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Author SHA1 Message Date
leeferandmultica-agent c5aa575ac3 feat(workflows): UI→API 转换器 + 批量导入 + 元数据轻量列表 (HEL-681 S2)
- 新增 comfyui/ui_convert.py:离线确定性转换(reroute/bypass/mute 透传、
  子图展开为 packed:inner 限定 id、Set/Get 变量解析、控件三种映射来源,
  无法可靠映射的文件进入需人工确认,绝不静默猜测)
- 新增 convert / import-batch / import-scan 端点:dry-run 逐文件
  ok/warn/fail 报告 + 建议元数据;导入端冲突跳过、重复执行幂等
- workflows 表加列 category/model_family/media_io/tags/favorite/
  last_used_at/source/source_path(纯加列迁移,旧行为零影响)
- GET /api/workflows?view=meta 轻量列表不含全量 JSON;旧接口行为不变
- 元数据建议:分类/模型家族(主加载器加权+目录回退,规避 qwen_image_vae
  误标)/输入输出媒介/MarkdownNote 描述素材
- enqueue 时记录 last_used_at;PATCH 支持 favorite/tags 等字段
- 测试 23 项新增(转换语义单测+146 文件语料+对拍+端点/迁移/幂等)

Co-authored-by: multica-agent <github@multica.ai>
2026-10-11 11:20:23 +08:00
leefer 1fc8bdb8bb Add 146 ComfyUI workflow JSONs organized by category (0-基础处理/1-语音/2-音乐/3-图像/4-视频/5-数字人/6-动作迁移) 2026-10-10 20:30:14 +08:00
总工 2c3c05277b HEL-672: merge H3 first-last frame (feat/hel-671-first-last-frame) 2026-10-04 13:53:26 +08:00
157 changed files with 8566 additions and 1 deletions
@@ -0,0 +1,128 @@
"""Regenerate ``src/calliope/comfyui/ui_widget_orders.py`` (HEL-681).
Offline widget-order registry for the UI→API converter. Sources, in priority:
1. ``widgets_values_named`` instances across ``example_ComfyUI_workflows``
(including subgraph inner nodes) — the frontend serializes named widgets
in widget order, so the key order IS the serialization order;
2. the repo's 10 ground-truth API exports (root ``*_API.json``) — scalar
input names in export order (control_after_generate entries are absent
there; the converter's walk skips them positionally).
Run from anywhere inside the repo:
python scripts/build_widget_orders.py
"""
from __future__ import annotations
import collections
import json
from pathlib import Path
BACKEND = Path(__file__).resolve().parents[1]
REPO = BACKEND.parent
EXAMPLES = REPO / "example_ComfyUI_workflows"
OUT = BACKEND / "src" / "calliope" / "comfyui" / "ui_widget_orders.py"
BUTTONS = {"preview", "audioUI", "compare_view", "ToggleableColorPicker", "imagebrowser"}
MAX_SIGNATURES = 3
MAX_ORDER_LEN = 48
# Hand-curated fallbacks for node classes the corpus never serializes with
# names (classic core/custom widgets whose order is stable and public).
CURATED: dict[str, list[list[str]]] = {
"PrimitiveNode": [["value"]],
"Seed (rgthree)": [["seed"]],
}
def _iter_ui_nodes() -> list[dict]:
nodes: list[dict] = []
for path in sorted(EXAMPLES.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
nodes.extend(n for n in data["nodes"] if isinstance(n, dict))
for sub in data.get("definitions", {}).get("subgraphs", []) or []:
if isinstance(sub, dict):
nodes.extend(n for n in sub.get("nodes", []) or [] if isinstance(n, dict))
return nodes
def _iter_api_workflows() -> list[dict]:
out: list[dict] = []
for path in sorted(EXAMPLES.glob("*_API.json")):
try:
data = json.loads(path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, OSError):
continue
if isinstance(data, dict) and "nodes" not in data:
out.append(data)
return out
def main() -> None:
learned: dict[str, collections.Counter[tuple[str, ...]]] = collections.defaultdict(
collections.Counter
)
for node in _iter_ui_nodes():
named = node.get("widgets_values_named")
if not isinstance(named, dict) or not named:
continue
keys = tuple(
str(k) for k in named.keys() if k and k not in BUTTONS
)
if keys and len(keys) <= MAX_ORDER_LEN:
learned[str(node.get("type") or "")][keys] += 1
for workflow in _iter_api_workflows():
for node in workflow.values():
if not isinstance(node, dict):
continue
names = [
str(k)
for k, v in (node.get("inputs") or {}).items()
if not isinstance(v, list) and k and k not in BUTTONS
]
if len(names) > MAX_ORDER_LEN:
continue
# Display nodes (PreviewAny…) carry zero scalar inputs — that
# empty order is real signal: their positional arrays are pure
# button leftovers and map to {}.
learned[str(node.get("class_type") or "")][tuple(names)] += 1
registry: dict[str, list[list[str]]] = {}
for node_type, counter in sorted(learned.items()):
if not node_type:
continue
orders: list[list[str]] = []
for signature, _count in counter.most_common(MAX_SIGNATURES):
orders.append(list(signature))
if orders:
registry[node_type] = orders
for node_type, orders in CURATED.items():
registry.setdefault(node_type, orders)
body = json.dumps(registry, ensure_ascii=False, indent=1, sort_keys=True)
OUT.write_text(
'"""GENERATED by scripts/build_widget_orders.py — do not edit by hand.\n'
"\n"
"Widget-order registry for the UI→API converter: class_type → candidate\n"
"widget name orders, learned from the repo's named-widget UI files and\n"
"ground-truth API exports (HEL-681).\n"
'"""\n'
"\n"
"from __future__ import annotations\n"
"\n"
f"WIDGET_ORDERS: dict[str, list[list[str]]] = {body}\n",
encoding="utf-8",
)
total = sum(len(o) for orders in registry.values() for o in orders)
print(f"wrote {OUT.name}: {len(registry)} node types, {total} orders total")
if __name__ == "__main__":
main()
@@ -0,0 +1,170 @@
"""Generate the HEL-681 dry-run report over the repo's UI workflow library.
Walks ``example_ComfyUI_workflows`` (or ``--root``), runs every file through
the production converter + lint + parser pipeline (exactly what
``POST /api/workflows/convert`` does, minus HTTP), and writes a JSON detail
file plus a human-readable Markdown summary. Read-only: nothing is imported,
no DB is touched.
Usage:
python scripts/ui_import_dryrun.py [--root DIR] [--out PREFIX]
"""
from __future__ import annotations
import argparse
import collections
import json
import sys
from pathlib import Path
BACKEND = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(BACKEND / "src"))
from calliope.comfyui.lint import workflow_warnings # noqa: E402
from calliope.comfyui.metadata import suggested_metadata # noqa: E402
from calliope.comfyui.parser import classify_usage # noqa: E402
from calliope.comfyui.ui_convert import convert_ui_workflow # noqa: E402
REPO = BACKEND.parent
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("--root", default=str(REPO / "example_ComfyUI_workflows"))
parser.add_argument("--out", default=str(REPO / "dryrun_report"))
args = parser.parse_args()
root = Path(args.root)
out_prefix = Path(args.out)
entries = []
for path in sorted(root.rglob("*.json")):
try:
data = json.loads(path.read_text(encoding="utf-8"))
except (json.JSONDecodeError, OSError) as exc:
entries.append(
{
"source_path": str(path.relative_to(root)),
"status": "fail",
"issues": [{"code": "unreadable", "message": str(exc)}],
}
)
continue
if not (isinstance(data, dict) and isinstance(data.get("nodes"), list)):
continue # API-format / non-workflow files are out of scope
rel = str(path.relative_to(root))
result = convert_ui_workflow(data)
entry: dict = {
"source_path": rel,
"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 not None:
entry["node_count"] = len(result.workflow)
entry["suggested"] = suggested_metadata(result.workflow, rel, data)
errors = [w for w in workflow_warnings(result.workflow) if w["level"] == "error"]
entry["lint_errors"] = [e["code"] for e in errors]
entry["importable"] = not result.needs_confirmation and not errors
else:
entry["importable"] = False
entries.append(entry)
counts = collections.Counter(e["status"] for e in entries)
code_counts = collections.Counter(
i["code"] for e in entries for i in e["issues"]
)
category_counts = collections.Counter(
(e.get("suggested") or {}).get("category") or "?" for e in entries
)
family_counts = collections.Counter(
(e.get("suggested") or {}).get("model_family") or "?" for e in entries
)
importable = sum(1 for e in entries if e.get("importable"))
needs_confirmation = sum(1 for e in entries if e["needs_confirmation"])
lint_blocked = [e for e in entries if e.get("lint_errors")]
detail = {
"root": str(root),
"total": len(entries),
"status_counts": dict(counts),
"issue_code_counts": dict(code_counts),
"importable": importable,
"needs_confirmation": needs_confirmation,
