||
background: var(--accent-soft);
|
||||
color: var(--accent);
|
||||
}
|
||||
.a-chip.sel::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
inset: 2px;
|
||||
pointer-events: none;
|
||||
background-image:
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0);
|
||||
background-position:
|
||||
left top,
|
||||
left top,
|
||||
right top,
|
||||
right top,
|
||||
left bottom,
|
||||
left bottom,
|
||||
right bottom,
|
||||
right bottom;
|
||||
background-size:
|
||||
6px 1.5px,
|
||||
1.5px 6px,
|
||||
6px 1.5px,
|
||||
1.5px 6px,
|
||||
6px 1.5px,
|
||||
1.5px 6px,
|
||||
6px 1.5px,
|
||||
1.5px 6px;
|
||||
background-repeat: no-repeat;
|
||||
}
|
||||
.a-chip.warn {
|
||||
color: var(--warn);
|
||||
}
|
||||
@@ -753,6 +800,81 @@ button.a-tile:disabled {
|
||||
box-shadow: 0 0 0 1px var(--line);
|
||||
}
|
||||
|
||||
/* ------------------------------------------------------------------
|
||||
* 取景框角线选中 (HEL-680):内容级选中态的唯一语言——四角短线取景,
|
||||
* 不整框描边。挂在需要角线的元素上(元素自身可 overflow 可见;被
|
||||
* overflow:hidden 裁切的容器改用 --frame-inset 正值画在内侧)。
|
||||
* ------------------------------------------------------------------ */
|
||||
.a-frame {
|
||||
position: relative;
|
||||
}
|
||||
.a-frame::after {
|
||||
content: '';
|
||||
position: absolute;
|
||||
inset: var(--frame-inset, -4px);
|
||||
z-index: 3;
|
||||
pointer-events: none;
|
||||
background-image:
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0),
|
||||
linear-gradient(var(--accent) 0 0);
|
||||
background-position:
|
||||
left top,
|
||||
left top,
|
||||
right top,
|
||||
right top,
|
||||
left bottom,
|
||||
left bottom,
|
||||
right bottom,
|
||||
right bottom;
|
||||
background-size:
|
||||
var(--frame-arm, 12px) var(--frame-w, 2px),
|
||||
var(--frame-w, 2px) var(--frame-arm, 12px),
|
||||
var(--frame-arm, 12px) var(--frame-w, 2px),
|
||||
var(--frame-w, 2px) var(--frame-arm, 12px),
|
||||
var(--frame-arm, 12px) var(--frame-w, 2px),
|
||||
var(--frame-w, 2px) var(--frame-arm, 12px),
|
||||
var(--frame-arm, 12px) var(--frame-w, 2px),
|
||||
var(--frame-w, 2px) var(--frame-arm, 12px);
|
||||
background-repeat: no-repeat;
|
||||
}
|
||||
|
||||
/* 相纸白边 (HEL-680):结果媒体外的相纸白框,底边略厚如手工相纸。
|
||||
挂在承载 img/video 的媒体容器上;容器尺寸由调用方决定。 */
|
||||
.a-photo {
|
||||
background: var(--accent);
|
||||
border: var(--paper-w, 4px) solid var(--accent);
|
||||
border-bottom-width: calc(var(--paper-w, 4px) + 2px);
|
||||
border-radius: 2px;
|
||||
box-shadow: 0 2px 12px rgba(0, 0, 0, 0.35);
|
||||
box-sizing: border-box;
|
||||
}
|
||||
|
||||
/* 「定影」完成章 (HEL-680):已定影结果右上角的完成印记,随 jobst.done
|
||||
文案走(中文=定影)。absolute 定位,挂在有媒体的结果容器内。 */
|
||||
.a-fix {
|
||||
position: absolute;
|
||||
top: var(--sp-3);
|
||||
right: var(--sp-3);
|
||||
z-index: 2;
|
||||
padding: 1px 6px;
|
||||
border: 1px solid currentColor;
|
||||
border-radius: 3px;
|
||||
background: var(--media-scrim);
|
||||
color: var(--ok);
|
||||
font-size: var(--fs-mini);
|
||||
font-weight: 700;
|
||||
letter-spacing: 0.1em;
|
||||
text-indent: 0.1em;
|
||||
transform: rotate(-4deg);
|
||||
pointer-events: none;
|
||||
}
|
||||
|
||||
/* Floating surface for pop / drawer / confirm / toast / lightbox (§四.3). */
|
||||
.a-float {
|
||||
background: var(--float-bg);
|
||||
|
||||
@@ -209,7 +209,13 @@
|
||||
