Files
ttulttul-ComfyUI-Modal/api_intercept.py
T

994 lines
38 KiB
Python

"""Prompt interception and graph rewriting for Modal-backed execution."""
from __future__ import annotations
import copy
import logging
import time
import uuid
from collections import defaultdict
from dataclasses import dataclass, field
from typing import Any, Iterator
from aiohttp import web
from .modal_executor_node import ensure_modal_component_proxy_node_registered
from .settings import ModalSyncSettings, get_settings
from .sync_engine import ModalAssetSyncEngine, SyncedAsset
logger = logging.getLogger(__name__)
_ROUTE_REGISTERED = False
_TRANSPORTABLE_OUTPUT_TYPES = frozenset(
{
"*",
"BOOLEAN",
"FLOAT",
"IMAGE",
"INT",
"LATENT",
"MASK",
"NOISE",
"SIGMAS",
"STRING",
}
)
@dataclass(frozen=True)
class LinkedOutputRef:
"""Reference a node output slot within a prompt graph."""
node_id: str
output_index: int
@dataclass(frozen=True)
class InputTarget:
"""Describe a target input inside a remote component."""
node_id: str
input_name: str
@dataclass
class BoundaryInputSpec:
"""Describe one local-to-remote boundary value for a component."""
proxy_input_name: str
source: LinkedOutputRef
targets: list[InputTarget] = field(default_factory=list)
@dataclass
class BoundaryOutputSpec:
"""Describe one remote-to-local boundary value for a component."""
proxy_output_name: str
source: LinkedOutputRef
io_type: str
is_list: bool
@dataclass
class RemoteComponentPlan:
"""Execution and rewrite plan for one connected remote component."""
node_ids: list[str]
representative_node_id: str
boundary_inputs: list[BoundaryInputSpec]
boundary_outputs: list[BoundaryOutputSpec]
execute_node_ids: list[str]
contains_output_node: bool
@dataclass
class RewriteSummary:
"""Summary of the prompt rewrite performed for a queue request."""
remote_node_ids: list[str] = field(default_factory=list)
remote_component_ids: list[str] = field(default_factory=list)
component_node_ids_by_representative: dict[str, list[str]] = field(default_factory=dict)
rewritten_node_id_map: dict[str, str] = field(default_factory=dict)
synced_assets: list[SyncedAsset] = field(default_factory=list)
custom_nodes_bundle: SyncedAsset | None = None
class ModalPromptValidationError(ValueError):
"""Raised when a prompt cannot be executed with the current Modal transport."""
def _emit_modal_status(
prompt_server: Any,
phase: str,
*,
client_id: str | None,
prompt_id: str | None,
node_ids: list[str],
component_node_ids_by_representative: dict[str, list[str]] | None = None,
active_node_id: str | None = None,
active_node_class_type: str | None = None,
active_node_role: str | None = None,
error_message: str | None = None,
) -> None:
"""Send a Modal execution status event to the active websocket client."""
if client_id is None:
logger.debug("Skipping Modal status event %s because no client id is available.", phase)
return
payload: dict[str, Any] = {
"phase": phase,
"prompt_id": prompt_id,
"node_ids": list(node_ids),
}
if component_node_ids_by_representative:
payload["components"] = [
{
"representative_node_id": representative_node_id,
"node_ids": list(component_node_ids),
}
for representative_node_id, component_node_ids in sorted(
component_node_ids_by_representative.items()
)
]
if active_node_id is not None:
payload["active_node_id"] = active_node_id
if active_node_class_type is not None:
payload["active_node_class_type"] = active_node_class_type
if active_node_role is not None:
payload["active_node_role"] = active_node_role
if error_message is not None:
payload["error_message"] = error_message
prompt_server.send_sync("modal_status", payload, client_id)
def _get_nodes_module() -> Any:
"""Import the ComfyUI nodes module lazily."""
import nodes
return nodes
def _get_server_module() -> Any:
"""Import the ComfyUI server module lazily."""
import server
return server
def _get_execution_module() -> Any:
"""Import the ComfyUI execution module lazily."""
import execution
return execution
def _is_link(value: Any) -> bool:
"""Return whether a prompt input value is a ComfyUI link."""
