72 lines
2.4 KiB
Markdown
72 lines
2.4 KiB
Markdown
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# Documentation
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- Class name: LLMRegexCreator
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- Category: SALT/Language Toolkit/Tools/Regex
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- Output node: False
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LLMRegexCreator节点旨在根据给定的描述和可选的额外指示生成正则表达式（regex）模式。它利用语言模型来解析需求，并生成一个符合指定标准的完整正则表达式模式。
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# Input types
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## Required
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- llm_model
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- 指定用于生成正则表达式模式的语言模型。它对于解析描述和额外指示以创建正则表达式至关重要。
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- Comfy dtype: LLM_MODEL
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- Python dtype: Dict[str, Any]
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- description
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- 要创建的正则表达式模式的主要描述。这个描述是正则表达式生成的基础，指导语言模型构建模式。
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- Comfy dtype: STRING
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- Python dtype: str
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## Optional
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- extra_directions
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- 可选的附加指示或约束，用于指导语言模型生成正则表达式模式。这些指示可以通过提供更多上下文或特定要求来优化输出。
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- Comfy dtype: STRING
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- Python dtype: str
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# Output types
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- regex_pattern
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- 根据提供的描述和可选的额外指示生成的正则表达式模式。
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- Comfy dtype: STRING
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- Python dtype: str
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## Usage tips
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- Infra type: `CPU`
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- Common nodes: unknown
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## Source code
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```python
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class LLMRegexCreator:
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"llm_model": ("LLM_MODEL",),
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"description": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Describe regex pattern to create, optionally provide example"}),
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},
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"optional": {
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"extra_directions": ("STRING", {"multiline": True, "dynamicPrompts": False, "placeholder": "Extra directions for the LLM to follow..."}),
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}
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}
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RETURN_TYPES = ("STRING",)
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RETURN_NAMES = ("regex_pattern",)
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FUNCTION = "create_regex"
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CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Tools/Regex"
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def create_regex(self, llm_model, description, extra_directions=""):
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prompt = (
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f"Create only a well formed regex pattern based on the following description:\n\n"
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f"{description}\n\n"
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f"{extra_directions}\n\n"
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"Please ensure the regex pattern is concise and accurately matches the described criteria."
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)
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response = llm_model['llm'].complete(prompt)
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return (response.text,)
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```
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