refactor: replace print() with structured logging across backend

Replace all print()/stderr logging with Python logging module using
logger = logging.getLogger(__name__) pattern for consistent log levels
and formatting. Extract score conversion to shared score_utils module.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend/src/api/chat.py

@@ -1,11 +1,13 @@
 """
 聊天对话API
 """
+import logging
+
 from fastapi import APIRouter, Depends, HTTPException, status
 from fastapi.responses import StreamingResponse
 from sqlalchemy.orm import Session
-from pydantic import BaseModel
-from typing import List, Optional, Dict, Any
+from pydantic import BaseModel, Field
+from typing import List, Optional, Dict, Any, Literal
 import json
 import asyncio
 
@@ -17,6 +19,8 @@ from ..rag.chains import create_rag_chain
 from ..rag.conversation_chains import create_conversation_chain
 from ..llm.siliconflow import get_llm_client
 
+logger = logging.getLogger(__name__)
+
 router = APIRouter(prefix="/chat", tags=["聊天"])
 
 
@@ -33,11 +37,11 @@ def get_user_id_by_username(db: Session, username: str) -> int:
 
 class ChatRequest(BaseModel):
     """聊天请求模型"""
-    message: str
+    message: str = Field(..., min_length=1, max_length=5000, description="用户消息")
     session_id: Optional[int] = None
-    mode: str = "normal"  # normal, rag
-    knowledge_base_ids: Optional[List[int]] = None
-    model: Optional[str] = None  # 模型ID，如 deepseek-ai/DeepSeek-V3, Qwen/QwQ-32B
+    mode: Literal["normal", "rag"] = "normal"
+    knowledge_base_ids: Optional[List[int]] = Field(None, description="RAG模式使用的知识库ID列表")
+    model: Optional[str] = None
 
 
 class ChatResponse(BaseModel):
@@ -105,24 +109,24 @@ async def send_message(
             new_title = request.message.strip()[:30] + "..." if len(request.message.strip()) > 30 else request.message.strip()
             session.title = new_title
             db.commit()
-            print(f"[DEBUG-AUTO-TITLE] 自动更新会话标题: {new_title}")
-        
+            logger.debug(f"自动更新会话标题: {new_title}")
+
         # 根据模式运行不同的问答工作流
         if request.mode == "rag":
-            print(f"[DEBUG-RAG] 非流式RAG模式")
-            print(f"[DEBUG-RAG] 接收到的knowledge_base_ids: {request.knowledge_base_ids}")
-            print(f"[DEBUG-RAG] knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
+            logger.debug(f"非流式RAG模式")
+            logger.debug(f"接收到的knowledge_base_ids: {request.knowledge_base_ids}")
+            logger.debug(f"knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
             if request.knowledge_base_ids:
-                print(f"[DEBUG-RAG] 第一个ID: {request.knowledge_base_ids[0]}, 类型: {type(request.knowledge_base_ids[0])}")
-            
+                logger.debug(f"第一个ID: {request.knowledge_base_ids[0]}, 类型: {type(request.knowledge_base_ids[0])}")
+
             # 使用LangChain 1.0 RAG链
-            print(f"[DEBUG-RAG] 模型: {request.model}")
+            logger.debug(f"模型: {request.model}")
             rag_chain = create_rag_chain(knowledge_base_ids=request.knowledge_base_ids, model=request.model)
             result = rag_chain.invoke(request.message)
         else:
             # 普通模式：使用LangChain 1.0对话链
-            print(f"[DEBUG-CHAT] 普通模式 - 使用LangChain对话链")
-            print(f"[DEBUG-CHAT] 模型: {request.model}")
+            logger.debug(f"普通模式 - 使用LangChain对话链")
+            logger.debug(f"模型: {request.model}")
             conversation_chain = create_conversation_chain(model=request.model)
             
             # 获取聊天历史
@@ -175,7 +179,7 @@ async def stream_message(
         db = SessionLocal()
         try:
             # 打印请求参数调试信息
-            print(f"[DEBUG-CHAT] 接收流式请求 - mode: {request.mode}, knowledge_base_ids: {request.knowledge_base_ids}, model: {request.model}, message: {request.message[:50]}...")
+            logger.debug(f"接收流式请求 - mode: {request.mode}, knowledge_base_ids: {request.knowledge_base_ids}, model: {request.model}, message: {request.message[:50]}...")
             
             # 获取或创建会话
             if request.session_id:
@@ -215,7 +219,7 @@ async def stream_message(
                 new_title = request.message.strip()[:30] + "..." if len(request.message.strip()) > 30 else request.message.strip()
                 session.title = new_title
                 db.commit()
-                print(f"[DEBUG-AUTO-TITLE] 自动更新会话标题: {new_title}")
+                logger.debug(f"自动更新会话标题: {new_title}")
             
             # 获取聊天历史
             chat_history = []
@@ -231,12 +235,12 @@ async def stream_message(
             
             # 根据模式选择不同的处理方式
             if request.mode == "rag":
-                print(f"[DEBUG-RAG] 使用LangChain 1.0 RAG链")
-                print(f"[DEBUG-RAG] 接收到的knowledge_base_ids: {request.knowledge_base_ids}")
-                print(f"[DEBUG-RAG] knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
-                print(f"[DEBUG-RAG] 模型: {request.model}")
+                logger.debug(f"使用LangChain 1.0 RAG链")
+                logger.debug(f"接收到的knowledge_base_ids: {request.knowledge_base_ids}")
+                logger.debug(f"knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
+                logger.debug(f"模型: {request.model}")
                 if request.knowledge_base_ids:
-                    print(f"[DEBUG-RAG] 第一个ID: {request.knowledge_base_ids[0]}, 类型: {type(request.knowledge_base_ids[0])}")
+                    logger.debug(f"第一个ID: {request.knowledge_base_ids[0]}, 类型: {type(request.knowledge_base_ids[0])}")
                 
                 # 创建RAG链
                 rag_chain = create_rag_chain(
@@ -288,8 +292,8 @@ async def stream_message(
 
             else:
                 # 普通模式：使用LangChain 1.0对话链
-                print(f"[DEBUG-CHAT] 普通模式 - 使用LangChain流式对话链")
-                print(f"[DEBUG-CHAT] 模型: {request.model}")
+                logger.debug(f"普通模式 - 使用LangChain流式对话链")
+                logger.debug(f"模型: {request.model}")
                 conversation_chain = create_conversation_chain(model=request.model)
                 
                 # 使用带思考过程的流式输出
@@ -739,7 +743,7 @@ async def run_rag_workflow_with_context(question: str, session_id: int, db: Sess
         return result
         
     except Exception as e:
-        print(f"RAG工作流执行失败: {str(e)}")
+        logger.error(f"RAG工作流执行失败: {str(e)}")
         # 降级到基础问答
         rag_chain = create_rag_chain(model=model)
         return rag_chain.invoke(question)

backend/src/graph/nodes.py

@@ -2,6 +2,7 @@
 LangGraph节点定义
 """
 import json
+import logging
 import re
 from typing import Dict, Any, List, TypedDict
 from langchain.schema import HumanMessage, AIMessage, SystemMessage
@@ -9,6 +10,8 @@ from ..llm.siliconflow import get_llm_client
 from ..rag.retrievers import KnowledgeBaseRetriever
 from ..rag.vector_store import get_vector_store
 
