diff --git a/comfy_api/latest/_io.py b/comfy_api/latest/_io.py index 58e49d8e2..0ecdbb0c8 100644 --- a/comfy_api/latest/_io.py +++ b/comfy_api/latest/_io.py @@ -1110,7 +1110,7 @@ class Autogrow(ComfyTypeI): self.template.validate() @staticmethod - def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None): + def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None, live_input_types: dict[str, str] | None = None): # NOTE: purposely do not include self in out_dict; instead use only the template inputs # need to figure out names based on template type is_names = ("names" in value[1]["template"]) @@ -1159,7 +1159,7 @@ class Autogrow(ComfyTypeI): finalized_prefix = finalize_prefix(curr_prefix) out_dict["dynamic_paths"][finalized_prefix] = finalized_prefix out_dict["dynamic_paths_default_value"][finalized_prefix] = DynamicPathsDefaultValue.EMPTY_DICT - parse_class_inputs(out_dict, live_inputs, new_dict, curr_prefix) + parse_class_inputs(out_dict, live_inputs, new_dict, curr_prefix, live_input_types) @comfytype(io_type="COMFY_DYNAMICCOMBO_V3") class DynamicCombo(ComfyTypeI): @@ -1197,7 +1197,7 @@ class DynamicCombo(ComfyTypeI): input.validate() @staticmethod - def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None): + def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None, live_input_types: dict[str, str] | None = None): finalized_id = finalize_prefix(curr_prefix) if finalized_id in live_inputs: key = live_inputs[finalized_id] @@ -1209,57 +1209,206 @@ class DynamicCombo(ComfyTypeI): selected_option = option break if selected_option is not None: - parse_class_inputs(out_dict, live_inputs, selected_option["inputs"], curr_prefix) + parse_class_inputs(out_dict, live_inputs, selected_option["inputs"], curr_prefix, live_input_types) # add self to inputs out_dict[input_type][finalized_id] = value out_dict["dynamic_paths"][finalized_id] = finalize_prefix(curr_prefix, curr_prefix[-1]) @comfytype(io_type="COMFY_DYNAMICSLOT_V3") class DynamicSlot(ComfyTypeI): + """A slot whose revealed inputs depend on the type connected upstream. + + Each ``Option`` declares a ``when`` condition; the first option whose + condition matches the slot's resolved upstream type (or whose + ``when=None`` matches an empty slot) decides which child inputs are + exposed. + + Each concrete type may appear in at most one option's ``when``, so the + matching branch is unambiguous. The unconnected case (``when=None``) is + its own bucket and may also appear at most once. + + The AnyType limitation documented in + :py:mod:`comfy_execution.type_resolver` applies: an upstream output + declared as ``AnyType`` resolves to ``"*"`` and will only match a + ``when=io.AnyType`` option, never a concrete-type one. + """ Type = dict[str, Any] - class Input(DynamicInput): - def __init__(self, slot: Input, inputs: list[Input], - display_name: str=None, tooltip: str=None, lazy: bool=None, extra_dict=None): - assert(not isinstance(slot, DynamicInput)) - self.slot = copy.copy(slot) - self.slot.display_name = slot.display_name if slot.display_name is not None else display_name - optional = True - self.slot.tooltip = slot.tooltip if slot.tooltip is not None else tooltip - self.slot.lazy = slot.lazy if slot.lazy is not None else lazy - self.slot.extra_dict = slot.extra_dict if slot.extra_dict is not None else extra_dict - super().__init__(slot.id, self.slot.display_name, optional, self.slot.tooltip, self.slot.lazy, self.slot.extra_dict) + class Option: + """One branch of inputs revealed when the slot's resolved type matches ``when``. + + ``when`` accepts: + * ``None`` — no link present + * ``io.AnyType`` — upstream resolved type is literally ``"*"`` + * a single ComfyType class (e.g. ``io.Image``) + * a list of ComfyType classes (shared branch across multiple types) + * a ``MultiType.Input`` instance (parsed via its ``.io_types``) + """ + def __init__(self, when: Any, inputs: list[Input]): + self.when = when self.inputs = inputs - self.force_input = None - # force widget inputs to have no widgets, otherwise this would be awkward - if isinstance(self.slot, WidgetInput): - self.force_input = True - self.slot.force_input = True + # ``_when_types`` is the ordered tuple of io_types (deterministic); + # ``_when_set`` is the same content as a set for fast matching. + self._when_types = self._normalize_when(when) + self._when_set: frozenset[str] | None = ( + None if self._when_types is None else frozenset(self._when_types) + ) + + @staticmethod + def _normalize_when(when: Any) -> tuple[str, ...] | None: + """Normalize ``when`` to an ordered, deduplicated tuple of io_types, or ``None`` for the unconnected case.""" + if when is None: + return None + if isinstance(when, type) and issubclass(when, _ComfyType): + return (when.io_type,) + if isinstance(when, MultiType.Input): + result = tuple(dict.fromkeys(t.io_type for t in when.io_types)) + if "*" in result and len(result) > 1: + raise ValueError( + "DynamicSlot.Option: AnyType cannot be grouped with concrete types; " + "use a separate Option(when=io.AnyType, ...) instead" + ) + return result + if isinstance(when, Iterable) and not isinstance(when, str): + types: list[str] = [] + for t in when: + if not (isinstance(t, type) and issubclass(t, _ComfyType)): + raise ValueError( + f"DynamicSlot.Option: list entries must be ComfyType classes, got {t!r}" + ) + if t.io_type not in types: + types.append(t.io_type) + if not types: + raise ValueError("DynamicSlot.Option: when=[] is not allowed; use when=None instead") + if "*" in types and len(types) > 1: + raise ValueError( + "DynamicSlot.Option: AnyType cannot be grouped with concrete types; " + "use a separate Option(when=io.AnyType, ...) instead" + ) + return tuple(types) + raise ValueError( + "DynamicSlot.Option: when must be None, a ComfyType class, a list of ComfyType classes, " + f"or a MultiType.Input; got {when!r}" + ) + + def as_dict(self): + return { + "when": None if self._when_types is None else list(self._when_types), + "inputs": create_input_dict_v1(self.inputs), + } + + class Input(DynamicInput): + def __init__(self, id: str, options: list[DynamicSlot.Option], + display_name: str=None, optional: bool=True, tooltip: str=None, lazy: bool=None, extra_dict=None): + if not options: + raise ValueError("DynamicSlot.Input: at least one Option is required") + for opt in options: + if not isinstance(opt, DynamicSlot.Option): + raise ValueError( + f"DynamicSlot.Input: options must be DynamicSlot.Option instances, got {opt!r}" + ) + super().__init__(id, display_name, optional, tooltip, lazy, extra_dict) + self.options = options + # Enforce uniqueness: each io_type (and the unconnected case) may + # appear in at most one option's ``when``. Also derive the slot's + # declared connection type as the ordered union of every non-None + # option's ``when`` set so authors control displayed precedence. + seen_types: set[str] = set() + seen_none = False + connected_types: list[str] = [] + for opt in options: + if opt._when_types is None: + if seen_none: + raise ValueError("DynamicSlot.Input: only one Option may declare when=None") + seen_none = True + continue + for t in opt._when_types: + if t in seen_types: + raise ValueError( + f"DynamicSlot.Input: type {t!r} appears in more than one Option's `when`; " + "each type must be claimed by exactly one option" + ) + seen_types.add(t) + connected_types.append(t) + if not connected_types: + raise ValueError( + "DynamicSlot.Input: at least one Option must have a non-None `when`; " + "a slot with only a `when=None` option can never be connected" + ) + # A required slot demands a link, so the when=None branch is unreachable. + if not optional and seen_none: + raise ValueError( + "DynamicSlot.Input: optional=False forbids when=None options; " + "the unconnected branch is unreachable when a link is required" + ) + self._slot_io_type = ",".join(connected_types) + + # parse_class_inputs dispatches on the class io_type (COMFY_DYNAMICSLOT_V3), + # so get_all/get_io_type must not be overridden; slotType is published via as_dict. def get_all(self) -> list[Input]: - return [self.slot] + self.inputs + seen_ids: set[str] = set() + children: list[Input] = [] + for opt in self.options: + for inp in opt.inputs: + if inp.id in seen_ids: + continue + seen_ids.add(inp.id) + children.append(inp) + return [self] + children def as_dict(self): return super().as_dict() | prune_dict({ - "slotType": str(self.slot.get_io_type()), - "inputs": create_input_dict_v1(self.inputs), - "forceInput": self.force_input, + "slotType": self._slot_io_type, + "options": [o.as_dict() for o in self.options], + # Always render as a connector — slotType may include widget-capable + # types (INT/STRING/etc.) but a DynamicSlot is a connection point. + "forceInput": True, }) def validate(self): - self.slot.validate() - for input in self.inputs: - input.validate() + for opt in self.options: + for inp in opt.inputs: + inp.validate() @staticmethod - def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None): + def _select_option(options: list[dict[str, Any]], live_input_types: dict[str, str] | None, + finalized_id: str, has_link: bool) -> dict[str, Any] | None: + """Pick the first option whose ``when`` matches the slot's state. + + Connected: pick the first option whose ``when`` set intersects the + comma-split resolved type. Unconnected: pick the first ``when=None``. + With per-option type uniqueness, at most one connected option can match + any single concrete type; ordering only matters when upstream declares + a multi-type union (e.g. ``"IMAGE,MASK"``). + """ + if not has_link: + for opt in options: + if opt["when"] is None: + return opt + return None + resolved = (live_input_types or {}).get(finalized_id, "*") + resolved_set = {t.strip() for t in resolved.split(",")} + for opt in options: + when = opt["when"] + if when is None: + continue + if resolved_set & set(when): + return opt + return None + + @staticmethod + def _expand_schema_for_dynamic(out_dict: dict[str, Any], live_inputs: dict[str, Any], value: tuple[str, dict[str, Any]], input_type: str, curr_prefix: list[str] | None, live_input_types: dict[str, str] | None = None): finalized_id = finalize_prefix(curr_prefix) - if finalized_id in live_inputs: - inputs = value[1]["inputs"] - parse_class_inputs(out_dict, live_inputs, inputs, curr_prefix) - # add self to inputs - out_dict[input_type][finalized_id] = value - out_dict["dynamic_paths"][finalized_id] = finalize_prefix(curr_prefix, curr_prefix[-1]) + options: list[dict[str, Any]] = value[1].get("options", []) + has_link = finalized_id in live_inputs and live_inputs[finalized_id] is not None + selected = DynamicSlot._select_option(options, live_input_types, finalized_id, has_link) + if selected is not None: + parse_class_inputs(out_dict, live_inputs, selected["inputs"], curr_prefix, live_input_types) + # Always advertise the slot itself so the connector renders even when no + # option matched (unmatched concrete + no AnyType option). + out_dict[input_type][finalized_id] = value + out_dict["dynamic_paths"][finalized_id] = finalize_prefix(curr_prefix, curr_prefix[-1]) @comfytype(io_type="IMAGECOMPARE") class ImageCompare(ComfyTypeI): @@ -1404,11 +1553,18 @@ class Range(ComfyTypeIO): }) -DYNAMIC_INPUT_LOOKUP: dict[str, Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]] = {} -def register_dynamic_input_func(io_type: str, func: Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]): +# Signature: (out_dict, live_inputs, value, input_type, curr_prefix, live_input_types). +# live_input_types is {input_id: resolved_io_type} from TypeResolver; existing +# expanders ignore it, future type-discriminated ones use it as discriminator. +_DynamicInputFunc = Callable[ + [dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None, dict[str, str] | None], + None, +] +DYNAMIC_INPUT_LOOKUP: dict[str, _DynamicInputFunc] = {} +def register_dynamic_input_func(io_type: str, func: _DynamicInputFunc): DYNAMIC_INPUT_LOOKUP[io_type] = func -def get_dynamic_input_func(io_type: str) -> Callable[[dict[str, Any], dict[str, Any], tuple[str, dict[str, Any]], str, list[str] | None], None]: +def get_dynamic_input_func(io_type: str) -> _DynamicInputFunc: return DYNAMIC_INPUT_LOOKUP[io_type] def setup_dynamic_input_funcs(): @@ -1764,7 +1920,12 @@ class Schema: ) return info -def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], include_hidden=False) -> tuple[dict[str, Any], V3Data]: +def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], include_hidden=False, live_input_types: dict[str, str] | None = None) -> tuple[dict[str, Any], V3Data]: + """Expand a node's V3 schema against a concrete prompt. + + ``live_input_types`` is an optional ``{input_id: resolved_io_type}`` map + (from ``TypeResolver``) used by future type-discriminated dynamic inputs. + """ out_dict = { "required": {}, "optional": {}, @@ -1774,7 +1935,7 @@ def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], i d = d.copy() # ignore hidden for parsing hidden = d.pop("hidden", None) - parse_class_inputs(out_dict, live_inputs, d) + parse_class_inputs(out_dict, live_inputs, d, None, live_input_types) if hidden is not None and include_hidden: out_dict["hidden"] = hidden v3_data = {} @@ -1787,7 +1948,7 @@ def get_finalized_class_inputs(d: dict[str, Any], live_inputs: dict[str, Any], i v3_data["dynamic_paths_default_value"] = dynamic_paths_default_value return out_dict, hidden, v3_data -def parse_class_inputs(out_dict: dict[str, Any], live_inputs: dict[str, Any], curr_dict: dict[str, Any], curr_prefix: list[str] | None=None) -> None: +def parse_class_inputs(out_dict: dict[str, Any], live_inputs: dict[str, Any], curr_dict: dict[str, Any], curr_prefix: list[str] | None=None, live_input_types: dict[str, str] | None = None) -> None: for input_type, inner_d in curr_dict.items(): for id, value in inner_d.items(): io_type = value[0] @@ -1795,7 +1956,7 @@ def parse_class_inputs(out_dict: dict[str, Any], live_inputs: dict[str, Any], cu # dynamic inputs need to be handled with lookup functions dynamic_input_func = get_dynamic_input_func(io_type) new_prefix = handle_prefix(curr_prefix, id) - dynamic_input_func(out_dict, live_inputs, value, input_type, new_prefix) + dynamic_input_func(out_dict, live_inputs, value, input_type, new_prefix, live_input_types) else: # non-dynamic inputs get directly transferred finalized_id = finalize_prefix(curr_prefix, id) diff --git a/comfy_execution/graph.py b/comfy_execution/graph.py index 479ee8a53..eb9ac79fa 100644 --- a/comfy_execution/graph.py +++ b/comfy_execution/graph.py @@ -26,6 +26,7 @@ class DynamicPrompt: self.ephemeral_prompt = {} self.ephemeral_parents = {} self.ephemeral_display = {} + self._type_resolver = None # lazy; invalidated by add_ephemeral_node def get_node(self, node_id): if node_id in self.ephemeral_prompt: @@ -41,6 +42,17 @@ class DynamicPrompt: self.ephemeral_prompt[node_id] = node_info self.ephemeral_parents[node_id] = parent_id self.ephemeral_display[node_id] = display_id + # Selective downstream invalidation would need topological info; the + # cache is small, so just wipe it. + if self._type_resolver is not None: + self._type_resolver.invalidate() + + def get_type_resolver(self): + """Lazily build and return the per-prompt TypeResolver.""" + if self._type_resolver is None: + from comfy_execution.type_resolver import TypeResolver + self._type_resolver = TypeResolver(self) + return self._type_resolver def get_real_node_id(self, node_id): while node_id in self.ephemeral_parents: diff --git a/comfy_execution/type_resolver.py b/comfy_execution/type_resolver.py new file mode 100644 index 000000000..31c3b3059 --- /dev/null +++ b/comfy_execution/type_resolver.py @@ -0,0 +1,369 @@ +"""Server-side type resolver for prompt graphs. + +Resolves the concrete io_type of any output/input slot by walking the prompt +graph. Handles V1/V3 ``RETURN_TYPES``, V3 ``MatchType`` template chains, and +falls back to ``AnyType`` (with a one-shot warning) on cycles, depth overflow, +or unresolvable wildcards. + +Works against either a raw prompt dict or a ``DynamicPrompt``. All resolved +values are strings, so resolver state is cross-process serializable. + +Known limitation: when an upstream node declares its output as ``AnyType`` +(``"*"``) — Reroute, generic If/Else, many V1 utility nodes — the resolver +returns ``"*"``. It has no way to introspect the runtime value to recover a +more specific type. Downstream consumers (e.g. :py:class:`DynamicSlot`) will +treat such links as AnyType and select their ``AnyType`` branch (or none), +not a concrete-type branch. +""" + +from __future__ import annotations + +import logging +from typing import Any + +from comfy_api.latest import _io as io +from comfy_api.internal import _ComfyNodeInternal + + +def _parse_link(val: Any) -> tuple[str, int] | None: + """Return ``(src_node_id, src_slot_idx)`` if ``val`` is a well-formed link, else ``None``. + + A link is ``[node_id: str, slot_idx: int]``. Malformed shapes return ``None`` + so callers can fall back to AnyType rather than raise. + """ + if not isinstance(val, (list, tuple)) or len(val) != 2: + return None + src_node, src_slot = val[0], val[1] + if not isinstance(src_node, str): + return None + # bool is a subclass of int — reject so True/False aren't read as slot 1/0. + if isinstance(src_slot, bool) or not isinstance(src_slot, int): + return None + return src_node, src_slot + +ANY_TYPE: str = io.AnyType.io_type +MAX_RESOLVE_DEPTH: int = 64 # belt-and-suspenders cap; real MatchType chains stay tiny + + +class TypeResolver: + """Resolves concrete io_types for a prompt graph. + + Instantiate once per prompt (or per ``DynamicPrompt``) and reuse; results + are cached. Call :py:meth:`invalidate` (or :py:meth:`invalidate_node`) when + the underlying graph mutates (e.g. when an ephemeral node is added). + """ + + def __init__(self, prompt_source: Any): + """Args: + prompt_source: Either a ``DynamicPrompt`` (anything with + ``get_node(node_id)`` / ``has_node(node_id)``) or a plain + ``dict[node_id, {"class_type", "inputs"}]``. + """ + self._source = prompt_source + self._output_cache: dict[tuple[str, int], str] = {} + self._is_output_list_cache: dict[tuple[str, int], bool] = {} + self._warned: set[tuple[str, Any, str]] = set() + + # ---- prompt access ---------------------------------------------------- + def _has_node(self, node_id: str) -> bool: + if hasattr(self._source, "has_node"): + return self._source.has_node(node_id) + return node_id in self._source + + def _get_node(self, node_id: str) -> dict[str, Any] | None: + try: + if hasattr(self._source, "get_node"): + return self._source.get_node(node_id) + return self._source[node_id] + except Exception: + return None + + @staticmethod + def _get_class_def(class_type: str): + # Local import: nodes <-> comfy_execution would cycle at import time. + import nodes + return nodes.NODE_CLASS_MAPPINGS.get(class_type) + + def _get_class_def_for_node(self, node_id: str): + """Return (node_dict, class_def) for ``node_id``, or ``(None, None)``.""" + if not self._has_node(node_id): + return None, None + node = self._get_node(node_id) + if node is None: + return None, None + class_type = node.get("class_type") + if not isinstance(class_type, str): + return node, None + return node, self._get_class_def(class_type) + + # ---- cache management ------------------------------------------------- + def invalidate(self) -> None: + """Clear all cached resolutions. Cheap; call after any graph mutation.""" + self._output_cache.clear() + self._is_output_list_cache.clear() + # Keep self._warned: re-emitting already-logged warnings would just spam. + + def invalidate_node(self, node_id: str) -> None: + """Clear cached entries for a single node (e.g. after node-level expand).""" + for key in [k for k in self._output_cache if k[0] == node_id]: + del self._output_cache[key] + for key in [k for k in self._is_output_list_cache if k[0] == node_id]: + del self._is_output_list_cache[key] + + # ---- output resolution ----------------------------------------------- + def resolve_output_type(self, node_id: str, slot_idx: int, + _stack: frozenset[tuple[str, int]] | None = None) -> str: + """Return the resolved io_type string of ``node_id``'s output slot. + + Falls back to ``ANY_TYPE`` on cycle, depth-overflow, unknown class, + out-of-range slot, missing node, malformed link, or unresolved + MatchType template. + """ + # Degrade gracefully on non-int slot_idx (e.g. malformed API JSON). + if isinstance(slot_idx, bool) or not isinstance(slot_idx, int): + return ANY_TYPE + + cache_key = (node_id, slot_idx) + if cache_key in self._output_cache: + return self._output_cache[cache_key] + + if _stack is None: + _stack = frozenset() + if cache_key in _stack: + self._warn(node_id, slot_idx, "cycle detected during type resolution; defaulting to AnyType") + return ANY_TYPE + if len(_stack) >= MAX_RESOLVE_DEPTH: + self._warn(node_id, slot_idx, f"exceeded MAX_RESOLVE_DEPTH={MAX_RESOLVE_DEPTH}; defaulting to AnyType") + return ANY_TYPE + next_stack = _stack | {cache_key} + + node, class_def = self._get_class_def_for_node(node_id) + if class_def is None: + return ANY_TYPE + class_type = node.get("class_type") + + try: + return_types = class_def.RETURN_TYPES + except Exception: + return ANY_TYPE + if return_types is None or slot_idx < 0 or slot_idx >= len(return_types): + return ANY_TYPE + + declared = return_types[slot_idx] + + # Only V3 schemas carry MatchType template info; V1 RETURN_TYPES are + # always concrete strings. + resolved = declared + if isinstance(class_def, type) and issubclass(class_def, _ComfyNodeInternal): + schema = getattr(class_def, "SCHEMA", None) + if schema is None: + # RETURN_TYPES access above usually populates SCHEMA — be defensive. + try: + schema = class_def.GET_SCHEMA() + except Exception: + schema = None + if schema is not None and slot_idx < len(schema.outputs): + out = schema.outputs[slot_idx] + if isinstance(out, io.MatchType.Output): + resolved = self._resolve_match_template( + node_id, schema, out.template.template_id, next_stack + ) + + # Warn only for V1 wildcards declared as "*"; unresolved MatchType + # templates warn separately in _resolve_match_template, avoiding double-warns. + if isinstance(resolved, str) and resolved == ANY_TYPE and declared == ANY_TYPE: + self._warn( + node_id, slot_idx, + f"node '{class_type}' output slot {slot_idx} is wildcard; defaulting to AnyType", + ) + + if not isinstance(resolved, str): + # e.g. legacy combo declared as a list of options. + self._warn(node_id, slot_idx, + f"node '{class_type}' output slot {slot_idx} has non-string return type {type(resolved).__name__}; defaulting to AnyType") + resolved = ANY_TYPE + + self._output_cache[cache_key] = resolved + return resolved + + def _resolve_match_template(self, node_id: str, schema, template_id: str, + stack: frozenset[tuple[str, int]]) -> str: + """Walk MatchType.Inputs sharing ``template_id``; return first concrete resolution or ``ANY_TYPE``.""" + node = self._get_node(node_id) + inputs_dict = (node or {}).get("inputs", {}) or {} + any_input_seen = False + for inp in schema.inputs: + if not isinstance(inp, io.MatchType.Input): + continue + if inp.template.template_id != template_id: + continue + any_input_seen = True + val = inputs_dict.get(inp.id) + if val is None: + continue + link = _parse_link(val) + if link is not None: + t = self.resolve_output_type(link[0], link[1], stack) + if t != ANY_TYPE: + return t + # Literal or malformed link: MatchType slots have no declared concrete type. + if not any_input_seen: + # Node-author bug: output template has no matching Input. + self._warn(node_id, None, + f"MatchType output template '{template_id}' has no matching Input on the node; defaulting to AnyType") + else: + self._warn(node_id, None, + f"MatchType template '{template_id}' has no bound concrete upstream input; defaulting to AnyType") + return ANY_TYPE + + def is_output_list(self, node_id: str, slot_idx: int) -> bool: + """Whether the source slot is declared as a list output (``OUTPUT_IS_LIST[idx]``).""" + if isinstance(slot_idx, bool) or not isinstance(slot_idx, int): + return False + cache_key = (node_id, slot_idx) + if cache_key in self._is_output_list_cache: + return self._is_output_list_cache[cache_key] + result = False + _, class_def = self._get_class_def_for_node(node_id) + if class_def is not None: + lst = getattr(class_def, "OUTPUT_IS_LIST", None) + if lst is not None and 0 <= slot_idx < len(lst): + result = bool(lst[slot_idx]) + self._is_output_list_cache[cache_key] = result + return result + + # ---- input resolution ------------------------------------------------ + def resolve_input_type(self, node_id: str, input_id: str) -> str: + """Resolve the io_type of the value currently bound to a node's input. + + * If the value is a link, return the resolved type of the source slot. + * If the value is a literal, return the declared slot's effective + io_type (peeling dynamic-input wrappers — e.g. an Autogrow-of-Image + slot resolves to ``IMAGE``, not ``COMFY_AUTOGROW_V3``). + * If the value is missing, malformed, or the slot is unknown, return + ``ANY_TYPE``. + """ + node = self._get_node(node_id) + if node is None: + return ANY_TYPE + inputs = node.get("inputs", {}) or {} + if input_id not in inputs: + return ANY_TYPE + link = _parse_link(inputs[input_id]) + if link is not None: + return self.resolve_output_type(link[0], link[1]) + return self.get_declared_slot_io_type(node_id, input_id) + + def is_input_list(self, node_id: str, input_id: str) -> bool: + """Whether the value bound to ``input_id`` originates from a list output.""" + node = self._get_node(node_id) + if node is None: + return False + link = _parse_link((node.get("inputs", {}) or {}).get(input_id)) + if link is None: + return False + return self.is_output_list(link[0], link[1]) + + def get_declared_slot_io_type(self, node_id: str, input_id: str) -> str: + """Return the effective declared io_type of a node's input slot. + + Peels dynamic-input wrappers so that the user-facing element type is + returned: + + * Autogrow → wrapped template input's io_type + * DynamicSlot → underlying slot's io_type + * Anything else → the slot's own io_type + * DynamicCombo / unsupported → ``ANY_TYPE`` (the combo key is itself + dynamic, not a meaningful type for consumers) + """ + _, class_def = self._get_class_def_for_node(node_id) + if class_def is None: + return ANY_TYPE + + # Prefer V3 schema (carries dynamic-input wrapper info). + if isinstance(class_def, type) and issubclass(class_def, _ComfyNodeInternal): + schema = getattr(class_def, "SCHEMA", None) + if schema is None: + try: + class_def.GET_SCHEMA() + schema = getattr(class_def, "SCHEMA", None) + except Exception: + schema = None + if schema is not None: + # Top-level input id. + for inp in schema.inputs: + if inp.id == input_id: + return self._effective_io_type(inp) + # Nested (DynamicSlot / DynamicCombo `parent.child`). + if "." in input_id: + top, _, _ = input_id.partition(".") + for inp in schema.inputs: + if inp.id != top: + continue + for child in inp.get_all(): + if child is inp: + continue + if child.id == input_id.split(".", 1)[1]: + return self._effective_io_type(child) + # Fall through to V1 dict (hidden inputs, etc.). + + try: + inputs = class_def.INPUT_TYPES() + except Exception: + return ANY_TYPE + for section in ("required", "optional"): + section_d = inputs.get(section, {}) + if input_id in section_d: + entry = section_d[input_id] + if not entry: + return ANY_TYPE + t = entry[0] + if isinstance(t, str): + return t + if isinstance(t, list): # legacy combo declared as list of options + return io.Combo.io_type + return ANY_TYPE + return ANY_TYPE + + @staticmethod + def _effective_io_type(inp) -> str: + """Return the consumer-facing io_type of a (possibly dynamic) input.""" + # Autogrow / DynamicSlot wrap a real element type; that's what consumers care about. + if isinstance(inp, io.Autogrow.Input): + try: + return inp.template.input.get_io_type() + except Exception: + return ANY_TYPE + if isinstance(inp, io.DynamicSlot.Input): + # Auto-derived slot type — comma-joined union of all option `when` types. + return getattr(inp, "_slot_io_type", ANY_TYPE) + # DynamicCombo's "type" is a key selector, not a connection type. + if isinstance(inp, io.DynamicCombo.Input): + return ANY_TYPE + try: + return inp.get_io_type() + except Exception: + return ANY_TYPE + + # ---- bulk helpers ---------------------------------------------------- + def compute_live_input_types(self, node_id: str) -> dict[str, str]: + """Build the ``{input_id: resolved_io_type}`` map for a node. + + Consumed by ``_io.get_finalized_class_inputs`` so future per-type + dynamic-input expansion can branch on what was actually connected. + """ + node = self._get_node(node_id) + if node is None: + return {} + out: dict[str, str] = {} + for input_id in (node.get("inputs", {}) or {}).keys(): + out[input_id] = self.resolve_input_type(node_id, input_id) + return out + + # ---- diagnostics ----------------------------------------------------- + def _warn(self, node_id: str, slot_idx: Any, msg: str) -> None: + key = (node_id, slot_idx, msg) + if key in self._warned: + return + self._warned.add(key) + logging.warning("TypeResolver: node=%s slot=%s %s", node_id, slot_idx, msg) diff --git a/execution.py b/execution.py index c45317593..0ae99f50b 100644 --- a/execution.py +++ b/execution.py @@ -84,8 +84,8 @@ class IsChangedCache: self.is_changed[node_id] = node["is_changed"] return self.is_changed[node_id] - # Intentionally do not use cached outputs here. We only want constants in IS_CHANGED - input_data_all, _, v3_data = get_input_data(node["inputs"], class_def, node_id, None) + # Intentionally do not use cached outputs here. We only want constants in IS_CHANGED. + input_data_all, _, v3_data = get_input_data(node["inputs"], class_def, node_id, None, self.dynprompt) try: is_changed = await _async_map_node_over_list(self.prompt_id, node_id, class_def, input_data_all, is_changed_name, v3_data=v3_data) is_changed = await resolve_map_node_over_list_results(is_changed) @@ -153,13 +153,16 @@ class CacheSet: SENSITIVE_EXTRA_DATA_KEYS = ("auth_token_comfy_org", "api_key_comfy_org") -def get_input_data(inputs, class_def, unique_id, execution_list=None, dynprompt=None, extra_data={}): +def get_input_data(inputs, class_def, unique_id, execution_list=None, dynprompt=None, extra_data={}, live_input_types=None): is_v3 = issubclass(class_def, _ComfyNodeInternal) v3_data: io.V3Data = {} hidden_inputs_v3 = {} valid_inputs = class_def.INPUT_TYPES() if is_v3: - valid_inputs, hidden, v3_data = _io.get_finalized_class_inputs(valid_inputs, inputs) + # Let dynamic schemas branch on resolved upstream types, not just literal values. + if live_input_types is None and dynprompt is not None and hasattr(dynprompt, "get_type_resolver"): + live_input_types = dynprompt.get_type_resolver().compute_live_input_types(unique_id) + valid_inputs, hidden, v3_data = _io.get_finalized_class_inputs(valid_inputs, inputs, live_input_types=live_input_types) input_data_all = {} missing_keys = {} for x in inputs: @@ -831,9 +834,17 @@ class PromptExecutor: self._notify_prompt_lifecycle("end", prompt_id) -async def validate_inputs(prompt_id, prompt, item, validated, visiting=None): +async def validate_inputs(prompt_id, prompt, item, validated, visiting=None, type_resolver=None): + """Validate inputs for a single node, recursing into upstream nodes. + + ``type_resolver`` is built once at the top of recursion and shared so + MatchType chains are only walked once per prompt. + """ if visiting is None: visiting = [] + if type_resolver is None: + from comfy_execution.type_resolver import TypeResolver + type_resolver = TypeResolver(prompt) unique_id = item if unique_id in validated: @@ -865,10 +876,12 @@ async def validate_inputs(prompt_id, prompt, item, validated, visiting=None): v3_data = None validate_function_inputs = [] validate_has_kwargs = False + live_input_types = None if issubclass(obj_class, _ComfyNodeInternal): obj_class: _io._ComfyNodeBaseInternal class_inputs = obj_class.INPUT_TYPES() - class_inputs, _, v3_data = _io.get_finalized_class_inputs(class_inputs, inputs) + live_input_types = type_resolver.compute_live_input_types(unique_id) + class_inputs, _, v3_data = _io.get_finalized_class_inputs(class_inputs, inputs, live_input_types=live_input_types) validate_function_name = "validate_inputs" validate_function = first_real_override(obj_class, validate_function_name) else: @@ -918,11 +931,20 @@ async def validate_inputs(prompt_id, prompt, item, validated, visiting=None): continue o_id = val[0] - o_class_type = prompt[o_id]['class_type'] - r = nodes.NODE_CLASS_MAPPINGS[o_class_type].RETURN_TYPES - received_type = r[val[1]] + # Walks MatchType/template chains so API workflows without + # frontend-injected type metadata get the same answer as the UI. + received_type = type_resolver.resolve_output_type(o_id, val[1]) received_types[x] = received_type - if 'input_types' not in validate_function_inputs and not validate_node_input(received_type, input_type): + # DynamicSlot's declared input_type is just the dispatch tag + # (COMFY_DYNAMICSLOT_V3); a link is valid iff some Option would + # actually claim the resolved upstream type. + if input_type == _io.DynamicSlot.io_type and isinstance(extra_info, dict): + link_valid = _io.DynamicSlot._select_option( + extra_info.get("options", []), {x: received_type}, x, has_link=True + ) is not None + else: + link_valid = validate_node_input(received_type, input_type) + if 'input_types' not in validate_function_inputs and not link_valid: details = f"{x}, received_type({received_type}) mismatch input_type({input_type})" error = { "type": "return_type_mismatch", @@ -940,7 +962,7 @@ async def validate_inputs(prompt_id, prompt, item, validated, visiting=None): try: visiting.append(unique_id) try: - r = await validate_inputs(prompt_id, prompt, o_id, validated, visiting) + r = await validate_inputs(prompt_id, prompt, o_id, validated, visiting, type_resolver) finally: visiting.pop() if r[0] is False: @@ -1068,7 +1090,11 @@ async def validate_inputs(prompt_id, prompt, item, validated, visiting=None): continue if len(validate_function_inputs) > 0 or validate_has_kwargs: - input_data_all, _, v3_data = get_input_data(inputs, obj_class, unique_id) + # Reuse the precomputed live_input_types so a custom validate_inputs() + # sees the same DynamicSlot branch that finalization picked above. + input_data_all, _, v3_data = get_input_data( + inputs, obj_class, unique_id, live_input_types=live_input_types + ) input_filtered = {} for x in input_data_all: if x in validate_function_inputs or validate_has_kwargs: @@ -1165,11 +1191,14 @@ async def validate_prompt(prompt_id, prompt, partial_execution_list: Union[list[ errors = [] node_errors = {} validated = {} + # Shared across output validations so MatchType chains walk only once. + from comfy_execution.type_resolver import TypeResolver + type_resolver = TypeResolver(prompt) for o in outputs: valid = False reasons = [] try: - m = await validate_inputs(prompt_id, prompt, o, validated) + m = await validate_inputs(prompt_id, prompt, o, validated, None, type_resolver) valid = m[0] reasons = m[1] except Exception as ex: diff --git a/tests-unit/comfy_api_test/test_dynamic_slot.py b/tests-unit/comfy_api_test/test_dynamic_slot.py new file mode 100644 index 000000000..ef2850e99 --- /dev/null +++ b/tests-unit/comfy_api_test/test_dynamic_slot.py @@ -0,0 +1,350 @@ +"""Unit tests for the redesigned ``DynamicSlot`` with type-keyed options.""" + +import pytest + +from comfy_api.latest import _io as io + + +def _opt(when, ids=None): + """Build an Option whose inputs are placeholder String widgets named after ids.""" + ids = ids or [] + inputs = [io.String.Input(name) for name in ids] + return io.DynamicSlot.Option(when=when, inputs=inputs) + + +# --------------------------------------------------------------------------- +# Option.when normalization +# --------------------------------------------------------------------------- + +def test_option_when_none(): + o = _opt(None, ["a"]) + assert o._when_types is None + assert o._when_set is None + assert o.as_dict()["when"] is None + + +def test_option_when_single_type(): + o = _opt(io.Image) + assert o._when_types == ("IMAGE",) + assert o._when_set == frozenset({"IMAGE"}) + assert o.as_dict()["when"] == ["IMAGE"] + + +def test_option_when_anytype(): + o = _opt(io.AnyType) + assert o._when_types == ("*",) + assert o.as_dict()["when"] == ["*"] + + +def test_option_when_list_preserves_order(): + """Declaration order is preserved in both the tuple and the serialized form.""" + o = _opt([io.Mask, io.Image]) + assert o._when_types == ("MASK", "IMAGE") + assert o.as_dict()["when"] == ["MASK", "IMAGE"] + + +def test_option_when_list_dedups_within_option(): + o = _opt([io.Image, io.Image, io.Mask]) + assert o._when_types == ("IMAGE", "MASK") + + +def test_option_when_multitype_input(): + mt = io.MultiType.Input("x", types=[io.Image, io.Latent]) + o = _opt(mt) + assert o._when_types == ("IMAGE", "LATENT") + + +def test_option_when_empty_list_rejected(): + with pytest.raises(ValueError, match="when=\\[\\]"): + io.DynamicSlot.Option(when=[], inputs=[]) + + +def test_option_when_garbage_rejected(): + with pytest.raises(ValueError, match="when must be"): + io.DynamicSlot.Option(when="IMAGE", inputs=[]) + + +def test_option_when_list_with_non_comfytype_rejected(): + with pytest.raises(ValueError, match="list entries"): + io.DynamicSlot.Option(when=[io.Image, "MASK"], inputs=[]) + + +def test_option_when_list_with_anytype_rejected(): + """AnyType must stand alone — it represents the unresolvable-wildcard + state, not a concrete type that can share a branch with concrete types.""" + with pytest.raises(ValueError, match="AnyType cannot be grouped"): + io.DynamicSlot.Option(when=[io.Image, io.AnyType], inputs=[]) + + +def test_option_when_multitype_with_anytype_rejected(): + mt = io.MultiType.Input("x", types=[io.Image, io.AnyType]) + with pytest.raises(ValueError, match="AnyType cannot be grouped"): + io.DynamicSlot.Option(when=mt, inputs=[]) + + +# --------------------------------------------------------------------------- +# DynamicSlot.Input construction and serialization +# --------------------------------------------------------------------------- + +def test_input_requires_at_least_one_option(): + with pytest.raises(ValueError, match="at least one Option"): + io.DynamicSlot.Input("x", options=[]) + + +def test_input_requires_non_none_option(): + with pytest.raises(ValueError, match="non-None `when`"): + io.DynamicSlot.Input("x", options=[_opt(None, ["a"])]) + + +def test_input_auto_derives_slot_type(): + inp = io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["a"]), + _opt(io.Mask, ["b"]), + _opt(None, ["c"]), + ]) + # Declared order preserved across non-None options; None contributes nothing. + assert inp._slot_io_type == "IMAGE,MASK" + d = inp.as_dict() + assert d["slotType"] == "IMAGE,MASK" + assert len(d["options"]) == 3 + + +def test_input_includes_anytype_in_slot_type(): + inp = io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["a"]), + _opt(io.AnyType, ["b"]), + ]) + assert inp._slot_io_type == "IMAGE,*" + + +def test_input_rejects_duplicate_type_across_options(): + with pytest.raises(ValueError, match="appears in more than one"): + io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["a"]), + _opt([io.Image, io.Mask], ["b"]), + ]) + + +def test_input_rejects_duplicate_anytype_across_options(): + with pytest.raises(ValueError, match="appears in more than one"): + io.DynamicSlot.Input("x", options=[ + _opt(io.AnyType, ["a"]), + _opt(io.AnyType, ["b"]), + ]) + + +def test_input_rejects_duplicate_when_none(): + with pytest.raises(ValueError, match="only one Option may declare when=None"): + io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["a"]), + _opt(None, ["b"]), + _opt(None, ["c"]), + ]) + + +def test_input_rejects_non_option_entry(): + with pytest.raises(ValueError, match="must be DynamicSlot.Option instances"): + io.DynamicSlot.Input("x", options=[_opt(io.Image, ["a"]), "not an option"]) + + +def test_input_defaults_to_optional_and_always_force_input(): + """The slot is always rendered as a connector, never as a widget, even + when slotType includes widget-capable types like INT/STRING.""" + inp = io.DynamicSlot.Input("x", options=[_opt(io.Int, ["n"])]) + d = inp.as_dict() + assert d["forceInput"] is True + # default optional=True → slot lives in optional bucket via DynamicInput + assert inp.optional is True + + +def test_input_required_slot_allowed_without_when_none(): + inp = io.DynamicSlot.Input("x", optional=False, options=[_opt(io.Image, ["a"])]) + assert inp.optional is False + + +def test_input_required_slot_rejects_when_none_option(): + with pytest.raises(ValueError, match="optional=False forbids when=None"): + io.DynamicSlot.Input( + "x", + optional=False, + options=[_opt(io.Image, ["a"]), _opt(None, ["b"])], + ) + + +def test_input_get_all_prepends_self_and_dedups_children(): + inp = io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["shared", "image_only"]), + _opt(io.Mask, ["shared", "mask_only"]), + ]) + items = inp.get_all() + # Convention shared with Autogrow / DynamicCombo: parent first, then children. + assert items[0] is inp + assert [i.id for i in items[1:]] == ["shared", "image_only", "mask_only"] + + +# --------------------------------------------------------------------------- +# Option selection +# --------------------------------------------------------------------------- + +def _select(options, live_input_types, has_link, finalized_id="x"): + """Convenience wrapper that runs the dispatch through the dict form (post-as_dict).""" + serialized = [o.as_dict() for o in options] + return io.DynamicSlot._select_option( + serialized, live_input_types, finalized_id, has_link + ) + + +def test_select_unconnected_picks_none_option(): + options = [_opt(io.Image, ["img_widgets"]), _opt(None, ["empty_widgets"])] + sel = _select(options, {}, has_link=False) + assert sel is not None + assert sel["when"] is None + + +def test_select_unconnected_with_no_none_option_returns_none(): + options = [_opt(io.Image, ["x"])] + assert _select(options, {}, has_link=False) is None + + +def test_select_concrete_type_match(): + options = [ + _opt(io.Image, ["a"]), + _opt(io.Mask, ["b"]), + _opt(io.AnyType, ["c"]), + ] + sel = _select(options, {"x": "MASK"}, has_link=True) + assert sel["when"] == ["MASK"] + + +def test_select_anytype_matches_wildcard_resolved(): + options = [_opt(io.Image, ["a"]), _opt(io.AnyType, ["c"])] + sel = _select(options, {"x": "*"}, has_link=True) + assert sel["when"] == ["*"] + + +def test_select_anytype_does_not_match_concrete(): + options = [_opt(io.AnyType, ["c"])] + # MASK isn't in any option's set; AnyType only matches "*". No expansion. + assert _select(options, {"x": "MASK"}, has_link=True) is None + + +def test_select_anytype_branch_does_not_swallow_unenumerated_concrete(): + """Regression: a slot exposing IMAGE + AnyType must reject LATENT upstream + instead of expanding the AnyType branch. validate_inputs relies on this + to compute link validity (slotType="IMAGE,*" alone would over-accept).""" + options = [_opt(io.Image, ["image_widget"]), _opt(io.AnyType, ["any_widget"])] + assert _select(options, {"x": "LATENT"}, has_link=True) is None + # Sanity: IMAGE still matches the IMAGE branch and "*" still matches AnyType. + assert _select(options, {"x": "IMAGE"}, has_link=True)["when"] == ["IMAGE"] + assert _select(options, {"x": "*"}, has_link=True)["when"] == ["*"] + + +def test_select_first_match_wins_on_union_upstream(): + """Ordering only matters when upstream declares a multi-type union; with + per-option type uniqueness, single concrete types can never match two + options.""" + options = [ + _opt([io.Image, io.Mask], ["image_or_mask"]), + _opt(io.Latent, ["latent_only"]), + ] + # Upstream union "IMAGE,LATENT" intersects both options; first option wins. + sel = _select(options, {"x": "IMAGE,LATENT"}, has_link=True) + first_input_id = next(iter(sel["inputs"]["required"].keys())) + assert first_input_id == "image_or_mask" + + +def test_select_multitype_upstream_intersects_option_set(): + """When upstream declares MultiType like 'IMAGE,MASK', any option that + intersects with that set matches (first wins).""" + options = [ + _opt(io.Latent, ["latent_only"]), + _opt(io.Mask, ["mask_only"]), + ] + sel = _select(options, {"x": "IMAGE,MASK"}, has_link=True) + assert sel["when"] == ["MASK"] + + +def test_select_missing_resolved_falls_through_to_anytype(): + """If live_input_types lacks an entry for this slot but a link exists, + we treat it as '*' (resolver default for unresolvable links).""" + options = [_opt(io.Image, ["a"]), _opt(io.AnyType, ["c"])] + sel = _select(options, {}, has_link=True) + assert sel["when"] == ["*"] + + +# --------------------------------------------------------------------------- +# End-to-end expansion via _expand_schema_for_dynamic +# --------------------------------------------------------------------------- + +def test_expand_unconnected_path(): + """An unconnected slot with a `when=None` option expands that option's children.""" + inp = io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["image_widget"]), + _opt(None, ["empty_widget"]), + ]) + d = inp.as_dict() + value = (io.DynamicSlot.io_type, d) + out_dict = { + "required": {}, "optional": {}, "hidden": {}, + "dynamic_paths": {}, "dynamic_paths_default_value": {}, + } + io.DynamicSlot._expand_schema_for_dynamic( + out_dict=out_dict, + live_inputs={}, # no entry for "x" → unconnected + value=value, + input_type="optional", + curr_prefix=["x"], + live_input_types=None, + ) + # The slot itself is always advertised in the caller's bucket. + assert "x" in out_dict["optional"] + # Children land in their own buckets (required by default) with + # parent-prefixed ids. + assert "x.empty_widget" in out_dict["required"] + assert "x.image_widget" not in out_dict["required"] + + +def test_expand_typed_path(): + """A connected slot expands the matching type's children.""" + inp = io.DynamicSlot.Input("x", options=[ + _opt(io.Image, ["image_widget"]), + _opt(io.Mask, ["mask_widget"]), + ]) + d = inp.as_dict() + value = (io.DynamicSlot.io_type, d) + out_dict = { + "required": {}, "optional": {}, "hidden": {}, + "dynamic_paths": {}, "dynamic_paths_default_value": {}, + } + io.DynamicSlot._expand_schema_for_dynamic( + out_dict=out_dict, + live_inputs={"x": ["src_node", 0]}, # link present + value=value, + input_type="optional", + curr_prefix=["x"], + live_input_types={"x": "MASK"}, + ) + assert "x" in out_dict["optional"] + assert "x.mask_widget" in out_dict["required"] + assert "x.image_widget" not in out_dict["required"] + + +def test_expand_unmatched_concrete_still_advertises_slot(): + """Resolved type not in any option → no children, but the slot itself stays.""" + inp = io.DynamicSlot.Input("x", options=[_opt(io.Image, ["image_widget"])]) + d = inp.as_dict() + value = (io.DynamicSlot.io_type, d) + out_dict = { + "required": {}, "optional": {}, "hidden": {}, + "dynamic_paths": {}, "dynamic_paths_default_value": {}, + } + io.DynamicSlot._expand_schema_for_dynamic( + out_dict=out_dict, + live_inputs={"x": ["src_node", 0]}, + value=value, + input_type="optional", + curr_prefix=["x"], + live_input_types={"x": "LATENT"}, + ) + assert "x" in out_dict["optional"] + assert "x.image_widget" not in out_dict["required"] diff --git a/tests-unit/execution_test/test_type_resolver.py b/tests-unit/execution_test/test_type_resolver.py new file mode 100644 index 000000000..48ddc4c20 --- /dev/null +++ b/tests-unit/execution_test/test_type_resolver.py @@ -0,0 +1,482 @@ +"""Unit tests for :mod:`comfy_execution.type_resolver`. + +These tests stand up a small in-memory ``NODE_CLASS_MAPPINGS`` for the test +node classes (V1 and V3) and a fake DynamicPrompt-like dict, then verify the +resolver's behaviour for: + + * Static V1 ``RETURN_TYPES`` resolution. + * V1 wildcard outputs (must yield ``AnyType`` and warn once). + * V3 ``MatchType`` chains resolved via the downstream node's bound inputs. + * ``MatchType`` with no upstream bound (fall back to ``AnyType`` + warn). + * ``MatchType`` cycles (termination at ``AnyType`` + warn, no recursion blow-up). + * Deep chains capped by ``MAX_RESOLVE_DEPTH``. + * Input-type resolution for both literal values and links. + * Effective slot io_type peeling for ``Autogrow`` (returns the wrapped type). + * ``compute_live_input_types`` produces the right shape. + * Cache invalidation. + +The tests deliberately patch ``nodes.NODE_CLASS_MAPPINGS`` so they don't need +the whole ComfyUI bootstrap. +""" + +from __future__ import annotations + +import logging +import sys +import types as _pytypes + +import pytest + + +# --------------------------------------------------------------------------- +# Lightweight V1 test node factory +# --------------------------------------------------------------------------- + +def _v1_node(return_types: tuple[str, ...], input_types_dict: dict | None = None, + output_is_list: tuple[bool, ...] | None = None): + """Build a V1 node class with the given RETURN_TYPES / INPUT_TYPES().""" + if input_types_dict is None: + input_types_dict = {"required": {}} + + class _V1: + RETURN_TYPES = return_types + if output_is_list is not None: + OUTPUT_IS_LIST = output_is_list + + @classmethod + def INPUT_TYPES(cls): + return input_types_dict + + return _V1 + + +# --------------------------------------------------------------------------- +# Fixture: install fake nodes module before importing the resolver +# --------------------------------------------------------------------------- + +@pytest.fixture +def fake_nodes_module(): + """Install a synthetic ``nodes`` module with an empty mappings dict. + + Yields the mappings dict so tests can populate it per case. Cleans up + afterwards. We also have to make sure comfy_execution.type_resolver picks + up our fake module on its local import. + """ + real_nodes = sys.modules.get("nodes") + fake = _pytypes.ModuleType("nodes") + fake.NODE_CLASS_MAPPINGS = {} + sys.modules["nodes"] = fake + try: + yield fake.NODE_CLASS_MAPPINGS + finally: + if real_nodes is not None: + sys.modules["nodes"] = real_nodes + else: + del sys.modules["nodes"] + + +@pytest.fixture +def TypeResolver(fake_nodes_module): + # Late import so it picks up our fake `nodes` module. + from comfy_execution.type_resolver import TypeResolver as TR + return TR + + +# --------------------------------------------------------------------------- +# V1 resolution +# --------------------------------------------------------------------------- + +def test_v1_static_return_types_resolves(fake_nodes_module, TypeResolver): + fake_nodes_module["AddNode"] = _v1_node(("INT",)) + prompt = {"n1": {"class_type": "AddNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("n1", 0) == "INT" + + +def test_v1_wildcard_warns_once_and_returns_any(fake_nodes_module, TypeResolver, caplog): + fake_nodes_module["WildNode"] = _v1_node(("*",)) + prompt = {"n1": {"class_type": "WildNode", "inputs": {}}} + r = TypeResolver(prompt) + with caplog.at_level(logging.WARNING, logger="root"): + assert r.resolve_output_type("n1", 0) == "*" + # second call should still return * but not produce a second warning + assert r.resolve_output_type("n1", 0) == "*" + warnings = [rec for rec in caplog.records if "TypeResolver" in rec.message] + assert len(warnings) == 1, f"expected exactly one warning, got {warnings}" + + +def test_unknown_node_returns_any(fake_nodes_module, TypeResolver): + prompt = {"n1": {"class_type": "NopeNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("n1", 0) == "*" + + +def test_out_of_range_slot_returns_any(fake_nodes_module, TypeResolver): + fake_nodes_module["AddNode"] = _v1_node(("INT",)) + prompt = {"n1": {"class_type": "AddNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("n1", 5) == "*" + + +def test_missing_node_returns_any(fake_nodes_module, TypeResolver): + fake_nodes_module["AddNode"] = _v1_node(("INT",)) + prompt = {"n1": {"class_type": "AddNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("nonexistent", 0) == "*" + + +# --------------------------------------------------------------------------- +# is_output_list / is_input_list +# --------------------------------------------------------------------------- + +def test_is_output_list(fake_nodes_module, TypeResolver): + fake_nodes_module["ListNode"] = _v1_node(("IMAGE", "MASK"), output_is_list=(True, False)) + prompt = {"n1": {"class_type": "ListNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.is_output_list("n1", 0) is True + assert r.is_output_list("n1", 1) is False + + +def test_is_input_list_follows_link(fake_nodes_module, TypeResolver): + fake_nodes_module["ListNode"] = _v1_node(("IMAGE",), output_is_list=(True,)) + fake_nodes_module["Consumer"] = _v1_node( + ("INT",), + {"required": {"img": ("IMAGE",)}}, + ) + prompt = { + "src": {"class_type": "ListNode", "inputs": {}}, + "dst": {"class_type": "Consumer", "inputs": {"img": ["src", 0]}}, + } + r = TypeResolver(prompt) + assert r.is_input_list("dst", "img") is True + + +# --------------------------------------------------------------------------- +# V3 MatchType resolution +# --------------------------------------------------------------------------- + +def _make_switch_node_class(): + """Build a V3 Switch-like node with MatchType inputs/outputs.""" + from comfy_api.latest import io + + class Switch(io.ComfyNode): + @classmethod + def define_schema(cls): + template = io.MatchType.Template("switch") + return io.Schema( + node_id="TestSwitch", + inputs=[ + io.Boolean.Input("switch"), + io.MatchType.Input("on_false", template=template, optional=True), + io.MatchType.Input("on_true", template=template, optional=True), + ], + outputs=[io.MatchType.Output(template=template)], + ) + + @classmethod + def execute(cls, switch, on_false=None, on_true=None): + return io.NodeOutput(on_true if switch else on_false) + + # Force schema computation so SCHEMA / RETURN_TYPES are populated. + Switch.GET_SCHEMA() + return Switch + + +def test_matchtype_resolves_to_upstream_concrete(fake_nodes_module, TypeResolver): + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + fake_nodes_module["ImageSrc"] = _v1_node(("IMAGE",)) + prompt = { + "img": {"class_type": "ImageSrc", "inputs": {}}, + "sw": { + "class_type": "TestSwitch", + "inputs": {"switch": True, "on_true": ["img", 0]}, + }, + } + r = TypeResolver(prompt) + assert r.resolve_output_type("sw", 0) == "IMAGE" + + +def test_matchtype_first_concrete_wins(fake_nodes_module, TypeResolver): + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + fake_nodes_module["ImageSrc"] = _v1_node(("IMAGE",)) + fake_nodes_module["LatentSrc"] = _v1_node(("LATENT",)) + prompt = { + "img": {"class_type": "ImageSrc", "inputs": {}}, + "lat": {"class_type": "LatentSrc", "inputs": {}}, + "sw": { + "class_type": "TestSwitch", + "inputs": { + "switch": False, + "on_false": ["img", 0], # listed first in schema → wins + "on_true": ["lat", 0], + }, + }, + } + r = TypeResolver(prompt) + assert r.resolve_output_type("sw", 0) == "IMAGE" + + +def test_matchtype_no_bound_input_returns_any(fake_nodes_module, TypeResolver, caplog): + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + prompt = {"sw": {"class_type": "TestSwitch", "inputs": {"switch": True}}} + r = TypeResolver(prompt) + with caplog.at_level(logging.WARNING, logger="root"): + assert r.resolve_output_type("sw", 0) == "*" + assert any("MatchType" in rec.message for rec in caplog.records) + + +def test_matchtype_skips_wildcard_input(fake_nodes_module, TypeResolver): + """If the first matched input resolves to AnyType, the resolver tries the next.""" + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + fake_nodes_module["WildNode"] = _v1_node(("*",)) + fake_nodes_module["ImageSrc"] = _v1_node(("IMAGE",)) + prompt = { + "wild": {"class_type": "WildNode", "inputs": {}}, + "img": {"class_type": "ImageSrc", "inputs": {}}, + "sw": { + "class_type": "TestSwitch", + "inputs": { + "switch": True, + "on_false": ["wild", 0], + "on_true": ["img", 0], + }, + }, + } + r = TypeResolver(prompt) + assert r.resolve_output_type("sw", 0) == "IMAGE" + + +def test_matchtype_cycle_terminates_at_any(fake_nodes_module, TypeResolver): + """Two switches that feed each other must not recurse forever.""" + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + prompt = { + "a": {"class_type": "TestSwitch", "inputs": {"switch": True, "on_true": ["b", 0]}}, + "b": {"class_type": "TestSwitch", "inputs": {"switch": True, "on_true": ["a", 0]}}, + } + r = TypeResolver(prompt) + # Must not raise / recurse forever; both resolve to AnyType. + assert r.resolve_output_type("a", 0) == "*" + assert r.resolve_output_type("b", 0) == "*" + + +def test_matchtype_chain_resolves_through(fake_nodes_module, TypeResolver): + """A → B → C → IMAGE: chain must walk all the way.""" + fake_nodes_module["TestSwitch"] = _make_switch_node_class() + fake_nodes_module["ImageSrc"] = _v1_node(("IMAGE",)) + prompt = { + "src": {"class_type": "ImageSrc", "inputs": {}}, + "a": {"class_type": "TestSwitch", "inputs": {"switch": True, "on_true": ["src", 0]}}, + "b": {"class_type": "TestSwitch", "inputs": {"switch": True, "on_true": ["a", 0]}}, + "c": {"class_type": "TestSwitch", "inputs": {"switch": True, "on_true": ["b", 0]}}, + } + r = TypeResolver(prompt) + assert r.resolve_output_type("c", 0) == "IMAGE" + + +# --------------------------------------------------------------------------- +# Input resolution and effective io_type peeling +# --------------------------------------------------------------------------- + +def test_resolve_input_type_literal_uses_declared(fake_nodes_module, TypeResolver): + fake_nodes_module["Sink"] = _v1_node(("INT",), {"required": {"steps": ("INT",)}}) + prompt = {"n1": {"class_type": "Sink", "inputs": {"steps": 20}}} + r = TypeResolver(prompt) + assert r.resolve_input_type("n1", "steps") == "INT" + + +def test_resolve_input_type_link(fake_nodes_module, TypeResolver): + fake_nodes_module["Src"] = _v1_node(("LATENT",)) + fake_nodes_module["Sink"] = _v1_node(("INT",), {"required": {"x": ("*",)}}) + prompt = { + "src": {"class_type": "Src", "inputs": {}}, + "sink": {"class_type": "Sink", "inputs": {"x": ["src", 0]}}, + } + r = TypeResolver(prompt) + assert r.resolve_input_type("sink", "x") == "LATENT" + + +def test_effective_slot_type_peels_autogrow(fake_nodes_module, TypeResolver): + from comfy_api.latest import io + + class AutogrowImg(io.ComfyNode): + @classmethod + def define_schema(cls): + template = io.Autogrow.TemplatePrefix( + input=io.Image.Input("img"), + prefix="img", + min=1, + ) + return io.Schema( + node_id="AutogrowImg", + inputs=[io.Autogrow.Input("imgs", template=template)], + outputs=[io.Image.Output()], + ) + + @classmethod + def execute(cls, imgs): + return io.NodeOutput(None) + + AutogrowImg.GET_SCHEMA() + fake_nodes_module["AutogrowImg"] = AutogrowImg + prompt = {"n1": {"class_type": "AutogrowImg", "inputs": {}}} + r = TypeResolver(prompt) + # The user-facing element type, not the autogrow wrapper. + assert r.get_declared_slot_io_type("n1", "imgs") == "IMAGE" + + +# --------------------------------------------------------------------------- +# compute_live_input_types +# --------------------------------------------------------------------------- + +def test_effective_slot_type_on_v3_plain_input(fake_nodes_module, TypeResolver): + """V3 input that is neither Autogrow/DynamicSlot/DynamicCombo must still resolve. + + Regression test: importing ``io`` from the public re-export skipped + ``DynamicSlot``, so an ``isinstance`` chain in ``_effective_io_type`` raised + ``AttributeError`` the first time it ran against a plain V3 input. + """ + from comfy_api.latest import io + + class BoolSink(io.ComfyNode): + @classmethod + def define_schema(cls): + return io.Schema( + node_id="BoolSink", + inputs=[io.Boolean.Input("flag")], + outputs=[io.Boolean.Output()], + ) + + @classmethod + def execute(cls, flag): + return io.NodeOutput(flag) + + BoolSink.GET_SCHEMA() + fake_nodes_module["BoolSink"] = BoolSink + prompt = {"n": {"class_type": "BoolSink", "inputs": {"flag": True}}} + r = TypeResolver(prompt) + assert r.get_declared_slot_io_type("n", "flag") == "BOOLEAN" + assert r.compute_live_input_types("n") == {"flag": "BOOLEAN"} + + +def test_effective_slot_type_peels_dynamic_slot(fake_nodes_module, TypeResolver): + """A DynamicSlot input reports its auto-derived slotType (union of `when` types).""" + from comfy_api.latest import _io as io + + class DSNode(io.ComfyNode): + @classmethod + def define_schema(cls): + return io.Schema( + node_id="DSNode", + inputs=[ + io.DynamicSlot.Input("slot", options=[ + io.DynamicSlot.Option(when=io.Image, inputs=[]), + io.DynamicSlot.Option(when=io.Latent, inputs=[]), + ]), + ], + outputs=[io.String.Output()], + ) + + @classmethod + def execute(cls, **kwargs): + return io.NodeOutput("") + + DSNode.GET_SCHEMA() + fake_nodes_module["DSNode"] = DSNode + prompt = {"n": {"class_type": "DSNode", "inputs": {}}} + r = TypeResolver(prompt) + assert r.get_declared_slot_io_type("n", "slot") == "IMAGE,LATENT" + + +def test_compute_live_input_types_mixes_links_and_literals(fake_nodes_module, TypeResolver): + fake_nodes_module["Src"] = _v1_node(("MODEL",)) + fake_nodes_module["Sink"] = _v1_node( + ("INT",), + {"required": {"model": ("MODEL",), "steps": ("INT",)}}, + ) + prompt = { + "src": {"class_type": "Src", "inputs": {}}, + "sink": { + "class_type": "Sink", + "inputs": {"model": ["src", 0], "steps": 20}, + }, + } + r = TypeResolver(prompt) + assert r.compute_live_input_types("sink") == {"model": "MODEL", "steps": "INT"} + + +# --------------------------------------------------------------------------- +# Cache invalidation +# --------------------------------------------------------------------------- + +def test_invalidate_clears_cache(fake_nodes_module, TypeResolver): + fake_nodes_module["Src"] = _v1_node(("IMAGE",)) + prompt = {"n1": {"class_type": "Src", "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("n1", 0) == "IMAGE" + # Mutate the underlying class and invalidate; the resolver must re-read. + fake_nodes_module["Src"] = _v1_node(("LATENT",)) + r.invalidate() + assert r.resolve_output_type("n1", 0) == "LATENT" + + +# --------------------------------------------------------------------------- +# Malformed input robustness +# --------------------------------------------------------------------------- + +def test_malformed_link_does_not_crash(fake_nodes_module, TypeResolver): + """A link with a non-int slot index must not raise; resolver returns AnyType.""" + fake_nodes_module["Src"] = _v1_node(("IMAGE",)) + fake_nodes_module["Sink"] = _v1_node(("INT",), {"required": {"x": ("*",)}}) + prompt = { + "src": {"class_type": "Src", "inputs": {}}, + # slot index sent as a string (common API JSON mistake) + "sink": {"class_type": "Sink", "inputs": {"x": ["src", "0"]}}, + } + r = TypeResolver(prompt) + # Falls back to declared slot type (still "*"), no exception. + assert r.resolve_input_type("sink", "x") == "*" + + +def test_malformed_link_wrong_arity_does_not_crash(fake_nodes_module, TypeResolver): + fake_nodes_module["Src"] = _v1_node(("IMAGE",)) + fake_nodes_module["Sink"] = _v1_node(("INT",), {"required": {"x": ("*",)}}) + prompt = { + "src": {"class_type": "Src", "inputs": {}}, + "sink": {"class_type": "Sink", "inputs": {"x": ["src"]}}, # arity 1 + } + r = TypeResolver(prompt) + assert r.resolve_input_type("sink", "x") == "*" + + +def test_direct_resolve_output_type_with_bad_slot_idx_returns_any(fake_nodes_module, TypeResolver): + fake_nodes_module["Src"] = _v1_node(("IMAGE",)) + prompt = {"src": {"class_type": "Src", "inputs": {}}} + r = TypeResolver(prompt) + # type-wise these should be unreachable through normal validation but the + # resolver must still degrade gracefully. + assert r.resolve_output_type("src", "0") == "*" + assert r.resolve_output_type("src", True) == "*" # bool is a subclass of int + assert r.is_output_list("src", "0") is False + + +def test_non_string_class_type_returns_any(fake_nodes_module, TypeResolver): + prompt = {"n1": {"class_type": 42, "inputs": {}}} + r = TypeResolver(prompt) + assert r.resolve_output_type("n1", 0) == "*" + + +def test_invalidate_node_only_clears_that_node(fake_nodes_module, TypeResolver): + fake_nodes_module["SrcA"] = _v1_node(("IMAGE",)) + fake_nodes_module["SrcB"] = _v1_node(("LATENT",)) + prompt = { + "a": {"class_type": "SrcA", "inputs": {}}, + "b": {"class_type": "SrcB", "inputs": {}}, + } + r = TypeResolver(prompt) + r.resolve_output_type("a", 0) + r.resolve_output_type("b", 0) + fake_nodes_module["SrcA"] = _v1_node(("MASK",)) + r.invalidate_node("a") + assert r.resolve_output_type("a", 0) == "MASK" + # b's cached result survives even though SrcB was unchanged + assert ("b", 0) in r._output_cache