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341c9f2e90
ComfyUI/comfy/cmd/execution.py
doctorpangloss 341c9f2e90 Improvements to node loading, node API, folder paths and progress 
- Improve node loading order. It now occurs "as late as possible".
   Configuration should be exposed as per the README.
 - Added methods to specify custom folders and models used in examples
   more robustly for custom nodes.
 - Downloading models can now be gracefully interrupted.
 - Progress notifications are now sent over the network for distributed
   ComfyUI operations.
 - Python objects have been moved around to prevent less transitive
   package importing issues.
2024-03-13 16:14:18 -07:00

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from __future__ import annotations
import copy
import heapq
import inspect
import logging
import sys
import threading
import traceback
import typing
from typing import List, Optional, Tuple, Union
from typing_extensions import TypedDict
import torch
import lazy_object_proxy
from .. import interruption
from ..component_model.abstract_prompt_queue import AbstractPromptQueue
from ..component_model.queue_types import QueueTuple, HistoryEntry, QueueItem, MAXIMUM_HISTORY_SIZE, ExecutionStatus
from ..component_model.executor_types import ExecutorToClientProgress
from .. import model_management
from ..nodes.package_typing import ExportedNodes
from ..nodes.package import import_all_nodes_in_workspace
# ideally this would be passed in from main, but the way this is authored, we can't easily pass nodes down to the
# various functions that are declared here. It should have been a context in the first place.
nodes: ExportedNodes = lazy_object_proxy.Proxy(import_all_nodes_in_workspace)
def get_input_data(inputs, class_def, unique_id, outputs=None, prompt=None, extra_data=None):
if extra_data is None:
extra_data = {}
if prompt is None:
prompt = {}
if outputs is None:
outputs = {}
valid_inputs = class_def.INPUT_TYPES()
input_data_all = {}
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
input_data_all[x] = (None,)
continue
obj = outputs[input_unique_id][output_index]
input_data_all[x] = obj
else:
if ("required" in valid_inputs and x in valid_inputs["required"]) or (
"optional" in valid_inputs and x in valid_inputs["optional"]):
input_data_all[x] = [input_data]
if "hidden" in valid_inputs:
h = valid_inputs["hidden"]
for x in h:
if h[x] == "PROMPT":
input_data_all[x] = [prompt]
if h[x] == "EXTRA_PNGINFO":
input_data_all[x] = [extra_data.get('extra_pnginfo', None)]
if h[x] == "UNIQUE_ID":
input_data_all[x] = [unique_id]
return input_data_all
def map_node_over_list(obj, input_data_all, func, allow_interrupt=False):
# check if node wants the lists
input_is_list = False
if hasattr(obj, "INPUT_IS_LIST"):
input_is_list = obj.INPUT_IS_LIST
if len(input_data_all) == 0:
max_len_input = 0
else:
max_len_input = max([len(x) for x in input_data_all.values()])
# get a slice of inputs, repeat last input when list isn't long enough
def slice_dict(d, i):
d_new = dict()
for k, v in d.items():
d_new[k] = v[i if len(v) > i else -1]
return d_new
results = []
if input_is_list:
if allow_interrupt:
interruption.throw_exception_if_processing_interrupted()
results.append(getattr(obj, func)(**input_data_all))
elif max_len_input == 0:
if allow_interrupt:
interruption.throw_exception_if_processing_interrupted()
results.append(getattr(obj, func)())
else:
for i in range(max_len_input):
if allow_interrupt:
interruption.throw_exception_if_processing_interrupted()
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
return results
def get_output_data(obj, input_data_all):
results = []
uis = []
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
for r in return_values:
if isinstance(r, dict):
if 'ui' in r:
uis.append(r['ui'])
if 'result' in r:
results.append(r['result'])
else:
results.append(r)
output = []