+logger = logging.getLogger(__name__)
+
 
 def _parse_json_from_response(text: str) -> dict:
     """从LLM响应中提取JSON，兼容markdown代码块包裹的情况"""
@@ -73,7 +76,7 @@ def analyze_question_node(state: GraphState) -> GraphState:
         return new_state
 
     except Exception as e:
-        print(f"问题分析失败: {str(e)}")
+        logger.error(f"问题分析失败: {str(e)}")
         new_state = state.copy()
         new_state["metadata"] = {**state["metadata"], "analysis": {
             "question_type": "通用",
@@ -138,9 +141,7 @@ def retrieve_knowledge_node(state: GraphState) -> GraphState:
         return new_state
         
     except Exception as e:
-        print(f"知识检索失败: {str(e)}")
-        import traceback
-        print(traceback.format_exc())
+        logger.error(f"知识检索失败: {str(e)}", exc_info=True)
         new_state = state.copy()
         new_state["retrieved_docs"] = []
         new_state["sources"] = []
@@ -186,7 +187,7 @@ def generate_answer_node(state: GraphState) -> GraphState:
         return new_state
         
     except Exception as e:
-        print(f"答案生成失败: {str(e)}")
+        logger.error(f"答案生成失败: {str(e)}")
         new_state = state.copy()
         new_state["answer"] = "抱歉，我无法生成合适的回答。请稍后重试。"
         return new_state
@@ -208,5 +209,5 @@ def format_response_node(state: GraphState) -> GraphState:
         return new_state
         
     except Exception as e:
-        print(f"响应格式化失败: {str(e)}")
+        logger.error(f"响应格式化失败: {str(e)}")
         return state

backend/src/graph/qa_graph.py

@@ -1,10 +1,13 @@
 """
 问答LangGraph工作流
 """
+import logging
 from typing import Dict, Any, Optional, List
 from langgraph.graph import StateGraph, END
 from .nodes import GraphState, analyze_question_node, retrieve_knowledge_node, generate_answer_node, format_response_node
 
+logger = logging.getLogger(__name__)
+
 
 def create_qa_graph() -> StateGraph:
     """创建问答图"""
@@ -57,7 +60,7 @@ def run_qa_workflow(question: str, knowledge_base_ids: Optional[List[int]] = Non
         }
         
     except Exception as e:
-        print(f"问答工作流执行失败: {str(e)}")
+        logger.error(f"问答工作流执行失败: {str(e)}")
         return {
             "answer": "抱歉，处理您的问题时出现了错误。请稍后重试。",
             "sources": [],

backend/src/llm/siliconflow.py

@@ -1,6 +1,7 @@
 """
 大模型API集成 — 支持 SiliconFlow 和 DeepSeek 官方 + 视觉模型
 """
+import logging
 import os
 import base64
 from typing import List, Dict, Any, Optional, AsyncGenerator, Tuple
@@ -12,6 +13,8 @@ import openai
 
 from ..core.config import get_settings
 
+logger = logging.getLogger(__name__)
+
 settings = get_settings()
 
 # 图片描述提示词
@@ -56,7 +59,7 @@ class SiliconFlowLLM:
         api_key, base_url, resolved_model = _resolve_provider(raw_model)
 
         self.model_name = resolved_model
-        print(f"[LLM] 模型: {resolved_model}, API: {base_url}")
+        logger.info(f"模型: {resolved_model}, API: {base_url}")
 
         self.llm = ChatOpenAI(
             model=resolved_model,
@@ -210,7 +213,7 @@ class SiliconFlowLLM:
                 return response.choices[0].message.content or ""
 
             except Exception as e:
-                print(f"[VLM] 描述失败 attempt={attempt+1}: {e}")
+                logger.warning(f"描述失败 attempt={attempt+1}: {e}")
                 if attempt < max_retries - 1:
                     await asyncio.sleep(2 ** attempt)
 

backend/src/migrations/migrate_orphaned_documents.py

@@ -1,12 +1,15 @@
 """
 迁移孤立文档到默认知识库
 """
+import logging
 from sqlalchemy.orm import Session
 from ..core.database import get_db
 from ..models.user import User
 from ..models.knowledge_base import KnowledgeBase
 from ..models.document import Document
 
+logger = logging.getLogger(__name__)
+
 
 def migrate_orphaned_documents():
     """将没有知识库的文档迁移到用户的默认知识库"""
@@ -40,12 +43,12 @@ def migrate_orphaned_documents():
                     doc.knowledge_base_id = default_kb.id
                 
                 db.commit()
-                print(f"用户 {user.username} 的 {len(orphaned_docs)} 个文档已迁移到默认知识库")
+                logger.info(f"用户 {user.username} 的 {len(orphaned_docs)} 个文档已迁移到默认知识库")
         
-        print("孤立文档迁移完成")
+        logger.info("孤立文档迁移完成")
         
     except Exception as e:
-        print(f"迁移失败: {str(e)}")
+        logger.error(f"迁移失败: {str(e)}")
         db.rollback()
     finally:
         db.close()

backend/src/rag/chains.py

@@ -1,6 +1,7 @@
 """
 RAG检索链（LangChain 1.0）
 """
+import logging
 from typing import List, Optional, Dict, Any
 from langchain_core.runnables import RunnablePassthrough, RunnableLambda
 from langchain_core.prompts import ChatPromptTemplate
@@ -11,6 +12,8 @@ from .retrievers import KnowledgeBaseRetriever
 from .vector_store import get_vector_store
 from ..llm.siliconflow import get_llm_client
 
+logger = logging.getLogger(__name__)
+
 class RAGChain:
     """RAG问答链（LangChain 1.0标准API）"""
     
@@ -31,7 +34,7 @@ class RAGChain:
             score_threshold: 相似度阈值
             model: 可选的模型名称，如 deepseek-ai/DeepSeek-V3, Qwen/QwQ-32B
         """
-        print(f"[DEBUG-RAGChain] 初始化，knowledge_base_ids: {knowledge_base_ids}, model: {model}")
+        logger.debug(f"初始化RAG链，knowledge_base_ids: {knowledge_base_ids}, model: {model}")
         _sf_client = get_llm_client(model=model)
         self.llm = _sf_client.llm
         self.client = _sf_client
@@ -46,7 +49,7 @@ class RAGChain:
             search_kwargs={"k": k},
             score_threshold=score_threshold
         )
-        print(f"[DEBUG-RAGChain] 检索器创建完成，knowledge_base_ids: {self.retriever.knowledge_base_ids}")
+        logger.debug(f"检索器创建完成，knowledge_base_ids: {self.retriever.knowledge_base_ids}")
         
         # 创建Prompt
         self.prompt = create_rag_prompt()

backend/src/rag/document_loaders.py

@@ -1,6 +1,7 @@
 """
 LangChain 1.0 文档加载器封装 + PDF图片提取
 """
+import logging
 from typing import List, Optional, Dict
 from pathlib import Path
 import fitz  # pymupdf
@@ -12,6 +13,8 @@ from langchain_community.document_loaders import (
 )
 from langchain_core.documents import Document
 
