60 lines
2.3 KiB
Python
60 lines
2.3 KiB
Python
from typing import List
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from lark import Transformer, Token
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from comfy.sd1_clip import SDTokenizer
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from custom_nodes.KepPromptLang.lib.action.base import Action, ActionArity
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from custom_nodes.KepPromptLang.lib.parser.registration import get_action_by_name
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from custom_nodes.KepPromptLang.lib.parser.utils import build_prompt_segment
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from custom_nodes.KepPromptLang.lib.parser.prompt_segment import PromptSegment
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class PromptTransformer(Transformer):
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"""
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Transforms the parsed prompt into a list of segments and actions
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Types from the grammar are mapped to the methods in this class
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"""
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# def WORD(self, items):
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# return items
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def __init__(self, tokenizer: SDTokenizer):
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super().__init__()
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self.tokenizer = tokenizer
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def item(self, items: List[Token]):
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for item in items:
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if isinstance(item, (Action, PromptSegment)):
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return item
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if item.type == "WORD":
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return build_prompt_segment(str(item), self.tokenizer)
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elif item.type == "QUOTED_STRING":
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# Remove the quotes
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unquoted = item[1:-1]
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# Replace escaped quotes with quotes
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unescaped = unquoted.replace("\\\"", "\"").replace("\\\'", "\'")
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return build_prompt_segment(unescaped, self.tokenizer)
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elif item.type == "embedding":
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return build_prompt_segment(item, self.tokenizer)
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elif item.type == "function":
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raise Exception("Unexpected type in prompt transformer: function. Please report this issue on GitHub.")
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else:
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raise Exception("Unknown item type: " + str(item.type))
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def arg(self, items):
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return items
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def embedding(self, items):
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return build_prompt_segment(f'{self.tokenizer.embedding_identifier}{items[0]}', self.tokenizer)
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def generic_function(self, items):
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action = get_action_by_name(items[0])
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if action.arity == ActionArity.SINGLE:
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if len(items) != 2:
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raise ValueError(f"Action {action.name} should have exactly one argument")
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return action(items[1])
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elif action.arity == ActionArity.MULTI:
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return action(items[1:][:])
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else:
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raise ValueError(f"Unknown action arity: {action.arity}")
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