{:else}
|
||||
<div class="grid">
|
||||
{#each visible as item (item.path)}
|
||||
<div class="card" class:selected={selected.has(item.path)}>
|
||||
<div
|
||||
class="card"
|
||||
class:selected={selected.has(item.path)}
|
||||
class:a-frame={selected.has(item.path)}
|
||||
style:--frame-inset="3px"
|
||||
style:--frame-arm="16px"
|
||||
>
|
||||
<label class="check">
|
||||
<input
|
||||
type="checkbox"
|
||||
@@ -217,12 +223,12 @@
|
||||
onchange={() => toggle(item.path)}
|
||||
/>
|
||||
</label>
|
||||
<button
|
||||
type="button"
|
||||
class="media"
|
||||
onclick={() => openPreview(item)}
|
||||
title={item.name}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
class="media a-photo"
|
||||
onclick={() => openPreview(item)}
|
||||
title={item.name}
|
||||
>
|
||||
<SafeMedia src={assetUrl(item.path)} kind={item.kind} alt={item.name} controls={false} />
|
||||
</button>
|
||||
<div class="meta">
|
||||
@@ -341,7 +347,6 @@
|
||||
transition: border-color var(--d-state) ease;
|
||||
}
|
||||
.card.selected {
|
||||
border-color: var(--accent-line);
|
||||
background: linear-gradient(180deg, var(--accent-soft), transparent 32%), var(--bg-2);
|
||||
}
|
||||
.card :global(.media-el) {
|
||||
@@ -380,6 +385,14 @@
|
||||
cursor: zoom-in;
|
||||
overflow: hidden;
|
||||
}
|
||||
/* 相纸白边 (HEL-680):素材墙里的作品按相纸呈现 */
|
||||
.media.a-photo {
|
||||
border: var(--paper-w, 4px) solid var(--accent);
|
||||
border-bottom-width: calc(var(--paper-w, 4px) + 2px);
|
||||
background: var(--accent);
|
||||
border-radius: 0;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
.media :global(img),
|
||||
.media :global(video) {
|
||||
width: 100%;
|
||||
|
||||
@@ -392,14 +392,8 @@
|
||||
char: string;
|
||||
dark?: boolean;
|
||||
}[] = [
|
||||
{
|
||||
role: 'story',
|
||||
labelKey: 'models.agentStory',
|
||||
color: 'var(--avatar-1)',
|
||||
char: '剧',
|
||||
dark: true,
|
||||
},
|
||||
{ role: 'style', labelKey: 'models.agentStyle', color: 'var(--avatar-2)', char: '视' },
|
||||
{ role: 'story', labelKey: 'models.agentStory', color: 'var(--avatar-1)', char: '剧', dark: true },
|
||||
{ role: 'style', labelKey: 'models.agentStyle', color: 'var(--avatar-2)', char: '视', dark: true },
|
||||
{ role: 'script', labelKey: 'models.agentScript', color: 'var(--avatar-3)', char: '分' },
|
||||
{ role: 'assets', labelKey: 'models.agentAssets', color: 'var(--avatar-4)', char: '素' },
|
||||
{ role: 'video', labelKey: 'models.agentVideo', color: 'var(--avatar-5)', char: '镜' },
|
||||
|
||||
@@ -496,7 +496,11 @@
|
||||
<aside class="side-col">
|
||||
{#if currentAgent}
|
||||
<div class="side-card agent-card">
|
||||
<span class="agent-avatar" style:background={`var(--avatar-${currentAgent.avatar})`}>
|
||||
<span
|
||||
class="agent-avatar"
|
||||
class:light={(currentAgent.avatar ?? 1) <= 2}
|
||||
style:background={`var(--avatar-${currentAgent.avatar})`}
|
||||
>
|
||||
{currentAgent.char}
|
||||
</span>
|
||||
<div class="agent-copy">
|
||||
@@ -740,6 +744,10 @@
|
||||
color: var(--text);
|
||||
flex-shrink: 0;
|
||||
}
|
||||
/* HEL-680 灰阶头像:1–2 亮阶用深字 */
|
||||
.agent-avatar.light {
|
||||
color: var(--accent-ink);
|
||||
}
|
||||
.agent-copy {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
|
||||
Reference in New Issue
Block a user