+logger = logging.getLogger(__name__)
+
 
 class PDFImageExtractor:
     """使用pymupdf从PDF中提取内嵌图片"""
@@ -59,7 +62,7 @@ class PDFImageExtractor:
                         "size": len(image_bytes),
                     })
                 except Exception as e:
-                    print(f"[ImageExtractor] 提取图片失败 page={page_num+1} img={img_idx}: {e}")
+                    logger.warning(f"提取图片失败 page={page_num+1} img={img_idx}: {e}")
                     continue
 
         doc.close()

backend/src/rag/embeddings.py

@@ -1,12 +1,15 @@
 """
 嵌入模型管理
 """
+import logging
 from typing import List
 from sentence_transformers import SentenceTransformer
 import numpy as np
 
 from ..core.config import get_settings
 
+logger = logging.getLogger(__name__)
+
 settings = get_settings()
 
 
@@ -23,7 +26,7 @@ class EmbeddingModel:
         """加载嵌入模型"""
         try:
             self.model = SentenceTransformer(self.model_name)
-            print(f"嵌入模型 {self.model_name} 加载成功")
+            logger.info(f"嵌入模型 {self.model_name} 加载成功")
         except Exception as e:
             raise Exception(f"嵌入模型加载失败: {str(e)}")
     

backend/src/rag/retriever.py

@@ -1,10 +1,13 @@
 """
 文档检索器
 """
+import logging
 from typing import List, Dict, Any, Optional
 from .vector_store import get_vector_store
 from .embeddings import get_embedding_model
 
+logger = logging.getLogger(__name__)
+
 
 class DocumentRetriever:
     """文档检索器"""
@@ -23,7 +26,7 @@ class DocumentRetriever:
     ) -> List[Dict[str, Any]]:
         """检索相关文档"""
         try:
-            print(f"[DEBUG-RETRIEVER] 开始检索 - query: {query[:50]}..., filter_metadata: {filter_metadata}")
+            logger.debug(f"开始检索 - query: {query[:50]}..., filter_metadata: {filter_metadata}")
             
             # 执行向量搜索
             results = self.vector_store.search(
@@ -31,19 +34,19 @@ class DocumentRetriever:
                 n_results=top_k,
                 filter_metadata=filter_metadata
             )
-            print(f"[DEBUG-RETRIEVER] 向量搜索返回结果数量: {len(results)}")
+            logger.debug(f"向量搜索返回结果数量: {len(results)}")
             
             # 过滤低分结果
             filtered_results = [
                 result for result in results 
                 if result.get("distance", 1.0) <= (1 - score_threshold)
             ]
-            print(f"[DEBUG-RETRIEVER] 过滤后结果数量: {len(filtered_results)}")
+            logger.debug(f"过滤后结果数量: {len(filtered_results)}")
             
             return filtered_results
             
         except Exception as e:
-            print(f"文档检索失败: {str(e)}")
+            logger.error(f"文档检索失败: {str(e)}")
             return []
     
     def retrieve_by_document_id(self, document_id: str) -> List[Dict[str, Any]]:
@@ -56,7 +59,7 @@ class DocumentRetriever:
             )
             return results
         except Exception as e:
-            print(f"按文档ID检索失败: {str(e)}")
+            logger.error(f"按文档ID检索失败: {str(e)}")
             return []
     
     def get_relevant_context(self, query: str, max_length: int = 2000) -> str:

backend/src/rag/retrievers.py

@@ -1,10 +1,13 @@
 """
 自定义知识库检索器（LangChain 1.0）
 """
+import logging
 from typing import List, Optional
-import math
+
+logger = logging.getLogger(__name__)
 from langchain_core.documents import Document
 from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun
+from .score_utils import convert_distance_to_score
 from langchain_core.retrievers import BaseRetriever
 
 class KnowledgeBaseRetriever(BaseRetriever):
@@ -23,16 +26,16 @@ class KnowledgeBaseRetriever(BaseRetriever):
         run_manager: CallbackManagerForRetrieverRun
     ) -> List[Document]:
         """获取相关文档（LangChain 1.0标准接口）"""
-        print(f"[DEBUG-Retriever] 查询: {query}")
-        print(f"[DEBUG-Retriever] knowledge_base_ids: {self.knowledge_base_ids}")
+        logger.debug(f"查询: {query}")
+        logger.debug(f"knowledge_base_ids: {self.knowledge_base_ids}")
         
         # 构建知识库过滤条件
         filter_dict = None
         if self.knowledge_base_ids:
             filter_dict = {"knowledge_base_id": {"$in": self.knowledge_base_ids}}
-            print(f"[DEBUG-Retriever] 构建的过滤条件: {filter_dict}")
+            logger.debug(f"构建的过滤条件: {filter_dict}")
         else:
-            print(f"[DEBUG-Retriever] 没有知识库ID，不进行过滤")
+            logger.debug("没有知识库ID，不进行过滤")
         
         # 执行搜索
         if self.search_type == "similarity":
@@ -41,21 +44,21 @@ class KnowledgeBaseRetriever(BaseRetriever):
                 k=self.search_kwargs.get("k", 5),
                 filter=filter_dict
             )
-            print(f"[DEBUG-Retriever] 搜索返回文档数量: {len(docs_and_scores)}")
+            logger.debug(f"搜索返回文档数量: {len(docs_and_scores)}")
             
             # 打印每个文档的知识库ID
             for i, (doc, distance) in enumerate(docs_and_scores):
                 kb_id = doc.metadata.get("knowledge_base_id", "未知")
-                print(f"[DEBUG-Retriever] 文档{i+1}: knowledge_base_id={kb_id}, distance={distance:.4f}")
+                logger.debug(f"文档{i+1}: knowledge_base_id={kb_id}, distance={distance:.4f}")
             
             # 转换距离为分数并过滤
             filtered_docs = []
             for doc, distance in docs_and_scores:
-                score = self._convert_distance_to_score(distance)
+                score = convert_distance_to_score(distance)
                 if score > self.score_threshold:
                     filtered_docs.append(doc)
             
-            print(f"[DEBUG-Retriever] 过滤后文档数量: {len(filtered_docs)}")
+            logger.debug(f"过滤后文档数量: {len(filtered_docs)}")
             return filtered_docs
         
         elif self.search_type == "mmr":
@@ -67,16 +70,3 @@ class KnowledgeBaseRetriever(BaseRetriever):
             )
         
         return []
-    
-    def _convert_distance_to_score(self, distance: float) -> float:
-        """将ChromaDB的distance转换为0-1范围的相似度分数"""
-        # 内积距离（负值）
-        if distance < 0:
-            return (1 + distance) / 2
-        
-        # 大距离使用对数缩放
-        if distance > 100:
-            return 1 / (1 + math.log(distance))
-        
-        # 标准距离转换
-        return 1 / (1 + distance)

backend/src/rag/vector_store.py

@@ -2,6 +2,7 @@
 LangChain 1.0 向量存储封装
 """
 import os
+import logging
 import json
 import hashlib
 from typing import List, Dict, Any, Optional
@@ -12,6 +13,8 @@ from langchain_core.documents import Document as LangChainDocument
 from ..core.config import get_settings
 from .embeddings import get_embedding_model
 
+logger = logging.getLogger(__name__)
+
 settings = get_settings()
 