"lint_blocked": [e["source_path"] for e in lint_blocked],
"files": entries,
}
out_prefix.parent.mkdir(parents=True, exist_ok=True)
(out_prefix.with_suffix(".json")).write_text(
json.dumps(detail, ensure_ascii=False, indent=1), encoding="utf-8"
)
lines = [
"# HEL-681 工作流 UI→API 转换 dry-run 报告",
"",
f"- 扫描目录:`{root}`(根目录 10 个 API 格式旧文件不在本管线范围)",
f"- UI 格式文件总数:**{len(entries)}**",
f"- 转换结果:ok **{counts.get('ok', 0)}** / warn **{counts.get('warn', 0)}** / fail **{counts.get('fail', 0)}**",
f"- 其中「需人工确认」(控件无法可靠映射,禁止直接导入):**{needs_confirmation}**",
f"- 通过转换+lint 后可直接导入:**{importable}**",
f"- 转换成功但被现有 lint 拦截(导入时按阻止处理):**{len(lint_blocked)}**",
"",
"## 分类分布(自动提取)",
"",
"| 分类 | 数量 |",
"|---|---|",
]
for cat, n in sorted(category_counts.items()):
lines.append(f"| {cat} | {n} |")
lines += ["", "## 模型家族分布(自动提取)", "", "| 家族 | 数量 |", "|---|---|"]
for fam, n in sorted(family_counts.items(), key=lambda kv: -kv[1]):
lines.append(f"| {fam} | {n} |")
lines += ["", "## 问题代码统计", "", "| 代码 | 次数 | 含义 |", "|---|---|---|"]
meaning = {
"muted_input_dropped": "上游节点被静音,输入按未连接处理",
"variable_upstream_dropped": "Set/Get 变量上游被旁路,取值按未连接处理",
"get_without_set": "GetNode 没有同名 SetNode",
"widget_unmapped": "控件值无法可靠映射到输入名(需人工确认)",
"widget_order_mismatch": "控件数量与已知顺序不符(需人工确认)",
"no_output_node": "图中无已知输出节点,全部活跃节点保留待确认",
"cyclic_variable": "Set/Get 循环(FOR 循环流),该连线按未连接处理",
"dangling_link": "连线指向不存在的节点",
}
for code, n in code_counts.most_common():
lines.append(f"| `{code}` | {n} | {meaning.get(code, '')} |")
lines += ["", "## 需人工确认文件清单", ""]
for e in entries:
if e["needs_confirmation"]:
reasons = sorted({i["code"] for i in e["issues"]})[:3]
lines.append(f"- `{e['source_path']}`({', '.join(reasons)})")
lines += ["", "## lint 拦截文件清单", ""]
for e in lint_blocked:
lines.append(f"- `{e['source_path']}`({', '.join(e['lint_errors'])})")
lines += [
"",
"## 逐文件结果",
"",
"| 文件 | 状态 | 节点数 | 分类 | 模型家族 | 用途 | 问题 |",
"|---|---|---|---|---|---|---|",
]
for e in entries:
sug = e.get("suggested") or {}
issues = collections.Counter(i["code"] for i in e["issues"])
issue_text = ", ".join(f"{c}×{n}" for c, n in issues.most_common(2)) or "-"
usage = sug.get("usage") or ("待定" if sug.get("usage_ambiguous") else "-")
lines.append(
f"| `{e['source_path']}` | {e['status']} | {e.get('node_count', '-')} "
f"| {sug.get('category') or '-'} | {sug.get('model_family') or '-'} "
f"| {usage} | {issue_text} |"
)
(out_prefix.with_suffix(".md")).write_text("\n".join(lines) + "\n", encoding="utf-8")
print(f"{len(entries)} files: {dict(counts)}, importable={importable}, nc={needs_confirmation}")
print(f"report → {out_prefix}.md / {out_prefix}.json")
return 0
if __name__ == "__main__":
raise SystemExit(main())
@@ -0,0 +1,160 @@
"""Suggested workflow metadata for imports (HEL-681 / S2 data layer).
Everything here derives from two honest sources: the repo directory the file
came from (category) and the converted API graph itself (usage, media in/out,
model family, note text). Per HEL-675's inventory, clean display names and
tags stay human work — the suggestion is a starting point, never a guess that
hides uncertainty.
"""
from __future__ import annotations
import re
from typing import Any
from calliope.comfyui.parser import (
classify_usage,
parse_dynamic_inputs,
parse_dynamic_outputs,
)
# Repo top-level directory → (category key, display label). Directory names
# are mapping sources only — they never surface to users verbatim.
CATEGORY_DIRS: dict[str, tuple[str, str]] = {
"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"),
"1-语音生成": ("audio_tts", "语音生成"),
"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
+21
View File
@@ -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()
+449
View File
@@ -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()
@@ -0,0 +1,315 @@
{
"id": "e3f2b845-8f2c-4b5a-9caf-eac1029d3e7e",
"revision": 0,
"last_node_id": 173,
"last_link_id": 338,
"nodes": [
{
"id": 169,
"type": "MiniMaxH3GuidedWriter",
"pos": [
0,
0
],
"size": [
400,
654
],
"flags": {},
"order": 0,
"mode": 0,
"inputs": [
{
"name": "options",
"shape": 7,
"type": "H3_REWRITER_OPTIONS",
"link": null
}
],
"outputs": [
{
"name": "rewritten_prompt",
"type": "STRING",
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