return (
isinstance(value, list)
and len(value) == 2
and all(not isinstance(item, dict) for item in value)
)
def _looks_like_workflow_node(fragment: dict[str, Any]) -> bool:
"""Return whether a JSON fragment resembles a saved ComfyUI workflow node."""
return "id" in fragment and "properties" in fragment
def _iter_workflow_nodes(
workflow_fragment: Any,
visited_object_ids: set[int] | None = None,
) -> Iterator[dict[str, Any]]:
"""Yield workflow node dictionaries from a nested saved workflow fragment."""
if visited_object_ids is None:
visited_object_ids = set()
if isinstance(workflow_fragment, dict):
object_id = id(workflow_fragment)
if object_id in visited_object_ids:
return
visited_object_ids.add(object_id)
if _looks_like_workflow_node(workflow_fragment):
yield workflow_fragment
for value in workflow_fragment.values():
yield from _iter_workflow_nodes(value, visited_object_ids)
return
if isinstance(workflow_fragment, list):
object_id = id(workflow_fragment)
if object_id in visited_object_ids:
return
visited_object_ids.add(object_id)
for item in workflow_fragment:
yield from _iter_workflow_nodes(item, visited_object_ids)
def extract_remote_node_ids(
workflow: dict[str, Any] | None,
settings: ModalSyncSettings | None = None,
) -> set[str]:
"""Return the node ids marked for remote execution in the workflow metadata."""
if workflow is None:
return set()
marker = (settings or get_settings()).marker_property
remote_node_ids: set[str] = set()
for node in _iter_workflow_nodes(workflow):
properties = node.get("properties") or {}
if properties.get(marker):
remote_node_ids.add(str(node.get("id")))
return remote_node_ids
def _normalize_output_metadata(node_class: type[Any]) -> tuple[tuple[str, ...], tuple[str, ...], tuple[bool, ...]]:
"""Return normalized output metadata for a node class."""
if hasattr(node_class, "GET_SCHEMA"):
node_class.GET_SCHEMA()
output_types = tuple(getattr(node_class, "RETURN_TYPES", ("*",))) or ("*",)
default_names = tuple(f"output_{index}" for index, _ in enumerate(output_types))
output_names = tuple(getattr(node_class, "RETURN_NAMES", default_names))
output_is_list = tuple(getattr(node_class, "OUTPUT_IS_LIST", (False,) * len(output_types)))
if len(output_names) < len(output_types):
output_names = output_names + default_names[len(output_names) :]
if len(output_is_list) < len(output_types):
output_is_list = output_is_list + (False,) * (len(output_types) - len(output_is_list))
return output_types, output_names[: len(output_types)], output_is_list[: len(output_types)]
def _is_transportable_output_type(io_type: str) -> bool:
"""Return whether a ComfyUI output type can cross the current transport."""
normalized_parts = [part.strip() for part in io_type.split(",") if part.strip()]
return bool(normalized_parts) and all(part in _TRANSPORTABLE_OUTPUT_TYPES for part in normalized_parts)
def _build_consumer_map(prompt: dict[str, Any]) -> dict[LinkedOutputRef, list[InputTarget]]:
"""Build a reverse map from node outputs to downstream prompt inputs."""
consumers: dict[LinkedOutputRef, list[InputTarget]] = defaultdict(list)
for node_id, prompt_node in prompt.items():
for input_name, input_value in (prompt_node.get("inputs") or {}).items():
if not _is_link(input_value):
continue
source = LinkedOutputRef(node_id=str(input_value[0]), output_index=int(input_value[1]))
consumers[source].append(InputTarget(node_id=str(node_id), input_name=str(input_name)))
return consumers
def _build_remote_components(prompt: dict[str, Any], remote_node_ids: set[str]) -> list[list[str]]:
"""Partition remote-marked nodes into connected components."""
