138 lines
4.9 KiB
Python
138 lines
4.9 KiB
Python
# 文件名：nodes.py
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import json
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import os
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import random
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import time
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class PromptComposerNode:
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@classmethod
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def INPUT_TYPES(cls):
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base_dir = os.path.dirname(__file__)
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config_path = os.path.join(base_dir, "config", "prompt_config.txt")
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group_path = os.path.join(base_dir, "config", "prompt_group.txt")
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with open(config_path, "r", encoding="utf-8") as f:
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prompt_config = json.load(f)
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with open(group_path, "r", encoding="utf-8") as f:
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prompt_group = json.load(f)
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dynamic_inputs = {}
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for key, default_idx in prompt_config.items():
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group = prompt_group.get(key, [])
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options = ["-1:随机"] + [f"{idx}:{v}" if v else f"{idx}:(空)"
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for idx, v in enumerate(group)]
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try:
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default = options[default_idx + 1] if default_idx != -1 else options[0]
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except:
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default = options[0]
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dynamic_inputs[key] = (options, {"default": default})
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return {"required": dynamic_inputs}
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RETURN_TYPES = ("STRING", "STRING")
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RETURN_NAMES = ("positive_prompt", "negative_prompt")
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FUNCTION = "process"
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CATEGORY = "Prompt"
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# 添加这一行，表示节点需要每次都重新执行
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IS_CHANGED = True
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def process(self, **kwargs):
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# 生成纳秒级随机种子
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random.seed(int(time.time() * 1e9) % 0xFFFFFFFF)
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base_dir = os.path.dirname(__file__)
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group_path = os.path.join(base_dir, "config", "prompt_group.txt")
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with open(group_path, "r", encoding="utf-8") as f:
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prompt_group = json.load(f)
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# 统一处理所有参数
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processed_values = {
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key: self._process_param(key, value, prompt_group)
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for key, value in kwargs.items()
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}
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# 构建提示词
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positive = self._build_positive_prompt(processed_values, prompt_group)
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negative = self._build_negative_prompt(processed_values, prompt_group)
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return (
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self._clean_prompt(positive),
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self._clean_prompt(negative)
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)
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def _process_param(self, key, value_str, prompt_group):
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"""统一处理每个参数"""
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selected = self._parse_selection(value_str)
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group = prompt_group.get(key, [])
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# 处理随机选择
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if selected == -1:
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valid_indices = [i for i, v in enumerate(group) if v.strip()]
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return random.choice(valid_indices) if valid_indices else -1
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return selected if 0 <= selected < len(group) else -1
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def _build_positive_prompt(self, values, prompt_group):
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"""构建正面提示词"""
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if values["套装"] > 0:
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return self._get_group_value("套装", values["套装"], prompt_group)
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# 处理颜色提示词（独立逻辑）
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color_prompt = None
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if values["颜色"]>0:
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color_prompt=self._get_group_value("颜色", values["颜色"], prompt_group)
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# 处理材质提示词（独立逻辑）
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material_prompt = None
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if values["材质"]>0:
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material_prompt=self._get_group_value("材质", values["材质"], prompt_group)
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parts = []
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for key in list(values.keys()):
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if key in ["套装", "负面提示词", "颜色", "材质"]:
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continue
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value = self._get_group_value(key, values[key], prompt_group)
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if value:
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if (key == "上装" or key == "下装" ) and values["服装"] > 0: # 服装不为空（>0），则忽略上装和下装
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continue
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if (key == "服装" or key == "上装") and values[key] >1:#服装或者上装不为空（0）不为裸（1），就加上颜色和材质
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if material_prompt:
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value = f"{material_prompt}_" + value
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if color_prompt:
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value = f"{color_prompt}_" + value
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parts.append(value)
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return ",".join(parts)
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def _build_negative_prompt(self, values, prompt_group):
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"""构建负面提示词"""
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return self._get_group_value("负面提示词", values["负面提示词"], prompt_group)
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def _parse_selection(self, selection_str):
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"""解析选择值"""
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try:
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return int(selection_str.split(":")[0])
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except:
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return -1
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def _get_group_value(self, key, index, prompt_group):
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"""安全获取分组值"""
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if index == -1:
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return ""
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group = prompt_group.get(key, [])
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return group[index].strip() if 0 <= index < len(group) else ""
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def _clean_prompt(self, text):
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"""清理提示词格式"""
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return text.strip().strip(",").replace(" ,", ",").replace(",,", ",")
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NODE_CLASS_MAPPINGS = {
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"PromptComposer": PromptComposerNode
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"PromptComposer": "🎲 Prompt Composer"
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} |