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refactor: replace print() with structured logging across backend

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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>
This commit is contained in:
xiaopeng
2026-05-28 15:52:44 +08:00
parent 4bb50ae9c1
commit 37c0364e7e
19 changed files with 257 additions and 216 deletions
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backend/src/api/chat.py
+28 -24
View File
@@ -1,11 +1,13 @@
""" """
聊天对话API 聊天对话API
""" """
import logging
from fastapi import APIRouter, Depends, HTTPException, status from fastapi import APIRouter, Depends, HTTPException, status
from fastapi.responses import StreamingResponse from fastapi.responses import StreamingResponse
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
from pydantic import BaseModel from pydantic import BaseModel, Field
from typing import List, Optional, Dict, Any from typing import List, Optional, Dict, Any, Literal
import json import json
import asyncio import asyncio
@@ -17,6 +19,8 @@ from ..rag.chains import create_rag_chain
from ..rag.conversation_chains import create_conversation_chain from ..rag.conversation_chains import create_conversation_chain
from ..llm.siliconflow import get_llm_client from ..llm.siliconflow import get_llm_client
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/chat", tags=["聊天"]) 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): class ChatRequest(BaseModel):
"""聊天请求模型""" """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 session_id: Optional[int] = None
mode: str = "normal" # normal, rag mode: Literal["normal", "rag"] = "normal"
knowledge_base_ids: Optional[List[int]] = None 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 # 模型ID，如 deepseek-ai/DeepSeek-V3, Qwen/QwQ-32B model: Optional[str] = None
class ChatResponse(BaseModel): 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() new_title = request.message.strip()[:30] + "..." if len(request.message.strip()) > 30 else request.message.strip()
session.title = new_title session.title = new_title
db.commit() 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 # 根据模式运行不同的问答工作流
if request.mode == "rag": if request.mode == "rag":
print(f"[DEBUG-RAG] 非流式RAG模式") logger.debug(f"非流式RAG模式")
print(f"[DEBUG-RAG] 接收到的knowledge_base_ids: {request.knowledge_base_ids}") logger.debug(f"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"knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
if 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 # 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) rag_chain = create_rag_chain(knowledge_base_ids=request.knowledge_base_ids, model=request.model)
result = rag_chain.invoke(request.message) result = rag_chain.invoke(request.message)
else: else:
# 普通模式：使用LangChain 1.0对话链 # 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") logger.debug(f"普通模式 - 使用LangChain对话链")
print(f"[DEBUG-CHAT] 模型: {request.model}") logger.debug(f"模型: {request.model}")
conversation_chain = create_conversation_chain(model=request.model) conversation_chain = create_conversation_chain(model=request.model)
# 获取聊天历史 # 获取聊天历史
@@ -175,7 +179,7 @@ async def stream_message(
db = SessionLocal() db = SessionLocal()
try: try:
# 打印请求参数调试信息 # 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 # 获取或创建会话
if request.session_id: 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() new_title = request.message.strip()[:30] + "..." if len(request.message.strip()) > 30 else request.message.strip()
session.title = new_title session.title = new_title
db.commit() 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 # 获取聊天历史
chat_history = [] chat_history = []
@@ -231,12 +235,12 @@ async def stream_message(
# 根据模式选择不同的处理方式 # 根据模式选择不同的处理方式
if request.mode == "rag": if request.mode == "rag":
print(f"[DEBUG-RAG] 使用LangChain 1.0 RAG链") logger.debug(f"使用LangChain 1.0 RAG链")
print(f"[DEBUG-RAG] 接收到的knowledge_base_ids: {request.knowledge_base_ids}") logger.debug(f"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"knowledge_base_ids类型: {type(request.knowledge_base_ids)}")
print(f"[DEBUG-RAG] 模型: {request.model}") logger.debug(f"模型: {request.model}")
if 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])}")
# 创建RAG链 # 创建RAG链
rag_chain = create_rag_chain( rag_chain = create_rag_chain(
@@ -288,8 +292,8 @@ async def stream_message(
else: else:
# 普通模式：使用LangChain 1.0对话链 # 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") logger.debug(f"普通模式 - 使用LangChain流式对话链")
print(f"[DEBUG-CHAT] 模型: {request.model}") logger.debug(f"模型: {request.model}")
conversation_chain = create_conversation_chain(model=request.model) conversation_chain = create_conversation_chain(model=request.model)
# 使用带思考过程的流式输出 # 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 return result
except Exception as e: 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 # 降级到基础问答
rag_chain = create_rag_chain(model=model) rag_chain = create_rag_chain(model=model)
return rag_chain.invoke(question) return rag_chain.invoke(question)
backend/src/graph/nodes.py
+7 -6
View File
@@ -2,6 +2,7 @@
LangGraph节点定义 LangGraph节点定义
""" """
import json import json
import logging
import re import re
from typing import Dict, Any, List, TypedDict from typing import Dict, Any, List, TypedDict
from langchain.schema import HumanMessage, AIMessage, SystemMessage 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.retrievers import KnowledgeBaseRetriever