 
@@ -40,7 +43,7 @@ class VectorStore:
             self.vectorstore.add_documents(documents)
             return True
         except Exception as e:
-            print(f"添加文档失败: {str(e)}")
+            logger.error(f"添加文档失败: {str(e)}")
             return False
     
     def as_retriever(self, **kwargs):
@@ -54,7 +57,7 @@ class VectorStore:
         filter: Optional[Dict] = None
     ):
         """相似度搜索（带分数）"""
-        print(f"[DEBUG-VectorStore] 查询参数 - k: {k}, filter: {filter}")
+        logger.debug(f"查询参数 - k: {k}, filter: {filter}")
         
         result = self.vectorstore.similarity_search_with_score(
             query=query,
@@ -62,7 +65,7 @@ class VectorStore:
             filter=filter
         )
         
-        print(f"[DEBUG-VectorStore] 返回结果数量: {len(result)}")
+        logger.debug(f"返回结果数量: {len(result)}")
         return result
     
     def delete_by_document_id(self, document_id: int) -> bool:
@@ -73,7 +76,7 @@ class VectorStore:
             )
             return True
         except Exception as e:
-            print(f"删除向量数据失败: {str(e)}")
+            logger.error(f"删除向量数据失败: {str(e)}")
             return False
 
     def max_marginal_relevance_search(

backend/src/services/analytics_service.py

@@ -2,12 +2,14 @@
 学习分析服务
 提供用户学习数据的统计和分析功能
 """
-
+import logging
 from typing import Dict, Any, List
 from sqlalchemy.orm import Session
 from sqlalchemy import func, distinct, and_
 from datetime import datetime, timedelta
 
+logger = logging.getLogger(__name__)
+
 from ..models.user import User
 from ..models.chat import ChatSession, ChatMessage
 from ..models.document import Document
@@ -65,7 +67,7 @@ class AnalyticsService:
             }
             
         except Exception as e:
-            print(f"[ERROR] 获取用户统计数据失败: {str(e)}")
+            logger.error(f"获取用户统计数据失败: {str(e)}")
             raise Exception(f"获取统计数据失败: {str(e)}")
     
     def get_user_learning_trends(self, user_id: int, days: int = 30) -> List[Dict[str, Any]]:
@@ -107,7 +109,7 @@ class AnalyticsService:
             return trends
             
         except Exception as e:
-            print(f"[ERROR] 获取学习趋势数据失败: {str(e)}")
+            logger.error(f"获取学习趋势数据失败: {str(e)}")
             raise Exception(f"获取学习趋势失败: {str(e)}")
     
     def get_popular_questions(self, user_id: int, limit: int = 10) -> List[Dict[str, Any]]:
@@ -141,7 +143,7 @@ class AnalyticsService:
             return popular_questions
             
         except Exception as e:
-            print(f"[ERROR] 获取热门问题失败: {str(e)}")
+            logger.error(f"获取热门问题失败: {str(e)}")
             raise Exception(f"获取热门问题失败: {str(e)}")
     
     def get_knowledge_coverage(self, user_id: int) -> List[Dict[str, Any]]:
@@ -160,7 +162,7 @@ class AnalyticsService:
             return coverage_data
             
         except Exception as e:
-            print(f"[ERROR] 获取知识覆盖度失败: {str(e)}")
+            logger.error(f"获取知识覆盖度失败: {str(e)}")
             raise Exception(f"获取知识覆盖度失败: {str(e)}")
     
     def get_learning_report(self, user_id: int) -> Dict[str, Any]:
@@ -211,5 +213,5 @@ class AnalyticsService:
             }
             
         except Exception as e:
-            print(f"[ERROR] 获取学习报告失败: {str(e)}")
+            logger.error(f"获取学习报告失败: {str(e)}")
             raise Exception(f"获取学习报告失败: {str(e)}")

backend/src/services/auth_service.py

@@ -1,6 +1,7 @@
 """
 用户认证服务
 """
+import logging
 from datetime import datetime, timedelta
 from typing import Optional, Dict, Any
 from sqlalchemy.orm import Session
@@ -10,6 +11,8 @@ from ..models.user import User
 from ..core.security import get_password_hash, verify_password, create_access_token
 from ..core.config import get_settings
 
+logger = logging.getLogger(__name__)
+
 settings = get_settings()
 
 
@@ -58,7 +61,7 @@ class AuthService:
             
         except Exception as e:
             self.db.rollback()
-            print(f"创建用户失败: {str(e)}")
+            logger.error(f"创建用户失败: {str(e)}")
             return None
     
     def authenticate_user(self, username: str, password: str) -> Optional[User]:
@@ -85,7 +88,7 @@ class AuthService:
             return user
             
         except Exception as e:
-            print(f"用户认证失败: {str(e)}")
+            logger.error(f"用户认证失败: {str(e)}")
             return None
     
     def get_user_by_username(self, username: str) -> Optional[User]:
@@ -117,7 +120,7 @@ class AuthService:
             
         except Exception as e:
             self.db.rollback()
-            print(f"更新用户失败: {str(e)}")
+            logger.error(f"更新用户失败: {str(e)}")
             return None
     
     def deactivate_user(self, user_id: int) -> bool:
@@ -133,7 +136,7 @@ class AuthService:
             
         except Exception as e:
             self.db.rollback()
-            print(f"停用用户失败: {str(e)}")
+            logger.error(f"停用用户失败: {str(e)}")
             return False
     
     def change_password(self, user_id: int, old_password: str, new_password: str) -> bool:
@@ -152,7 +155,7 @@ class AuthService:
             
         except Exception as e:
             self.db.rollback()
-            print(f"修改密码失败: {str(e)}")
+            logger.error(f"修改密码失败: {str(e)}")
             return False
     
     def create_access_token_for_user(self, user: User) -> Dict[str, Any]:
@@ -193,7 +196,7 @@ class AuthService:
             }
             
         except Exception as e:
-            print(f"获取用户统计失败: {str(e)}")
+            logger.error(f"获取用户统计失败: {str(e)}")
             return {
                 "total_users": 0,
                 "active_users": 0,

backend/src/services/book_content_service.py

@@ -3,6 +3,7 @@
 根据数据库中的行号范围从LaTeX文件动态读取内容
 层级结构：书籍 -> Chapter -> Section -> Subsection（知识点）
 """
+import logging
 from pathlib import Path
 from typing import Optional
 from sqlalchemy.orm import Session
@@ -10,6 +11,8 @@ from sqlalchemy.orm import Session
 from ..models.book_structure import Chapter, Section, Subsection
 from .latex_parser import LaTeXParser
 
+logger = logging.getLogger(__name__)
+
 
 class BookContentService:
     """书籍内容服务"""
@@ -59,7 +62,7 @@ class BookContentService:
             )
             return content
         except Exception as e:
-            print(f"读取章节内容失败: {e}")
+            logger.error(f"读取章节内容失败: {e}")
             return None
     
     def get_section_content(self, db: Session, section_id: int) -> Optional[str]:
@@ -91,7 +94,7 @@ class BookContentService:
             )
             return content
         except Exception as e:
-            print(f"读取节内容失败: {e}")
+            logger.error(f"读取节内容失败: {e}")
             return None
     
     def get_subsection_content(self, db: Session, subsection_id: int) -> Optional[str]:
@@ -127,6 +130,6 @@ class BookContentService:
             )
             return content
         except Exception as e:
-            print(f"读取小节内容失败: {e}")
+            logger.error(f"读取小节内容失败: {e}")
             return None
 

backend/src/services/file_watcher_service.py

@@ -3,6 +3,7 @@
 """
 import os
 import time
+import logging
 import threading
 from pathlib import Path
 from typing import Optional, Callable
@@ -13,6 +14,7 @@ from ..core.config import get_settings
 from ..core.database import get_db
 from .knowledge_base_service import KnowledgeBaseService
 
