refactor: 清理未使用的导入和优化代码格式

Makefile

@@ -23,5 +23,5 @@ lint:
 	uv run python -m ruff check --select I src
 
 format format_diff:
-	uv run ruff format
-	uv run ruff check --select I --fix
+	uv run ruff format .
+	uv run ruff check . --fix

scripts/batch_upload.py

@@ -418,7 +418,8 @@ def upload(
                 all_processed_files = processed_files | newly_processed_hashes
                 save_processed_files(record_file, all_processed_files)
                 console.print(
-                    f"[bold green]Updated processed files record with {len(newly_processed_hashes)} new entries.[/bold green]"
+                    f"[bold green]Updated processed files record with "
+                    f"{len(newly_processed_hashes)} new entries.[/bold green]"
                 )
 
             console.print("[bold green]Batch operation complete.[/bold green]")

server/db_manager.py

@@ -6,8 +6,6 @@ from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker
 
 from server.models import Base
-from server.models.kb_models import KnowledgeDatabase, KnowledgeFile, KnowledgeNode
-from server.models.thread_model import Thread
 from server.models.user_model import User
 from src import config
 from src.utils import logger

server/main.py

@@ -1,7 +1,6 @@
 import uvicorn
-from fastapi import Depends, FastAPI, HTTPException, Request, status
+from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
-from fastapi.responses import JSONResponse
 from starlette.middleware.base import BaseHTTPMiddleware
 
 from server.routers import router

server/models/thread_model.py

@@ -1,6 +1,4 @@
-from sqlalchemy import Column, DateTime, ForeignKey, Integer, String, Text
-from sqlalchemy.dialects.mysql import JSON
-from sqlalchemy.orm import relationship
+from sqlalchemy import Column, DateTime, Integer, String
 from sqlalchemy.sql import func
 
 from server.models import Base

server/routers/auth_router.py

@@ -6,8 +6,8 @@ from pydantic import BaseModel
 from sqlalchemy.orm import Session
 
 from server.db_manager import db_manager
-from server.models.user_model import OperationLog, User
-from server.utils.auth_middleware import get_admin_user, get_current_user, get_db, get_superadmin_user, oauth2_scheme
+from server.models.user_model import User
+from server.utils.auth_middleware import get_admin_user, get_current_user, get_db
 from server.utils.auth_utils import AuthUtils
 from server.utils.common_utils import log_operation
 

server/routers/chat_router.py

@@ -1,11 +1,9 @@
 import asyncio
 import json
-import os
-import time
 import traceback
 import uuid
 
-from fastapi import APIRouter, Body, Depends, HTTPException, Query
+from fastapi import APIRouter, Body, Depends, HTTPException
 from fastapi.responses import StreamingResponse
 from langchain_core.messages import AIMessageChunk, HumanMessage
 from pydantic import BaseModel

server/routers/knowledge_router.py

@@ -1,13 +1,12 @@
-import asyncio
 import os
 import traceback
 
-from fastapi import APIRouter, Body, Depends, File, Form, HTTPException, Query, UploadFile
+from fastapi import APIRouter, Body, Depends, File, HTTPException, Query, UploadFile
 from fastapi.responses import FileResponse
 
 from server.models.user_model import User
 from server.utils.auth_middleware import get_admin_user
-from src import config, executor, knowledge_base
+from src import config, knowledge_base
 from src.knowledge.indexing import process_file_to_markdown
 from src.utils import hashstr, logger
 
@@ -41,7 +40,8 @@ async def create_database(
 ):
     """创建知识库"""
     logger.debug(
-        f"Create database {database_name} with kb_type {kb_type}, additional_params {additional_params}, llm_info {llm_info}"
+        f"Create database {database_name} with kb_type {kb_type}, "
+        f"additional_params {additional_params}, llm_info {llm_info}"
     )
     try:
         embed_info = config.embed_model_names[embed_model_name]

server/routers/system_router.py

@@ -4,11 +4,11 @@ from pathlib import Path
 
 import requests
 import yaml
-from fastapi import APIRouter, Body, Depends, HTTPException, Request
+from fastapi import APIRouter, Body, Depends, HTTPException
 
 from server.models.user_model import User
 from server.utils.auth_middleware import get_admin_user, get_superadmin_user
-from src import config, graph_base, knowledge_base
+from src import config, graph_base
 from src.utils.logging_config import logger
 
 system = APIRouter(prefix="/system", tags=["system"])

server/utils/auth_middleware.py

@@ -2,7 +2,7 @@ import re
 
 from fastapi import Depends, HTTPException, status
 from fastapi.security import OAuth2PasswordBearer
-from jose import JWTError, jwt
+from jose import JWTError
 from sqlalchemy.orm import Session
 
 from server.db_manager import db_manager

src/agents/common/mcp.py

@@ -1,13 +1,11 @@
 """MCP Client setup and management for LangGraph ReAct Agent."""
 
-import traceback
 from collections.abc import Callable
 from typing import Any, cast
 
 from langchain_mcp_adapters.client import (  # type: ignore[import-untyped]
     MultiServerMCPClient,
 )
-from langchain_mcp_adapters.tools import load_mcp_tools
 
 from src.utils import logger
 

src/agents/common/tools.py

@@ -1,5 +1,4 @@
 import asyncio
-import inspect
 import traceback
 from typing import Annotated, Any
 
@@ -18,7 +17,8 @@ def query_knowledge_graph(query: Annotated[str, "The keyword to query knowledge
         logger.debug(f"Querying knowledge graph with: {query}")
         result = graph_base.query_node(query, hops=2, return_format="triples")
         logger.debug(
-            f"Knowledge graph query returned {len(result.get('triples', [])) if isinstance(result, dict) else 'N/A'} triples"
+            f"Knowledge graph query returned "
+            f"{len(result.get('triples', [])) if isinstance(result, dict) else 'N/A'} triples"
         )
         return result
     except Exception as e:
@@ -79,7 +79,10 @@ def get_kb_based_tools() -> list:
             tool_id = f"query_{db_id[:8]}"
 
             # 构建工具描述
-            description = f"使用 {retrieve_info['name']} 知识库进行检索。\n下面是这个知识库的描述：\n{retrieve_info['description'] or '没有描述。'} "
+            description = (
+                f"使用 {retrieve_info['name']} 知识库进行检索。\n"
+                f"下面是这个知识库的描述：\n{retrieve_info['description'] or '没有描述。'} "
+            )
 
             # 使用工厂函数创建检索器包装函数，避免闭包问题
             retriever_wrapper = _create_retriever_wrapper(db_id, retrieve_info)

src/agents/common/utils.py

@@ -1,7 +1,6 @@
-import asyncio
 import os
 import traceback
-from datetime import UTC, datetime, timezone
+from datetime import UTC, datetime
 
 from langchain_core.language_models import BaseChatModel
 from langchain_core.messages import AIMessageChunk, ToolMessage

src/agents/react/graph.py

@@ -1,4 +1,3 @@
-import os
 from pathlib import Path
 
 from langchain_core.messages import AnyMessage, SystemMessage

src/config/__init__.py

@@ -52,8 +52,10 @@ class Config(SimpleConfig):
         self.add_item(
             "enable_web_search",
             default=False,
-            des="是否开启网页搜索（注：现阶段会根据 TAVILY_API_KEY 自动开启，无法手动配置，将会在下个版本移除此配置项）",
-        )  # noqa: E501
+            des=(
+                "是否开启网页搜索（注：现阶段会根据 TAVILY_API_KEY 自动开启，无法手动配置，将会在下个版本移除此配置项）"
+            ),
+        )
         # 默认智能体配置
         self.add_item("default_agent_id", default="", des="默认智能体ID")
         # 模型配置
@@ -133,11 +135,14 @@ class Config(SimpleConfig):
         if self.model_dir:
             if os.path.exists(self.model_dir):
                 logger.debug(
-                    f"The model directory （{self.model_dir}） contains the following folders: {os.listdir(self.model_dir)}"
+                    f"The model directory （{self.model_dir}） "
+                    f"contains the following folders: {os.listdir(self.model_dir)}"
                 )
             else:
                 logger.warning(
-                    f"Warning: The model directory （{self.model_dir}） does not exist. If not configured, please ignore it. If configured, please check if the configuration is correct;"
+                    f"Warning: The model directory （{self.model_dir}） does not exist. "
+                    "If not configured, please ignore it. "
+                    "If configured, please check if the configuration is correct; "
                     "For example, the mapping in the docker-compose file"
                 )
 

src/knowledge/__init__.py

@@ -1 +1,3 @@
 from .graphbase import GraphDatabase
+
+__all__ = ["GraphDatabase"]

src/knowledge/chroma_kb.py

@@ -1,17 +1,12 @@
-import json
 import os
-import time
 import traceback
 from datetime import datetime
-from pathlib import Path
-from typing import Any, Optional
+from typing import Any
 
 import chromadb
-from chromadb.api.types import Documents, EmbeddingFunction, Embeddings
 from chromadb.config import Settings
 from chromadb.utils.embedding_functions import OpenAIEmbeddingFunction
 
-from src import config
 from src.knowledge.indexing import process_file_to_markdown, process_url_to_markdown
 from src.knowledge.kb_utils import (
     get_embedding_config,
@@ -20,7 +15,7 @@ from src.knowledge.kb_utils import (
     split_text_into_qa_chunks,
 )
 from src.knowledge.knowledge_base import KnowledgeBase
-from src.utils import hashstr, logger
+from src.utils import logger
 
 
 class ChromaKB(KnowledgeBase):
@@ -84,7 +79,8 @@ class ChromaKB(KnowledgeBase):
             # 如果模型不匹配，删除现有集合并重新创建
             if current_model != expected_model:
                 logger.warning(
-                    f"Collection {collection_name} uses model '{current_model}', but expected '{expected_model}'. Recreating collection."
+                    f"Collection {collection_name} uses model '{current_model}', "
+                    f"but expected '{expected_model}'. Recreating collection."
                 )
                 self.chroma_client.delete_collection(name=collection_name)
                 raise Exception("Model mismatch, recreating collection")

src/knowledge/graphbase.py

@@ -4,7 +4,6 @@ import traceback
 import warnings
 
 from neo4j import GraphDatabase as GD
-from neo4j import Query
 
 from src import config
 from src.models import select_embedding_model
@@ -301,7 +300,8 @@ class GraphDatabase:
             for i in range(0, total_entities, max_batch_size):
                 batch_entities = nodes_without_embedding[i : i + max_batch_size]
                 logger.debug(
-                    f"Processing entities batch {i // max_batch_size + 1}/{(total_entities - 1) // max_batch_size + 1} ({len(batch_entities)} entities)"
+                    f"Processing entities batch {i // max_batch_size + 1}/"
+                    f"{(total_entities - 1) // max_batch_size + 1} ({len(batch_entities)} entities)"
                 )
 
                 # 批量获取嵌入向量

src/knowledge/indexing.py

@@ -2,7 +2,6 @@ import asyncio
 import os
 from pathlib import Path
 
-from langchain.schema.document import Document
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.document_loaders import (
     CSVLoader,
@@ -14,7 +13,7 @@ from langchain_community.document_loaders import (
     UnstructuredMarkdownLoader,
 )
 
-from src.utils import hashstr, logger
+from src.utils import logger
 
 
 def chunk_with_parser(file_path, params=None):

src/knowledge/kb_factory.py

@@ -1,5 +1,3 @@
-from typing import Any
-
 from src.knowledge.knowledge_base import KBNotFoundError, KnowledgeBase
 from src.utils import logger
 

src/knowledge/kb_manager.py

@@ -1,12 +1,10 @@
 import asyncio
 import json
 import os
-import time
 from datetime import datetime
-from typing import Any
 
 from src.knowledge.kb_factory import KnowledgeBaseFactory
-from src.knowledge.knowledge_base import KBNotFoundError, KBOperationError, KnowledgeBase
+from src.knowledge.knowledge_base import KBNotFoundError, KnowledgeBase
 from src.utils import logger
 
 

src/knowledge/kb_utils.py

@@ -1,12 +1,11 @@
 import os
 import time
 from pathlib import Path
-from typing import Any
 
 from langchain_text_splitters import MarkdownTextSplitter
 
 from src import config
-from src.utils import get_docker_safe_url, hashstr, logger
+from src.utils import hashstr, logger
 
 
 def split_text_into_chunks(text: str, file_id: str, filename: str, params: dict = {}) -> list[dict]:

src/knowledge/knowledge_base.py

@@ -2,9 +2,7 @@ import json
 import os
 import time
 from abc import ABC, abstractmethod
-from collections.abc import AsyncGenerator
 from datetime import datetime
-from pathlib import Path
 from typing import Any
 
 from src.utils import logger

src/knowledge/milvus_kb.py

@@ -1,16 +1,11 @@
 import asyncio
-import json
 import os
-import time
 import traceback
-from datetime import datetime
 from functools import partial
-from pathlib import Path
 from typing import Any
 
 from pymilvus import Collection, CollectionSchema, DataType, FieldSchema, connections, db, utility
 
-from src import config
 from src.knowledge.indexing import process_file_to_markdown, process_url_to_markdown
 from src.knowledge.kb_utils import (
     get_embedding_config,

src/models/chat_model.py

@@ -1,7 +1,5 @@
 import os
 
-import requests
-from langchain_openai import ChatOpenAI
 from openai import OpenAI
 
 from src.utils import get_docker_safe_url, logger
@@ -38,7 +36,10 @@ class OpenAIBase:
                     yield chunk.choices[0].delta
 
         except Exception as e:
-            err = f"Error streaming response: {e}, URL: {self.base_url}, API Key: {self.api_key[:5]}***, Model: {self.model_name}"
+            err = (
+                f"Error streaming response: {e}, URL: {self.base_url}, "
+                f"API Key: {self.api_key[:5]}***, Model: {self.model_name}"
+            )
             logger.error(err)
             raise Exception(err)
 

src/models/embedding.py

@@ -6,7 +6,6 @@ from abc import ABC, abstractmethod
 import httpx
 import requests
 
-from src import config
 from src.utils import get_docker_safe_url, hashstr, logger
 
 

src/models/rerank_model.py

@@ -5,7 +5,7 @@ import numpy as np
 import requests
 
 from src import config
-from src.utils import get_docker_safe_url, logger
+from src.utils import get_docker_safe_url
 
 
 def sigmoid(x):

src/plugins/_ocr.py

@@ -3,7 +3,6 @@ import time
 import uuid
 from argparse import ArgumentParser
 from collections import defaultdict
-from pathlib import Path
 
 import fitz  # fitz就是pip install PyMuPDF
 import numpy as np  # Added import for numpy
@@ -11,7 +10,7 @@ from PIL import Image
 from rapidocr_onnxruntime import RapidOCR
 from tqdm import tqdm
 
-from src.utils import is_text_pdf, logger
+from src.utils import logger
 
 GOLBAL_STATE = {}
 

src/plugins/mineru.py

@@ -196,7 +196,10 @@ def parse_doc(
     Parameter description:
     path_list: List of document paths to be parsed, can be PDF or image files.
     output_dir: Output directory for storing parsing results.
-    lang: Language option, default is 'ch', optional values include['ch', 'ch_server', 'ch_lite', 'en', 'korean', 'japan', 'chinese_cht', 'ta', 'te', 'ka']。
+    lang: Language option, default is 'ch',
+        optional values include[
+            'ch', 'ch_server', 'ch_lite', 'en', 'korean', 'japan', 'chinese_cht', 'ta', 'te', 'ka'
+        ]。
         Input the languages in the pdf (if known) to improve OCR accuracy.  Optional.
         Adapted only for the case where the backend is set to "pipeline"
     backend: the backend for parsing pdf:

src/plugins/paddlex.py

@@ -3,7 +3,7 @@ import json
 import os
 import time
 from pathlib import Path
-from typing import Any, Optional
+from typing import Any
 
 import requests
 

src/utils/logging_config.py

@@ -32,7 +32,12 @@ def setup_logger(name, level="DEBUG", console=True):
         loguru_logger.add(
             lambda msg: print(msg, end=""),
             level=level,
-            format="<green>{time:MM-DD HH:mm:ss}</green> <level>{level}</level> <cyan>{name}:{line}</cyan>: <level>{message}</level>",
+            format=(
+                "<green>{time:MM-DD HH:mm:ss}</green> "
+                "<level>{level}</level> "
+                "<cyan>{name}:{line}</cyan>: "
+                "<level>{message}</level>"
+            ),
             colorize=True,
         )
 

src/utils/prompts.py

@@ -66,4 +66,8 @@ keywords_prompt_template = """
 <文本>{text}</文本>
 """
 
-HYDE_PROMPT_TEMPLATE = "Please write a passage to answer the question\nTry to include as many key details as possible.\n\n\n{context_str}\n\n{query}\n\nPassage:\n"
+HYDE_PROMPT_TEMPLATE = (
+    "Please write a passage to answer the question\n"
+    "Try to include as many key details as possible.\n\n\n"
+    "{context_str}\n\n{query}\n\nPassage:\n"
+)

test/test_concurrency.py

@@ -18,7 +18,9 @@ async def make_request(session: aiohttp.ClientSession, request_id: int) -> dict:
             end_time = time.time()
             duration = end_time - start_time
             print(
-                f"请求 {request_id} 完成时间: {time.strftime('%H:%M:%S', time.localtime(end_time))} (耗时: {duration:.2f}秒)"
+                f"请求 {request_id} 完成时间: "
+                f"{time.strftime('%H:%M:%S', time.localtime(end_time))} "
+                f"(耗时: {duration:.2f}秒)"
             )
             return {
                 "request_id": request_id,
@@ -32,7 +34,9 @@ async def make_request(session: aiohttp.ClientSession, request_id: int) -> dict:
         end_time = time.time()
         duration = end_time - start_time
         print(
-            f"请求 {request_id} 失败时间: {time.strftime('%H:%M:%S', time.localtime(end_time))} (耗时: {duration:.2f}秒)"
+            f"请求 {request_id} 失败时间: "
+            f"{time.strftime('%H:%M:%S', time.localtime(end_time))} "
+            f"(耗时: {duration:.2f}秒)"
         )
         return {
             "request_id": request_id,
@@ -102,7 +106,10 @@ def analyze_results(results: list[dict]) -> None:
         active_requests.append(end_time)
 
         print(
-            f"{result['request_id']:^7} {time.strftime('%H:%M:%S', time.localtime(start_time))}  {time.strftime('%H:%M:%S', time.localtime(end_time))}  {result['time']:^8.2f}  {len(active_requests):^6}"
+            f"{result['request_id']:^7} "
+            f"{time.strftime('%H:%M:%S', time.localtime(start_time))} "
+            f"{time.strftime('%H:%M:%S', time.localtime(end_time))} "
+            f"{result['time']:^8.2f}  {len(active_requests):^6}"
         )
 
     # 计算最大并发数