aimusic / ComfyUI /custom_nodes /koolook /scripts /validate_workflow.py
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"""Validate a ComfyUI workflow JSON for internal consistency.
Usage:
python scripts/validate_workflow.py <workflow.json> [--quiet]
Checks performed:
- The file parses as JSON.
- Every link referenced by node inputs/outputs is declared in the top-level
`links` table.
- Every entry in the `links` table is referenced by both endpoints (no
orphans).
- For each link, the source/destination nodes and slots exist and the slot
type matches the declared link type.
- `last_node_id >= max(node ids)` and `last_link_id >= max(link ids)`.
- No duplicate node IDs or link IDs.
Exit codes:
0 All checks passed.
1 Problems found (printed to stderr).
2 File not found or not valid JSON.
This catches the class of bugs that come from hand-editing workflow JSONs
(e.g. when an agent re-wires a graph to build a slim variant). Run it after
any non-trivial edit before re-loading the workflow into ComfyUI — Comfy's
loader will sometimes silently drop or mis-wire the bad parts, producing a
graph that looks fine but behaves wrong.
stdlib only, no third-party dependencies.
"""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
def _sanitize_slots(
node: dict, key: str, problems: list[str]
) -> list[dict]:
"""Return a list-of-dicts view of node[key], appending a problem for any
malformed entry. Non-list `node[key]` → reported and treated as empty.
Non-dict entries → reported and dropped.
"""
slots = node.get(key)
if slots is None:
return []
if not isinstance(slots, list):
problems.append(
f"node {node.get('id')!r}: {key!r} must be a list, got {type(slots).__name__}"
)
return []
cleaned: list[dict] = []
for j, slot in enumerate(slots):
if not isinstance(slot, dict):
problems.append(
f"node {node.get('id')!r}: {key}[{j}] must be an object, got {type(slot).__name__}"
)
continue
cleaned.append(slot)
return cleaned
def _slot_type_matches(slot_type, link_type) -> bool:
"""ComfyUI wildcard sockets (`*`) accept any concrete link type."""
return slot_type == link_type or slot_type == "*"
def validate(data) -> list[str]:
"""Return a list of problem strings; empty list means OK.
Defensive: every shape assumption is guarded so that malformed-but-valid
JSON produces problem lines, never an uncaught exception. Top-level not
being an object is the only short-circuit return (nothing else is safe
to do without a dict).
"""
problems: list[str] = []
# Top-level must be a JSON object.
if not isinstance(data, dict):
return [
f"top-level JSON must be an object, got {type(data).__name__}"
]
# `nodes` and `links` arrays — must be lists; non-list reported and skipped.
raw_nodes = data.get("nodes") or []
if not isinstance(raw_nodes, list):
problems.append(
f"'nodes' must be a list, got {type(raw_nodes).__name__}"
)
raw_nodes = []
raw_links = data.get("links") or []
if not isinstance(raw_links, list):
problems.append(
f"'links' must be a list, got {type(raw_links).__name__}"
)
raw_links = []
# Filter to well-shaped node entries, recording each bad one.
nodes: list[dict] = []
for i, n in enumerate(raw_nodes):
if not isinstance(n, dict):
problems.append(
f"nodes[{i}]: must be an object, got {type(n).__name__}"
)
continue
nodes.append(n)
# Filter to well-shaped link entries. Each must be a 6-element list.
links: list[list] = []
for i, link in enumerate(raw_links):
if not isinstance(link, list):
problems.append(
f"links[{i}]: must be a list of 6 elements, got {type(link).__name__}"
)
continue
if len(link) != 6:
problems.append(
f"links[{i}]: malformed — expected 6 elements "
f"[id, src, src_slot, dst, dst_slot, type], got {len(link)}"
)
continue
links.append(link)
# Pre-sanitize each node's inputs/outputs into list-of-dict views so
# downstream code can index safely. Caches per-node so problems aren't
# double-reported when a node is touched by multiple links.
sanitized_io: dict[int, dict[str, list[dict]]] = {}
for n in nodes:
sanitized_io[id(n)] = {
"inputs": _sanitize_slots(n, "inputs", problems),
"outputs": _sanitize_slots(n, "outputs", problems),
}
# Duplicate IDs (over good entries).
node_ids = [n.get("id") for n in nodes]
link_ids = [link[0] for link in links]
dup_nodes = sorted({i for i in node_ids if node_ids.count(i) > 1})
dup_links = sorted({i for i in link_ids if link_ids.count(i) > 1})
if dup_nodes:
problems.append(f"Duplicate node IDs: {dup_nodes}")
if dup_links:
problems.append(f"Duplicate link IDs: {dup_links}")
