增加显示详细日志开关

configs/model_config.py.example

@@ -5,6 +5,8 @@ LOG_FORMAT = "%(asctime)s - %(filename)s[line:%(lineno)d] - %(levelname)s: %(mes
 logger = logging.getLogger()
 logger.setLevel(logging.INFO)
 logging.basicConfig(format=LOG_FORMAT)
+# 是否显示详细日志
+log_verbose = False
 
 
 # 在以下字典中修改属性值，以指定本地embedding模型存储位置

server/api.py

@@ -6,7 +6,7 @@ sys.path.append(os.path.dirname(os.path.dirname(__file__)))
 
 from configs.model_config import LLM_MODEL, NLTK_DATA_PATH
 from configs.server_config import OPEN_CROSS_DOMAIN, HTTPX_DEFAULT_TIMEOUT
-from configs import VERSION
+from configs import VERSION, logger, log_verbose
 import argparse
 import uvicorn
 from fastapi import Body
@@ -140,6 +140,8 @@ def create_app():
             r = httpx.post(controller_address + "/list_models")
             return BaseResponse(data=r.json()["models"])
         except Exception as e:
+            logger.error(f'{e.__class__.__name__}: {e}',
+                         exc_info=e if log_verbose else None)
             return BaseResponse(
                 code=500,
                 data=[],
@@ -165,6 +167,8 @@ def create_app():
             )
             return r.json()
         except Exception as e:
+            logger.error(f'{e.__class__.__name__}: {e}',
+                         exc_info=e if log_verbose else None)
             return BaseResponse(
                 code=500,
                 msg=f"failed to stop LLM model {model_name} from controller: {controller_address}。错误信息是： {e}")
@@ -190,6 +194,8 @@ def create_app():
             )
             return r.json()
         except Exception as e:
+            logger.error(f'{e.__class__.__name__}: {e}',
+                         exc_info=e if log_verbose else None)
             return BaseResponse(
                 code=500,
                 msg=f"failed to switch LLM model from controller: {controller_address}。错误信息是： {e}")

server/chat/openai_chat.py

@@ -1,7 +1,7 @@
 from fastapi.responses import StreamingResponse
 from typing import List
 import openai
-from configs.model_config import llm_model_dict, LLM_MODEL, logger
+from configs.model_config import llm_model_dict, LLM_MODEL, logger, log_verbose
 from pydantic import BaseModel
 
 
@@ -46,7 +46,9 @@ async def openai_chat(msg: OpenAiChatMsgIn):
                     print(answer)
                     yield(answer)
         except Exception as e:
-            logger.error(f"获取ChatCompletion时出错：{e}")
+            msg = f"获取ChatCompletion时出错：{e}"
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
 
     return StreamingResponse(
         get_response(msg),

server/chat/utils.py

@@ -2,6 +2,7 @@ import asyncio
 from typing import Awaitable, List, Tuple, Dict, Union
 from pydantic import BaseModel, Field
 from langchain.prompts.chat import ChatMessagePromptTemplate
+from configs import logger, log_verbose
 
 
 async def wrap_done(fn: Awaitable, event: asyncio.Event):
@@ -10,7 +11,9 @@ async def wrap_done(fn: Awaitable, event: asyncio.Event):
         await fn
     except Exception as e:
         # TODO: handle exception
-        print(f"Caught exception: {e}")
+        msg = f"Caught exception: {e}"
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
     finally:
         # Signal the aiter to stop.
         event.set()

server/knowledge_base/kb_api.py

@@ -3,7 +3,7 @@ from server.utils import BaseResponse, ListResponse
 from server.knowledge_base.utils import validate_kb_name
 from server.knowledge_base.kb_service.base import KBServiceFactory
 from server.db.repository.knowledge_base_repository import list_kbs_from_db
-from configs.model_config import EMBEDDING_MODEL, logger
+from configs.model_config import EMBEDDING_MODEL, logger, log_verbose
 from fastapi import Body
 
 
@@ -31,7 +31,8 @@ async def create_kb(knowledge_base_name: str = Body(..., examples=["samples"]),
         kb.create_kb()
     except Exception as e:
         msg = f"创建知识库出错： {e}"
-        logger.error(msg)
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
         return BaseResponse(code=500, msg=msg)
 
     return BaseResponse(code=200, msg=f"已新增知识库 {knowledge_base_name}")
@@ -57,7 +58,8 @@ async def delete_kb(
             return BaseResponse(code=200, msg=f"成功删除知识库 {knowledge_base_name}")
     except Exception as e:
         msg = f"删除知识库时出现意外： {e}"
-        logger.error(msg)
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
         return BaseResponse(code=500, msg=msg)
 
     return BaseResponse(code=500, msg=f"删除知识库失败 {knowledge_base_name}")

server/knowledge_base/kb_doc_api.py

@@ -3,7 +3,7 @@ import urllib
 from fastapi import File, Form, Body, Query, UploadFile
 from configs.model_config import (DEFAULT_VS_TYPE, EMBEDDING_MODEL,
                                 VECTOR_SEARCH_TOP_K, SCORE_THRESHOLD,
-                                logger,)
+                                logger, log_verbose,)
 from server.utils import BaseResponse, ListResponse, run_in_thread_pool
 from server.knowledge_base.utils import (validate_kb_name, list_files_from_folder,get_file_path,
                                         files2docs_in_thread, KnowledgeFile)
@@ -80,7 +80,8 @@ def _save_files_in_thread(files: List[UploadFile],
             return dict(code=200, msg=f"成功上传文件 {filename}", data=data)
         except Exception as e:
             msg = f"{filename} 文件上传失败，报错信息为: {e}"
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             return dict(code=500, msg=msg, data=data)
 
     params = [{"file": file, "knowledge_base_name": knowledge_base_name, "override": override} for file in files]
@@ -185,7 +186,8 @@ async def delete_docs(knowledge_base_name: str = Body(..., examples=["samples"])
             kb.delete_doc(kb_file, delete_content, not_refresh_vs_cache=True)
         except Exception as e:
             msg = f"{file_name} 文件删除失败，错误信息：{e}"
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             failed_files[file_name] = msg
 
     if not not_refresh_vs_cache:
@@ -225,7 +227,8 @@ async def update_docs(
                 kb_files.append(KnowledgeFile(filename=file_name, knowledge_base_name=knowledge_base_name))
             except Exception as e:
                 msg = f"加载文档 {file_name} 时出错：{e}"
-                logger.error(msg)
+                logger.error(f'{e.__class__.__name__}: {msg}',
+                             exc_info=e if log_verbose else None)
                 failed_files[file_name] = msg
 
     # 从文件生成docs，并进行向量化。
@@ -249,7 +252,8 @@ async def update_docs(
             kb.update_doc(kb_file, docs=v, not_refresh_vs_cache=True)
         except Exception as e:
             msg = f"为 {file_name} 添加自定义docs时出错：{e}"
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             failed_files[file_name] = msg
 
     if not not_refresh_vs_cache:
@@ -291,7 +295,8 @@ def download_doc(
             )
     except Exception as e:
         msg = f"{kb_file.filename} 读取文件失败，错误信息是：{e}"
-        logger.error(msg)
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
         return BaseResponse(code=500, msg=msg)
 
     return BaseResponse(code=500, msg=f"{kb_file.filename} 读取文件失败")

server/knowledge_base/kb_service/faiss_kb_service.py

@@ -6,7 +6,7 @@ from configs.model_config import (
     CACHED_VS_NUM,
     EMBEDDING_MODEL,
     SCORE_THRESHOLD,
-    logger,
+    logger, log_verbose,
 )
 from server.knowledge_base.kb_service.base import KBService, SupportedVSType
 from functools import lru_cache

server/knowledge_base/migrate.py

@@ -1,4 +1,4 @@
-from configs.model_config import EMBEDDING_MODEL, DEFAULT_VS_TYPE
+from configs.model_config import EMBEDDING_MODEL, DEFAULT_VS_TYPE, logger, log_verbose
 from server.knowledge_base.utils import (get_file_path, list_kbs_from_folder,
                                         list_files_from_folder, run_in_thread_pool,
                                         files2docs_in_thread,
@@ -30,7 +30,9 @@ def file_to_kbfile(kb_name: str, files: List[str]) -> List[KnowledgeFile]:
             kb_file = KnowledgeFile(filename=file, knowledge_base_name=kb_name)
             kb_files.append(kb_file)
         except Exception as e:
-            print(f"{e}，已跳过")
+            msg = f"{e}，已跳过"
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
     return kb_files
 
 

server/knowledge_base/utils.py

@@ -8,7 +8,7 @@ from configs.model_config import (
     CHUNK_SIZE,
     OVERLAP_SIZE,
     ZH_TITLE_ENHANCE,
-    logger,
+    logger, log_verbose,
 )
 from functools import lru_cache
 import importlib
@@ -189,7 +189,9 @@ def get_loader(loader_name: str, file_path_or_content: Union[str, bytes, io.Stri
             document_loaders_module = importlib.import_module('langchain.document_loaders')
         DocumentLoader = getattr(document_loaders_module, loader_name)
     except Exception as e:
-        logger.error(f"为文件{file_path_or_content}查找加载器{loader_name}时出错：{e}")
+        msg = f"为文件{file_path_or_content}查找加载器{loader_name}时出错：{e}"
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
         document_loaders_module = importlib.import_module('langchain.document_loaders')
         DocumentLoader = getattr(document_loaders_module, "UnstructuredFileLoader")
 
@@ -228,7 +230,9 @@ def make_text_splitter(
             chunk_overlap=chunk_overlap,
         )
     except Exception as e:
-        logger.error(f"查找分词器 {splitter_name} 时出错：{e}")
+        msg = f"查找分词器 {splitter_name} 时出错：{e}"
+        logger.error(f'{e.__class__.__name__}: {msg}',
+                     exc_info=e if log_verbose else None)
         TextSplitter = getattr(text_splitter_module, "RecursiveCharacterTextSplitter")
         text_splitter = TextSplitter(
             chunk_size=chunk_size,
@@ -330,7 +334,8 @@ def files2docs_in_thread(
             return True, (file.kb_name, file.filename, file.file2text(**kwargs))
         except Exception as e:
             msg = f"从文件 {file.kb_name}/{file.filename} 加载文档时出错：{e}"
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             return False, (file.kb_name, file.filename, msg)
 
     kwargs_list = []

server/llm_api.py

@@ -4,7 +4,7 @@ import sys
 import os
 
 sys.path.append(os.path.dirname(os.path.dirname(__file__)))
-from configs.model_config import llm_model_dict, LLM_MODEL, LOG_PATH, logger
+from configs.model_config import llm_model_dict, LLM_MODEL, LOG_PATH, logger, log_verbose
 from server.utils import MakeFastAPIOffline, set_httpx_timeout, llm_device
 
 

server/utils.py

@@ -4,7 +4,7 @@ from typing import List
 from fastapi import FastAPI
 from pathlib import Path
 import asyncio
-from configs.model_config import LLM_MODEL, llm_model_dict, LLM_DEVICE, EMBEDDING_DEVICE
+from configs.model_config import LLM_MODEL, llm_model_dict, LLM_DEVICE, EMBEDDING_DEVICE, logger, log_verbose
 from configs.server_config import FSCHAT_MODEL_WORKERS
 import os
 from server import model_workers
@@ -86,9 +86,10 @@ def torch_gc():
             from torch.mps import empty_cache
             empty_cache()
         except Exception as e:
-            print(e)
+            msg=("如果您使用的是 macOS 建议将 pytorch 版本升级至 2.0.0 或更高版本，"
-            print("如果您使用的是 macOS 建议将 pytorch 版本升级至 2.0.0 或更高版本，以支持及时清理 torch 产生的内存占用。")
+                 "以支持及时清理 torch 产生的内存占用。")
-
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
 
 def run_async(cor):
     '''
@@ -217,7 +218,9 @@ def get_model_worker_config(model_name: str = LLM_MODEL) -> dict:
             try:
                 config["worker_class"] = getattr(model_workers, provider)
             except Exception as e:
-                print(f"在线模型 ‘{model_name}’ 的provider没有正确配置")
+                msg = f"在线模型 ‘{model_name}’ 的provider没有正确配置"
+                logger.error(f'{e.__class__.__name__}: {msg}',
+                             exc_info=e if log_verbose else None)
 
     config["device"] = llm_device(config.get("device") or LLM_DEVICE)
     return config

webui_pages/utils.py

@@ -11,7 +11,7 @@ from configs.model_config import (
     SCORE_THRESHOLD,
     VECTOR_SEARCH_TOP_K,
     SEARCH_ENGINE_TOP_K,
-    logger,
+    logger, log_verbose,
 )
 from configs.server_config import HTTPX_DEFAULT_TIMEOUT
 import httpx
@@ -78,7 +78,9 @@ class ApiRequest:
                 else:
                     return httpx.get(url, params=params, **kwargs)
             except Exception as e:
-                logger.error(f"error when get {url}: {e}")
+                msg = f"error when get {url}: {e}"
+                logger.error(f'{e.__class__.__name__}: {msg}',
+                             exc_info=e if log_verbose else None)
                 retry -= 1
 
     async def aget(
@@ -99,7 +101,9 @@ class ApiRequest:
                     else:
                         return await client.get(url, params=params, **kwargs)
                 except Exception as e:
-                    logger.error(f"error when aget {url}: {e}")
+                    msg = f"error when aget {url}: {e}"
+                    logger.error(f'{e.__class__.__name__}: {msg}',
+                                 exc_info=e if log_verbose else None)
                     retry -= 1
 
     def post(
@@ -121,7 +125,9 @@ class ApiRequest:
                 else:
                     return httpx.post(url, data=data, json=json, **kwargs)
             except Exception as e:
-                logger.error(f"error when post {url}: {e}")
+                msg = f"error when post {url}: {e}"
+                logger.error(f'{e.__class__.__name__}: {msg}',
+                             exc_info=e if log_verbose else None)
                 retry -= 1
 
     async def apost(
@@ -143,7 +149,9 @@ class ApiRequest:
                     else:
                         return await client.post(url, data=data, json=json, **kwargs)
                 except Exception as e:
-                    logger.error(f"error when apost {url}: {e}")
+                    msg = f"error when apost {url}: {e}"
+                    logger.error(f'{e.__class__.__name__}: {msg}',
+                                 exc_info=e if log_verbose else None)
                     retry -= 1
 
     def delete(
@@ -164,7 +172,9 @@ class ApiRequest:
                 else:
                     return httpx.delete(url, data=data, json=json, **kwargs)
             except Exception as e:
-                logger.error(f"error when delete {url}: {e}")
+                msg = f"error when delete {url}: {e}"
+                logger.error(f'{e.__class__.__name__}: {msg}',
+                             exc_info=e if log_verbose else None)
                 retry -= 1
 
     async def adelete(
@@ -186,7 +196,9 @@ class ApiRequest:
                     else:
                         return await client.delete(url, data=data, json=json, **kwargs)
                 except Exception as e:
-                    logger.error(f"error when adelete {url}: {e}")
+                    msg = f"error when adelete {url}: {e}"
+                    logger.error(f'{e.__class__.__name__}: {msg}',
+                                 exc_info=e if log_verbose else None)
                     retry -= 1
 
     def _fastapi_stream2generator(self, response: StreamingResponse, as_json: bool =False):
@@ -205,7 +217,9 @@ class ApiRequest:
                 elif chunk.strip():
                     yield chunk
         except Exception as e:
-            logger.error(f"error when run fastapi router: {e}")
+            msg = f"error when run fastapi router: {e}"
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
 
     def _httpx_stream2generator(
         self,
@@ -226,7 +240,9 @@ class ApiRequest:
                             pprint(data, depth=1)
                             yield data
                         except Exception as e:
-                            logger.error(f"接口返回json错误： ‘{chunk}’。错误信息是：{e}。")
+                            msg = f"接口返回json错误： ‘{chunk}’。错误信息是：{e}。"
+                            logger.error(f'{e.__class__.__name__}: {msg}',
+                                         exc_info=e if log_verbose else None)
                     else:
                         print(chunk, end="", flush=True)
                         yield chunk
@@ -241,7 +257,8 @@ class ApiRequest:
             yield {"code": 500, "msg": msg}
         except Exception as e:
             msg = f"API通信遇到错误：{e}"
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             yield {"code": 500, "msg": msg}
 
     # 对话相关操作
@@ -414,7 +431,8 @@ class ApiRequest:
             return response.json()
         except Exception as e:
             msg = "API未能返回正确的JSON。" + (errorMsg or str(e))
-            logger.error(msg)
+            logger.error(f'{e.__class__.__name__}: {msg}',
+                         exc_info=e if log_verbose else None)
             return {"code": 500, "msg": msg}
 
     def list_knowledge_bases(