adjacency: dict[str, set[str]] = {node_id: set() for node_id in remote_node_ids}
for node_id in remote_node_ids:
prompt_node = prompt.get(node_id)
if prompt_node is None:
continue
for input_value in (prompt_node.get("inputs") or {}).values():
if not _is_link(input_value):
continue
upstream_node_id = str(input_value[0])
if upstream_node_id not in remote_node_ids:
continue
adjacency[node_id].add(upstream_node_id)
adjacency[upstream_node_id].add(node_id)
components: list[list[str]] = []
visited: set[str] = set()
for node_id in sorted(remote_node_ids):
if node_id in visited:
continue
pending = [node_id]
component: list[str] = []
while pending:
current = pending.pop()
if current in visited:
continue
visited.add(current)
component.append(current)
pending.extend(sorted(adjacency[current] - visited))
components.append(sorted(component))
logger.info(
"Partitioned %d remote nodes into %d remote components: %s",
len(remote_node_ids),
len(components),
components,
)
return components
def _expand_remote_node_ids_for_non_transportable_inputs(
prompt: dict[str, Any],
remote_node_ids: set[str],
nodes_module: Any,
) -> set[str]:
"""Grow the remote set upstream until non-transportable inputs stay inside the remote island."""
expanded_remote_node_ids = set(remote_node_ids)
added_node_ids: list[str] = []
changed = True
while changed:
changed = False
for node_id in sorted(expanded_remote_node_ids):
prompt_node = prompt.get(node_id)
if prompt_node is None:
continue
for input_value in (prompt_node.get("inputs") or {}).values():
if not _is_link(input_value):
continue
upstream_node_id = str(input_value[0])
if upstream_node_id in expanded_remote_node_ids:
continue
upstream_prompt_node = prompt.get(upstream_node_id)
if upstream_prompt_node is None:
continue
upstream_class_type = str(upstream_prompt_node["class_type"])
upstream_class = nodes_module.NODE_CLASS_MAPPINGS.get(upstream_class_type)
if upstream_class is None:
continue
output_types, _, _ = _normalize_output_metadata(upstream_class)
output_index = int(input_value[1])
if output_index >= len(output_types):
continue
io_type = str(output_types[output_index])
if _is_transportable_output_type(io_type):
continue
expanded_remote_node_ids.add(upstream_node_id)
added_node_ids.append(upstream_node_id)
changed = True
logger.info(
"Auto-expanded remote execution upstream: added node %s (%s) because node %s depends on non-transportable type '%s'.",
upstream_node_id,
upstream_class_type,
node_id,
io_type,
)
break
if changed:
break
if added_node_ids:
logger.info(
"Expanded remote node set from %d to %d nodes by absorbing upstream non-transportable dependencies: %s",
len(remote_node_ids),
len(expanded_remote_node_ids),
sorted(set(added_node_ids)),
)
return expanded_remote_node_ids
def _build_component_plan(
component_node_ids: list[str],
prompt: dict[str, Any],
consumers: dict[LinkedOutputRef, list[InputTarget]],
nodes_module: Any,
) -> RemoteComponentPlan:
"""Build rewrite metadata for a connected remote component."""
component_node_id_set = set(component_node_ids)
representative_node_id = component_node_ids[0]
boundary_inputs_by_source: dict[LinkedOutputRef, BoundaryInputSpec] = {}
boundary_outputs_by_source: dict[LinkedOutputRef, BoundaryOutputSpec] = {}
output_execution_targets: set[str] = set()
contains_output_node = False
for node_id in component_node_ids:
prompt_node = prompt[node_id]
class_type = str(prompt_node["class_type"])
node_class = nodes_module.NODE_CLASS_MAPPINGS[class_type]
output_types, output_names, output_is_list = _normalize_output_metadata(node_class)
if getattr(node_class, "OUTPUT_NODE", False):
contains_output_node = True
output_execution_targets.add(node_id)
for input_name, input_value in (prompt_node.get("inputs") or {}).items():
if not _is_link(input_value):
continue
upstream_node_id = str(input_value[0])
if upstream_node_id in component_node_id_set:
continue