# Header counters should bound observed IDs (Comfy uses these to assign
# the next id when adding nodes; if they lag, the next add can collide).
int_node_ids = [i for i in node_ids if isinstance(i, int)]
int_link_ids = [i for i in link_ids if isinstance(i, int)]
if int_node_ids:
last_node_id = data.get("last_node_id", -1)
if not isinstance(last_node_id, int) or last_node_id < max(int_node_ids):
problems.append(
f"last_node_id={last_node_id!r} < max(node id)={max(int_node_ids)}"
)
if int_link_ids:
last_link_id = data.get("last_link_id", -1)
if not isinstance(last_link_id, int) or last_link_id < max(int_link_ids):
problems.append(
f"last_link_id={last_link_id!r} < max(link id)={max(int_link_ids)}"
)
# Cross-reference link declarations vs node IO references.
declared = set(int_link_ids)
referenced: set[int] = set()
for n in nodes:
io = sanitized_io[id(n)]
for inp in io["inputs"]:
link_val = inp.get("link")
if isinstance(link_val, int):
referenced.add(link_val)
for out in io["outputs"]:
out_links = out.get("links") or []
if not isinstance(out_links, list):
problems.append(
f"node {n.get('id')!r}: output.links must be a list, "
f"got {type(out_links).__name__}"
)
continue
for lk in out_links:
if isinstance(lk, int):
referenced.add(lk)
for missing in sorted(referenced - declared):
problems.append(
f"link {missing}: referenced by a node but not in the links table"
)
for orphan in sorted(declared - referenced):
problems.append(
f"link {orphan}: declared in the links table but unused by any node"
)
# Per-link endpoint validation.
# Build node_by_id over int ids only — non-int ids can't match a link's
# src/dst (which are ints in the link tuple), and treating them as keys
# would mask bad data.
node_by_id = {n.get("id"): n for n in nodes if isinstance(n.get("id"), int)}
for link in links:
lid, src, src_slot, dst, dst_slot, ltype = link
src_node = node_by_id.get(src)
dst_node = node_by_id.get(dst)
if src_node is None:
problems.append(f"link {lid}: src node {src!r} missing")
continue
if dst_node is None:
problems.append(f"link {lid}: dst node {dst!r} missing")
continue
src_outs = sanitized_io[id(src_node)]["outputs"]
dst_ins = sanitized_io[id(dst_node)]["inputs"]
# Slot index bounds + type checks.
if not isinstance(src_slot, int) or src_slot < 0 or src_slot >= len(src_outs):
problems.append(
f"link {lid}: src slot {src_slot!r} out of bounds on node {src} "
f"(has {len(src_outs)} outputs)"
)
elif not _slot_type_matches(src_outs[src_slot].get("type"), ltype):
problems.append(
f"link {lid}: src type mismatch — link declares {ltype!r}, "
f"slot is {src_outs[src_slot].get('type')!r}"
)
if not isinstance(dst_slot, int) or dst_slot < 0 or dst_slot >= len(dst_ins):
problems.append(
f"link {lid}: dst slot {dst_slot!r} out of bounds on node {dst} "
f"(has {len(dst_ins)} inputs)"
)
elif not _slot_type_matches(dst_ins[dst_slot].get("type"), ltype):
problems.append(
f"link {lid}: dst type mismatch — link declares {ltype!r}, "
f"slot is {dst_ins[dst_slot].get('type')!r}"
)
# Endpoint cross-check: node IO must reference this link id symmetrically.
if isinstance(src_slot, int) and 0 <= src_slot < len(src_outs):
out_links = src_outs[src_slot].get("links") or []
if isinstance(out_links, list) and lid not in out_links:
problems.append(
f"link {lid}: missing from node {src} output[{src_slot}].links={out_links}"
)
if isinstance(dst_slot, int) and 0 <= dst_slot < len(dst_ins):
in_link = dst_ins[dst_slot].get("link")
if in_link != lid:
problems.append(
f"link {lid}: node {dst} input[{dst_slot}].link={in_link} "
f"does not match"
)
return problems
def main(argv: list[str] | None = None) -> int:
parser = argparse.ArgumentParser(
description=__doc__.splitlines()[0],
)
parser.add_argument(
"path",
type=Path,
help="Path to the workflow JSON file.",
)
parser.add_argument(
"-q",
"--quiet",
action="store_true",
help="Suppress the OK summary; only print problems.",
)
args = parser.parse_args(argv)
if not args.path.exists():
print(f"error: file not found: {args.path}", file=sys.stderr)
return 2
try:
data = json.loads(args.path.read_text(encoding="utf-8"))
except json.JSONDecodeError as exc:
print(f"error: {args.path.name}: JSON parse error: {exc}", file=sys.stderr)
return 2
problems = validate(data)
if problems:
print(
f"FAIL: {args.path.name} ({len(problems)} problem(s))",
file=sys.stderr,
)
for p in problems:
print(f" - {p}", file=sys.stderr)
return 1
if not args.quiet:
print(
f"OK: {args.path.name} — "
f"{len(data.get('nodes') or [])} nodes, "
f"{len(data.get('links') or [])} links, "
f"{len(data.get('groups') or [])} groups"
)
return 0
if __name__ == "__main__":
sys.exit(main())