from ..rag.vector_store import get_vector_store from ..rag.vector_store import get_vector_store
logger = logging.getLogger(__name__)
def _parse_json_from_response(text: str) -> dict: 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""" """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 return new_state
except Exception as e: 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 = state.copy()
new_state["metadata"] = {**state["metadata"], "analysis": { new_state["metadata"] = {**state["metadata"], "analysis": {
"question_type": "通用", "question_type": "通用",
@@ -138,9 +141,7 @@ def retrieve_knowledge_node(state: GraphState) -> GraphState:
return new_state return new_state
except Exception as e: except Exception as e:
print(f"知识检索失败: {str(e)}") logger.error(f"知识检索失败: {str(e)}", exc_info=True)
import traceback
print(traceback.format_exc())
new_state = state.copy() new_state = state.copy()
new_state["retrieved_docs"] = [] new_state["retrieved_docs"] = []
new_state["sources"] = [] new_state["sources"] = []
@@ -186,7 +187,7 @@ def generate_answer_node(state: GraphState) -> GraphState:
return new_state return new_state
except Exception as e: 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 = state.copy()
new_state["answer"] = "抱歉，我无法生成合适的回答。请稍后重试。" new_state["answer"] = "抱歉，我无法生成合适的回答。请稍后重试。"
return new_state return new_state
@@ -208,5 +209,5 @@ def format_response_node(state: GraphState) -> GraphState:
return new_state return new_state
except Exception as e: 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 return state
backend/src/graph/qa_graph.py
+4 -1
View File
@@ -1,10 +1,13 @@
""" """
问答LangGraph工作流 问答LangGraph工作流
""" """
import logging
from typing import Dict, Any, Optional, List from typing import Dict, Any, Optional, List
from langgraph.graph import StateGraph, END from langgraph.graph import StateGraph, END
from .nodes import GraphState, analyze_question_node, retrieve_knowledge_node, generate_answer_node, format_response_node 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: def create_qa_graph() -> StateGraph:
"""创建问答图""" """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: 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 { return {
"answer": "抱歉，处理您的问题时出现了错误。请稍后重试。", "answer": "抱歉，处理您的问题时出现了错误。请稍后重试。",
"sources": [], "sources": [],
backend/src/llm/siliconflow.py
+5 -2
View File
@@ -1,6 +1,7 @@
""" """
大模型API集成 — 支持 SiliconFlow 和 DeepSeek 官方 + 视觉模型 大模型API集成 — 支持 SiliconFlow 和 DeepSeek 官方 + 视觉模型
""" """
import logging
import os import os
import base64 import base64
from typing import List, Dict, Any, Optional, AsyncGenerator, Tuple from typing import List, Dict, Any, Optional, AsyncGenerator, Tuple
@@ -12,6 +13,8 @@ import openai
from ..core.config import get_settings from ..core.config import get_settings
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
# 图片描述提示词 # 图片描述提示词
@@ -56,7 +59,7 @@ class SiliconFlowLLM:
api_key, base_url, resolved_model = _resolve_provider(raw_model) api_key, base_url, resolved_model = _resolve_provider(raw_model)
self.model_name = resolved_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( self.llm = ChatOpenAI(
model=resolved_model, model=resolved_model,
@@ -210,7 +213,7 @@ class SiliconFlowLLM:
return response.choices[0].message.content or "" return response.choices[0].message.content or ""
except Exception as e: 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: if attempt < max_retries - 1:
await asyncio.sleep(2 ** attempt) await asyncio.sleep(2 ** attempt)
backend/src/migrations/migrate_orphaned_documents.py
+6 -3
View File
@@ -1,12 +1,15 @@
""" """
迁移孤立文档到默认知识库 迁移孤立文档到默认知识库
""" """
import logging
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
from ..core.database import get_db from ..core.database import get_db
from ..models.user import User from ..models.user import User
from ..models.knowledge_base import KnowledgeBase from ..models.knowledge_base import KnowledgeBase
from ..models.document import Document from ..models.document import Document
logger = logging.getLogger(__name__)
def migrate_orphaned_documents(): def migrate_orphaned_documents():
"""将没有知识库的文档迁移到用户的默认知识库""" """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 doc.knowledge_base_id = default_kb.id
db.commit() 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: except Exception as e:
print(f"迁移失败: {str(e)}") logger.error(f"迁移失败: {str(e)}")
db.rollback() db.rollback()
finally: finally:
db.close() db.close()
backend/src/rag/chains.py
+5 -2
View File
@@ -1,6 +1,7 @@
""" """
RAG检索链（LangChain 1.0） RAG检索链（LangChain 1.0）
""" """
import logging
from typing import List, Optional, Dict, Any from typing import List, Optional, Dict, Any
from langchain_core.runnables import RunnablePassthrough, RunnableLambda from langchain_core.runnables import RunnablePassthrough, RunnableLambda
from langchain_core.prompts import ChatPromptTemplate from langchain_core.prompts import ChatPromptTemplate
@@ -11,6 +12,8 @@ from .retrievers import KnowledgeBaseRetriever
from .vector_store import get_vector_store from .vector_store import get_vector_store
from ..llm.siliconflow import get_llm_client from ..llm.siliconflow import get_llm_client
logger = logging.getLogger(__name__)
class RAGChain: class RAGChain:
"""RAG问答链（LangChain 1.0标准API）""" """RAG问答链（LangChain 1.0标准API）"""
@@ -31,7 +34,7 @@ class RAGChain:
score_threshold: 相似度阈值 score_threshold: 相似度阈值
model: 可选的模型名称，如 deepseek-ai/DeepSeek-V3, Qwen/QwQ-32B 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) _sf_client = get_llm_client(model=model)
