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476 lines
17 KiB
476 lines
17 KiB
import os |
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import sys |
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import copy |
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import json |
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import threading |
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import heapq |
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import traceback |
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if __name__ == "__main__": |
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if '--help' in sys.argv: |
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print("Valid Command line Arguments:") |
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print("\t--listen\t\t\tListen on 0.0.0.0 so the UI can be accessed from other computers.") |
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print("\t--port 8188\t\t\tSet the listen port.") |
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print("\t--dont-upcast-attention\t\tDisable upcasting of attention \n\t\t\t\t\tcan boost speed but increase the chances of black images.\n") |
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print("\t--use-split-cross-attention\tUse the split cross attention optimization instead of the sub-quadratic one.\n\t\t\t\t\tIgnored when xformers is used.") |
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print() |
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print("\t--normalvram\t\t\tUsed to force normal vram use if lowvram gets automatically enabled.") |
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print("\t--lowvram\t\t\tSplit the unet in parts to use less vram.") |
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print("\t--novram\t\t\tWhen lowvram isn't enough.") |
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print() |
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exit() |
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if '--dont-upcast-attention' in sys.argv: |
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print("disabling upcasting of attention") |
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os.environ['ATTN_PRECISION'] = "fp16" |
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import torch |
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import nodes |
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def get_input_data(inputs, class_def, outputs={}, prompt={}, extra_data={}): |
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valid_inputs = class_def.INPUT_TYPES() |
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input_data_all = {} |
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for x in inputs: |
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input_data = inputs[x] |
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if isinstance(input_data, list): |
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input_unique_id = input_data[0] |
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output_index = input_data[1] |
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obj = outputs[input_unique_id][output_index] |
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input_data_all[x] = obj |
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else: |
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if ("required" in valid_inputs and x in valid_inputs["required"]) or ("optional" in valid_inputs and x in valid_inputs["optional"]): |
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input_data_all[x] = input_data |
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if "hidden" in valid_inputs: |
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h = valid_inputs["hidden"] |
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for x in h: |
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if h[x] == "PROMPT": |
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input_data_all[x] = prompt |
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if h[x] == "EXTRA_PNGINFO": |
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if "extra_pnginfo" in extra_data: |
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input_data_all[x] = extra_data['extra_pnginfo'] |
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return input_data_all |
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def recursive_execute(prompt, outputs, current_item, extra_data={}): |
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unique_id = current_item |
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inputs = prompt[unique_id]['inputs'] |
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class_type = prompt[unique_id]['class_type'] |
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class_def = nodes.NODE_CLASS_MAPPINGS[class_type] |
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if unique_id in outputs: |
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return [] |
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executed = [] |
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for x in inputs: |
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input_data = inputs[x] |
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if isinstance(input_data, list): |
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input_unique_id = input_data[0] |
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output_index = input_data[1] |
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if input_unique_id not in outputs: |
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executed += recursive_execute(prompt, outputs, input_unique_id, extra_data) |
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input_data_all = get_input_data(inputs, class_def, outputs, prompt, extra_data) |
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obj = class_def() |
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outputs[unique_id] = getattr(obj, obj.FUNCTION)(**input_data_all) |
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return executed + [unique_id] |
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def recursive_will_execute(prompt, outputs, current_item): |
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unique_id = current_item |
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inputs = prompt[unique_id]['inputs'] |
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will_execute = [] |
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if unique_id in outputs: |
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return [] |
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for x in inputs: |
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input_data = inputs[x] |
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if isinstance(input_data, list): |
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input_unique_id = input_data[0] |
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output_index = input_data[1] |
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if input_unique_id not in outputs: |
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will_execute += recursive_will_execute(prompt, outputs, input_unique_id) |
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return will_execute + [unique_id] |
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def recursive_output_delete_if_changed(prompt, old_prompt, outputs, current_item): |
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unique_id = current_item |
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inputs = prompt[unique_id]['inputs'] |
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class_type = prompt[unique_id]['class_type'] |
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class_def = nodes.NODE_CLASS_MAPPINGS[class_type] |
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is_changed_old = '' |
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is_changed = '' |
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if hasattr(class_def, 'IS_CHANGED'): |
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if unique_id in old_prompt and 'is_changed' in old_prompt[unique_id]: |
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is_changed_old = old_prompt[unique_id]['is_changed'] |
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if 'is_changed' not in prompt[unique_id]: |
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input_data_all = get_input_data(inputs, class_def) |
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is_changed = class_def.IS_CHANGED(**input_data_all) |
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prompt[unique_id]['is_changed'] = is_changed |
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else: |
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is_changed = prompt[unique_id]['is_changed'] |
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if unique_id not in outputs: |
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return True |
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to_delete = False |
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if is_changed != is_changed_old: |
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to_delete = True |
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elif unique_id not in old_prompt: |
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to_delete = True |
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elif inputs == old_prompt[unique_id]['inputs']: |
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for x in inputs: |
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input_data = inputs[x] |
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if isinstance(input_data, list): |
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input_unique_id = input_data[0] |
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output_index = input_data[1] |
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if input_unique_id in outputs: |
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to_delete = recursive_output_delete_if_changed(prompt, old_prompt, outputs, input_unique_id) |
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else: |
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to_delete = True |
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if to_delete: |
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break |
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else: |
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to_delete = True |
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if to_delete: |
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print("deleted", unique_id) |
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d = outputs.pop(unique_id) |
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del d |
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return to_delete |
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class PromptExecutor: |
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def __init__(self): |
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self.outputs = {} |
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self.old_prompt = {} |
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def execute(self, prompt, extra_data={}): |
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with torch.no_grad(): |
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for x in prompt: |
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recursive_output_delete_if_changed(prompt, self.old_prompt, self.outputs, x) |
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current_outputs = set(self.outputs.keys()) |
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executed = [] |
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try: |
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to_execute = [] |
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for x in prompt: |
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']] |
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if hasattr(class_, 'OUTPUT_NODE'): |
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to_execute += [(0, x)] |
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while len(to_execute) > 0: |
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#always execute the output that depends on the least amount of unexecuted nodes first |
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to_execute = sorted(list(map(lambda a: (len(recursive_will_execute(prompt, self.outputs, a[-1])), a[-1]), to_execute))) |
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x = to_execute.pop(0)[-1] |
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']] |
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if hasattr(class_, 'OUTPUT_NODE'): |
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if class_.OUTPUT_NODE == True: |
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valid = False |
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try: |
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m = validate_inputs(prompt, x) |
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valid = m[0] |
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except: |
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valid = False |
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if valid: |
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executed += recursive_execute(prompt, self.outputs, x, extra_data) |
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except Exception as e: |
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print(traceback.format_exc()) |
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to_delete = [] |
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for o in self.outputs: |
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if o not in current_outputs: |
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to_delete += [o] |
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if o in self.old_prompt: |
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d = self.old_prompt.pop(o) |
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del d |
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for o in to_delete: |
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d = self.outputs.pop(o) |
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del d |
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else: |
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executed = set(executed) |
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for x in executed: |
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self.old_prompt[x] = copy.deepcopy(prompt[x]) |
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def validate_inputs(prompt, item): |
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unique_id = item |
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inputs = prompt[unique_id]['inputs'] |
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class_type = prompt[unique_id]['class_type'] |
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obj_class = nodes.NODE_CLASS_MAPPINGS[class_type] |
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class_inputs = obj_class.INPUT_TYPES() |
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required_inputs = class_inputs['required'] |
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for x in required_inputs: |
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if x not in inputs: |
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return (False, "Required input is missing. {}, {}".format(class_type, x)) |
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val = inputs[x] |
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info = required_inputs[x] |
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type_input = info[0] |
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if isinstance(val, list): |
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if len(val) != 2: |
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return (False, "Bad Input. {}, {}".format(class_type, x)) |
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o_id = val[0] |
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o_class_type = prompt[o_id]['class_type'] |
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r = nodes.NODE_CLASS_MAPPINGS[o_class_type].RETURN_TYPES |
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if r[val[1]] != type_input: |
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return (False, "Return type mismatch. {}, {}".format(class_type, x)) |
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r = validate_inputs(prompt, o_id) |
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if r[0] == False: |
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return r |
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else: |
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if type_input == "INT": |
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val = int(val) |
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inputs[x] = val |
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if type_input == "FLOAT": |
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val = float(val) |
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inputs[x] = val |
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if type_input == "STRING": |
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val = str(val) |
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inputs[x] = val |
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if len(info) > 1: |
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if "min" in info[1] and val < info[1]["min"]: |
