Jacob Segal 46c8311d14 Support for async execution functions
This commit adds support for node execution functions defined as async. When
a node's execution function is defined as async, we can continue
executing other nodes while it is processing.

Standard uses of `await` should "just work", but people will still have
to be careful if they spawn actual threads. Because torch doesn't really
have async/await versions of functions, this won't particularly help
with most locally-executing nodes, but it does work for e.g. web
requests to other machines.

In addition to the execute function, the `VALIDATE_INPUTS` and
`check_lazy_status` functions can also be defined as async, though we'll
only resolve one node at a time right now for those.
2025-07-01 14:41:52 -07:00

47 lines
1.5 KiB
Python

import contextvars
from typing import Optional, NamedTuple
class ExecutionContext(NamedTuple):
"""
Context information about the currently executing node.
Attributes:
node_id: The ID of the currently executing node
list_index: The index in a list being processed (for operations on batches/lists)
"""
prompt_id: str
node_id: str
list_index: Optional[int]
current_executing_context: contextvars.ContextVar[Optional[ExecutionContext]] = contextvars.ContextVar("current_executing_context", default=None)
def get_executing_context() -> Optional[ExecutionContext]:
return current_executing_context.get(None)
class CurrentNodeContext:
"""
Context manager for setting the current executing node context.
Sets the current_executing_context on enter and resets it on exit.
Example:
with CurrentNodeContext(node_id="123", list_index=0):
# Code that should run with the current node context set
process_image()
"""
def __init__(self, prompt_id: str, node_id: str, list_index: Optional[int] = None):
self.context = ExecutionContext(
prompt_id= prompt_id,
node_id= node_id,
list_index= list_index
)
self.token = None
def __enter__(self):
self.token = current_executing_context.set(self.context)
return self
def __exit__(self, exc_type, exc_val, exc_tb):
if self.token is not None:
current_executing_context.reset(self.token)