self.llm = _sf_client.llm self.llm = _sf_client.llm
self.client = _sf_client self.client = _sf_client
@@ -46,7 +49,7 @@ class RAGChain:
search_kwargs={"k": k}, search_kwargs={"k": k},
score_threshold=score_threshold 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 # 创建Prompt
self.prompt = create_rag_prompt() self.prompt = create_rag_prompt()
backend/src/rag/document_loaders.py
+4 -1
View File
@@ -1,6 +1,7 @@
""" """
LangChain 1.0 文档加载器封装 + PDF图片提取 LangChain 1.0 文档加载器封装 + PDF图片提取
""" """
import logging
from typing import List, Optional, Dict from typing import List, Optional, Dict
from pathlib import Path from pathlib import Path
import fitz # pymupdf import fitz # pymupdf
@@ -12,6 +13,8 @@ from langchain_community.document_loaders import (
) )
from langchain_core.documents import Document from langchain_core.documents import Document
logger = logging.getLogger(__name__)
class PDFImageExtractor: class PDFImageExtractor:
"""使用pymupdf从PDF中提取内嵌图片""" """使用pymupdf从PDF中提取内嵌图片"""
@@ -59,7 +62,7 @@ class PDFImageExtractor:
"size": len(image_bytes), "size": len(image_bytes),
}) })
except Exception as e: 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 continue
doc.close() doc.close()
backend/src/rag/embeddings.py
+4 -1
View File
@@ -1,12 +1,15 @@
""" """
嵌入模型管理 嵌入模型管理
""" """
import logging
from typing import List from typing import List
from sentence_transformers import SentenceTransformer from sentence_transformers import SentenceTransformer
import numpy as np import numpy as np
from ..core.config import get_settings from ..core.config import get_settings
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
@@ -23,7 +26,7 @@ class EmbeddingModel:
"""加载嵌入模型""" """加载嵌入模型"""
try: try:
self.model = SentenceTransformer(self.model_name) 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: except Exception as e:
raise Exception(f"嵌入模型加载失败: {str(e)}") raise Exception(f"嵌入模型加载失败: {str(e)}")
backend/src/rag/retriever.py
+8 -5
View File
@@ -1,10 +1,13 @@
""" """
文档检索器 文档检索器
""" """
import logging
from typing import List, Dict, Any, Optional from typing import List, Dict, Any, Optional
from .vector_store import get_vector_store from .vector_store import get_vector_store
from .embeddings import get_embedding_model from .embeddings import get_embedding_model
logger = logging.getLogger(__name__)
class DocumentRetriever: class DocumentRetriever:
"""文档检索器""" """文档检索器"""
@@ -23,7 +26,7 @@ class DocumentRetriever:
) -> List[Dict[str, Any]]: ) -> List[Dict[str, Any]]:
"""检索相关文档""" """检索相关文档"""
try: 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 # 执行向量搜索
results = self.vector_store.search( results = self.vector_store.search(
@@ -31,19 +34,19 @@ class DocumentRetriever:
n_results=top_k, n_results=top_k,
filter_metadata=filter_metadata 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 # 过滤低分结果
filtered_results = [ filtered_results = [
result for result in results result for result in results
if result.get("distance", 1.0) <= (1 - score_threshold) 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 return filtered_results
except Exception as e: 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 [] return []
def retrieve_by_document_id(self, document_id: str) -> List[Dict[str, Any]]: def retrieve_by_document_id(self, document_id: str) -> List[Dict[str, Any]]:
@@ -56,7 +59,7 @@ class DocumentRetriever:
) )
return results return results
except Exception as e: 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 [] return []
def get_relevant_context(self, query: str, max_length: int = 2000) -> str: def get_relevant_context(self, query: str, max_length: int = 2000) -> str:
backend/src/rag/retrievers.py
+12 -22
View File
@@ -1,10 +1,13 @@
""" """
自定义知识库检索器（LangChain 1.0） 自定义知识库检索器（LangChain 1.0）
""" """
import logging
from typing import List, Optional from typing import List, Optional
import math
logger = logging.getLogger(__name__)
from langchain_core.documents import Document from langchain_core.documents import Document
from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun from langchain_core.callbacks.manager import CallbackManagerForRetrieverRun
from .score_utils import convert_distance_to_score
from langchain_core.retrievers import BaseRetriever from langchain_core.retrievers import BaseRetriever
class KnowledgeBaseRetriever(BaseRetriever): class KnowledgeBaseRetriever(BaseRetriever):
@@ -23,16 +26,16 @@ class KnowledgeBaseRetriever(BaseRetriever):
run_manager: CallbackManagerForRetrieverRun run_manager: CallbackManagerForRetrieverRun
) -> List[Document]: ) -> List[Document]:
"""获取相关文档（LangChain 1.0标准接口）""" """获取相关文档（LangChain 1.0标准接口）"""
print(f"[DEBUG-Retriever] 查询: {query}") logger.debug(f"查询: {query}")
print(f"[DEBUG-Retriever] knowledge_base_ids: {self.knowledge_base_ids}") logger.debug(f"knowledge_base_ids: {self.knowledge_base_ids}")
# 构建知识库过滤条件 # 构建知识库过滤条件
filter_dict = None filter_dict = None
if self.knowledge_base_ids: if self.knowledge_base_ids:
filter_dict = {"knowledge_base_id": {"$in": self.knowledge_base_ids}} filter_dict = {"knowledge_base_id": {"$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: 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 # 执行搜索
if self.search_type == "similarity": if self.search_type == "similarity":
@@ -41,21 +44,21 @@ class KnowledgeBaseRetriever(BaseRetriever):
k=self.search_kwargs.get("k", 5), k=self.search_kwargs.get("k", 5),