+logger = logging.getLogger(__name__)
 settings = get_settings()
 
 
@@ -27,19 +29,19 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
     def on_created(self, event):
         """处理文件创建事件"""
         if not event.is_directory and self._is_supported_file(event.src_path):
-            print(f"检测到新文件: {event.src_path}")
+            logger.info(f"检测到新文件: {event.src_path}")
             self._process_file_async(event.src_path, "created")
     
     def on_modified(self, event):
         """处理文件修改事件"""
         if not event.is_directory and self._is_supported_file(event.src_path):
-            print(f"检测到文件修改: {event.src_path}")
+            logger.info(f"检测到文件修改: {event.src_path}")
             self._process_file_async(event.src_path, "modified")
     
     def on_deleted(self, event):
         """处理文件删除事件"""
         if not event.is_directory and self._is_supported_file(event.src_path):
-            print(f"检测到文件删除: {event.src_path}")
+            logger.info(f"检测到文件删除: {event.src_path}")
             self._handle_file_deletion(event.src_path)
     
     def _is_supported_file(self, file_path: str) -> bool:
@@ -54,10 +56,10 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
                 time.sleep(1)
                 
                 result = self.kb_service.process_file(file_path)
-                print(f"文件处理结果 ({event_type}): {result}")
+                logger.info(f"文件处理结果 ({event_type}): {result}")
                 
             except Exception as e:
-                print(f"处理文件失败: {file_path}, 错误: {str(e)}")
+                logger.error(f"处理文件失败: {file_path}, 错误: {str(e)}")
         
         # 在后台线程中处理
         thread = threading.Thread(target=process)
@@ -80,12 +82,12 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
             
             if document:
                 result = self.kb_service.delete_document(document.id)
-                print(f"文件删除处理结果: {result}")
+                logger.info(f"文件删除处理结果: {result}")
             else:
-                print(f"未找到对应的数据库记录: {file_path}")
+                logger.info(f"未找到对应的数据库记录: {file_path}")
                 
         except Exception as e:
-            print(f"处理文件删除失败: {file_path}, 错误: {str(e)}")
+            logger.error(f"处理文件删除失败: {file_path}, 错误: {str(e)}")
 
 
 class FileWatcherService:
@@ -99,15 +101,15 @@ class FileWatcherService:
     def start(self):
         """启动文件监控"""
         if self.is_running:
-            print("文件监控服务已在运行")
+            logger.info("文件监控服务已在运行")
             return
         
         if not settings.enable_file_watcher:
-            print("文件监控服务已禁用")
+            logger.info("文件监控服务已禁用")
             return
         
         if not self.knowledge_base_dir.exists():
-            print(f"知识库目录不存在: {self.knowledge_base_dir}")
+            logger.info(f"知识库目录不存在: {self.knowledge_base_dir}")
             return
         
         try:
@@ -130,19 +132,19 @@ class FileWatcherService:
             self.observer.start()
             self.is_running = True
             
-            print(f"文件监控服务已启动，监控目录: {self.knowledge_base_dir}")
+            logger.info(f"文件监控服务已启动，监控目录: {self.knowledge_base_dir}")
             
             # 确保子目录对应的系统知识库存在
-            print("确保系统知识库与目录同步...")
+            logger.info("确保系统知识库与目录同步...")
             kb_service.ensure_system_knowledge_bases()
 
             # 执行初始扫描
-            print("执行初始知识库扫描...")
+            logger.info("执行初始知识库扫描...")
             scan_result = kb_service.scan_directory()
-            print(f"初始扫描结果: {scan_result}")
+            logger.info(f"初始扫描结果: {scan_result}")
             
         except Exception as e:
-            print(f"启动文件监控服务失败: {str(e)}")
+            logger.error(f"启动文件监控服务失败: {str(e)}")
             self.is_running = False
     
     def stop(self):
@@ -151,7 +153,7 @@ class FileWatcherService:
             self.observer.stop()
             self.observer.join()
             self.is_running = False
-            print("文件监控服务已停止")
+            logger.info("文件监控服务已停止")
     
     def is_active(self) -> bool:
         """检查监控服务是否活跃"""

backend/src/services/image_generation_service.py

@@ -4,12 +4,15 @@
 """
 
 import base64
+import logging
 import uuid
 from pathlib import Path
 from typing import Dict, Any
 import httpx
 from src.core.config import settings
 
+logger = logging.getLogger(__name__)
+
 
 class ImageGenerationService:
     """统一的图像生成服务基类"""
@@ -21,9 +24,9 @@ class ImageGenerationService:
     
     async def call_api(self, model: str, payload: dict) -> dict:
         """调用硅基流动 API"""
-        print(f"[DEBUG] 调用SiliconFlow API: {self.base_url}")
-        print(f"[DEBUG] 模型: {model}")
-        print(f"[DEBUG] 请求参数: {payload}")
+        logger.debug(f"调用SiliconFlow API: {self.base_url}")
+        logger.debug(f"模型: {model}")
+        logger.debug(f"请求参数: {payload}")
         
         async with httpx.AsyncClient(timeout=self.timeout) as client:
             response = await client.post(
@@ -37,9 +40,9 @@ class ImageGenerationService:
             response.raise_for_status()
             
             result = response.json()
-            print(f"[DEBUG] API响应状态: {response.status_code}")
-            print(f"[DEBUG] API响应类型: {type(result)}")
-            print(f"[DEBUG] API响应键: {list(result.keys()) if isinstance(result, dict) else '非字典类型'}")
+            logger.debug(f"API响应状态: {response.status_code}")
+            logger.debug(f"API响应类型: {type(result)}")
+            logger.debug(f"API响应键: {list(result.keys()) if isinstance(result, dict) else '非字典类型'}")
             
             return result
     
@@ -53,7 +56,7 @@ class ImageGenerationService:
             # 移除可能的空白字符
             base64_data = base64_data.strip()
             
-            print(f"[DEBUG] 开始解码base64数据，长度: {len(base64_data)}")
+            logger.debug(f"开始解码base64数据，长度: {len(base64_data)}")
             
             # 解码 base64 数据
             image_bytes = base64.b64decode(base64_data)
@@ -62,7 +65,7 @@ class ImageGenerationService:
             if len(image_bytes) == 0:
                 raise Exception("解码后的图像数据为空")
             
-            print(f"[DEBUG] 图像数据大小: {len(image_bytes)} bytes")
+            logger.debug(f"图像数据大小: {len(image_bytes)} bytes")
             
             # 确保目录存在
             image_dir = Path(settings.generated_images_dir)
@@ -73,13 +76,13 @@ class ImageGenerationService:
             with open(image_path, "wb") as f:
                 f.write(image_bytes)
             