if len(results) > 0:
# check which outputs need concatenating
output_is_list = [False] * len(results[0])
if hasattr(obj, "OUTPUT_IS_LIST"):
output_is_list = obj.OUTPUT_IS_LIST
# merge node execution results
for i, is_list in zip(range(len(results[0])), output_is_list):
if is_list:
output.append([x for o in results for x in o[i]])
else:
output.append([o[i] for o in results])
ui = dict()
if len(uis) > 0:
ui = {k: [y for x in uis for y in x[k]] for k in uis[0].keys()}
return output, ui
def format_value(x):
if x is None:
return None
elif isinstance(x, (int, float, bool, str)):
return x
else:
return str(x)
def recursive_execute(server: ExecutorToClientProgress,
prompt,
outputs,
current_item,
extra_data,
executed,
prompt_id,
outputs_ui,
object_storage):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
if unique_id in outputs:
return (True, None, None)
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
result = recursive_execute(server, prompt, outputs, input_unique_id, extra_data, executed, prompt_id,
outputs_ui, object_storage)
if result[0] is not True:
# Another node failed further upstream
return result
input_data_all = None
try:
input_data_all = get_input_data(inputs, class_def, unique_id, outputs, prompt, extra_data)
if server.client_id is not None:
server.last_node_id = unique_id
server.send_sync("executing", {"node": unique_id, "prompt_id": prompt_id}, server.client_id)
obj = object_storage.get((unique_id, class_type), None)
if obj is None:
obj = class_def()
object_storage[(unique_id, class_type)] = obj
output_data, output_ui = get_output_data(obj, input_data_all)
outputs[unique_id] = output_data
if len(output_ui) > 0:
outputs_ui[unique_id] = output_ui
if server.client_id is not None:
server.send_sync("executed", {"node": unique_id, "output": output_ui, "prompt_id": prompt_id},
server.client_id)
except interruption.InterruptProcessingException as iex:
logging.info("Processing interrupted")
# skip formatting inputs/outputs
error_details = {
"node_id": unique_id,
}
return (False, error_details, iex)
except Exception as ex:
typ, _, tb = sys.exc_info()
exception_type = full_type_name(typ)
input_data_formatted = {}
if input_data_all is not None:
input_data_formatted = {}
for name, inputs in input_data_all.items():
input_data_formatted[name] = [format_value(x) for x in inputs]
output_data_formatted = {}
for node_id, node_outputs in outputs.items():
output_data_formatted[node_id] = [[format_value(x) for x in l] for l in node_outputs]
logging.error("!!! Exception during processing !!!")
logging.error(traceback.format_exc())
error_details = {
"node_id": unique_id,
"exception_message": str(ex),
"exception_type": exception_type,
"traceback": traceback.format_tb(tb),
"current_inputs": input_data_formatted,
"current_outputs": output_data_formatted
}
return (False, error_details, ex)
executed.add(unique_id)
return (True, None, None)
def recursive_will_execute(prompt, outputs, current_item, memo={}):
unique_id = current_item
if unique_id in memo:
return memo[unique_id]
inputs = prompt[unique_id]['inputs']
will_execute = []
if unique_id in outputs:
return []
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id not in outputs:
will_execute += recursive_will_execute(prompt, outputs, input_unique_id, memo)
memo[unique_id] = will_execute + [unique_id]
return memo[unique_id]
def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item):
unique_id = current_item
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
class_def = nodes.NODE_CLASS_MAPPINGS[class_type]
is_changed_old = ''
is_changed = ''
to_delete = False
if hasattr(class_def, 'IS_CHANGED'):
if unique_id in old_prompt and 'is_changed' in old_prompt[unique_id]:
is_changed_old = old_prompt[unique_id]['is_changed']
if 'is_changed' not in prompt[unique_id]:
input_data_all = get_input_data(inputs, class_def, unique_id, outputs)
if input_data_all is not None:
try:
# is_changed = class_def.IS_CHANGED(**input_data_all)
is_changed = map_node_over_list(class_def, input_data_all, "IS_CHANGED")
prompt[unique_id]['is_changed'] = is_changed
except:
to_delete = True
else:
is_changed = prompt[unique_id]['is_changed']
if unique_id not in outputs:
return True
if not to_delete:
if is_changed != is_changed_old:
to_delete = True
elif unique_id not in old_prompt:
to_delete = True
elif inputs == old_prompt[unique_id]['inputs']:
for x in inputs:
input_data = inputs[x]
if isinstance(input_data, list):
input_unique_id = input_data[0]
output_index = input_data[1]
if input_unique_id in outputs:
to_delete = recursive_output_delete_if_changed(prompt, old_prompt, outputs, input_unique_id)
else:
to_delete = True
if to_delete:
break
else:
to_delete = True
if to_delete:
d = outputs.pop(unique_id)
del d
return to_delete
class PromptExecutor:
def __init__(self, server: ExecutorToClientProgress):
self.success = None
self.server = server
self.reset()
def reset(self):
self.outputs = {}
self.object_storage = {}
self.outputs_ui = {}
self.status_messages = []
self.success = True
self.old_prompt = {}
def add_message(self, event, data, broadcast: bool):
self.status_messages.append((event, data))
if self.server.client_id is not None or broadcast:
self.server.send_sync(event, data, self.server.client_id)
def handle_execution_error(self, prompt_id, prompt, current_outputs, executed, error, ex):
node_id = error["node_id"]
class_type = prompt[node_id]["class_type"]
# First, send back the status to the frontend depending
# on the exception type
if isinstance(ex, interruption.InterruptProcessingException):
mes = {
"prompt_id": prompt_id,
"node_id": node_id,
"node_type": class_type,
"executed": list(executed),
}
self.add_message("execution_interrupted", mes, broadcast=True)
else:
mes = {
"prompt_id": prompt_id,
"node_id": node_id,
"node_type": class_type,
"executed": list(executed),
"exception_message": error["exception_message"],
"exception_type": error["exception_type"],
"traceback": error["traceback"],
"current_inputs": error["current_inputs"],
"current_outputs": error["current_outputs"],
}
self.add_message("execution_error", mes, broadcast=False)
# Next, remove the subsequent outputs since they will not be executed
to_delete = []
for o in self.outputs:
if (o not in current_outputs) and (o not in executed):
to_delete += [o]
if o in self.old_prompt:
d = self.old_prompt.pop(o)
del d
for o in to_delete:
d = self.outputs.pop(o)
del d
def execute(self, prompt, prompt_id, extra_data=None, execute_outputs: List[str] = None):
if execute_outputs is None:
execute_outputs = []
if extra_data is None:
extra_data = {}
interruption.interrupt_current_processing(False)
if "client_id" in extra_data:
self.server.client_id = extra_data["client_id"]
else:
self.server.client_id = None
self.status_messages = []
self.add_message("execution_start", {"prompt_id": prompt_id}, broadcast=False)
with torch.inference_mode():
# delete cached outputs if nodes don't exist for them
to_delete = []
for o in self.outputs:
if o not in prompt:
to_delete += [o]
for o in to_delete:
d = self.outputs.pop(o)
del d
to_delete = []
for o in self.object_storage:
if o[0] not in prompt:
to_delete += [o]
else:
p = prompt[o[0]]
if o[1] != p['class_type']:
to_delete += [o]
for o in to_delete:
d = self.object_storage.pop(o)
del d
for x in prompt:
recursive_output_delete_if_changed(prompt, self.old_prompt, self.outputs, x)
current_outputs = set(self.outputs.keys())
for x in list(self.outputs_ui.keys()):
if x not in current_outputs:
d = self.outputs_ui.pop(x)
del d
model_management.cleanup_models()
self.add_message("execution_cached",
{"nodes": list(current_outputs), "prompt_id": prompt_id},
broadcast=False)
executed = set()
output_node_id = None
to_execute = []
for node_id in list(execute_outputs):
to_execute += [(0, node_id)]
while len(to_execute) > 0:
# always execute the output that depends on the least amount of unexecuted nodes first
memo = {}
to_execute = sorted(list(
map(lambda a: (len(recursive_will_execute(prompt, self.outputs, a[-1], memo)), a[-1]), to_execute)))
output_node_id = to_execute.pop(0)[-1]
# This call shouldn't raise anything if there's an error deep in
# the actual SD code, instead it will report the node where the
# error was raised
# todo: if we're using a distributed queue, we must wrap the server instance to correctly communicate back to the client via the exchange
self.success, error, ex = recursive_execute(self.server, prompt, self.outputs, output_node_id,
extra_data, executed, prompt_id, self.outputs_ui,
self.object_storage)
if self.success is not True:
self.handle_execution_error(prompt_id, prompt, current_outputs, executed, error, ex)
break
for x in executed:
self.old_prompt[x] = copy.deepcopy(prompt[x])
self.server.last_node_id = None
if model_management.DISABLE_SMART_MEMORY:
model_management.unload_all_models()
def validate_inputs(prompt, item, validated) -> Tuple[bool, typing.List[dict], typing.Any]:
# todo: this should check if LoadImage / LoadImageMask paths exist
# todo: or, nodes should provide a way to validate their values
unique_id = item
if unique_id in validated:
return validated[unique_id]
inputs = prompt[unique_id]['inputs']
class_type = prompt[unique_id]['class_type']
obj_class = nodes.NODE_CLASS_MAPPINGS[class_type]
class_inputs = obj_class.INPUT_TYPES()
required_inputs = class_inputs['required']
errors = []
valid = True
# todo: investigate if these are at the right indent level
info = None
val = None
validate_function_inputs = []
if hasattr(obj_class, "VALIDATE_INPUTS"):
validate_function_inputs = inspect.getfullargspec(obj_class.VALIDATE_INPUTS).args
for x in required_inputs:
if x not in inputs:
error = {
"type": "required_input_missing",
"message": "Required input is missing",
"details": f"{x}",
"extra_info": {
"input_name": x
}
}
errors.append(error)
continue
val = inputs[x]
info = required_inputs[x]
type_input = info[0]
if isinstance(val, list):
if len(val) != 2:
error = {
"type": "bad_linked_input",
"message": "Bad linked input, must be a length-2 list of [node_id, slot_index]",
"details": f"{x}",
"extra_info": {
"input_name": x,
"input_config": info,
"received_value": val
}
}
errors.append(error)
continue
o_id = val[0]
o_class_type = prompt[o_id]['class_type']
r = nodes.NODE_CLASS_MAPPINGS[o_class_type].RETURN_TYPES
if r[val[1]] != type_input:
received_type = r[val[1]]
details = f"{x}, {received_type} != {type_input}"
error = {
"type": "return_type_mismatch",
"message": "Return type mismatch between linked nodes",
"details": details,
"extra_info": {
"input_name": x,
"input_config": info,
"received_type": received_type,
"linked_node": val
}
}
errors.append(error)
continue
try:
r2 = validate_inputs(prompt, o_id, validated)
if r2[0] is False:
# `r` will be set in `validated[o_id]` already
valid = False
continue
except Exception as ex:
typ, _, tb = sys.exc_info()
valid = False
exception_type = full_type_name(typ)
reasons = [{
"type": "exception_during_inner_validation",
"message": "Exception when validating inner node",
"details": str(ex),
"extra_info": {
"input_name": x,
"input_config": info,
"exception_message": str(ex),
"exception_type": exception_type,
"traceback": traceback.format_tb(tb),
"linked_node": val
}
}]
validated[o_id] = (False, reasons, o_id)
continue
else:
try:
if type_input == "INT":
val = int(val)
inputs[x] = val
if type_input == "FLOAT":
val = float(val)
inputs[x] = val
if type_input == "STRING":
val = str(val)
inputs[x] = val
except Exception as ex:
error = {
"type": "invalid_input_type",
"message": f"Failed to convert an input value to a {type_input} value",
"details": f"{x}, {val}, {ex}",
"extra_info": {
"input_name": x,
"input_config": info,
"received_value": val,
"exception_message": str(ex)
}
}
errors.append(error)
continue
if len(info) > 1:
if "min" in info[1] and val < info[1]["min"]:
error = {
"type": "value_smaller_than_min",
"message": "Value {} smaller than min of {}".format(val, info[1]["min"]),
"details": f"{x}",
"extra_info": {
"input_name": x,
"input_config": info,
"received_value": val,
}
}
errors.append(error)
continue
if "max" in info[1] and val > info[1]["max"]:
error = {
"type": "value_bigger_than_max",
"message": "Value {} bigger than max of {}".format(val, info[1]["max"]),
"details": f"{x}",
"extra_info": {
"input_name": x,
"input_config": info,
"received_value": val,
}
}
errors.append(error)
continue
if x not in validate_function_inputs:
if isinstance(type_input, list):
if val not in type_input:
input_config = info
list_info = ""
# Don't send back gigantic lists like if they're lots of
# scanned model filepaths
if len(type_input) > 20:
list_info = f"(list of length {len(type_input)})"
input_config = None
else:
list_info = str(type_input)
error = {
"type": "value_not_in_list",
"message": "Value not in list",
"details": f"{x}: '{val}' not in {list_info}",
"extra_info": {
"input_name": x,
"input_config": input_config,
"received_value": val,
}
}
errors.append(error)
continue
if len(validate_function_inputs) > 0:
input_data_all = get_input_data(inputs, obj_class, unique_id)
input_filtered = {}
for x in input_data_all:
if x in validate_function_inputs:
input_filtered[x] = input_data_all[x]
# ret = obj_class.VALIDATE_INPUTS(**input_filtered)
ret = map_node_over_list(obj_class, input_filtered, "VALIDATE_INPUTS")
for x in input_filtered:
for i, r in enumerate(ret):
if r is not True:
details = f"{x}"
if r is not False:
details += f" - {str(r)}"
error = {
"type": "custom_validation_failed",
"message": "Custom validation failed for node",
"details": details,
"extra_info": {
"input_name": x,
"input_config": info,
"received_value": val,
}
}
errors.append(error)
continue
if len(errors) > 0 or valid is not True:
ret = (False, errors, unique_id)
else:
ret = (True, [], unique_id)
validated[unique_id] = ret
return ret
def full_type_name(klass):
module = klass.__module__
if module == 'builtins':
return klass.__qualname__
return module + '.' + klass.__qualname__
class ValidationErrorExtraInfoDict(TypedDict):
exception_type: str
traceback: List[str]
class ValidationErrorDict(TypedDict):
type: str
message: str
details: str
extra_info: ValidationErrorExtraInfoDict | dict
ValidationTuple = typing.Tuple[bool, Optional[ValidationErrorDict], typing.List[str], Union[dict, list]]
def validate_prompt(prompt: typing.Mapping[str, typing.Any]) -> ValidationTuple:
outputs = set()
for x in prompt:
class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']]
if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True:
outputs.add(x)
if len(outputs) == 0:
error = {
"type": "prompt_no_outputs",
"message": "Prompt has no outputs",
"details": "",
"extra_info": {}
}
return False, error, [], []
good_outputs = set()
errors = []
node_errors = {}
validated = {}
for o in outputs:
valid = False
reasons = []
try:
m = validate_inputs(prompt, o, validated)
valid = m[0]
reasons = m[1]
except Exception as ex:
typ, _, tb = sys.exc_info()
valid = False
exception_type = full_type_name(typ)
reasons = [{
"type": "exception_during_validation",
"message": "Exception when validating node",
"details": str(ex),
"extra_info": {
"exception_type": exception_type,
"traceback": traceback.format_tb(tb)
}
}]
validated[o] = (False, reasons, o)
if valid is True:
good_outputs.add(o)
else:
logging.error(f"Failed to validate prompt for output {o}:")
if len(reasons) > 0:
logging.error("* (prompt):")
for reason in reasons:
logging.error(f" - {reason['message']}: {reason['details']}")
errors += [(o, reasons)]
for node_id, result in validated.items():
valid = result[0]
reasons = result[1]
# If a node upstream has errors, the nodes downstream will also
# be reported as invalid, but there will be no errors attached.
# So don't return those nodes as having errors in the response.
if valid is not True and len(reasons) > 0:
if node_id not in node_errors:
class_type = prompt[node_id]['class_type']
node_errors[node_id] = {
"errors": reasons,
"dependent_outputs": [],
"class_type": class_type
}
logging.error(f"* {class_type} {node_id}:")
for reason in reasons:
logging.error(f" - {reason['message']}: {reason['details']}")
node_errors[node_id]["dependent_outputs"].append(o)
logging.error("Output will be ignored")
if len(good_outputs) == 0:
errors_list = []
for o, _errors in errors:
for error in _errors:
errors_list.append(f"{error['message']}: {error['details']}")
errors_list = "\n".join(errors_list)
error = {
"type": "prompt_outputs_failed_validation",
"message": "Prompt outputs failed validation",
"details": errors_list,
"extra_info": {}
}
return False, error, list(good_outputs), node_errors
return True, None, list(good_outputs), node_errors
class PromptQueue(AbstractPromptQueue):
def __init__(self, server: ExecutorToClientProgress):
self.server = server
self.mutex = threading.RLock()
self.not_empty = threading.Condition(self.mutex)
self.queue: typing.List[QueueItem] = []
self.currently_running: typing.Dict[str, QueueItem] = {}
# history maps the second integer prompt id in the queue tuple to a dictionary with keys "prompt" and "outputs
# todo: use the new History class for the sake of simplicity
self.history: typing.Dict[str, HistoryEntry] = {}
self.flags = {}
def size(self) -> int:
return len(self.queue)
def put(self, item: QueueItem):
with self.mutex:
heapq.heappush(self.queue, item)
self.server.queue_updated()
self.not_empty.notify()
def get(self, timeout=None) -> typing.Optional[typing.Tuple[QueueTuple, str]]:
with self.not_empty:
while len(self.queue) == 0:
self.not_empty.wait(timeout=timeout)
if timeout is not None and len(self.queue) == 0:
return None
item_with_future: QueueItem = heapq.heappop(self.queue)
assert item_with_future.prompt_id is not None
assert item_with_future.prompt_id != ""
assert item_with_future.prompt_id not in self.currently_running
assert isinstance(item_with_future.prompt_id, str)
task_id = item_with_future.prompt_id
self.currently_running[task_id] = item_with_future
self.server.queue_updated()
return copy.deepcopy(item_with_future.queue_tuple), task_id
def task_done(self, item_id: str, outputs: dict,
status: Optional[ExecutionStatus]):
with self.mutex:
queue_item = self.currently_running.pop(item_id)
prompt = queue_item.queue_tuple
if len(self.history) > MAXIMUM_HISTORY_SIZE:
self.history.pop(next(iter(self.history)))
status_dict: Optional[dict] = None
if status is not None:
status_dict = copy.deepcopy(ExecutionStatus(*status)._asdict())
self.history[prompt[1]] = {
"prompt": prompt,
"outputs": copy.deepcopy(outputs),
'status': status_dict,
}
self.server.queue_updated()
if queue_item.completed:
queue_item.completed.set_result(outputs)
def get_current_queue(self) -> Tuple[typing.List[QueueTuple], typing.List[QueueTuple]]:
with self.mutex:
out: typing.List[QueueTuple] = []
for x in self.currently_running.values():
out += [x.queue_tuple]
return out, copy.deepcopy([item.queue_tuple for item in self.queue])
def get_tasks_remaining(self):
with self.mutex:
return len(self.queue) + len(self.currently_running)
def wipe_queue(self):
with self.mutex:
for item in self.queue:
if item.completed:
item.completed.set_exception(Exception("queue cancelled"))
self.queue = []
self.server.queue_updated()
def delete_queue_item(self, function):
with self.mutex:
for x in range(len(self.queue)):
if function(self.queue[x].queue_tuple):
if len(self.queue) == 1:
self.wipe_queue()
else:
item = self.queue.pop(x)
if item.completed:
item.completed.set_exception(Exception("queue item deleted"))
heapq.heapify(self.queue)
self.server.queue_updated()
return True
return False
def get_history(self, prompt_id=None, max_items=None, offset=-1):
with self.mutex:
if prompt_id is None:
out = {}
i = 0
if offset < 0 and max_items is not None:
offset = len(self.history) - max_items
for k in self.history:
if i >= offset:
out[k] = self.history[k]
if max_items is not None and len(out) >= max_items:
break
i += 1
return out
elif prompt_id in self.history:
return {prompt_id: copy.deepcopy(self.history[prompt_id])}
else:
return {}
def wipe_history(self):
with self.mutex:
self.history.clear()
def delete_history_item(self, id_to_delete: str):
with self.mutex:
self.history.pop(id_to_delete, None)
def set_flag(self, name, data):
with self.mutex:
self.flags[name] = data
self.not_empty.notify()
def get_flags(self, reset=True):
with self.mutex:
if reset:
ret = self.flags
self.flags = {}
return ret
else:
return self.flags.copy()
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