Vito Sansevero
9424cd2e35
Bound the semantics loader: at most 1 MiB is read, containers may nest at most eight levels, and a RecursionError from the JSON parser becomes a SemanticsError instead of escaping. The table is no longer loaded at import. get_semantics() reads it on first use and caches only a valid result, and the resolver imports it lazily, only for a profile with semantics on. The default ingestion profile never imports the module, so a missing or corrupt table cannot break scan, monitor or admin import. Inspection of a prompt graph with an unusable table is unresolved with the reason "Inspection node semantics are unavailable" and an error log, rather than a crash. INSPECTION_PROFILE now has semantics on; no strategy consumes the table yet, so resolution is unchanged.
438 lines
17 KiB
Python
438 lines
17 KiB
Python
"""Load and validate the declarative inspection node semantics table (#240).
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The table lives once in ``web/js/inspection-semantics.json`` so a browser-local
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resolver can load the same data. It maps node classes (or ``(class, output
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slot)`` pairs) to a named strategy from the closed ``STRATEGIES`` set plus the
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exact input names that strategy reads. Code implements each strategy; adding a
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node that reuses one is a data-only change.
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Only the inspection resolver profile consumes this table, through
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``get_semantics()``, which reads and validates it on first use and caches only a
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valid result. Importing this module reads nothing, and the default (ingestion)
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profile never imports it, so a missing or bad table can never break ingestion.
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An invalid table raises ``SemanticsError`` so a bad edit fails loudly instead of
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silently changing what the inspector resolves. The file is bounded in size and
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nesting before it is validated. Every class appears in exactly one category;
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classes that are not listed stay ``unsupported-node``.
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"""
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import json
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from dataclasses import dataclass
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from functools import lru_cache
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from pathlib import Path
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from types import MappingProxyType
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from typing import Any, Callable, Dict, FrozenSet, Mapping, Optional, Tuple, Union
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SEMANTICS_PATH = (
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Path(__file__).resolve().parents[1] / "web" / "js" / "inspection-semantics.json"
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)
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SCHEMA_VERSION = 1
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# The real table is a few KiB and four levels deep; these only reject nonsense.
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MAX_TABLE_BYTES = 1024 * 1024
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MAX_NESTING = 8
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_NAME_LENGTH = 128
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# Comfy output slots are small; this only rejects nonsense, never a real node.
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_MAX_SLOT = 255
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STRATEGIES: Mapping[str, FrozenSet[str]] = MappingProxyType(
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{
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"samplers": frozenset({"ksampler", "custom-advanced", "detailer-stage"}),
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"guiders": frozenset({"cfg", "basic"}),
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"conditioning": frozenset({"passthrough", "zeroed"}),
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"selectors": frozenset({"boolean-select"}),
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"composites": frozenset({"combine"}),
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"encoders": frozenset({"single", "parts-equal", "pm-compose"}),
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"strings": frozenset({"literal", "strip-newlines", "join-multi", "concat"}),
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"savers": frozenset({"comfy-counter", "vhs-counter"}),
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}
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)
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# Shapes of the facts each sampler class provides (consumed by comfy-metadata.js).
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FACT_SHAPES = frozenset({"ksampler", "custom", "custom-advanced"})
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SAVER_PATTERNS = MappingProxyType(
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{
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"comfy-counter": "{name}_{counter:05}_.{ext}",
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"vhs-counter": "{name}_{counter:05}.{ext}",
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}
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)
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_CONFIGURATION_KINDS = frozenset({"noise", "sampler", "sigmas", "guider"})
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_SCALAR_KINDS = frozenset({"number", "string"})
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_CLASS_CATEGORIES = ("samplers", "guiders", "selectors", "composites", "savers")
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_SLOT_CATEGORIES = ("conditioning", "encoders", "strings")
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_SET_CATEGORIES = ("runtime", "non_file_outputs")
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_FACTS_TABLES = (
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"configuration_outputs",
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"model_outputs",
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"model_passthroughs",
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"scalar_outputs",
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)
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_CATEGORIES = frozenset(
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("schema",) + _CLASS_CATEGORIES + _SLOT_CATEGORIES + _SET_CATEGORIES + ("facts",)
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)
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_STRING_PARAMS = MappingProxyType(
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{
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"literal": frozenset(),
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"concat": frozenset(),
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"strip-newlines": frozenset({"flag"}),
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"join-multi": frozenset({"count", "delimiter", "list_flag", "input_prefix"}),
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}
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)
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Frozen = Union[Mapping[str, Any], Tuple[Any, ...], str, int, None]
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class SemanticsError(ValueError):
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"""The semantics table is unreadable or violates its schema."""
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@dataclass(frozen=True)
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class Semantics:
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"""Validated, deeply frozen semantics. Slot categories key by ``(class, slot)``."""
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samplers: Mapping[str, Mapping[str, Any]]
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guiders: Mapping[str, Mapping[str, Any]]
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conditioning: Mapping[Tuple[str, int], Mapping[str, Any]]
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selectors: Mapping[str, Mapping[str, Any]]
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composites: Mapping[str, Mapping[str, Any]]
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encoders: Mapping[Tuple[str, int], Mapping[str, Any]]
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strings: Mapping[Tuple[str, int], Mapping[str, Any]]
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runtime: FrozenSet[str]
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savers: Mapping[str, Mapping[str, Any]]
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non_file_outputs: FrozenSet[str]
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facts: Mapping[str, Any]
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all_classes: FrozenSet[str]
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def _freeze(value: Any) -> Frozen:
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if isinstance(value, dict):
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return MappingProxyType({key: _freeze(item) for key, item in value.items()})
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if isinstance(value, list):
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return tuple(_freeze(item) for item in value)
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return value
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def _reject_duplicate_keys(pairs: list) -> dict:
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result: Dict[str, Any] = {}
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for key, value in pairs:
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if key in result:
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raise SemanticsError(f"duplicate key {key!r}")
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result[key] = value
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return result
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def _reject_constant(name: str) -> None:
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raise SemanticsError(f"non-finite number {name} is not allowed")
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def _name(value: Any, where: str, what: str = "input") -> str:
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if not isinstance(value, str) or not value or len(value) > _NAME_LENGTH:
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raise SemanticsError(f"{where}: missing or invalid {what} name {value!r}")
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return value
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def _names(value: Any, where: str, minimum: int = 1) -> None:
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if not isinstance(value, list) or len(value) < minimum:
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raise SemanticsError(f"{where}: needs at least {minimum} input name(s)")
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for item in value:
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_name(item, where)
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if len(set(value)) != len(value):
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raise SemanticsError(f"{where}: repeated input name")
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def _fields(
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entry: Any, where: str, required: FrozenSet[str], optional: FrozenSet[str]
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) -> None:
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if not isinstance(entry, dict):
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raise SemanticsError(f"{where}: entry must be an object")
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missing = sorted(required - entry.keys())
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if missing:
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raise SemanticsError(f"{where}: missing input field(s) {missing}")
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unknown = sorted(entry.keys() - required - optional)
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if unknown:
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raise SemanticsError(f"{where}: unknown field(s) {unknown}")
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def _strategy(entry: Any, category: str, where: str) -> str:
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strategy = entry.get("strategy") if isinstance(entry, dict) else None
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if not isinstance(strategy, str) or strategy not in STRATEGIES[category]:
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raise SemanticsError(f"{where}: unknown strategy {strategy!r}")
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return strategy
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def _check_sampler(entry: dict, strategy: str, where: str) -> None:
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stage = "image_stage" if strategy == "detailer-stage" else "latent"
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_fields(
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entry,
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where,
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frozenset({"strategy", "conditioning", stage, "facts"}),
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frozenset(),
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)
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_name(entry[stage], where)
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keys = {"guider"} if strategy == "custom-advanced" else {"positive", "negative"}
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conditioning = entry["conditioning"]
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_fields(conditioning, where + ".conditioning", frozenset(keys), frozenset())
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for key in keys:
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_name(conditioning[key], where + ".conditioning")
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if entry["facts"] not in FACT_SHAPES:
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raise SemanticsError(f"{where}: unknown facts shape {entry['facts']!r}")
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def _check_guider(entry: dict, strategy: str, where: str) -> None:
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if strategy == "cfg":
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_fields(
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entry, where, frozenset({"strategy", "positive", "negative"}), frozenset()
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)
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_name(entry["negative"], where)
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else:
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# Negative absent by design; its reason is fixed text, not an input.
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_fields(
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entry,
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where,
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frozenset({"strategy", "positive"}),
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frozenset({"absent_reason"}),
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)
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if "absent_reason" in entry:
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_name(entry["absent_reason"], where, "absent reason")
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_name(entry["positive"], where)
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def _check_selector(entry: dict, strategy: str, where: str) -> None:
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_fields(entry, where, frozenset({"strategy", "condition", "branches"}), frozenset())
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_name(entry["condition"], where)
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branches = entry["branches"]
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_fields(branches, where + ".branches", frozenset({"true", "false"}), frozenset())
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_name(branches["true"], where)
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_name(branches["false"], where)
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def _check_composite(entry: dict, strategy: str, where: str) -> None:
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_fields(entry, where, frozenset({"strategy", "inputs"}), frozenset())
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_names(entry["inputs"], where, minimum=2)
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def _check_saver(entry: dict, strategy: str, where: str) -> None:
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_fields(
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entry,
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where,
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frozenset({"strategy", "prefix_input", "image_input", "pattern"}),
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frozenset(),
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)
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_name(entry["prefix_input"], where)
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_name(entry["image_input"], where)
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if entry["pattern"] != SAVER_PATTERNS[strategy]:
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raise SemanticsError(f"{where}: pattern does not match {strategy}")
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def _check_conditioning(entry: dict, strategy: str, where: str) -> None:
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_fields(entry, where, frozenset({"strategy", "input"}), frozenset())
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_name(entry["input"], where)
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def _check_encoder(entry: dict, strategy: str, where: str) -> None:
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_fields(entry, where, frozenset({"strategy", "inputs"}), frozenset({"compose"}))
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_names(entry["inputs"], where, minimum=2 if strategy == "parts-equal" else 1)
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if "compose" in entry and not isinstance(entry["compose"], bool):
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raise SemanticsError(f"{where}: compose must be a boolean")
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def _check_string(entry: dict, strategy: str, where: str) -> None:
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required = _STRING_PARAMS[strategy]
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if required:
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_fields(entry, where, frozenset({"strategy", "inputs", "params"}), frozenset())
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params = entry["params"]
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if not isinstance(params, dict) or set(params) != required:
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raise SemanticsError(f"{where}: params must be exactly {sorted(required)}")
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for value in params.values():
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_name(value, where + ".params")
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else:
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_fields(entry, where, frozenset({"strategy", "inputs"}), frozenset())
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_names(entry["inputs"], where)
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_CHECKS: Mapping[str, Callable[[dict, str, str], None]] = MappingProxyType(
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{
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"samplers": _check_sampler,
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"guiders": _check_guider,
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"selectors": _check_selector,
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"composites": _check_composite,
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"savers": _check_saver,
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"conditioning": _check_conditioning,
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"encoders": _check_encoder,
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"strings": _check_string,
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}
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)
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class _Owners:
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"""Each class belongs to one category; each (class, slot) is listed once."""
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def __init__(self) -> None:
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self._category: Dict[str, str] = {}
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self._outputs: set = set()
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def claim(self, name: str, category: str, slot: Optional[int] = None) -> None:
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owner = self._category.setdefault(name, category)
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if owner != category:
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raise SemanticsError(f"duplicate class {name!r} in {owner} and {category}")
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key = (name, slot)
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if slot is not None and key in self._outputs:
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raise SemanticsError(f"{category}: duplicate output key {key!r}")
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self._outputs.add(key)
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def classes(self) -> FrozenSet[str]:
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return frozenset(self._category)
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def _class_category(doc: dict, category: str, owners: _Owners) -> Mapping:
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table = doc[category]
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if not isinstance(table, dict):
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raise SemanticsError(f"category {category} must be an object")
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result = {}
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for name, entry in table.items():
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where = f"{category}[{name!r}]"
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_name(name, where, "class")
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strategy = _strategy(entry, category, where)
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_CHECKS[category](entry, strategy, where)
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owners.claim(name, category)
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result[name] = _freeze(entry)
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return MappingProxyType(result)
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def _slot(entry: dict, where: str) -> int:
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slot = entry.get("slot")
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# bool is an int subclass; a JSON true is not an output slot.
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if type(slot) is not int or not 0 <= slot <= _MAX_SLOT:
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raise SemanticsError(f"{where}: slot must be a non-negative int, not {slot!r}")
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return slot
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def _slot_category(doc: dict, category: str, owners: _Owners) -> Mapping:
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rows = doc[category]
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if not isinstance(rows, list):
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raise SemanticsError(f"category {category} must be a list")
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result = {}
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for index, row in enumerate(rows):
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where = f"{category}[{index}]"
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if not isinstance(row, dict):
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raise SemanticsError(f"{where}: entry must be an object")
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name = _name(row.get("class"), where, "class")
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slot = _slot(row, where)
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entry = {
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key: value for key, value in row.items() if key not in ("class", "slot")
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}
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strategy = _strategy(entry, category, where)
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_CHECKS[category](entry, strategy, where)
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owners.claim(name, category, slot)
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result[(name, slot)] = _freeze(entry)
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return MappingProxyType(result)
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def _set_category(doc: dict, category: str, owners: _Owners) -> FrozenSet[str]:
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rows = doc[category]
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if not isinstance(rows, list):
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raise SemanticsError(f"category {category} must be a list")
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seen: set = set()
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for name in rows:
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_name(name, category, "class")
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if name in seen:
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raise SemanticsError(f"{category}: duplicate class {name!r}")
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seen.add(name)
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owners.claim(name, category)
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return frozenset(seen)
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def _string_map(table: Any, where: str, allowed: Optional[FrozenSet[str]]) -> None:
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if not isinstance(table, dict):
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raise SemanticsError(f"{where} must be an object")
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for name, value in table.items():
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_name(name, where, "class")
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_name(value, where)
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if allowed is not None and value not in allowed:
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raise SemanticsError(f"{where}[{name!r}]: unknown kind {value!r}")
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def _facts(doc: dict) -> Mapping[str, Any]:
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facts = doc["facts"]
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if not isinstance(facts, dict) or set(facts) != set(_FACTS_TABLES):
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raise SemanticsError(f"facts must have exactly {list(_FACTS_TABLES)}")
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configuration = facts["configuration_outputs"]
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if not isinstance(configuration, dict):
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raise SemanticsError("facts.configuration_outputs must be an object")
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for name, adapter in configuration.items():
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where = f"facts.configuration_outputs[{name!r}]"
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_name(name, where, "class")
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_fields(adapter, where, frozenset({"kind", "fields"}), frozenset())
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if adapter["kind"] not in _CONFIGURATION_KINDS:
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raise SemanticsError(f"{where}: unknown kind {adapter['kind']!r}")
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_names(adapter["fields"], where)
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_string_map(facts["model_outputs"], "facts.model_outputs", None)
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_string_map(facts["scalar_outputs"], "facts.scalar_outputs", _SCALAR_KINDS)
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passthroughs = facts["model_passthroughs"]
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_names(passthroughs, "facts.model_passthroughs", minimum=0)
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return _freeze(facts)
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def _check_nesting(doc: Any) -> None:
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"""Reject containers nested deeper than ``MAX_NESTING`` (iterative walk)."""
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stack = [(doc, 1)]
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while stack:
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value, level = stack.pop()
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if not isinstance(value, (dict, list)):
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continue
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if level > MAX_NESTING:
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raise SemanticsError(f"semantics table nests deeper than {MAX_NESTING}")
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items = value.values() if isinstance(value, dict) else value
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stack.extend((item, level + 1) for item in items)
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def _validate(doc: Any) -> Semantics:
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if not isinstance(doc, dict):
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raise SemanticsError("semantics table must be an object")
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if set(doc) != _CATEGORIES:
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missing = sorted(_CATEGORIES - doc.keys())
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unknown = sorted(doc.keys() - _CATEGORIES)
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raise SemanticsError(f"category mismatch: missing {missing}, unknown {unknown}")
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if type(doc["schema"]) is not int or doc["schema"] != SCHEMA_VERSION:
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raise SemanticsError(f"unsupported schema {doc['schema']!r}")
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owners = _Owners()
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tables: Dict[str, Any] = {}
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for category in _CLASS_CATEGORIES:
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tables[category] = _class_category(doc, category, owners)
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for category in _SLOT_CATEGORIES:
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tables[category] = _slot_category(doc, category, owners)
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for category in _SET_CATEGORIES:
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tables[category] = _set_category(doc, category, owners)
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return Semantics(facts=_facts(doc), all_classes=owners.classes(), **tables)
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def load_semantics(path: Optional[Union[str, Path]] = None) -> Semantics:
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"""Read and validate a semantics table; ``SemanticsError`` on any problem."""
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source = Path(path) if path is not None else SEMANTICS_PATH
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try:
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with source.open("rb") as stream:
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data = stream.read(MAX_TABLE_BYTES + 1)
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if len(data) > MAX_TABLE_BYTES:
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raise SemanticsError(
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f"semantics table {source.name} exceeds {MAX_TABLE_BYTES} bytes"
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)
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doc = json.loads(
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data.decode("utf-8"),
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object_pairs_hook=_reject_duplicate_keys,
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parse_constant=_reject_constant,
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)
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except SemanticsError:
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raise
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except RecursionError:
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raise SemanticsError(
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f"semantics table {source.name} nests deeper than {MAX_NESTING}"
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) from None
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except (OSError, UnicodeDecodeError, ValueError) as error:
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raise SemanticsError(f"cannot read semantics table {source.name}: {error}")
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_check_nesting(doc)
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return _validate(doc)
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@lru_cache(maxsize=1)
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def get_semantics() -> Semantics:
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"""The repository table, loaded on first use; failures are not cached."""
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return load_semantics()
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