filter=filter_dict 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 # 打印每个文档的知识库ID
for i, (doc, distance) in enumerate(docs_and_scores): for i, (doc, distance) in enumerate(docs_and_scores):
kb_id = doc.metadata.get("knowledge_base_id", "未知") 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 # 转换距离为分数并过滤
filtered_docs = [] filtered_docs = []
for doc, distance in docs_and_scores: 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: if score > self.score_threshold:
filtered_docs.append(doc) 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 return filtered_docs
elif self.search_type == "mmr": elif self.search_type == "mmr":
@@ -67,16 +70,3 @@ class KnowledgeBaseRetriever(BaseRetriever):
) )
return [] 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
+7 -4
View File
@@ -2,6 +2,7 @@
LangChain 1.0 向量存储封装 LangChain 1.0 向量存储封装
""" """
import os import os
import logging
import json import json
import hashlib import hashlib
from typing import List, Dict, Any, Optional 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 ..core.config import get_settings
from .embeddings import get_embedding_model from .embeddings import get_embedding_model
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
@@ -40,7 +43,7 @@ class VectorStore:
self.vectorstore.add_documents(documents) self.vectorstore.add_documents(documents)
return True return True
except Exception as e: 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 return False
def as_retriever(self, **kwargs): def as_retriever(self, **kwargs):
@@ -54,7 +57,7 @@ class VectorStore:
filter: Optional[Dict] = None filter: Optional[Dict] = None
): ):
"""相似度搜索（带分数）""" """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( result = self.vectorstore.similarity_search_with_score(
query=query, query=query,
@@ -62,7 +65,7 @@ class VectorStore:
filter=filter 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 return result
def delete_by_document_id(self, document_id: int) -> bool: def delete_by_document_id(self, document_id: int) -> bool:
@@ -73,7 +76,7 @@ class VectorStore:
) )
return True return True
except Exception as e: 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 return False
def max_marginal_relevance_search( def max_marginal_relevance_search(
backend/src/services/analytics_service.py
+8 -6
View File
@@ -2,12 +2,14 @@
学习分析服务 学习分析服务
提供用户学习数据的统计和分析功能 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 typing import Dict, Any, List
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
from sqlalchemy import func, distinct, and_ from sqlalchemy import func, distinct, and_
from datetime import datetime, timedelta from datetime import datetime, timedelta
logger = logging.getLogger(__name__)
from ..models.user import User from ..models.user import User
from ..models.chat import ChatSession, ChatMessage from ..models.chat import ChatSession, ChatMessage
from ..models.document import Document from ..models.document import Document
@@ -65,7 +67,7 @@ class AnalyticsService:
} }
except Exception as e: 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)}") 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]]: def get_user_learning_trends(self, user_id: int, days: int = 30) -> List[Dict[str, Any]]:
@@ -107,7 +109,7 @@ class AnalyticsService:
return trends return trends
except Exception as e: 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)}") 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]]: def get_popular_questions(self, user_id: int, limit: int = 10) -> List[Dict[str, Any]]:
@@ -141,7 +143,7 @@ class AnalyticsService:
return popular_questions return popular_questions
except Exception as e: 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)}") 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]]: def get_knowledge_coverage(self, user_id: int) -> List[Dict[str, Any]]:
@@ -160,7 +162,7 @@ class AnalyticsService:
return coverage_data return coverage_data
except Exception as e: 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)}") 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]: def get_learning_report(self, user_id: int) -> Dict[str, Any]:
@@ -211,5 +213,5 @@ class AnalyticsService:
} }
except Exception as e: 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)}") raise Exception(f"获取学习报告失败: {str(e)}")
backend/src/services/auth_service.py
+9 -6
View File
@@ -1,6 +1,7 @@
""" """
用户认证服务 用户认证服务
""" """
import logging
from datetime import datetime, timedelta from datetime import datetime, timedelta
from typing import Optional, Dict, Any from typing import Optional, Dict, Any
from sqlalchemy.orm import Session 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.security import get_password_hash, verify_password, create_access_token
from ..core.config import get_settings from ..core.config import get_settings
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
@@ -58,7 +61,7 @@ class AuthService:
except Exception as e: except Exception as e:
self.db.rollback() 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 return None
def authenticate_user(self, username: str, password: str) -> Optional[User]: def authenticate_user(self, username: str, password: str) -> Optional[User]:
@@ -85,7 +88,7 @@ class AuthService:
return user return user
except Exception as e: 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 return None
def get_user_by_username(self, username: str) -> Optional[User]: def get_user_by_username(self, username: str) -> Optional[User]:
@@ -117,7 +120,7 @@ class AuthService:
except Exception as e: except Exception as e:
self.db.rollback() 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 return None
def deactivate_user(self, user_id: int) -> bool: def deactivate_user(self, user_id: int) -> bool:
@@ -133,7 +136,7 @@ class AuthService:
except Exception as e: except Exception as e:
self.db.rollback() 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 return False
def change_password(self, user_id: int, old_password: str, new_password: str) -> bool: def change_password(self, user_id: int, old_password: str, new_password: str) -> bool:
@@ -152,7 +155,7 @@ class AuthService:
except Exception as e: except Exception as e:
self.db.rollback() 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 return False
def create_access_token_for_user(self, user: User) -> Dict[str, Any]: def create_access_token_for_user(self, user: User) -> Dict[str, Any]:
@@ -193,7 +196,7 @@ class AuthService:
} }
except Exception as e: 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 { return {
"total_users": 0, "total_users": 0,
"active_users": 0, "active_users": 0,
backend/src/services/book_content_service.py
+6 -3
View File
@@ -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 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） 层级结构：书籍 -> Chapter -> Section -> Subsection（知识点）
""" """
import logging
from pathlib import Path from pathlib import Path
from typing import Optional from typing import Optional
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
@@ -10,6 +11,8 @@ from sqlalchemy.orm import Session
from ..models.book_structure import Chapter, Section, Subsection from ..models.book_structure import Chapter, Section, Subsection
from .latex_parser import LaTeXParser from .latex_parser import LaTeXParser
logger = logging.getLogger(__name__)
class BookContentService: class BookContentService:
"""书籍内容服务""" """书籍内容服务"""
@@ -59,7 +62,7 @@ class BookContentService:
) )
return content return content
except Exception as e: 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 return None
def get_section_content(self, db: Session, section_id: int) -> Optional[str]: def get_section_content(self, db: Session, section_id: int) -> Optional[str]:
@@ -91,7 +94,7 @@ class BookContentService:
) )
return content return content
except Exception as e: 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 return None
def get_subsection_content(self, db: Session, subsection_id: int) -> Optional[str]: def get_subsection_content(self, db: Session, subsection_id: int) -> Optional[str]:
@@ -127,6 +130,6 @@ class BookContentService:
) )
return content return content
except Exception as e: 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 return None
backend/src/services/file_watcher_service.py
+19 -17
View File
@@ -3,6 +3,7 @@
""" """
import os import os
import time import time
import logging
import threading import threading
from pathlib import Path from pathlib import Path
from typing import Optional, Callable from typing import Optional, Callable
@@ -13,6 +14,7 @@ from ..core.config import get_settings
from ..core.database import get_db from ..core.database import get_db
from .knowledge_base_service import KnowledgeBaseService from .knowledge_base_service import KnowledgeBaseService
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
@@ -27,19 +29,19 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
def on_created(self, event): def on_created(self, event):
"""处理文件创建事件""" """处理文件创建事件"""
if not event.is_directory and self._is_supported_file(event.src_path): 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") self._process_file_async(event.src_path, "created")
def on_modified(self, event): def on_modified(self, event):
"""处理文件修改事件""" """处理文件修改事件"""
if not event.is_directory and self._is_supported_file(event.src_path): 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") self._process_file_async(event.src_path, "modified")
def on_deleted(self, event): def on_deleted(self, event):
"""处理文件删除事件""" """处理文件删除事件"""
if not event.is_directory and self._is_supported_file(event.src_path): 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) self._handle_file_deletion(event.src_path)
def _is_supported_file(self, file_path: str) -> bool: def _is_supported_file(self, file_path: str) -> bool:
@@ -54,10 +56,10 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
time.sleep(1) time.sleep(1)
result = self.kb_service.process_file(file_path) 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: 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 # 在后台线程中处理
thread = threading.Thread(target=process) thread = threading.Thread(target=process)
@@ -80,12 +82,12 @@ class KnowledgeBaseHandler(FileSystemEventHandler):
if document: if document:
result = self.kb_service.delete_document(document.id) 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: 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: 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: class FileWatcherService:
@@ -99,15 +101,15 @@ class FileWatcherService:
def start(self): def start(self):
"""启动文件监控""" """启动文件监控"""
if self.is_running: 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 return
if not settings.enable_file_watcher: 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 return
if not self.knowledge_base_dir.exists(): 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 return
try: try:
@@ -130,19 +132,19 @@ class FileWatcherService:
self.observer.start() self.observer.start()
self.is_running = True 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 # 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() kb_service.ensure_system_knowledge_bases()
# 执行初始扫描 # 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() 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: 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 self.is_running = False
def stop(self): def stop(self):
@@ -151,7 +153,7 @@ class FileWatcherService:
self.observer.stop() self.observer.stop()
self.observer.join() self.observer.join()
self.is_running = False 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: def is_active(self) -> bool:
"""检查监控服务是否活跃""" """检查监控服务是否活跃"""
backend/src/services/image_generation_service.py
+15 -12
View File
@@ -4,12 +4,15 @@
""" """
import base64 import base64
import logging
import uuid import uuid
from pathlib import Path from pathlib import Path
from typing import Dict, Any from typing import Dict, Any
import httpx import httpx
from src.core.config import settings from src.core.config import settings
logger = logging.getLogger(__name__)
class ImageGenerationService: class ImageGenerationService:
"""统一的图像生成服务基类""" """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: async def call_api(self, model: str, payload: dict) -> dict:
"""调用硅基流动 API""" """调用硅基流动 API"""
print(f"[DEBUG] 调用SiliconFlow API: {self.base_url}") logger.debug(f"调用SiliconFlow API: {self.base_url}")
print(f"[DEBUG] 模型: {model}") logger.debug(f"模型: {model}")
print(f"[DEBUG] 请求参数: {payload}") logger.debug(f"请求参数: {payload}")
async with httpx.AsyncClient(timeout=self.timeout) as client: async with httpx.AsyncClient(timeout=self.timeout) as client:
response = await client.post( response = await client.post(
@@ -37,9 +40,9 @@ class ImageGenerationService:
response.raise_for_status() response.raise_for_status()
result = response.json() result = response.json()
print(f"[DEBUG] API响应状态: {response.status_code}") logger.debug(f"API响应状态: {response.status_code}")
print(f"[DEBUG] API响应类型: {type(result)}") logger.debug(f"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响应键: {list(result.keys()) if isinstance(result, dict) else '非字典类型'}")
return result return result
@@ -53,7 +56,7 @@ class ImageGenerationService:
# 移除可能的空白字符 # 移除可能的空白字符
base64_data = base64_data.strip() 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 # 解码 base64 数据
image_bytes = base64.b64decode(base64_data) image_bytes = base64.b64decode(base64_data)
@@ -62,7 +65,7 @@ class ImageGenerationService:
if len(image_bytes) == 0: if len(image_bytes) == 0:
raise Exception("解码后的图像数据为空") 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 # 确保目录存在
image_dir = Path(settings.generated_images_dir) image_dir = Path(settings.generated_images_dir)
@@ -73,13 +76,13 @@ class ImageGenerationService:
with open(image_path, "wb") as f: with open(image_path, "wb") as f:
f.write(image_bytes) 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) return str(image_path)
except Exception as e: except Exception as e:
print(f"[ERROR] 保存图像失败: {str(e)}") logger.error(f"保存图像失败: {str(e)}")
print(f"[ERROR] base64数据长度: {len(base64_data) if base64_data else 0}") logger.error(f"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"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)}") raise Exception(f"保存图像失败: {str(e)}")
def generate_image_id(self) -> str: def generate_image_id(self) -> str:
backend/src/services/image_to_image_service.py
+47 -44
View File
@@ -4,12 +4,15 @@
""" """
import base64 import base64
import logging
import httpx import httpx
from typing import List, Dict, Any, Optional from typing import List, Dict, Any, Optional
from pathlib import Path from pathlib import Path
from fastapi import UploadFile from fastapi import UploadFile
from .image_generation_service import ImageGenerationService from .image_generation_service import ImageGenerationService
logger = logging.getLogger(__name__)
class ImageToImageService(ImageGenerationService): class ImageToImageService(ImageGenerationService):
"""图生图服务""" """图生图服务"""
@@ -59,13 +62,13 @@ class ImageToImageService(ImageGenerationService):
result = await self.call_api(self.MODEL, payload) result = await self.call_api(self.MODEL, payload)
# 调试信息 # 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): 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: 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"]: 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 # 保存结果
image_id = self.generate_image_id() image_id = self.generate_image_id()
@@ -73,56 +76,56 @@ class ImageToImageService(ImageGenerationService):
# 检查是否为字典类型 # 检查是否为字典类型
if isinstance(edited_image_data, dict): 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 # 优先检查URL字段
if "url" in edited_image_data: if "url" in edited_image_data:
image_url = edited_image_data["url"] 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: try:
image_path = await self.download_image_from_url(image_id, image_url) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
# 如果没有URL，尝试base64字段 # 如果没有URL，尝试base64字段
elif any(key in edited_image_data for key in ["b64_json", "b64", "data"]): 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") 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: try:
image_path = self.save_image(image_id, image_b64) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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") 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 # 如果直接是字符串，判断是URL还是base64
elif isinstance(edited_image_data, str): 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'): 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: try:
image_path = await self.download_image_from_url(image_id, edited_image_data) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
else: else:
print(f"[DEBUG] 检测到base64字符串") logger.debug(f"检测到base64字符串")
try: try:
image_path = self.save_image(image_id, edited_image_data) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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)}") raise Exception(f"不支持的图像数据类型: {type(edited_image_data)}")
return { return {
@@ -165,70 +168,70 @@ class ImageToImageService(ImageGenerationService):
result = await self.call_api(self.MODEL, payload) result = await self.call_api(self.MODEL, payload)
# 调试信息 # 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): 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: 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 # 处理变体结果
variations = [] variations = []
for i, img_data in enumerate(result["images"]): 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() image_id = self.generate_image_id()
# 检查是否为字典类型 # 检查是否为字典类型
if isinstance(img_data, dict): 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 # 优先检查URL字段
if "url" in img_data: if "url" in img_data:
image_url = img_data["url"] 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: try:
image_path = await self.download_image_from_url(image_id, image_url) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
# 如果没有URL，尝试base64字段 # 如果没有URL，尝试base64字段
elif any(key in img_data for key in ["b64_json", "b64", "data"]): 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") 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: try:
image_path = self.save_image(image_id, image_b64) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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") 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 # 如果直接是字符串，判断是URL还是base64
elif isinstance(img_data, str): 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'): 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: try:
image_path = await self.download_image_from_url(image_id, img_data) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
else: else:
print(f"[DEBUG] 检测到base64字符串") logger.debug(f"检测到base64字符串")
try: try:
image_path = self.save_image(image_id, img_data) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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)}") raise Exception(f"不支持的图像数据类型: {type(img_data)}")
variations.append({ variations.append({
@@ -320,7 +323,7 @@ class ImageToImageService(ImageGenerationService):
async def download_image_from_url(self, image_id: str, image_url: str) -> str: async def download_image_from_url(self, image_id: str, image_url: str) -> str:
"""从URL下载图像""" """从URL下载图像"""
try: 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 # 下载图像
async with httpx.AsyncClient(timeout=30) as client: async with httpx.AsyncClient(timeout=30) as client:
@@ -331,7 +334,7 @@ class ImageToImageService(ImageGenerationService):
if len(image_bytes) == 0: if len(image_bytes) == 0:
raise Exception("下载的图像数据为空") 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 # 确保目录存在
image_dir = Path(self.get_image_dir()) image_dir = Path(self.get_image_dir())
@@ -342,11 +345,11 @@ class ImageToImageService(ImageGenerationService):
with open(image_path, "wb") as f: with open(image_path, "wb") as f:
f.write(image_bytes) 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) return str(image_path)
except Exception as e: 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)}") raise Exception(f"下载图像失败: {str(e)}")
def get_image_dir(self) -> str: def get_image_dir(self) -> str:
backend/src/services/knowledge_base_service.py
+12 -9
View File
@@ -1,6 +1,7 @@
""" """
知识库管理服务 知识库管理服务
""" """
import logging
import os import os
import hashlib import hashlib
from pathlib import Path from pathlib import Path
@@ -15,6 +16,8 @@ from ..models.user import User
from ..core.config import get_settings from ..core.config import get_settings
from .document_service import DocumentService from .document_service import DocumentService
logger = logging.getLogger(__name__)
settings = get_settings() settings = get_settings()
@@ -106,7 +109,7 @@ class KnowledgeBaseService:
existing.user_id = admin.id existing.user_id = admin.id
self.db.commit() self.db.commit()
self.db.refresh(existing) 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 return existing.id
# 找到 admin 用户（或任意 superuser）作为 owner # 找到 admin 用户（或任意 superuser）作为 owner
@@ -123,7 +126,7 @@ class KnowledgeBaseService:
self.db.add(kb) self.db.add(kb)
self.db.commit() self.db.commit()
self.db.refresh(kb) 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 return kb.id
def _resolve_knowledge_base(self, file_path: Path) -> Optional[int]: def _resolve_knowledge_base(self, file_path: Path) -> Optional[int]:
@@ -249,12 +252,12 @@ class KnowledgeBaseService:
loop.run_until_complete(self.document_service.process_document(document.id)) loop.run_until_complete(self.document_service.process_document(document.id))
loop.close() loop.close()
except Exception as e: 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 = threading.Thread(target=process_in_background, daemon=True)
thread.start() thread.start()
except Exception as e: 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"} return {"status": "new", "document_id": document.id, "message": "文档创建成功，正在处理中"}
@@ -287,12 +290,12 @@ class KnowledgeBaseService:
loop.run_until_complete(self.document_service.process_document(document.id)) loop.run_until_complete(self.document_service.process_document(document.id))
loop.close() loop.close()
except Exception as e: 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 = threading.Thread(target=process_in_background, daemon=True)
thread.start() thread.start()
except Exception as e: 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"} return {"status": "updated", "document_id": document.id, "message": "文档更新成功，正在重新处理中"}
@@ -482,7 +485,7 @@ class KnowledgeBaseService:
all_files = [f for f in directory.rglob("*") if f.is_file() and self._is_supported_file(f)] all_files = [f for f in directory.rglob("*") if f.is_file() and self._is_supported_file(f)]
total_files = len(all_files) 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): for idx, file_path in enumerate(all_files, 1):
try: 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） # 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: if idx % 10 == 0 or idx == total_files:
percentage = (idx * 100) // total_files if total_files > 0 else 0 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: if existing_doc:
# 检查是否需要更新 # 检查是否需要更新
@@ -549,6 +552,6 @@ class KnowledgeBaseService:
"error": str(e) "error": str(e)
}) })
print() # 换行 logger.info("文件处理完成")
results["success"] = len(results["errors"]) == 0 results["success"] = len(results["errors"]) == 0
return results return results
backend/src/services/text_to_image_service.py
+28 -25
View File
@@ -3,12 +3,15 @@
支持 Kwai-Kolors/Kolors 和 Qwen/Qwen-Image 模型 支持 Kwai-Kolors/Kolors 和 Qwen/Qwen-Image 模型
""" """
import logging
import uuid import uuid
import httpx import httpx
from typing import List, Dict, Any from typing import List, Dict, Any
from pathlib import Path from pathlib import Path
from .image_generation_service import ImageGenerationService from .image_generation_service import ImageGenerationService
logger = logging.getLogger(__name__)
class TextToImageService(ImageGenerationService): class TextToImageService(ImageGenerationService):
"""文生图服务""" """文生图服务"""
@@ -73,72 +76,72 @@ class TextToImageService(ImageGenerationService):
result = await self.call_api(self.MODELS[model], payload) result = await self.call_api(self.MODELS[model], payload)
# 调试信息 # 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): 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: 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"]: 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 # 处理结果
images = [] images = []
for i, img_data in enumerate(result.get("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() image_id = self.generate_image_id()
# 检查是否为字典类型 # 检查是否为字典类型
if isinstance(img_data, dict): 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 # 优先检查URL字段
if "url" in img_data: if "url" in img_data:
image_url = img_data["url"] 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: try:
image_path = await self.download_image_from_url(image_id, image_url) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
# 如果没有URL，尝试base64字段 # 如果没有URL，尝试base64字段
elif any(key in img_data for key in ["b64_json", "b64", "data"]): 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") 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: try:
image_path = self.save_image(image_id, image_b64) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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") 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 # 如果直接是字符串，判断是URL还是base64
elif isinstance(img_data, str): 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'): 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: try:
image_path = await self.download_image_from_url(image_id, img_data) 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: 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)}") raise Exception(f"下载图像失败: {str(e)}")
else: else:
print(f"[DEBUG] 检测到base64字符串") logger.debug(f"检测到base64字符串")
try: try:
image_path = self.save_image(image_id, img_data) 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: 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)}") raise Exception(f"保存图像失败: {str(e)}")
else: 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)}") raise Exception(f"不支持的图像数据类型: {type(img_data)}")
images.append({ images.append({
@@ -182,7 +185,7 @@ class TextToImageService(ImageGenerationService):
async def download_image_from_url(self, image_id: str, image_url: str) -> str: async def download_image_from_url(self, image_id: str, image_url: str) -> str:
"""从URL下载图像""" """从URL下载图像"""
try: 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 # 下载图像
async with httpx.AsyncClient(timeout=30) as client: async with httpx.AsyncClient(timeout=30) as client:
@@ -193,7 +196,7 @@ class TextToImageService(ImageGenerationService):
if len(image_bytes) == 0: if len(image_bytes) == 0:
raise Exception("下载的图像数据为空") 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 # 确保目录存在
image_dir = Path(self.get_image_dir()) image_dir = Path(self.get_image_dir())
@@ -204,11 +207,11 @@ class TextToImageService(ImageGenerationService):
with open(image_path, "wb") as f: with open(image_path, "wb") as f:
f.write(image_bytes) 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) return str(image_path)
except Exception as e: 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)}") raise Exception(f"下载图像失败: {str(e)}")
def get_image_dir(self) -> str: def get_image_dir(self) -> str: