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src/summeryanyfile/graph/nodes.py

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+"""
+图节点实现 - 定义LangGraph工作流中的各个节点
+"""
+
+import json
+from typing import Dict, Any, Literal
+import logging
+from langchain_core.runnables import RunnableConfig
+
+from ..core.models import PPTState
+from ..core.json_parser import JSONParser
+from ..generators.chains import ChainManager, ChainExecutor
+from ..utils.logger import LoggerMixin
+
+logger = logging.getLogger(__name__)
+
+
+class GraphNodes(LoggerMixin):
+    """图节点集合，包含所有工作流节点的实现"""
+
+    def __init__(self, chain_manager: ChainManager, config=None):
+        self.chain_manager = chain_manager
+        self.chain_executor = ChainExecutor(chain_manager)
+        self.json_parser = JSONParser()
+        self.config = config  # 添加配置参数
+
+    def _get_slides_range_text(self, state: Dict[str, Any]) -> str:
+        """根据状态中的页数模式生成页数约束文本"""
+        page_count_mode = state.get("page_count_mode", "ai_decide")
+        min_pages = state.get("min_pages")
+        max_pages = state.get("max_pages")
+        fixed_pages = state.get("fixed_pages")
+
+        if page_count_mode == "fixed" and fixed_pages:
+            result = f"【强制要求】必须生成恰好{fixed_pages}页的PPT，不能多也不能少"
+        elif page_count_mode == "custom_range" and min_pages and max_pages:
+            result = f"【强制要求】必须严格控制在{min_pages}-{max_pages}页范围内，最少{min_pages}页，最多{max_pages}页，不能超出此范围"
+        else:  # ai_decide
+            result = "根据内容的复杂度、深度和逻辑结构，自主决定最合适的页数，确保内容充实且逻辑清晰"
+
+        return result
+    
+    async def analyze_structure(self, state: PPTState, config: RunnableConfig) -> Dict[str, Any]:
+        """
+        分析文档结构节点
+        
+        Args:
+            state: 当前状态
+            config: 运行配置
+            
+        Returns:
+            更新的状态字段
+        """
+        self.logger.info("开始分析文档结构...")
+        
+        try:
+            # 获取第一个文档块
+            first_chunk = state["document_chunks"][0] if state["document_chunks"] else ""
+            
+            if not first_chunk.strip():
+                self.logger.warning("第一个文档块为空，使用默认结构")
+                structure = {
+                    "title": "文档分析",
+                    "type": "通用文档",
+                    "sections": [],
+                    "key_concepts": [],
+                    "language": "中文",
+                    "complexity": "中等"
+                }
+            else:
+                # 调用结构分析链
+                structure_response = await self.chain_executor.execute_with_retry(
+                    "structure_analysis",
+                    {
+                        "content": first_chunk,
+                        "project_topic": state.get("project_topic", ""),
+                        "project_scenario": state.get("project_scenario", "general"),
+                        "project_requirements": state.get("project_requirements", ""),
+                        "target_audience": state.get("target_audience", "普通大众"),
+                        "custom_audience": state.get("custom_audience", ""),
+                        "ppt_style": state.get("ppt_style", "general"),
+                        "custom_style_prompt": state.get("custom_style_prompt", "")
+                    },
+                    config
+                )
+                
+                # 解析JSON响应
+                structure = self.json_parser.extract_json_from_response(structure_response)
+                
+                # 验证结构
+                if not isinstance(structure, dict):
+                    raise ValueError("结构分析返回的不是有效的字典")
+            
+            self.logger.info(f"文档结构分析完成: {structure.get('title', '未知标题')}")
+            
+            return {
+                "document_structure": structure,
+                "accumulated_context": first_chunk[:500]  # 保留前500字作为上下文
+            }
+            
+        except Exception as e:
+            self.logger.error(f"文档结构分析失败: {e}")
+            # 返回默认结构
+            return {
+                "document_structure": {
+                    "title": "文档分析",
+                    "type": "通用文档",
+                    "sections": [],
+                    "key_concepts": [],
+                    "language": "中文",
+                    "complexity": "中等"
+                },
+                "accumulated_context": first_chunk[:500] if state["document_chunks"] else ""
+            }
+    
+    async def generate_initial_outline(self, state: PPTState, config: RunnableConfig) -> Dict[str, Any]:
+        """
+        生成初始PPT框架节点
+        
+        Args:
+            state: 当前状态
+            config: 运行配置
+            
+        Returns:
+            更新的状态字段
+        """
+        self.logger.info("开始生成初始PPT框架...")
