sladro
c1292fcacc
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
146 lines
4.5 KiB
Python
146 lines
4.5 KiB
Python
"""用户交互节点
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与用户交互获取章节填写要求和RAG配置。
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"""
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import logging
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from typing import Any, Dict
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from ..base import BaseNode, NodeContext
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logger = logging.getLogger(__name__)
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class InteractWithUserNode(BaseNode):
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"""用户交互节点
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职责：
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1. 询问用户该章节需要强调的内容
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2. 询问是否使用RAG知识库
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3. 如果使用RAG，选择具体的知识库
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4. 保存配置供后续子章节继承
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"""
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@property
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def name(self) -> str:
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return "interact_user"
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@property
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def description(self) -> str:
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return "与用户交互获取章节配置"
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def execute(self, state: Dict[str, Any], context: NodeContext) -> Dict[str, Any]:
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"""执行用户交互
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Args:
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state: 当前状态
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context: 执行上下文
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Returns:
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更新后的状态
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"""
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chapter = state.get("current_chapter", {})
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chapter_id = chapter.get("id")
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chapter_title = chapter.get("title")
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if not chapter_id:
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raise ValueError("当前章节信息缺失")
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# 检查是否需要交互
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needs_interaction = state.get("needs_interaction", False)
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if not needs_interaction:
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# 不需要交互，直接返回
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return state
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# 获取交互处理器
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interaction_handler = state.get("interaction_handler")
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if not interaction_handler:
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# 无交互处理器时立即失败，暴露配置问题
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raise ValueError("交互处理器未配置，无法获取章节配置")
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logger.info(f"开始与用户交互，获取章节配置: {chapter_id} - {chapter_title}")
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# 1. 询问需要强调的内容
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emphasis = interaction_handler(
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interaction_type="text",
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prompt=f"📝 正在处理章节：{chapter_id}. {chapter_title}\n"
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f" 是否有需要特别强调的内容？（直接回车跳过）",
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default="",
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key=f"emphasis_{chapter_id}",
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)
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# 2. 询问是否使用RAG
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use_rag_response = interaction_handler(
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interaction_type="choice",
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prompt="是否使用RAG知识库辅助生成内容",
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options=["是", "否"],
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default="否",
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key=f"use_rag_{chapter_id}",
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)
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use_rag = use_rag_response == "是"
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rag_store = None
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# 3. 如果使用RAG，选择知识库
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if use_rag:
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rag_store = self._select_rag_store(interaction_handler, chapter_id, state)
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# 保存章节配置
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config = {
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"emphasis": emphasis.strip() if emphasis else "",
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"rag_enabled": use_rag,
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"rag_store": rag_store,
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}
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state.setdefault("chapter_configs", {})[chapter_id] = config
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logger.info(
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f"章节配置已保存: 强调内容={'有' if config['emphasis'] else '无'}, "
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f"RAG={'启用' if use_rag else '禁用'}"
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)
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return state
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def _select_rag_store(self, interaction_handler, chapter_id: str, state: Dict[str, Any]) -> str:
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"""选择RAG知识库
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Args:
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interaction_handler: 交互处理器
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chapter_id: 章节ID
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state: 当前状态
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Returns:
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知识库标识
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"""
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# 从state获取RAGTool实例（由InitConfigNode统一初始化）
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rag_tool = state.get("rag_tool")
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if not rag_tool:
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raise ValueError("RAGTool未初始化，请检查InitConfigNode配置")
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try:
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stats = rag_tool.get_stats()
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total_chunks = stats.get("total_chunks", 0)
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total_files = stats.get("total_files", 0)
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# 显示知识库统计信息
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store_info = f"默认知识库 ({total_files}个文档, {total_chunks}个文档块)"
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choice = interaction_handler(
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interaction_type="choice",
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prompt="选择知识库",
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options=[
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("default", store_info),
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("none", "不使用RAG")
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],
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default="default",
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key=f"rag_store_{chapter_id}",
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)
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if choice == "default":
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return "default"
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return None
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except Exception as e:
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logger.error(f"获取知识库信息失败: {e}", exc_info=True)
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raise ValueError("获取知识库信息失败，无法选择RAG存储") from e |