75 lines
2.6 KiB
Markdown
75 lines
2.6 KiB
Markdown
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# Documentation
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- Class name: LLMQueryEngineAsTool
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- Category: SALT/Language Toolkit/Querying
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- Output node: False
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该节点作为一种工具，用于使用语言模型执行查询，旨在促进复杂的信息检索和处理任务。它抽象了查询语言模型的复杂性，为用户提供了一个简化的接口，以利用先进的自然语言理解能力。
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# Input types
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## Required
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- name
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- 指定工具的名称，作为查询引擎的标识符和描述符。
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- Comfy dtype: STRING
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- Python dtype: str
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- description
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- 提供工具用途和功能的详细描述，为其使用提供背景和指导。
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- Comfy dtype: STRING
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- Python dtype: str
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- llm_index
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- 标识要查询的特定索引或数据库，允许基于输入查询进行有针对性的信息检索。
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- Comfy dtype: LLM_INDEX
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- Python dtype: LLM_INDEX
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# Output types
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- query_tool
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- 节点的输出，包括配置用于查询处理的工具，封装了函数及其参数。
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- Comfy dtype: TOOL
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- Python dtype: Dict[str, Any]
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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 LLMQueryEngineAsTool:
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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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"name": ("STRING", {"multiline": False, "dynamicPrompts": False, "placeholder": "code"}),
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"description": ("STRING", {"multiline": True, "dynamicPrompts": False, "default": "A function that allows you to communicate with a document. Ask a question and this function will find information in the document and generate an answer."}),
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"llm_index": ("LLM_INDEX",),
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},
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}
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RETURN_TYPES = ("TOOL",)
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RETURN_NAMES = ("query_tool",)
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FUNCTION = "return_tool"
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CATEGORY = f"{MENU_NAME}/{SUB_MENU_NAME}/Querying"
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def return_tool(self, name, description, llm_index):
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def query_engine(query: str) -> str:
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query_components = []
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query_components.append("Analyze the above document carefully to find your answer. If you can't find one, say so.")
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if query:
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if query.strip():
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query_components.append("user: " + query)
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query_components.append("assistant:")
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pprint(query_components, indent=4)
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query_join = "\n".join(query_components)
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query_engine = llm_index.as_query_engine()
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response = query_engine.query(query_join)
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pprint(response, indent=4)
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return (response.response,)
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tool = {"name": name, "description": description, "function": query_engine}
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return (tool,)
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```
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