+        
+        try:
+            # 准备输入
+            structure_json = json.dumps(state["document_structure"], ensure_ascii=False)
+            first_chunk = state["document_chunks"][0] if state["document_chunks"] else ""
+            
+            # 准备输入参数，包含页数范围、目标语言和项目信息
+            chain_inputs = {
+                "structure": structure_json,
+                "content": first_chunk,
+                "project_topic": state.get("project_topic", ""),
+                "project_scenario": state.get("project_scenario", "general"),
+                "project_requirements": state.get("project_requirements", ""),
+                "target_audience": state.get("target_audience", "普通大众"),
+                "custom_audience": state.get("custom_audience", ""),
+                "ppt_style": state.get("ppt_style", "general"),
+                "custom_style_prompt": state.get("custom_style_prompt", "")
+            }
+
+            # 添加页数范围信息
+            slides_range_text = self._get_slides_range_text(state)
+            chain_inputs["slides_range"] = slides_range_text
+            if self.config:
+                chain_inputs["target_language"] = self.config.target_language
+            else:
+                chain_inputs["target_language"] = "zh"  # 默认中文
+
+            # 调用初始大纲生成链
+            outline_response = await self.chain_executor.execute_with_retry(
+                "initial_outline",
+                chain_inputs,
+                config
+            )
+            
+            # 解析JSON响应
+            outline = self.json_parser.extract_json_from_response(outline_response)
+            
+            # 验证和修复大纲结构
+            outline = self.json_parser.validate_ppt_structure(outline)
+            
+            self.logger.info(f"初始PPT框架生成完成: {outline.get('title', '未知标题')}")
+            
+            return {
+                **state,  # 保留所有原始状态
+                "ppt_title": outline.get("title", "学术演示"),
+                "total_pages": outline.get("total_pages", 15),
+                "page_count_mode": state.get("page_count_mode", "estimated"),  # 保持原始页数模式
+                "slides": outline.get("slides", []),
+                "current_index": 1
+            }
+            
+        except Exception as e:
+            self.logger.error(f"初始PPT框架生成失败: {e}")
+            # 返回默认框架
+            return {
+                "ppt_title": "学术演示",
+                "total_pages": 15,
+                "page_count_mode": "estimated",
+                "slides": [
+                    {
+                        "page_number": 1,
+                        "title": "标题页",
+                        "content_points": ["演示标题", "演示者", "日期"],
+                        "slide_type": "title",
+                        "description": "PPT开场标题页"
+                    }
+                ],
+                "current_index": 1
+            }
+    
+    async def refine_outline(self, state: PPTState, config: RunnableConfig) -> Dict[str, Any]:
+        """
+        细化PPT大纲节点
+        
+        Args:
+            state: 当前状态
+            config: 运行配置
+            
+        Returns:
+            更新的状态字段
+        """
+        current_index = state["current_index"]
+        total_chunks = len(state["document_chunks"])
+        
+        self.logger.info(f"正在细化PPT大纲 ({current_index + 1}/{total_chunks})...")
+        
+        # 检查是否还有内容需要处理
+        if current_index >= total_chunks:
+            self.logger.info("所有文档块已处理完成")
+            return state
+        
+        try:
+            # 获取当前文档块
+            current_content = state["document_chunks"][current_index]
+            
+            # 准备现有大纲
+            existing_outline = {
+                "title": state["ppt_title"],
+                "total_pages": state["total_pages"],
+                "slides": state["slides"]
+            }
+            existing_outline_json = json.dumps(existing_outline, ensure_ascii=False)
+            
+            # 准备输入参数，包含页数范围、目标语言和项目信息
+            chain_inputs = {
+                "existing_outline": existing_outline_json,
+                "new_content": current_content,
+                "context": state["accumulated_context"],
+                "project_topic": state.get("project_topic", ""),
+                "project_scenario": state.get("project_scenario", "general"),
+                "project_requirements": state.get("project_requirements", ""),
+                "target_audience": state.get("target_audience", "普通大众"),
+                "custom_audience": state.get("custom_audience", ""),
+                "ppt_style": state.get("ppt_style", "general"),
+                "custom_style_prompt": state.get("custom_style_prompt", "")
+            }
+
+            # 添加页数范围信息和目标语言
+            slides_range_text = self._get_slides_range_text(state)
+            chain_inputs["slides_range"] = slides_range_text
+            if self.config:
+                chain_inputs["target_language"] = self.config.target_language
+            else:
+                chain_inputs["target_language"] = "zh"  # 默认中文
+
+            # 调用细化链
+            refined_response = await self.chain_executor.execute_with_retry(
+                "refine_outline",
+                chain_inputs,
+                config
+            )
+            
+            # 解析JSON响应
+            refined_outline = self.json_parser.extract_json_from_response(refined_response)
+            
+            # 验证和修复结构
+            refined_outline = self.json_parser.validate_ppt_structure(refined_outline)
+            
+            # 更新累积上下文
+            new_context = state["accumulated_context"] + "\n" + current_content[:300]
+            if len(new_context) > 2000:  # 限制上下文长度
+                new_context = new_context[-2000:]
+            
+            return {
+                **state,  # 保留所有原始状态
+                "ppt_title": refined_outline.get("title", state["ppt_title"]),
+                "total_pages": refined_outline.get("total_pages", state["total_pages"]),
+                "slides": refined_outline.get("slides", state["slides"]),
+                "current_index": current_index + 1,
+                "accumulated_context": new_context
+            }
+            
+        except Exception as e:
+            self.logger.error(f"PPT大纲细化失败: {e}")
+            # 继续处理下一个块
+            return {
+                **state,
+                "current_index": current_index + 1
+            }
+    
+    def should_continue_refining(self, state: PPTState) -> Literal["refine_outline", "end"]:
+        """
+        判断是否继续细化的条件函数
+        
+        Args:
+            state: 当前状态
+            
+        Returns:
+            下一个节点名称
+        """
+        current_index = state["current_index"]
+        total_chunks = len(state["document_chunks"])
+        
+        if current_index >= total_chunks:
+            self.logger.info("所有文档块已处理，完成大纲生成")
+            return "end"
+        else:
+            self.logger.debug(f"继续处理文档块 {current_index + 1}/{total_chunks}")
+            return "refine_outline"