-            print(f"[DEBUG] 图像已保存到: {image_path}")
+            logger.debug(f"图像已保存到: {image_path}")
             
             return str(image_path)
         except Exception as e:
-            print(f"[ERROR] 保存图像失败: {str(e)}")
-            print(f"[ERROR] base64数据长度: {len(base64_data) if base64_data else 0}")
-            print(f"[ERROR] base64数据前100字符: {base64_data[:100] if base64_data else 'None'}")
+            logger.error(f"保存图像失败: {str(e)}")
+            logger.error(f"base64数据长度: {len(base64_data) if base64_data else 0}")
+            logger.error(f"base64数据前100字符: {base64_data[:100] if base64_data else 'None'}")
             raise Exception(f"保存图像失败: {str(e)}")
     
     def generate_image_id(self) -> str:

backend/src/services/image_to_image_service.py

@@ -4,12 +4,15 @@
 """
 
 import base64
+import logging
 import httpx
 from typing import List, Dict, Any, Optional
 from pathlib import Path
 from fastapi import UploadFile
 from .image_generation_service import ImageGenerationService
 
+logger = logging.getLogger(__name__)
+
 
 class ImageToImageService(ImageGenerationService):
     """图生图服务"""
@@ -59,70 +62,70 @@ class ImageToImageService(ImageGenerationService):
             result = await self.call_api(self.MODEL, payload)
             
             # 调试信息
-            print(f"API响应结构: {type(result)}")
+            logger.debug(f"API响应结构: {type(result)}")
             if isinstance(result, dict):
-                print(f"响应键: {list(result.keys())}")
+                logger.debug(f"响应键: {list(result.keys())}")
                 if "images" in result:
-                    print(f"图像数量: {len(result['images'])}")
+                    logger.debug(f"图像数量: {len(result['images'])}")
                     if result["images"]:
-                        print(f"第一个图像键: {list(result['images'][0].keys()) if isinstance(result['images'][0], dict) else '非字典类型'}")
-            
+                        logger.debug(f"第一个图像键: {list(result['images'][0].keys()) if isinstance(result['images'][0], dict) else '非字典类型'}")
+
             # 保存结果
             image_id = self.generate_image_id()
             edited_image_data = result["images"][0]
-            
+
             # 检查是否为字典类型
             if isinstance(edited_image_data, dict):
-                print(f"[DEBUG] 图像数据是字典，键: {list(edited_image_data.keys())}")
-                
+                logger.debug(f"图像数据是字典，键: {list(edited_image_data.keys())}")
+
                 # 优先检查URL字段
                 if "url" in edited_image_data:
                     image_url = edited_image_data["url"]
-                    print(f"[DEBUG] 检测到URL字段: {image_url}")
+                    logger.info(f"检测到URL字段: {image_url}")
                     try:
                         image_path = await self.download_image_from_url(image_id, image_url)
-                        print(f"[DEBUG] URL下载成功: {image_path}")
+                        logger.info(f"URL下载成功: {image_path}")
                     except Exception as e:
-                        print(f"[ERROR] URL下载失败: {str(e)}")
+                        logger.error(f"URL下载失败: {str(e)}")
                         raise Exception(f"下载图像失败: {str(e)}")
-                
+
                 # 如果没有URL，尝试base64字段
                 elif any(key in edited_image_data for key in ["b64_json", "b64", "data"]):
                     image_b64 = edited_image_data.get("b64_json") or edited_image_data.get("b64") or edited_image_data.get("data")
-                    print(f"[DEBUG] 检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
+                    logger.debug(f"检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
                     try:
                         image_path = self.save_image(image_id, image_b64)
-                        print(f"[DEBUG] base64保存成功: {image_path}")
+                        logger.info(f"base64保存成功: {image_path}")
                     except Exception as e:
-                        print(f"[ERROR] base64保存失败: {str(e)}")
+                        logger.error(f"base64保存失败: {str(e)}")
                         raise Exception(f"保存图像失败: {str(e)}")
-                
+
                 else:
-                    print(f"[ERROR] 未找到有效的图像数据字段")
+                    logger.error(f"未找到有效的图像数据字段")
                     raise Exception("API响应中未找到有效的图像数据")
-            
+
             # 如果直接是字符串，判断是URL还是base64
             elif isinstance(edited_image_data, str):
-                print(f"[DEBUG] 图像数据是字符串，长度: {len(edited_image_data)}")
+                logger.debug(f"图像数据是字符串，长度: {len(edited_image_data)}")
                 if edited_image_data.startswith('http'):
-                    print(f"[DEBUG] 检测到URL字符串: {edited_image_data}")
+                    logger.info(f"检测到URL字符串: {edited_image_data}")
                     try:
                         image_path = await self.download_image_from_url(image_id, edited_image_data)
-                        print(f"[DEBUG] URL下载成功: {image_path}")
+                        logger.info(f"URL下载成功: {image_path}")
                     except Exception as e:
-                        print(f"[ERROR] URL下载失败: {str(e)}")
+                        logger.error(f"URL下载失败: {str(e)}")
                         raise Exception(f"下载图像失败: {str(e)}")
                 else:
-                    print(f"[DEBUG] 检测到base64字符串")
+                    logger.debug(f"检测到base64字符串")
                     try:
                         image_path = self.save_image(image_id, edited_image_data)
-                        print(f"[DEBUG] base64保存成功: {image_path}")
+                        logger.info(f"base64保存成功: {image_path}")
                     except Exception as e:
-                        print(f"[ERROR] base64保存失败: {str(e)}")
+                        logger.error(f"base64保存失败: {str(e)}")
                         raise Exception(f"保存图像失败: {str(e)}")
-            
+
             else:
-                print(f"[ERROR] 未知的图像数据类型: {type(edited_image_data)}")
+                logger.error(f"未知的图像数据类型: {type(edited_image_data)}")
                 raise Exception(f"不支持的图像数据类型: {type(edited_image_data)}")
             
             return {
@@ -165,70 +168,70 @@ class ImageToImageService(ImageGenerationService):
             result = await self.call_api(self.MODEL, payload)
             