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return (False, "Value smaller than min. {}, {}".format(class_type, x)) |
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if "max" in info[1] and val > info[1]["max"]: |
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return (False, "Value bigger than max. {}, {}".format(class_type, x)) |
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if isinstance(type_input, list): |
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if val not in type_input: |
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return (False, "Value not in list. {}, {}: {} not in {}".format(class_type, x, val, type_input)) |
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return (True, "") |
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def validate_prompt(prompt): |
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outputs = set() |
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for x in prompt: |
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class_ = nodes.NODE_CLASS_MAPPINGS[prompt[x]['class_type']] |
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if hasattr(class_, 'OUTPUT_NODE') and class_.OUTPUT_NODE == True: |
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outputs.add(x) |
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if len(outputs) == 0: |
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return (False, "Prompt has no outputs") |
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good_outputs = set() |
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errors = [] |
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for o in outputs: |
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valid = False |
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reason = "" |
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try: |
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m = validate_inputs(prompt, o) |
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valid = m[0] |
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reason = m[1] |
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except: |
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valid = False |
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reason = "Parsing error" |
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if valid == True: |
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good_outputs.add(x) |
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else: |
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print("Failed to validate prompt for output {} {}".format(o, reason)) |
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print("output will be ignored") |
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errors += [(o, reason)] |
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if len(good_outputs) == 0: |
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errors_list = "\n".join(map(lambda a: "{}".format(a[1]), errors)) |
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return (False, "Prompt has no properly connected outputs\n {}".format(errors_list)) |
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return (True, "") |
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def prompt_worker(q): |
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e = PromptExecutor() |
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while True: |
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item, item_id = q.get() |
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e.execute(item[-2], item[-1]) |
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q.task_done(item_id) |
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class PromptQueue: |
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def __init__(self): |
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self.mutex = threading.RLock() |
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self.not_empty = threading.Condition(self.mutex) |
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self.task_counter = 0 |
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self.queue = [] |
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self.currently_running = {} |
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def put(self, item): |
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with self.mutex: |
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heapq.heappush(self.queue, item) |
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self.not_empty.notify() |
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def get(self): |
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with self.not_empty: |
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while len(self.queue) == 0: |
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self.not_empty.wait() |
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item = heapq.heappop(self.queue) |
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i = self.task_counter |
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self.currently_running[i] = copy.deepcopy(item) |
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self.task_counter += 1 |
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return (item, i) |
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def task_done(self, item_id): |
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with self.mutex: |
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self.currently_running.pop(item_id) |
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def get_current_queue(self): |
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with self.mutex: |
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out = [] |
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for x in self.currently_running.values(): |
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out += [x] |
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return (out, copy.deepcopy(self.queue)) |
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def get_tasks_remaining(self): |
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with self.mutex: |
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return len(self.queue) + len(self.currently_running) |
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def wipe_queue(self): |
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with self.mutex: |
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self.queue = [] |
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def delete_queue_item(self, function): |
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with self.mutex: |
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for x in range(len(self.queue)): |
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if function(self.queue[x]): |
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if len(self.queue) == 1: |
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self.wipe_queue() |
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else: |
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self.queue.pop(x) |
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heapq.heapify(self.queue) |
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return True |
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return False |
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from http.server import BaseHTTPRequestHandler, HTTPServer |
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class PromptServer(BaseHTTPRequestHandler): |
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def _set_headers(self, code=200, ct='text/html'): |
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self.send_response(code) |
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self.send_header('Content-type', ct) |
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self.end_headers() |
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def log_message(self, format, *args): |
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pass |
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def do_GET(self): |
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if self.path == "/prompt": |
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self._set_headers(ct='application/json') |
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prompt_info = {} |
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exec_info = {} |
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exec_info['queue_remaining'] = self.server.prompt_queue.get_tasks_remaining() |
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prompt_info['exec_info'] = exec_info |
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self.wfile.write(json.dumps(prompt_info).encode('utf-8')) |
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elif self.path == "/queue": |
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self._set_headers(ct='application/json') |
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queue_info = {} |
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current_queue = self.server.prompt_queue.get_current_queue() |
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queue_info['queue_running'] = current_queue[0] |
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queue_info['queue_pending'] = current_queue[1] |
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self.wfile.write(json.dumps(queue_info).encode('utf-8')) |
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elif self.path == "/object_info": |
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self._set_headers(ct='application/json') |
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out = {} |
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for x in nodes.NODE_CLASS_MAPPINGS: |
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obj_class = nodes.NODE_CLASS_MAPPINGS[x] |
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info = {} |
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info['input'] = obj_class.INPUT_TYPES() |
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info['output'] = obj_class.RETURN_TYPES |
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info['name'] = x #TODO |
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info['description'] = '' |
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info['category'] = 'sd' |
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if hasattr(obj_class, 'CATEGORY'): |
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info['category'] = obj_class.CATEGORY |
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out[x] = info |
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self.wfile.write(json.dumps(out).encode('utf-8')) |
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elif self.path[1:] in os.listdir(self.server.server_dir): |
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if self.path[1:].endswith('.css'): |
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self._set_headers(ct='text/css') |
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elif self.path[1:].endswith('.js'): |
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self._set_headers(ct='text/javascript') |
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else: |
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self._set_headers() |
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with open(os.path.join(self.server.server_dir, self.path[1:]), "rb") as f: |
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self.wfile.write(f.read()) |
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else: |
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self._set_headers() |
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with open(os.path.join(self.server.server_dir, "index.html"), "rb") as f: |
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self.wfile.write(f.read()) |
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def do_HEAD(self): |
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self._set_headers() |
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def do_POST(self): |
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resp_code = 200 |
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out_string = "" |
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if self.path == "/prompt": |
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print("got prompt") |
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data_string = self.rfile.read(int(self.headers['Content-Length'])) |
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json_data = json.loads(data_string) |
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if "number" in json_data: |
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number = float(json_data['number']) |
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else: |
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number = self.server.number |
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if "front" in json_data: |
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if json_data['front']: |
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number = -number |
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self.server.number += 1 |
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if "prompt" in json_data: |
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prompt = json_data["prompt"] |
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valid = validate_prompt(prompt) |
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extra_data = {} |
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if "extra_data" in json_data: |
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extra_data = json_data["extra_data"] |
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if valid[0]: |
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self.server.prompt_queue.put((number, id(prompt), prompt, extra_data)) |
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else: |
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resp_code = 400 |
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out_string = valid[1] |
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print("invalid prompt:", valid[1]) |
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elif self.path == "/queue": |
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data_string = self.rfile.read(int(self.headers['Content-Length'])) |
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json_data = json.loads(data_string) |
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if "clear" in json_data: |
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if json_data["clear"]: |
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self.server.prompt_queue.wipe_queue() |
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if "delete" in json_data: |
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to_delete = json_data['delete'] |
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for id_to_delete in to_delete: |
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delete_func = lambda a: a[1] == int(id_to_delete) |
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self.server.prompt_queue.delete_queue_item(delete_func) |
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self._set_headers(code=resp_code) |
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self.end_headers() |
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self.wfile.write(out_string.encode('utf8')) |
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return |
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def run(prompt_queue, address='', port=8188): |
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server_address = (address, port) |
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httpd = HTTPServer(server_address, PromptServer) |
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httpd.server_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "webshit") |
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httpd.prompt_queue = prompt_queue |
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httpd.number = 0 |
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if server_address[0] == '': |
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addr = '0.0.0.0' |
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else: |
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addr = server_address[0] |
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print("Starting server\n") |
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print("To see the GUI go to: http://{}:{}".format(addr, server_address[1])) |
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httpd.serve_forever() |
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if __name__ == "__main__": |
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q = PromptQueue() |
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threading.Thread(target=prompt_worker, daemon=True, args=(q,)).start() |
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if '--listen' in sys.argv: |
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address = '0.0.0.0' |
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else: |
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address = '127.0.0.1' |
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port = 8188 |
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try: |
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p_index = sys.argv.index('--port') |
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port = int(sys.argv[p_index + 1]) |
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except: |
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pass |
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run(q, address=address, port=port) |
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