source = LinkedOutputRef(node_id=upstream_node_id, output_index=int(input_value[1]))
spec = boundary_inputs_by_source.get(source)
if spec is None:
spec = BoundaryInputSpec(
proxy_input_name=f"remote_input_{len(boundary_inputs_by_source)}",
source=source,
)
boundary_inputs_by_source[source] = spec
spec.targets.append(InputTarget(node_id=node_id, input_name=str(input_name)))
for output_index, io_type in enumerate(output_types):
source = LinkedOutputRef(node_id=node_id, output_index=output_index)
local_consumers = [
consumer for consumer in consumers.get(source, []) if consumer.node_id not in component_node_id_set
]
if not local_consumers:
continue
output_execution_targets.add(node_id)
if source in boundary_outputs_by_source:
continue
output_name = output_names[output_index]
boundary_outputs_by_source[source] = BoundaryOutputSpec(
proxy_output_name=f"{node_id}_{output_name}",
source=source,
io_type=str(io_type),
is_list=bool(output_is_list[output_index]),
)
component = RemoteComponentPlan(
node_ids=component_node_ids,
representative_node_id=representative_node_id,
boundary_inputs=sorted(
boundary_inputs_by_source.values(),
key=lambda spec: (spec.source.node_id, spec.source.output_index),
),
boundary_outputs=sorted(
boundary_outputs_by_source.values(),
key=lambda spec: (spec.source.node_id, spec.source.output_index),
),
execute_node_ids=sorted(output_execution_targets),
contains_output_node=contains_output_node,
)
logger.info(
"Planned remote component %s: nodes=%s boundary_inputs=%d boundary_outputs=%d execute_nodes=%s output_node=%s",
component.representative_node_id,
component.node_ids,
len(component.boundary_inputs),
len(component.boundary_outputs),
component.execute_node_ids,
component.contains_output_node,
)
return component
def _build_component_plans(
prompt: dict[str, Any],
remote_node_ids: set[str],
nodes_module: Any,
) -> list[RemoteComponentPlan]:
"""Build plans for every connected remote component."""
consumers = _build_consumer_map(prompt)
components = _build_remote_components(prompt, remote_node_ids)
return [
_build_component_plan(component, prompt, consumers, nodes_module)
for component in components
]
def _describe_output_boundary_error(
component: RemoteComponentPlan,
source: LinkedOutputRef,
source_class_type: str,
io_type: str,
local_consumer: InputTarget,
local_consumer_class_type: str,
) -> str:
"""Format a human-readable remote-to-local transport validation error."""
return (
"Remote component rooted at node "
f"{component.representative_node_id} exports node {source.node_id} "
f"({source_class_type}) output index {source.output_index} of type '{io_type}' "
f"to local node {local_consumer.node_id} ({local_consumer_class_type}) input "
f"'{local_consumer.input_name}', which cannot cross the current local/remote boundary. "
"Current ComfyUI-Modal transport only supports JSON-compatible values, bytes, "
"and tensor-like outputs such as IMAGE, MASK, LATENT, SIGMAS, NOISE, INT, "
"FLOAT, BOOLEAN, and STRING."
)
def _describe_input_boundary_error(
component: RemoteComponentPlan,
target: InputTarget,
target_class_type: str,
source: LinkedOutputRef,
source_class_type: str,
io_type: str,
) -> str:
"""Format a human-readable local-to-remote transport validation error."""
return (
"Remote node "
f"{target.node_id} ({target_class_type}) input '{target.input_name}' "
f"depends on upstream node {source.node_id} ({source_class_type}) output index "
f"{source.output_index} of type '{io_type}', which cannot cross the current "
"local/remote boundary. Current ComfyUI-Modal transport only supports "
"JSON-compatible values, bytes, and tensor-like outputs such as IMAGE, MASK, "
"LATENT, SIGMAS, NOISE, INT, FLOAT, BOOLEAN, and STRING."
)
def validate_remote_component_transport_compatibility(
prompt: dict[str, Any],
components: list[RemoteComponentPlan],
nodes_module: Any,
) -> None:
"""Reject remote components whose true graph boundaries require unsupported transport."""
validation_errors: list[str] = []
consumers = _build_consumer_map(prompt)
logger.info("Validating %d remote components for transport compatibility.", len(components))
for component in components:
for boundary_input in component.boundary_inputs:
source_prompt_node = prompt.get(boundary_input.source.node_id)
if source_prompt_node is None:
continue
source_class_type = str(source_prompt_node["class_type"])
source_class = nodes_module.NODE_CLASS_MAPPINGS.get(source_class_type)
if source_class is None:
continue
source_output_types, _, _ = _normalize_output_metadata(source_class)
if boundary_input.source.output_index >= len(source_output_types):
continue
io_type = str(source_output_types[boundary_input.source.output_index])
if _is_transportable_output_type(io_type):
continue
for target in boundary_input.targets:
target_class_type = str(prompt[target.node_id]["class_type"])
validation_errors.append(
_describe_input_boundary_error(
component=component,
target=target,
target_class_type=target_class_type,
source=boundary_input.source,
source_class_type=source_class_type,
io_type=io_type,
)
)
for boundary_output in component.boundary_outputs:
if _is_transportable_output_type(boundary_output.io_type):
continue
source_class_type = str(prompt[boundary_output.source.node_id]["class_type"])
for local_consumer in consumers.get(boundary_output.source, []):
if local_consumer.node_id in component.node_ids:
continue
local_consumer_class_type = str(prompt[local_consumer.node_id]["class_type"])
validation_errors.append(
_describe_output_boundary_error(
component=component,
source=boundary_output.source,
source_class_type=source_class_type,
io_type=boundary_output.io_type,
local_consumer=local_consumer,
local_consumer_class_type=local_consumer_class_type,
)
)
if validation_errors:
raise ModalPromptValidationError("\n".join(validation_errors))
logger.info("Remote component transport validation passed.")
def _sync_component_prompt_inputs(
component: RemoteComponentPlan,
rewritten_prompt: dict[str, Any],
sync_engine: ModalAssetSyncEngine,
) -> tuple[dict[str, Any], list[SyncedAsset]]:
"""Build a synced prompt payload for one remote component."""
component_prompt: dict[str, Any] = {}
synced_assets: list[SyncedAsset] = []
logger.info(
"Syncing prompt inputs for remote component %s with %d nodes.",
component.representative_node_id,
len(component.node_ids),
)
for node_id in component.node_ids:
prompt_node = rewritten_prompt[node_id]
synced_inputs, node_assets = sync_engine.sync_prompt_inputs(copy.deepcopy(prompt_node.get("inputs", {})))
synced_assets.extend(node_assets)
component_prompt[node_id] = {
"class_type": str(prompt_node["class_type"]),
"inputs": synced_inputs,
"_meta": copy.deepcopy(prompt_node.get("_meta", {})),
}
logger.info(
"Prepared remote node %s (%s) with %d synced assets.",
node_id,
component_prompt[node_id]["class_type"],
len(node_assets),
)
logger.info(
"Finished syncing remote component %s with %d total synced assets.",
component.representative_node_id,
len(synced_assets),
)
return component_prompt, synced_assets
def _build_component_payload(
component: RemoteComponentPlan,
component_prompt: dict[str, Any],
extra_data: dict[str, Any] | None,
synced_assets: list[SyncedAsset],
custom_nodes_bundle: SyncedAsset | None,
) -> dict[str, Any]:
"""Build the serialized execution payload for one remote component."""
requires_volume_reload = any(asset.uploaded for asset in synced_assets) or (
custom_nodes_bundle is not None and custom_nodes_bundle.uploaded
)
payload = {
"payload_kind": "subgraph",
"component_id": component.representative_node_id,
"prompt_id": (extra_data or {}).get("prompt_id"),
"component_node_ids": list(component.node_ids),
"subgraph_prompt": component_prompt,
"boundary_inputs": [
{
"proxy_input_name": boundary_input.proxy_input_name,
"targets": [
{"node_id": target.node_id, "input_name": target.input_name}
for target in boundary_input.targets
],
}
for boundary_input in component.boundary_inputs
],
"boundary_outputs": [
{
"proxy_output_name": boundary_output.proxy_output_name,
"node_id": boundary_output.source.node_id,
"output_index": boundary_output.source.output_index,
"io_type": boundary_output.io_type,
"is_list": boundary_output.is_list,
}
for boundary_output in component.boundary_outputs
],
"execute_node_ids": list(component.execute_node_ids),
"extra_data": copy.deepcopy(extra_data or {}),
"requires_volume_reload": requires_volume_reload,
"custom_nodes_bundle": (
custom_nodes_bundle.remote_path if custom_nodes_bundle is not None else None
),
}
logger.info(
"Built remote payload for component %s: boundary_inputs=%d boundary_outputs=%d execute_nodes=%s",
component.representative_node_id,
len(payload["boundary_inputs"]),
len(payload["boundary_outputs"]),
payload["execute_node_ids"],
)
logger.info(
"Remote payload for component %s requires_volume_reload=%s",
component.representative_node_id,
requires_volume_reload,
)
return payload
def _rewrite_component_into_proxy(
component: RemoteComponentPlan,
rewritten_prompt: dict[str, Any],
payload: dict[str, Any],
nodes_module: Any,
) -> str:
"""Replace a remote component with a single proxy node in the prompt."""
output_types = tuple(spec.io_type for spec in component.boundary_outputs)
output_names = tuple(spec.proxy_output_name for spec in component.boundary_outputs)
output_is_list = tuple(spec.is_list for spec in component.boundary_outputs)
proxy_node_id = ensure_modal_component_proxy_node_registered(
output_types=output_types,
output_names=output_names,
output_is_list=output_is_list,
nodes_module=nodes_module,
is_output_node=component.contains_output_node,
)
proxy_inputs: dict[str, Any] = {
boundary_input.proxy_input_name: [boundary_input.source.node_id, boundary_input.source.output_index]
for boundary_input in component.boundary_inputs
}
proxy_inputs["original_node_data"] = payload
representative_node_id = component.representative_node_id
representative_meta = copy.deepcopy(rewritten_prompt[representative_node_id].get("_meta", {}))
rewritten_prompt[representative_node_id] = {
"class_type": proxy_node_id,
"inputs": proxy_inputs,
"_meta": representative_meta,
}
boundary_output_indices = {
spec.source: index for index, spec in enumerate(component.boundary_outputs)
}
component_node_id_set = set(component.node_ids)
for node_id, prompt_node in list(rewritten_prompt.items()):
if node_id in component_node_id_set and node_id != representative_node_id:
del rewritten_prompt[node_id]
continue
if node_id == representative_node_id:
continue
for input_name, input_value in list((prompt_node.get("inputs") or {}).items()):
if not _is_link(input_value):
continue
source = LinkedOutputRef(node_id=str(input_value[0]), output_index=int(input_value[1]))
if source not in boundary_output_indices:
continue
prompt_node["inputs"][input_name] = [representative_node_id, boundary_output_indices[source]]
logger.info(
"Rewrote remote component %s with %d nodes to Modal proxy %s.",
representative_node_id,
len(component.node_ids),
proxy_node_id,
)
return representative_node_id
def rewrite_prompt_for_modal(
prompt: dict[str, Any],
workflow: dict[str, Any] | None,
sync_engine: ModalAssetSyncEngine | None = None,
settings: ModalSyncSettings | None = None,
nodes_module: Any | None = None,
extra_data: dict[str, Any] | None = None,
) -> tuple[dict[str, Any], RewriteSummary]:
"""Rewrite connected remote components into Modal proxy nodes."""
resolved_settings = settings or get_settings()
remote_node_ids = extract_remote_node_ids(workflow, resolved_settings)
summary = RewriteSummary(remote_node_ids=sorted(remote_node_ids))
logger.info("Found %d workflow nodes marked for Modal execution.", len(remote_node_ids))
if not remote_node_ids:
return copy.deepcopy(prompt), summary
resolved_nodes_module = nodes_module or _get_nodes_module()
resolved_sync_engine = sync_engine or ModalAssetSyncEngine.from_environment(resolved_settings)
rewritten_prompt = copy.deepcopy(prompt)
expanded_remote_node_ids = _expand_remote_node_ids_for_non_transportable_inputs(
prompt=rewritten_prompt,
remote_node_ids=remote_node_ids,
nodes_module=resolved_nodes_module,
)
summary.remote_node_ids = sorted(expanded_remote_node_ids)
components = _build_component_plans(
rewritten_prompt,
expanded_remote_node_ids,
resolved_nodes_module,
)
validate_remote_component_transport_compatibility(
prompt=rewritten_prompt,
components=components,
nodes_module=resolved_nodes_module,
)
if resolved_settings.sync_custom_nodes:
summary.custom_nodes_bundle = resolved_sync_engine.sync_custom_nodes_directory()
else:
logger.info(
"Skipping custom_nodes bundle sync because sync is disabled for execution_mode=%s.",
resolved_settings.execution_mode,
)
for component in components:
summary.remote_component_ids.append(component.representative_node_id)
summary.component_node_ids_by_representative[component.representative_node_id] = list(
component.node_ids
)
for node_id in component.node_ids:
summary.rewritten_node_id_map[node_id] = component.representative_node_id
logger.info(
"Rewriting remote component %s covering nodes %s.",
component.representative_node_id,
component.node_ids,
)
component_prompt, synced_assets = _sync_component_prompt_inputs(
component=component,
rewritten_prompt=rewritten_prompt,
sync_engine=resolved_sync_engine,
)
summary.synced_assets.extend(synced_assets)
payload = _build_component_payload(
component=component,
component_prompt=component_prompt,
extra_data=extra_data,
synced_assets=synced_assets,
custom_nodes_bundle=summary.custom_nodes_bundle,
)
_rewrite_component_into_proxy(
component=component,
rewritten_prompt=rewritten_prompt,
payload=payload,
nodes_module=resolved_nodes_module,
)
return rewritten_prompt, summary
async def _queue_prompt_json(prompt_server: Any, json_data: dict[str, Any]) -> web.Response:
"""Queue a possibly rewritten prompt using ComfyUI's native semantics."""
execution = _get_execution_module()
json_data = prompt_server.trigger_on_prompt(json_data)
if "number" in json_data:
number = float(json_data["number"])
else:
number = prompt_server.number
if json_data.get("front"):
number = -number
prompt_server.number += 1
if "prompt" not in json_data:
return web.json_response(
{
"error": {
"type": "no_prompt",
"message": "No prompt provided",
"details": "No prompt provided",
"extra_info": {},
}
},
status=400,
)
prompt = json_data["prompt"]
prompt_id = str(json_data.get("prompt_id", uuid.uuid4()))
partial_execution_targets = json_data.get("partial_execution_targets")
valid = await execution.validate_prompt(prompt_id, prompt, partial_execution_targets)
extra_data = dict(json_data.get("extra_data", {}))
if "client_id" in json_data:
extra_data["client_id"] = json_data["client_id"]
if not valid[0]:
logger.warning("invalid prompt: %s", valid[1])
return web.json_response({"error": valid[1], "node_errors": valid[3]}, status=400)
outputs_to_execute = valid[2]
sensitive: dict[str, Any] = {}
for sensitive_key in execution.SENSITIVE_EXTRA_DATA_KEYS:
if sensitive_key in extra_data:
sensitive[sensitive_key] = extra_data.pop(sensitive_key)
extra_data["create_time"] = int(time.time() * 1000)
prompt_server.prompt_queue.put(
(number, prompt_id, prompt, extra_data, outputs_to_execute, sensitive)
)
return web.json_response(
{"prompt_id": prompt_id, "number": number, "node_errors": valid[3]}
)
def setup_modal_queue_route(
prompt_server: Any | None = None,
sync_engine: ModalAssetSyncEngine | None = None,
settings: ModalSyncSettings | None = None,
) -> None:
"""Register the `/modal/queue_prompt` route once for the active PromptServer."""
global _ROUTE_REGISTERED
if _ROUTE_REGISTERED:
return
try:
resolved_server_module = _get_server_module()
except ModuleNotFoundError:
logger.debug("ComfyUI server module is not available; skipping route registration.")
return
resolved_settings = settings or get_settings()
prompt_server = prompt_server or getattr(resolved_server_module.PromptServer, "instance", None)
if prompt_server is None:
logger.debug("PromptServer.instance is not available; skipping route registration.")
return
resolved_sync_engine = sync_engine or ModalAssetSyncEngine.from_environment(resolved_settings)
@prompt_server.routes.post(resolved_settings.route_path)
async def modal_queue_prompt(request: web.Request) -> web.Response:
"""Handle prompt queue requests that include Modal remote markers."""
logger.info("Received Modal queue request.")
json_data: dict[str, Any] | None = None
workflow: dict[str, Any] | None = None
remote_node_ids: list[str] = []
summary = RewriteSummary()
try:
request_started_at = time.perf_counter()
json_data = await request.json()
json_data.setdefault("prompt_id", str(uuid.uuid4()))
json_data.setdefault("extra_data", {})
json_data["extra_data"]["prompt_id"] = json_data["prompt_id"]
if json_data.get("client_id") is not None:
json_data["extra_data"]["client_id"] = json_data["client_id"]
extra_pnginfo = ((json_data.get("extra_data") or {}).get("extra_pnginfo") or {})
workflow = extra_pnginfo.get("workflow")
remote_node_ids = sorted(extract_remote_node_ids(workflow, resolved_settings))
if "prompt" in json_data:
rewrite_started_at = time.perf_counter()
rewritten_prompt, summary = rewrite_prompt_for_modal(
prompt=json_data["prompt"],
workflow=workflow,
sync_engine=resolved_sync_engine,
settings=resolved_settings,
extra_data=json_data.get("extra_data"),
)
logger.info(
"Modal prompt rewrite finished in %.3fs for %d remote nodes across %d components.",
time.perf_counter() - rewrite_started_at,
len(summary.remote_node_ids),
len(summary.remote_component_ids),
)
remote_node_ids = list(summary.remote_node_ids)
json_data["prompt"] = rewritten_prompt
if json_data.get("partial_execution_targets"):
rewritten_targets = {
summary.rewritten_node_id_map.get(str(target), str(target))
for target in json_data["partial_execution_targets"]
}
json_data["partial_execution_targets"] = sorted(rewritten_targets)
json_data.setdefault("extra_data", {}).setdefault("modal", {})
json_data["extra_data"]["modal"]["remote_node_ids"] = summary.remote_node_ids
json_data["extra_data"]["modal"]["remote_component_ids"] = summary.remote_component_ids
json_data["extra_data"]["modal"]["synced_assets"] = [
asset.remote_path for asset in summary.synced_assets
]
if summary.custom_nodes_bundle is not None:
json_data["extra_data"]["modal"]["custom_nodes_bundle"] = (
summary.custom_nodes_bundle.remote_path
)
_emit_modal_status(
prompt_server=prompt_server,
phase="setup",
client_id=str(json_data.get("client_id")) if json_data.get("client_id") else None,
prompt_id=str(json_data.get("prompt_id")) if json_data.get("prompt_id") else None,
node_ids=remote_node_ids,
component_node_ids_by_representative=summary.component_node_ids_by_representative,
)
response = await _queue_prompt_json(prompt_server, json_data)
logger.info(
"Modal queue request completed in %.3fs.",
time.perf_counter() - request_started_at,
)
return response
except FileNotFoundError as exc:
logger.exception("Modal asset sync failed.")
if json_data is not None:
_emit_modal_status(
prompt_server=prompt_server,
phase="error",
client_id=str(json_data.get("client_id")) if json_data.get("client_id") else None,
prompt_id=str(json_data.get("prompt_id")) if json_data.get("prompt_id") else None,
node_ids=remote_node_ids,
error_message=str(exc),
)
return web.json_response({"error": str(exc), "node_errors": []}, status=400)
except ModalPromptValidationError as exc:
logger.exception("Modal prompt validation failed.")
if json_data is not None:
_emit_modal_status(
prompt_server=prompt_server,
phase="error",
client_id=str(json_data.get("client_id")) if json_data.get("client_id") else None,
prompt_id=str(json_data.get("prompt_id")) if json_data.get("prompt_id") else None,
node_ids=remote_node_ids,
error_message=str(exc),
)
return web.json_response({"error": str(exc), "node_errors": []}, status=400)
except Exception as exc:
logger.exception("Modal queue handler failed.")
if json_data is not None:
_emit_modal_status(
prompt_server=prompt_server,
phase="error",
client_id=str(json_data.get("client_id")) if json_data.get("client_id") else None,
prompt_id=str(json_data.get("prompt_id")) if json_data.get("prompt_id") else None,
node_ids=remote_node_ids,
error_message=str(exc),
)
return web.json_response({"error": str(exc), "node_errors": []}, status=500)
_ROUTE_REGISTERED = True
logger.info("Registered Modal queue route at %s", resolved_settings.route_path)