             # 调试信息
-            print(f"API响应结构: {type(result)}")
+            logger.debug(f"API响应结构: {type(result)}")
             if isinstance(result, dict):
-                print(f"响应键: {list(result.keys())}")
+                logger.debug(f"响应键: {list(result.keys())}")
                 if "images" in result:
-                    print(f"图像数量: {len(result['images'])}")
-            
+                    logger.debug(f"图像数量: {len(result['images'])}")
+
             # 处理变体结果
             variations = []
             for i, img_data in enumerate(result["images"]):
-                print(f"[DEBUG] 处理第 {i+1} 个变体")
+                logger.debug(f"处理第 {i+1} 个变体")
                 image_id = self.generate_image_id()
-                
+
                 # 检查是否为字典类型
                 if isinstance(img_data, dict):
-                    print(f"[DEBUG] 图像数据是字典，键: {list(img_data.keys())}")
-                    
+                    logger.debug(f"图像数据是字典，键: {list(img_data.keys())}")
+
                     # 优先检查URL字段
                     if "url" in img_data:
                         image_url = img_data["url"]
-                        print(f"[DEBUG] 检测到URL字段: {image_url}")
+                        logger.info(f"检测到URL字段: {image_url}")
                         try:
                             image_path = await self.download_image_from_url(image_id, image_url)
-                            print(f"[DEBUG] URL下载成功: {image_path}")
+                            logger.info(f"URL下载成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] URL下载失败: {str(e)}")
+                            logger.error(f"URL下载失败: {str(e)}")
                             raise Exception(f"下载图像失败: {str(e)}")
-                    
+
                     # 如果没有URL，尝试base64字段
                     elif any(key in img_data for key in ["b64_json", "b64", "data"]):
                         image_b64 = img_data.get("b64_json") or img_data.get("b64") or img_data.get("data")
-                        print(f"[DEBUG] 检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
+                        logger.debug(f"检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
                         try:
                             image_path = self.save_image(image_id, image_b64)
-                            print(f"[DEBUG] base64保存成功: {image_path}")
+                            logger.info(f"base64保存成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] base64保存失败: {str(e)}")
+                            logger.error(f"base64保存失败: {str(e)}")
                             raise Exception(f"保存图像失败: {str(e)}")
-                    
+
                     else:
-                        print(f"[ERROR] 未找到有效的图像数据字段")
+                        logger.error(f"未找到有效的图像数据字段")
                         raise Exception("API响应中未找到有效的图像数据")
-                
+
                 # 如果直接是字符串，判断是URL还是base64
                 elif isinstance(img_data, str):
-                    print(f"[DEBUG] 图像数据是字符串，长度: {len(img_data)}")
+                    logger.debug(f"图像数据是字符串，长度: {len(img_data)}")
                     if img_data.startswith('http'):
-                        print(f"[DEBUG] 检测到URL字符串: {img_data}")
+                        logger.info(f"检测到URL字符串: {img_data}")
                         try:
                             image_path = await self.download_image_from_url(image_id, img_data)
-                            print(f"[DEBUG] URL下载成功: {image_path}")
+                            logger.info(f"URL下载成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] URL下载失败: {str(e)}")
+                            logger.error(f"URL下载失败: {str(e)}")
                             raise Exception(f"下载图像失败: {str(e)}")
                     else:
-                        print(f"[DEBUG] 检测到base64字符串")
+                        logger.debug(f"检测到base64字符串")
                         try:
                             image_path = self.save_image(image_id, img_data)
-                            print(f"[DEBUG] base64保存成功: {image_path}")
+                            logger.info(f"base64保存成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] base64保存失败: {str(e)}")
+                            logger.error(f"base64保存失败: {str(e)}")
                             raise Exception(f"保存图像失败: {str(e)}")
-                
+
                 else:
-                    print(f"[ERROR] 未知的图像数据类型: {type(img_data)}")
+                    logger.error(f"未知的图像数据类型: {type(img_data)}")
                     raise Exception(f"不支持的图像数据类型: {type(img_data)}")
                 
                 variations.append({
@@ -320,7 +323,7 @@ class ImageToImageService(ImageGenerationService):
     async def download_image_from_url(self, image_id: str, image_url: str) -> str:
         """从URL下载图像"""
         try:
-            print(f"[DEBUG] 下载图像URL: {image_url}")
+            logger.debug(f"下载图像URL: {image_url}")
             
             # 下载图像
             async with httpx.AsyncClient(timeout=30) as client:
@@ -331,7 +334,7 @@ class ImageToImageService(ImageGenerationService):
             if len(image_bytes) == 0:
                 raise Exception("下载的图像数据为空")
             
-            print(f"[DEBUG] 下载图像数据大小: {len(image_bytes)} bytes")
+            logger.debug(f"下载图像数据大小: {len(image_bytes)} bytes")
             
             # 确保目录存在
             image_dir = Path(self.get_image_dir())
@@ -342,11 +345,11 @@ class ImageToImageService(ImageGenerationService):
             with open(image_path, "wb") as f:
                 f.write(image_bytes)
             
-            print(f"[DEBUG] 图像已保存到: {image_path}")
+            logger.debug(f"图像已保存到: {image_path}")
             return str(image_path)
             
         except Exception as e:
-            print(f"[ERROR] 下载图像失败: {str(e)}")
+            logger.error(f"下载图像失败: {str(e)}")
             raise Exception(f"下载图像失败: {str(e)}")
     
     def get_image_dir(self) -> str:

backend/src/services/knowledge_base_service.py

@@ -1,6 +1,7 @@
 """
 知识库管理服务
 """
+import logging
 import os
 import hashlib
 from pathlib import Path
@@ -15,6 +16,8 @@ from ..models.user import User
 from ..core.config import get_settings
 from .document_service import DocumentService
 
+logger = logging.getLogger(__name__)
+
 settings = get_settings()
 
 
@@ -106,7 +109,7 @@ class KnowledgeBaseService:
                 existing.user_id = admin.id
             self.db.commit()
             self.db.refresh(existing)
-            print(f"[KB] 升级为系统知识库: {name} (id={existing.id})")
+            logger.info(f"升级为系统知识库: {name} (id={existing.id})")
             return existing.id
 
         # 找到 admin 用户（或任意 superuser）作为 owner
@@ -123,7 +126,7 @@ class KnowledgeBaseService:
         self.db.add(kb)
         self.db.commit()
         self.db.refresh(kb)
-        print(f"[KB] 自动创建系统知识库: {name} (id={kb.id})")
+        logger.info(f"自动创建系统知识库: {name} (id={kb.id})")
         return kb.id
 
     def _resolve_knowledge_base(self, file_path: Path) -> Optional[int]:
@@ -249,13 +252,13 @@ class KnowledgeBaseService:
                         loop.run_until_complete(self.document_service.process_document(document.id))
                         loop.close()
                     except Exception as e:
-                        print(f"后台处理文档 {document.id} 失败: {e}")
+                        logger.error(f"后台处理文档 {document.id} 失败: {e}")
 
                 thread = threading.Thread(target=process_in_background, daemon=True)
                 thread.start()
             except Exception as e:
-                print(f"启动文档处理线程失败: {e}")
-            
+                logger.error(f"启动文档处理线程失败: {e}")
+
             return {"status": "new", "document_id": document.id, "message": "文档创建成功，正在处理中"}
                 
         except Exception as e:
@@ -287,13 +290,13 @@ class KnowledgeBaseService:
                         loop.run_until_complete(self.document_service.process_document(document.id))
                         loop.close()
                     except Exception as e:
-                        print(f"后台处理文档 {document.id} 失败: {e}")
+                        logger.error(f"后台处理文档 {document.id} 失败: {e}")
 
                 thread = threading.Thread(target=process_in_background, daemon=True)
                 thread.start()
             except Exception as e:
-                print(f"启动文档处理线程失败: {e}")
-            
+                logger.error(f"启动文档处理线程失败: {e}")
+
             return {"status": "updated", "document_id": document.id, "message": "文档更新成功，正在重新处理中"}
                 
         except Exception as e:
@@ -482,7 +485,7 @@ class KnowledgeBaseService:
         all_files = [f for f in directory.rglob("*") if f.is_file() and self._is_supported_file(f)]
         total_files = len(all_files)
         
-        print(f"  找到 {total_files} 个支持的文件，开始处理...")
+        logger.info(f"找到 {total_files} 个支持的文件，开始处理...")
         
         for idx, file_path in enumerate(all_files, 1):
             try:
@@ -506,7 +509,7 @@ class KnowledgeBaseService:
                 # 显示进度（每10个文件或最后一个文件时显示）
                 if idx % 10 == 0 or idx == total_files:
                     percentage = (idx * 100) // total_files if total_files > 0 else 0
-                    print(f"\r  处理进度: {idx}/{total_files} ({percentage}%)", end="", flush=True)
+                    logger.info(f"处理进度: {idx}/{total_files} ({percentage}%)")
                 
                 if existing_doc:
                     # 检查是否需要更新
@@ -549,6 +552,6 @@ class KnowledgeBaseService:
                     "error": str(e)
                 })
         
-        print()  # 换行
+        logger.info("文件处理完成")
         results["success"] = len(results["errors"]) == 0
         return results

backend/src/services/text_to_image_service.py

@@ -3,12 +3,15 @@
 支持 Kwai-Kolors/Kolors 和 Qwen/Qwen-Image 模型
 """
 
+import logging
 import uuid
 import httpx
 from typing import List, Dict, Any
 from pathlib import Path
 from .image_generation_service import ImageGenerationService
 
+logger = logging.getLogger(__name__)
+
 
 class TextToImageService(ImageGenerationService):
     """文生图服务"""
@@ -73,72 +76,72 @@ class TextToImageService(ImageGenerationService):
             result = await self.call_api(self.MODELS[model], payload)
             
             # 调试信息
-            print(f"API响应结构: {type(result)}")
+            logger.debug(f"API响应结构: {type(result)}")
             if isinstance(result, dict):
-                print(f"响应键: {list(result.keys())}")
+                logger.debug(f"响应键: {list(result.keys())}")
                 if "images" in result:
-                    print(f"图像数量: {len(result['images'])}")
+                    logger.debug(f"图像数量: {len(result['images'])}")
                     if result["images"]:
-                        print(f"第一个图像键: {list(result['images'][0].keys()) if isinstance(result['images'][0], dict) else '非字典类型'}")
+                        logger.debug(f"第一个图像键: {list(result['images'][0].keys()) if isinstance(result['images'][0], dict) else '非字典类型'}")
             
             # 处理结果
             images = []
             for i, img_data in enumerate(result.get("images", [])):
-                print(f"[DEBUG] 处理第 {i+1} 张图像")
+                logger.debug(f"处理第 {i+1} 张图像")
                 image_id = self.generate_image_id()
                 
                 # 检查是否为字典类型
                 if isinstance(img_data, dict):
-                    print(f"[DEBUG] 图像数据是字典，键: {list(img_data.keys())}")
-                    
+                    logger.debug(f"图像数据是字典，键: {list(img_data.keys())}")
+
                     # 优先检查URL字段
                     if "url" in img_data:
                         image_url = img_data["url"]
-                        print(f"[DEBUG] 检测到URL字段: {image_url}")
+                        logger.info(f"检测到URL字段: {image_url}")
                         try:
                             image_path = await self.download_image_from_url(image_id, image_url)
-                            print(f"[DEBUG] URL下载成功: {image_path}")
+                            logger.info(f"URL下载成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] URL下载失败: {str(e)}")
+                            logger.error(f"URL下载失败: {str(e)}")
                             raise Exception(f"下载图像失败: {str(e)}")
-                    
+
                     # 如果没有URL，尝试base64字段
                     elif any(key in img_data for key in ["b64_json", "b64", "data"]):
                         image_b64 = img_data.get("b64_json") or img_data.get("b64") or img_data.get("data")
-                        print(f"[DEBUG] 检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
+                        logger.debug(f"检测到base64字段，长度: {len(image_b64) if image_b64 else 0}")
                         try:
                             image_path = self.save_image(image_id, image_b64)
-                            print(f"[DEBUG] base64保存成功: {image_path}")
+                            logger.info(f"base64保存成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] base64保存失败: {str(e)}")
+                            logger.error(f"base64保存失败: {str(e)}")
                             raise Exception(f"保存图像失败: {str(e)}")
-                    
+
                     else:
-                        print(f"[ERROR] 未找到有效的图像数据字段")
+                        logger.error(f"未找到有效的图像数据字段")
                         raise Exception("API响应中未找到有效的图像数据")
-                
+
                 # 如果直接是字符串，判断是URL还是base64
                 elif isinstance(img_data, str):
-                    print(f"[DEBUG] 图像数据是字符串，长度: {len(img_data)}")
+                    logger.debug(f"图像数据是字符串，长度: {len(img_data)}")
                     if img_data.startswith('http'):
-                        print(f"[DEBUG] 检测到URL字符串: {img_data}")
+                        logger.info(f"检测到URL字符串: {img_data}")
                         try:
                             image_path = await self.download_image_from_url(image_id, img_data)
-                            print(f"[DEBUG] URL下载成功: {image_path}")
+                            logger.info(f"URL下载成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] URL下载失败: {str(e)}")
+                            logger.error(f"URL下载失败: {str(e)}")
                             raise Exception(f"下载图像失败: {str(e)}")
                     else:
-                        print(f"[DEBUG] 检测到base64字符串")
+                        logger.debug(f"检测到base64字符串")
                         try:
                             image_path = self.save_image(image_id, img_data)
-                            print(f"[DEBUG] base64保存成功: {image_path}")
+                            logger.info(f"base64保存成功: {image_path}")
                         except Exception as e:
-                            print(f"[ERROR] base64保存失败: {str(e)}")
+                            logger.error(f"base64保存失败: {str(e)}")
                             raise Exception(f"保存图像失败: {str(e)}")
-                
+
                 else:
-                    print(f"[ERROR] 未知的图像数据类型: {type(img_data)}")
+                    logger.error(f"未知的图像数据类型: {type(img_data)}")
                     raise Exception(f"不支持的图像数据类型: {type(img_data)}")
                 
                 images.append({
@@ -182,7 +185,7 @@ class TextToImageService(ImageGenerationService):
     async def download_image_from_url(self, image_id: str, image_url: str) -> str:
         """从URL下载图像"""
         try:
-            print(f"[DEBUG] 下载图像URL: {image_url}")
+            logger.debug(f"下载图像URL: {image_url}")
             
             # 下载图像
             async with httpx.AsyncClient(timeout=30) as client:
@@ -193,7 +196,7 @@ class TextToImageService(ImageGenerationService):
             if len(image_bytes) == 0:
                 raise Exception("下载的图像数据为空")
             
-            print(f"[DEBUG] 下载图像数据大小: {len(image_bytes)} bytes")
+            logger.debug(f"下载图像数据大小: {len(image_bytes)} bytes")
             
             # 确保目录存在
             image_dir = Path(self.get_image_dir())
@@ -204,11 +207,11 @@ class TextToImageService(ImageGenerationService):
             with open(image_path, "wb") as f:
                 f.write(image_bytes)
             
-            print(f"[DEBUG] 图像已保存到: {image_path}")
+            logger.debug(f"图像已保存到: {image_path}")
             return str(image_path)
             
         except Exception as e:
-            print(f"[ERROR] 下载图像失败: {str(e)}")
+            logger.error(f"下载图像失败: {str(e)}")
             raise Exception(f"下载图像失败: {str(e)}")
     
     def get_image_dir(self) -> str: