app_line.htm 出现的错误

最新推荐文章于 2023-07-17 14:13:15 发布
最新推荐文章于 2023-07-17 14:13:15 发布
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本文介绍了在程序调试过程中遇到的“app_offline.htm”文件导致的应用无法启动问题及其解决方案。通过从项目中移除该文件或直接删除，可以有效解决此问题。

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今天在调试程序的时候，出现一个

This application is currently offline. To enable the application, remove the app_offline.htm file from the application root directory.   的错误
解决方法：把 “app_offline.htm” 不包含在项目中，或者将它删除 ，问题即解。
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递归比较选项 self.recursive_var = tk.BooleanVar(value=True) recursive_check = ttk.Checkbutton(options_frame, text="递归比较子文件夹", variable=self.recursive_var) recursive_check.grid(row=0, column=0, padx=10, pady=5, sticky=tk.W) # 文件过滤 filter_frame = ttk.Frame(options_frame) filter_frame.grid(row=0, column=1, padx=10, pady=5, sticky=tk.W) ttk.Label(filter_frame, text="文件过滤:").pack(side=tk.LEFT, padx=(0, 5)) self.filter_var = tk.StringVar(value="*.*") filter_entry = ttk.Entry(filter_frame, textvariable=self.filter_var, width=15) filter_entry.pack(side=tk.LEFT) # 目标Excel选择 excel_frame = ttk.LabelFrame(main_frame, text="输出设置", padding="12") excel_frame.pack(fill=tk.X, pady=5) ttk.Label(excel_frame, text="目标Excel文件:").grid(row=0, column=0, sticky=tk.W, padx=5, pady=5) self.excel_file_entry = ttk.Entry(excel_frame, width=60) self.excel_file_entry.grid(row=0, column=1, padx=5, pady=5) ttk.Button(excel_frame, text="浏览...", command=lambda: self.select_file(self.excel_file_entry, [("Excel文件", "*.xlsx *.xlsm")])).grid(row=0, column=2, padx=5, pady=5) # 执行按钮区域 button_frame = ttk.Frame(main_frame) button_frame.pack(fill=tk.X, pady=10) self.run_button = ttk.Button(button_frame, text="执行比较", command=self.start_processing, width=20, style='TButton') self.run_button.pack(side=tk.LEFT) # 停止按钮 self.stop_button = ttk.Button(button_frame, text="停止", command=self.stop_processing, width=10, state=tk.DISABLED) self.stop_button.pack(side=tk.LEFT, padx=10) # 进度条 self.progress = ttk.Progressbar(main_frame, orient=tk.HORIZONTAL, length=700, mode='determinate') self.progress.pack(fill=tk.X, pady=5) # 状态信息 status_frame = ttk.Frame(main_frame) status_frame.pack(fill=tk.X, pady=5) self.status_var = tk.StringVar(value="准备就绪") status_label = ttk.Label(status_frame, textvariable=self.status_var, font=("Segoe UI", 9), foreground="#2E7D32") status_label.pack(side=tk.LEFT) # 日志和预览区域 notebook = ttk.Notebook(main_frame) notebook.pack(fill=tk.BOTH, expand=True, pady=5) # 文件夹结构标签 tree_frame = ttk.Frame(notebook, padding="5") notebook.add(tree_frame, text="文件夹结构") # 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使用win32com打开Excel excel = win32.gencache.EnsureDispatch('Excel.Application') excel.Visible = True workbook = excel.Workbooks.Open(os.path.abspath(excel_path)) sheet = workbook.Sheets("一覧") # 从第6行开始写入数据 start_row = 6 for i, row_data in enumerate(diff_data): for j, value in enumerate(row_data[:6]): # 确保值是字符串类型 sheet.Cells(start_row + i, j + 1).Value = str(value) # 保存Excel workbook.Save() self.log_message(f"数据已写入Excel第{start_row}行开始") # 触发"作成"按钮 self.log_message("正在触发'作成'按钮...") try: # 查找按钮并点击 button = sheet.Buttons("作成") button.OnAction = "作成按钮的处理" button.Click() self.log_message("已触发'作成'按钮") # 等待处理完成 self.update_status("处理中...请等待") # 简单等待机制 for _ in range(30): # 最多等待30秒 if not self.processing: break if excel.CalculationState == 0: # 0 = xlDone break time.sleep(1) self.log_message("处理中...") self.log_message("处理完成") self.update_status("处理完成") except Exception as e: # 修复TypeError: 使用f-string记录异常 self.log_message(f"按钮操作失败: {str(e)}. 请手动点击'作成'按钮") # 关闭Excel workbook.Close() excel.Quit() return True except Exception as e: # 修复TypeError: 使用f-string记录异常 self.log_message(f"Excel操作失败: {str(e)}\n{traceback.format_exc()}") return False def start_processing(self): """启动处理线程 - 修复无响应问题""" if self.processing: self.log_message("警告: 处理正在进行中") return # 获取路径 old_path = self.old_folder_entry.get() new_path = self.new_folder_entry.get() excel_file = self.excel_file_entry.get() # 详细路径验证 validation_errors = [] if not old_path: validation_errors.append("原始文件夹路径为空") elif not os.path.isdir(old_path): validation_errors.append(f"原始文件夹路径无效: {old_path}") if not new_path: validation_errors.append("新文件夹路径为空") elif not os.path.isdir(new_path): validation_errors.append(f"新文件夹路径无效: {new_path}") if not excel_file: validation_errors.append("Excel文件路径为空") elif not excel_file.lower().endswith(('.xlsx', '.xlsm')): validation_errors.append("Excel文件必须是.xlsx或.xlsm格式") if validation_errors: self.log_message("错误: " + "; ".join(validation_errors)) messagebox.showerror("输入错误", "\n".join(validation_errors)) return # 检查WinMerge安装 winmerge_path = r"E:\App\WinMerge\WinMerge2.16.12.0\WinMergeU.exe" if not os.path.exists(winmerge_path): self.log_message(f"错误: WinMerge未安装在默认位置 {winmerge_path}") messagebox.showwarning("WinMerge未安装", "请确保WinMerge已安装或更新路径配置") return # 禁用执行按钮，启用停止按钮 self.run_button.config(state=tk.DISABLED) self.stop_button.config(state=tk.NORMAL) self.processing = True # 启动处理线程 thread = threading.Thread(target=self.process_folders, args=(old_path, new_path, excel_file)) thread.daemon = True thread.start() self.log_message("处理线程已启动") def process_folders(self, old_path, new_path, excel_file): """处理文件夹比较的线程函数 - 增强异常处理""" output_html = None try: # 步骤1: 生成HTML差异文件 self.update_status("生成HTML差异文件...") self.update_progress(20) # 使用临时文件存储HTML报告 with tempfile.NamedTemporaryFile(suffix=".html", delete=False) as temp_file: output_html = temp_file.name if not self.run_winmerge(old_path, new_path, output_html): self.update_status("WinMerge执行失败") return # 步骤2: 将HTML文件与Excel放在同一目录 self.update_status("准备文件...") self.update_progress(40) excel_dir = os.path.dirname(excel_file) if excel_dir: target_html = os.path.join(excel_dir, "diff_report.html") try: shutil.copy(output_html, target_html) self.log_message(f"已将HTML文件复制到: {target_html}") except Exception as e: self.log_message(f"文件复制失败: {str(e)}") return # 步骤3: 解析HTML差异文件 self.update_status("解析差异数据...") self.update_progress(60) diff_data = self.parse_html_diff(output_html) if not diff_data: self.update_status("HTML解析失败") return # 步骤4: 写入Excel并触发按钮 self.update_status("写入Excel并触发处理...") self.update_progress(80) if not self.write_to_excel(excel_file, diff_data): self.update_status("Excel操作失败") return # 完成 self.update_progress(100) self.update_status("处理完成！") self.log_message("文件夹比较流程执行完毕") messagebox.showinfo("完成", "文件夹比较处理成功完成") except Exception as e: error_msg = f"执行过程中发生错误: {str(e)}\n{traceback.format_exc()}" self.log_message(error_msg) self.update_status("执行失败") messagebox.showerror("错误", f"处理失败: {str(e)}") finally: # 重新启用执行按钮 if self.processing: self.stop_processing() # 清理临时文件 if output_html and os.path.exists(output_html): try: os.remove(output_html) except: pass def run_winmerge(self, path1, path2, output_html): """增强的WinMerge调用方法 - 解决弹窗阻塞问题""" winmerge_path = r"E:\App\WinMerge\WinMerge2.16.12.0\WinMergeU.exe" # 验证WinMerge可执行文件 if not os.path.exists(winmerge_path): self.log_message(f"错误: WinMerge路径不存在 {winmerge_path}") return False # 构建抑制弹窗的命令参数 winmerge_cmd = [ winmerge_path, '/u', # 不显示GUI界面 '/minimize', # 最小化窗口 '/noprefs', # 不使用保存的选项 '/exit', # 完成后自动退出 - 关键参数[^1] '/dl', 'Base', '/dr', 'Modified', '/or', output_html, path1, path2 ] # 添加递归选项 if self.recursive_var.get(): winmerge_cmd.insert(1, '/r') self.log_message(f"执行命令: {' '.join(winmerge_cmd)}") try: # 使用Popen启动进程（非阻塞） proc = subprocess.Popen( winmerge_cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, creationflags=subprocess.CREATE_NO_WINDOW ) # 设置超时监控 timeout = 120 # 秒 start_time = time.time() while proc.poll() is None: # 进程仍在运行 # 更新状态 elapsed = int(time.time() - start_time) self.update_status(f"生成报告中...({elapsed}秒)") # 超时处理 if elapsed > timeout: self.log_message("WinMerge执行超时，强制终止进程") proc.terminate() try: proc.wait(timeout=5) except subprocess.TimeoutExpired: proc.kill() return False # 定期检查进程状态 time.sleep(1) # 检查退出码 if proc.returncode == 0: # 验证报告文件是否生成 if not os.path.exists(output_html): self.log_message(f"错误: 报告文件未生成 {output_html}") return False # 验证报告内容有效性 with open(output_html, 'r', encoding='utf-8') as f: content = f.read(1024) # 只读取前1KB检查 if '<table' not in content: self.log_message("警告: 报告文件不包含表格数据") self.log_message(f"HTML差异报告生成成功: {output_html}") return True else: # 获取错误输出 stderr_output = proc.stderr.read().decode('utf-8', errors='ignore') error_msg = f"WinMerge异常退出(代码{proc.returncode}): {stderr_output}" self.log_message(error_msg) return False except Exception as e: self.log_message(f"WinMerge执行错误: {str(e)}") return False def parse_html_diff(self, html_file): """增强的HTML报告解析方法 - 解决表格查找失败问题""" try: # 验证文件是否存在 if not os.path.exists(html_file): self.log_message(f"错误: HTML文件不存在 {html_file}") return [] # 读取文件内容（处理可能的编码问题） with open(html_file, 'r', encoding='utf-8', errors='ignore') as f: content = f.read() # 检查是否有有效内容 if not content.strip(): self.log_message("警告: HTML文件为空") return [] soup = BeautifulSoup(content, 'html.parser') # 增强表格查找方法 - 尝试多种定位方式[^2] table = None # 方式1: 通过特定ID查找 table = soup.find('table', id='filediff') # 方式2: 通过特定class查找 if not table: table = soup.find('table', class_='filediff') # 方式3: 查找包含特定标题的表格 if not table: for t in soup.find_all('table'): if t.find('th', text='Filename'): table = t break if not table: self.log_message("未找到差异表格，可能是无差异或格式变化") return [] # 提取差异文件列表 diff_files = [] for row in table.find_all('tr')[1:]: # 跳过表头 cols = row.find_all('td') if len(cols) >= 3: # 获取文件名（第二列或第三列） filename = cols[1].get_text(strip=True) or cols[2].get_text(strip=True) if filename: diff_files.append(filename) self.log_message(f"解析到 {len(diff_files)} 个差异文件") return diff_files except Exception as e: self.log_message(f"解析HTML报告错误: {str(e)}") return [] def write_to_excel(self, excel_path, diff_data): """将差异数据写入Excel - 增强健壮性""" self.log_message("正在写入Excel文件...") excel = None workbook = None try: # 验证Excel文件存在 if not os.path.exists(excel_path): self.log_message(f"错误: Excel文件不存在 {excel_path}") return False # 使用win32com打开Excel excel = win32.gencache.EnsureDispatch('Excel.Application') excel.Visible = True excel.DisplayAlerts = False # 禁用警告提示 # 尝试打开工作簿 try: workbook = excel.Workbooks.Open(os.path.abspath(excel_path)) except Exception as e: self.log_message(f"打开Excel文件失败: {str(e)}") return False # 检查工作表是否存在 sheet_names = [sheet.Name for sheet in workbook.Sheets] if "一覧" not in sheet_names: self.log_message("错误: Excel文件中缺少'一覧'工作表") return False sheet = workbook.Sheets("一覧") # 从第6行开始写入数据 start_row = 6 for i, row_data in enumerate(diff_data): for j, value in enumerate(row_data[:6]): # 确保值是字符串类型 sheet.Cells(start_row + i, j + 1).Value = str(value) # 保存Excel workbook.Save() self.log_message(f"数据已写入Excel第{start_row}行开始") # 触发"作成"按钮 self.log_message("正在触发'作成'按钮...") try: # 查找按钮并点击 button = sheet.Buttons("作成") button.OnAction = "作成按钮的处理" button.Click() self.log_message("已触发'作成'按钮") # 等待处理完成 self.update_status("处理中...请等待") wait_time = 0 max_wait = 60 # 最大等待60秒 while self.processing and wait_time < max_wait: if excel.CalculationState == 0: # 0 = xlDone break time.sleep(1) wait_time += 1 self.log_message(f"处理中...({wait_time}秒)") if wait_time >= max_wait: self.log_message("警告: 处理超时") else: self.log_message("处理完成") return True except Exception as e: self.log_message(f"按钮操作失败: {str(e)}. 请手动点击'作成'按钮") return False except Exception as e: self.log_message(f"Excel操作失败: {str(e)}\n{traceback.format_exc()}") return False finally: # 确保正确关闭Excel try: if workbook: workbook.Close(SaveChanges=False) if excel: excel.Quit() except Exception as e: self.log_message(f"关闭Excel时出错: {str(e)}") def stop_processing(self): """停止处理""" self.processing = False self.stop_button.config(state=tk.DISABLED) self.run_button.config(state=tk.NORMAL) self.update_status("操作已停止") def process_folders(self, old_path, new_path, excel_file): """处理文件夹比较的线程函数""" try: # 步骤1: 生成HTML差异文件 self.update_status("生成HTML差异文件...") self.update_progress(20) # 使用临时文件存储HTML报告 with tempfile.NamedTemporaryFile(suffix=".html", delete=False) as temp_file: output_html = temp_file.name if not self.run_winmerge(old_path, new_path, output_html): return # 步骤2: 将HTML文件与Excel放在同一目录 self.update_status("准备文件...") self.update_progress(40) excel_dir = os.path.dirname(excel_file) if excel_dir: target_html = os.path.join(excel_dir, "diff_report.html") shutil.copy(output_html, target_html) self.log_message(f"已将HTML文件复制到: {target_html}") # 步骤3: 解析HTML差异文件 self.update_status("解析差异数据...") self.update_progress(60) diff_data = self.parse_html_diff(output_html) if not diff_data: return # 步骤4: 写入Excel并触发按钮 self.update_status("写入Excel并触发处理...") self.update_progress(80) self.write_to_excel(excel_file, diff_data) # 完成 self.update_progress(100) self.update_status("处理完成！") self.log_message("文件夹比较流程执行完毕") except Exception as e: # 修复TypeError: 使用f-string记录异常 error_msg = f"执行过程中发生错误: {str(e)}\n{traceback.format_exc()}" self.log_message(error_msg) self.update_status("执行失败") finally: # 重新启用执行按钮 if self.processing: self.stop_processing() # 清理临时文件 if os.path.exists(output_html): try: os.remove(output_html) except: pass if __name__ == "__main__": root = tk.Tk() app = DiffProcessorApp(root) root.mainloop() 检查代码的问题，并提供完整代码实现我的要求
07-11
key = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, r"SOFTWARE\Microsoft\Windows\CurrentVersion\App Paths\WinMergeU.exe") path = winreg.QueryValue(key, None) return path except: # 尝试常见安装路径 ...
# mcp_server.py from datetime import datetime from mcp.server.fastmcp import FastMCP import logging import os import asyncio import hashlib import json import threading import time import numpy as np import faiss from langchain_community.docstore.in_memory import InMemoryDocstore from langchain_community.vectorstores import FAISS from langchain_community.llms import OpenAIChat from langchain.chains import RetrievalQA from ollama_embeding import CustomEmbeding from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler from langchain_community.document_loaders import ( TextLoader, PyPDFLoader, Docx2txtLoader, UnstructuredPowerPointLoader, UnstructuredExcelLoader, CSVLoader, UnstructuredHTMLLoader, UnstructuredMarkdownLoader, UnstructuredEmailLoader, UnstructuredFileLoader ) # 配置日志记录器 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logger = logging.getLogger(__name__) # 创建 FastMCP 实例 mcp = FastMCP("VectorService") class VectorService: def __init__(self): self.embedding_function = CustomEmbeding('shaw/dmeta-embedding-zh') self.docstore = InMemoryDocstore() self.index = faiss.IndexFlatL2(768) self.vector_store = None self.existing_index_path = "E:/llm_rag/faiss_index/index.faiss" self.existing_index_pkl_path = "E:/llm_rag/faiss_index/index.pkl" self.is_processing = False self.last_processed_count = 0 self.is_initialized = False # 添加初始化完成标志 self.load_or_init_vector_store() # 初始化向量存储 self.is_initialized = True # 初始化完成 def load_or_init_vector_store(self): if self.vector_store is not None: return self.vector_store # 已初始化 if os.path.exists(self.existing_index_path) and os.path.exists(self.existing_index_pkl_path): vector_store = FAISS.load_local( "E:/llm_rag/faiss_index", embeddings=self.embedding_function, allow_dangerous_deserialization=True ) logger.info("Loaded existing vector store.") self.vector_store = vector_store return vector_store else: vector_store = FAISS( embedding_function=self.embedding_function, index=self.index, docstore=self.docstore, index_to_docstore_id={} ) logger.info("Initialized new vector store.") self.vector_store = vector_store return vector_store def get_id(self, file_path): """Generate file id""" return hashlib.md5(file_path.encode()).hexdigest() def load_document(self, file_path: str): file_ext = file_path.split('.')[-1].lower() logger.info(f"Loading document from {file_path}") loader_map = { 'txt': TextLoader, 'pdf': PyPDFLoader, 'docx': Docx2txtLoader, 'pptx': UnstructuredPowerPointLoader, 'xlsx': UnstructuredExcelLoader, 'csv': CSVLoader, 'html': UnstructuredHTMLLoader, 'htm': UnstructuredHTMLLoader, 'md': UnstructuredMarkdownLoader, 'eml': UnstructuredEmailLoader, 'msg': UnstructuredEmailLoader } if file_ext not in loader_map: logger.warning(f"Unsupported file type: {file_ext}") return None loader_class = loader_map.get(file_ext, UnstructuredFileLoader) loader = loader_class(file_path) try: documents = loader.load() logger.info(f"Loaded {len(documents)} documents from {file_path}") return documents except Exception as e: logger.error(f"Error loading {file_path}: {str(e)}") return None def _add_vector_metadata(self, file_name, file_name_path): """ 添加文件元数据 :return: """ docs = [] metadatas = [] try: file_stats = os.stat(file_name_path) file_size = file_stats.st_size res = self.load_document(file_name_path) if res: # 生成文件唯一标识（使用文件路径的哈希值） id = self.get_id(file_name_path) for doc in res: # 合并用户提供的元数据和文档自身的元数据 doc_metadata = doc.metadata.copy() doc_metadata.update({ "source": file_name, "file_path": file_name_path, "id": id, "upload_time": datetime.now().isoformat() }) # docs.append(doc.page_content.strip()) # 将文件名融入内容（提高文件名的权重） enhanced_content = f"文件名: {file_name}\n内容: {doc.page_content.strip()}" docs.append(enhanced_content) metadatas.append(doc_metadata) logger.info(f"Processed {file_name} ({file_size / (1024 * 1024.0):.2f} MB)") except Exception as e: logger.error(f"Error processing {file_name_path}: {str(e)}") return docs, metadatas def process_documents(self, data_path: str): """把所有文件进行批量向量化，添加文件唯一标识""" try: self.is_processing = True all_docs = [] all_metadatas = [] for root, dirs, files in os.walk(data_path): for file_name in files: file_name_path = os.path.join(root, file_name) logger.info(f"Processing file: {file_name_path}") # 调用 _add_vector_metadata 处理文件 docs, metadatas = self._add_vector_metadata( file_name=file_name, file_name_path=file_name_path ) # 累积结果 all_docs.extend(docs) all_metadatas.extend(metadatas) # 保存所有文件的向量数据 self._save_data_vector(docs=all_docs, metadatas=all_metadatas) self.last_processed_count = len(all_docs) self.is_processing = False return { "status": "success", "message": "Documents processed successfully", "document_count": len(all_docs) } except Exception as e: logger.error(f"Error processing documents: {str(e)}") self.is_processing = False return {"status": "error", "message": str(e)} def _save_data_vector(self, docs, metadatas): """Save the data vector to faiss""" self.vector_store = self.load_or_init_vector_store() docs = [doc for doc in docs if doc] try: logger.info("Starting embedding process...") self.vector_store.add_texts(texts=docs, metadatas=metadatas) logger.info("Embedding process completed.") except Exception as e: logger.error(f"An error occurred during embedding: {str(e)}") try: logger.info("Saving updated vector store...") self.vector_store.save_local("E:/llm_rag/faiss_index") logger.info("Updated vector store saved to E:/llm_rag/faiss_index.") except Exception as e: logger.error(f"An error occurred during saving: {str(e)}") return docs def check_process_status(self): """检查处理状态""" if self.is_processing: return { "status": "processing", "message": "Documents are being processed" } else: if os.path.exists(self.existing_index_path) and os.path.exists(self.existing_index_pkl_path): if self.last_processed_count > 0: return { "status": "success", "message": "Vector data has been updated", "last_processed_count": self.last_processed_count } else: return { "status": "ready", "message": "Vector store exists but no new data processed" } else: return { "status": "empty", "message": "No vector store exists" } def add_vector(self, new_file_name_path: str, new_file_name: str): """添加单个文件的向量""" try: self.is_processing = True docs, metadatas = self._add_vector_metadata( file_name=new_file_name, file_name_path=new_file_name_path ) self._save_data_vector(docs=docs, metadatas=metadatas) self.last_processed_count = len(docs) self.is_processing = False return { "status": "success", "message": "Vector added successfully" } except Exception as e: logger.error(f"Error adding vector: {str(e)}") self.is_processing = False return { "status": "error", "message": str(e) } vector_service = VectorService() @mcp.tool() def process_documents(data_path: str): """处理指定路径下的所有文档并生成向量存储""" logger.info(f"Starting to process documents in {data_path}") return vector_service.process_documents(data_path) @mcp.tool() def check_process_status(): """检查处理状态""" logger.info("Checking process status") return vector_service.check_process_status() @mcp.tool() def add_vector(new_file_name_path: str, new_file_name: str): """添加单个文件的向量""" logger.info(f"Adding vector for file: {new_file_name_path}") return vector_service.add_vector(new_file_name_path, new_file_name) @mcp.tool(name="searchfile", description=f"根据关键词搜索文件并返回匹配的内容") def search_answer(query: str): """ 获取检索相关的文件 :param query: 用户问题 :return: 返回检索到的文档 """ if not vector_service.is_initialized: logger.info("Server is not initialized yet. Please wait.") return {"status": "error", "message": "Server is not initialized yet. Please wait."} logger.info(f"Searching for relevant documents: {query}") try: retriever = FAISS.load_local( "E:/llm_rag/faiss_index", CustomEmbeding('shaw/dmeta-embedding-zh'), allow_dangerous_deserialization=True ).as_retriever(search_kwargs={"k": 10}) docs = retriever.get_relevant_documents(query) logger.info(f"找到 {len(docs)} 个相关文档块") logger.info(f"docs:{docs}") # return docs results = [] for doc in docs: metadata = doc.metadata file_path = metadata.get("file_path", "") # 安全检查：确保文件在允许的目录内 allowed_dir = "E:\\llm_rag\\data\\" if file_path and file_path.startswith(allowed_dir): # 生成相对路径并构建下载URL download_url = os.path.relpath(file_path, allowed_dir) results.append({ "content": doc.page_content, # 文档内容 "download_url": download_url # 下载链接 }) return results except Exception as e: logger.error(f"搜索出错: {str(e)}") return {"status": "error", "message": str(e)} if __name__ == "__main__": mcp.settings.port = 8880 logger.info("Starting mcp server through MCP") mcp.run(transport="sse") # 使用标准输入输出通信 报了这个 + Exception Group Traceback (most recent call last): | File "E:\llm_rag\.venv\lib\site-packages\uvicorn\protocols\http\h11_impl.py", line 403, in run_asgi | result = await app( # type: ignore[func-returns-value] | File "E:\llm_rag\.venv\lib\site-packages\uvicorn\middleware\proxy_headers.py", line 60, in __call__ | return await self.app(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\applications.py", line 112, in __call__ | await self.middleware_stack(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\middleware\errors.py", line 187, in __call__ | raise exc | File "E:\llm_rag\.venv\lib\site-packages\starlette\middleware\errors.py", line 165, in __call__ | await self.app(scope, receive, _send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\middleware\exceptions.py", line 62, in __call__ | await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\_exception_handler.py", line 53, in wrapped_app | raise exc | File "E:\llm_rag\.venv\lib\site-packages\starlette\_exception_handler.py", line 42, in wrapped_app | await app(scope, receive, sender) | File "E:\llm_rag\.venv\lib\site-packages\starlette\routing.py", line 714, in __call__ | await self.middleware_stack(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\routing.py", line 734, in app | await route.handle(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\routing.py", line 288, in handle | await self.app(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\routing.py", line 76, in app | await wrap_app_handling_exceptions(app, request)(scope, receive, send) | File "E:\llm_rag\.venv\lib\site-packages\starlette\_exception_handler.py", line 53, in wrapped_app | raise exc | File "E:\llm_rag\.venv\lib\site-packages\starlette\_exception_handler.py", line 42, in wrapped_app | await app(scope, receive, sender) | File "E:\llm_rag\.venv\lib\site-packages\starlette\routing.py", line 73, in app | response = await f(request) | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\fastmcp\server.py", line 747, in sse_endpoint | return await handle_sse(request.scope, request.receive, request._send) # type: ignore[reportPrivateUsage] | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\fastmcp\server.py", line 680, in handle_sse | async with sse.connect_sse( | File "C:\Users\raywe\AppData\Local\Programs\Python\Python310\lib\contextlib.py", line 217, in __aexit__ | await self.gen.athrow(typ, value, traceback) | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\sse.py", line 146, in connect_sse | async with anyio.create_task_group() as tg: | File "E:\llm_rag\.venv\lib\site-packages\anyio\_backends\_asyncio.py", line 772, in __aexit__ | raise BaseExceptionGroup( | exceptiongroup.ExceptionGroup: unhandled errors in a TaskGroup (1 sub-exception) +-+---------------- 1 ---------------- | Exception Group Traceback (most recent call last): | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\sse.py", line 165, in connect_sse | yield (read_stream, write_stream) | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\fastmcp\server.py", line 685, in handle_sse | await self._mcp_server.run( | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\lowlevel\server.py", line 500, in run | async with AsyncExitStack() as stack: | File "C:\Users\raywe\AppData\Local\Programs\Python\Python310\lib\contextlib.py", line 714, in __aexit__ | raise exc_details[1] | File "C:\Users\raywe\AppData\Local\Programs\Python\Python310\lib\contextlib.py", line 217, in __aexit__ | await self.gen.athrow(typ, value, traceback) | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\lowlevel\server.py", line 125, in lifespan | yield {} | File "C:\Users\raywe\AppData\Local\Programs\Python\Python310\lib\contextlib.py", line 697, in __aexit__ | cb_suppress = await cb(*exc_details) | File "E:\llm_rag\.venv\lib\site-packages\mcp\shared\session.py", line 223, in __aexit__ | return await self._task_group.__aexit__(exc_type, exc_val, exc_tb) | File "E:\llm_rag\.venv\lib\site-packages\anyio\_backends\_asyncio.py", line 772, in __aexit__ | raise BaseExceptionGroup( | exceptiongroup.ExceptionGroup: unhandled errors in a TaskGroup (1 sub-exception) +-+---------------- 1 ---------------- | Traceback (most recent call last): | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\session.py", line 147, in _receive_loop | await super()._receive_loop() | File "E:\llm_rag\.venv\lib\site-packages\mcp\shared\session.py", line 374, in _receive_loop | await self._received_request(responder) | File "E:\llm_rag\.venv\lib\site-packages\mcp\server\session.py", line 175, in _received_request | raise RuntimeError( | RuntimeError: Received request before initialization was complete 如何解决
06-19
received_request(self,responder):ifnotself.initialized:#可选：返回错误或等待初始化完成awaitresponder.error(code=-32000,message="Initializationnotcomplete")returnawaitsuper()._received_request...
import webbrowser webbrowser.open("https://ai.csdn.net/?utm_source=cknow_pc_ntoolbar") # 默认浏览器打开 webbrowser.open_new_tab("https://8000.com") # 新标签页打开 import tkinter as tk import numpy as np from datetime import datetime, timedelta import random from urllib.request import urlopen from lxml import etree import chardet class WeatherForecastApp: def __init__(self, root): self.root = root self.root.title("24 小时天气预报 - 南昌") self.root.geometry("900x600") self.root.configure(bg="#f0f8ff") # 初始化数据 self.current_time = datetime.now() self.temperature_data, self.weather_conditions = self.fetch_weather_data() # 创建顶部标题 self.title_label = tk.Label( root, text=f"{self.current_time.strftime('%Y 年%m月%d日')} 24小时天气预报 - 南昌", font=("微软雅黑", 16, "bold"), bg="#4682b4", fg="white", padx=20, pady=10 ) self.title_label.pack(fill=tk.X) # 创建主框架 self.main_frame = tk.Frame(root, bg="#f0f8ff") self.main_frame.pack(fill=tk.BOTH, expand=True, padx=20, pady=10) # 创建左侧信息面板 self.info_frame = tk.Frame(self.main_frame, bg="#e6f2ff", bd=2, relief=tk.RAISED) self.info_frame.pack(side=tk.LEFT, fill=tk.Y, padx=(0, 20), pady=10) # 当前天气信息 current_temp = self.temperature_data[-1][1] current_weather_condition = self.weather_conditions[-1] tk.Label(self.info_frame, text="当前天气", font=("微软雅黑", 12, "bold"), bg="#e6f2ff").pack(pady=(10, 5)) self.current_weather = tk.StringVar() self.current_weather.set(f" 温度: {current_temp}°C\n条件: {current_weather_condition}") tk.Label(self.info_frame, textvariable=self.current_weather, bg="#e6f2ff", justify=tk.LEFT).pack(pady=5) # 预测信息 tk.Label(self.info_frame, text="预测信息", font=("微软雅黑", 12, "bold"), bg="#e6f2ff").pack(pady=(15, 5)) self.forecast_info = tk.StringVar() self.update_forecast_info() tk.Label(self.info_frame, textvariable=self.forecast_info, bg="#e6f2ff", justify=tk.LEFT).pack(pady=5) # 创建图表区域 self.chart_frame = tk.Frame(self.main_frame, bg="white", bd=2, relief=tk.SUNKEN) self.chart_frame.pack(side=tk.RIGHT, fill=tk.BOTH, expand=True, pady=10) self.canvas = tk.Canvas(self.chart_frame, bg="white", width=600, height=400) self.canvas.pack(fill=tk.BOTH, expand=True, padx=10, pady=10) # 创建控制面板 self.control_frame = tk.Frame(root, bg="#f0f8ff") self.control_frame.pack(fill=tk.X, padx=20, pady=(0, 10)) self.update_btn = tk.Button( self.control_frame, text="更新预测", command=self.update_forecast, bg="#4caf50", fg="white", font=("微软雅黑", 10), padx=15 ) self.update_btn.pack(side=tk.LEFT) self.simulate_btn = tk.Button( self.control_frame, text="模拟变化", command=self.toggle_simulation, bg="#2196f3", fg="white", font=("微软雅黑", 10), padx=15 ) self.simulate_btn.pack(side=tk.LEFT, padx=10) self.status_var = tk.StringVar() self.status_var.set(" 就绪") tk.Label(self.control_frame, textvariable=self.status_var, bg="#f0f8ff", font=("微软雅黑", 10)).pack(side=tk.RIGHT) # 初始化绘图 self.draw_chart() self.simulation_active = False def fetch_weather_data(self): try: url = "https://tianqi.2345.com/nanchang/58606.htm" response = urlopen(url) html = response.read() # 检测网页编码 result = chardet.detect(html) encoding = result['encoding'] html = html.decode(encoding) tree = etree.HTML(html) # 提取温度和天气状况数据 temperature_data = [] weather_conditions = [] now = datetime.now() # 这里需要根据实际网页结构调整 XPath temp_nodes = tree.xpath('//div[@class="hours-weather"]//span[@class="tem"]/text()') weather_nodes = tree.xpath('//div[@class="hours-weather"]//span[@class="wea"]/text()') for i in range(min(24, len(temp_nodes), len(weather_nodes))): temp = float(temp_nodes[i].replace('℃', '')) weather = weather_nodes[i] time_point = now - timedelta(hours=23 - i) temperature_data.append((time_point, temp)) weather_conditions.append(weather) return temperature_data, weather_conditions except Exception as e: print(f"获取天气数据时出错: {e}") # 生成初始数据作为备用 return self.generate_initial_data(), ["晴天"] * 24 def generate_initial_data(self): """生成初始24小时温度数据""" # 使用NumPy创建时间序列 hours = np.arange(24) # 使用正弦函数模拟温度变化 (白天高，夜晚低) base_temp = 20 + 8 * np.sin(2 * np.pi * (hours - 6) / 24) # 添加随机波动 random_variation = np.random.normal(0, 1.5, 24) temperatures = np.round(base_temp + random_variation, 1) # 创建时间-温度数据对 now = datetime.now() data = [] for i, temp in enumerate(temperatures): time_point = now - timedelta(hours=23 - i) data.append((time_point, temp)) return data def draw_chart(self): """在画布上绘制温度折线图""" self.canvas.delete("all") # 获取画布尺寸 canvas_width = self.canvas.winfo_width() canvas_height = self.canvas.winfo_height() if canvas_width < 100 or canvas_height < 100: return # 防止初始化时尺寸过小 # 设置边距 margin = 50 chart_width = canvas_width - 2 * margin chart_height = canvas_height - 2 * margin # 绘制坐标轴 self.canvas.create_line(margin, margin, margin, margin + chart_height, width=2) # Y轴 self.canvas.create_line(margin, margin + chart_height, margin + chart_width, margin + chart_height, width=2) # X轴 # 计算温度范围 temps = [item[1] for item in self.temperature_data] min_temp = min(temps) max_temp = max(temps) temp_range = max_temp - min_temp temp_range = max(temp_range, 12) # 确保最小范围 # 添加Y轴刻度和标签 for i in range(6): # 6个刻度 value = min_temp + (i * temp_range / 5) y = margin + chart_height - (i * chart_height / 5) self.canvas.create_line(margin - 5, y, margin, y, width=1) self.canvas.create_text(margin - 10, y, text=f"{value:.1f}°C", anchor="e", font=("Arial", 9)) # 添加X轴刻度和标签 points = [] for i, (time_point, temp) in enumerate(self.temperature_data): x = margin + (i * chart_width / 23) y = margin + chart_height - ((temp - min_temp) / temp_range) * chart_height points.append((x, y)) # 每2小时显示一个时间标签 if i % 2 == 0: self.canvas.create_line(x, margin + chart_height, x, margin + chart_height + 5, width=1) self.canvas.create_text( x, margin + chart_height + 15, text=time_point.strftime("%H:%M"), font=("Arial", 9) ) # 在时间标签下方显示天气状况 weather = self.weather_conditions[i] self.canvas.create_text( x, margin + chart_height + 30, text=weather, font=("Arial", 9) ) # 绘制折线 if len(points) > 1: for i in range(1, len(points)): x1, y1 = points[i - 1] x2, y2 = points[i] self.canvas.create_line(x1, y1, x2, y2, fill="#1e88e5", width=3, smooth=True) # 绘制数据点 for x, y in points: # 根据温度选择点颜色 temp = min_temp + ((margin + chart_height - y) / chart_height) * temp_range color = "#ff5252" if temp > 25 else "#1e88e5" # 高温红色，低温蓝色 self.canvas.create_oval(x - 5, y - 5, x + 5, y + 5, fill=color, outline=color) # 在点上方显示温度值 if points.index((x, y)) % 3 == 0: # 每3小时显示一次温度 self.canvas.create_text(x, y - 15, text=f"{temp:.1f}°C", font=("Arial", 9), fill="#333") # 添加当前时间标记 last_x, last_y = points[-1] self.canvas.create_line(last_x, margin, last_x, margin + chart_height, fill="#4caf50", dash=(4, 2), width=2) self.canvas.create_text( last_x, margin - 20, text="当前时间", fill="#4caf50", font=("Arial", 10, "bold") ) # 添加标题 self.canvas.create_text( canvas_width / 2, 20, text="24小时温度变化趋势 - 南昌", font=("微软雅黑", 12, "bold"), fill="#333" ) def update_forecast_info(self): """更新预测信息""" temps = [item[1] for item in self.temperature_data] max_temp = max(temps) min_temp = min(temps) avg_temp = np.mean(temps) # 找出最高温和最低温的时间 max_index = temps.index(max_temp) min_index = temps.index(min_temp) max_time = self.temperature_data[max_index][0].strftime("%H:%M") min_time = self.temperature_data[min_index][0].strftime("%H:%M") info = f"最高温度: {max_temp:.1f}°C ({max_time})\n" info += f"最低温度: {min_temp:.1f}°C ({min_time})\n" info += f"平均温度: {avg_temp:.1f}°C\n" info += f"天气变化: {random.choice([' 稳定', '逐渐升温', '小幅波动'])}" self.forecast_info.set(info) def update_forecast(self): """更新天气预报""" self.status_var.set(" 更新预测中...") self.root.update() # 重新获取天气数据 self.temperature_data, self.weather_conditions = self.fetch_weather_data() # 更新当前天气显示 current_temp = self.temperature_data[-1][1] current_weather_condition = self.weather_conditions[-1] self.current_weather.set(f" 温度: {current_temp}°C\n条件: {current_weather_condition}") # 更新预测信息 self.update_forecast_info() # 重绘图表 self.draw_chart() self.status_var.set(" 预测已更新") def toggle_simulation(self): """切换模拟状态""" if not self.simulation_active: self.simulation_active = True self.simulate_btn.config(text=" 停止模拟") self.status_var.set(" 模拟运行中...") self.simulate_changes() else: self.simulation_active = False self.simulate_btn.config(text=" 模拟变化") self.status_var.set(" 模拟已停止") def simulate_changes(self): """模拟天气变化""" if not self.simulation_active: return # 更新数据：移除最旧的数据点，添加新的数据点 self.temperature_data.pop(0) self.weather_conditions.pop(0) # 基于当前时间生成新数据点 current_time = datetime.now() # 基于前一个温度值生成新温度（加入随机变化） last_temp = self.temperature_data[-1][1] hour = current_time.hour # 根据一天中的时间调整变化方向 if 6 <= hour < 12: # 早晨升温 change = random.uniform(0.1, 1.5) elif 12 <= hour < 18: # 下午可能降温 change = random.uniform(-0.5, 0.5) else: # 晚上降温 change = random.uniform(-1.5, -0.1) new_temp = round(last_temp + change, 1) new_weather = random.choice([" 晴天", "多云", "小雨", "阴天", "雷阵雨"]) self.temperature_data.append((current_time, new_temp)) self.weather_conditions.append(new_weather) # 更新UI self.current_weather.set(f" 温度: {new_temp}°C\n条件: {new_weather}") self.update_forecast_info() self.draw_chart() # 安排下一次更新 self.root.after(990000, self.simulate_changes) if __name__ == "__main__": root = tk.Tk() app = WeatherForecastApp(root) root.mainloop() 不能用import chardet 库和其他外置库，只能用import tkinter as tk import numpy as np from datetime import datetime, timedelta import random from urllib.request import urlopen from lxml import etree 库，修改后的完整代码
07-16
但是，注意：在解析过程中，lxml会修正错误的编码声明，因此我们可能不需要显式指定编码。 不过，我们也可以不关心编码，因为解析器已经将文档解析为Unicode（内部表示）。然后我们可以使用xpath提取数据。 ...
Traceback (most recent call last): File "E:\llm_rag\debug_code.py", line 233, in <module> vector_service = VectorService() File "E:\llm_rag\debug_code.py", line 42, in __init__ self.init_task = asyncio.create_task(self.async_init()) # 创建异步初始化任务 File "C:\Users\raywe\AppData\Local\Programs\Python\Python310\lib\asyncio\tasks.py", line 336, in create_task loop = events.get_running_loop() RuntimeError: no running event loop sys:1: RuntimeWarning: coroutine 'VectorService.async_init' was never awaited 这个如何解决啊，你提供的代码是这个# mcp_server.py import os import json import time import hashlib import logging import asyncio import faiss from datetime import datetime from mcp.server.fastmcp import FastMCP from langchain_community.docstore.in_memory import InMemoryDocstore from langchain_community.vectorstores import FAISS from langchain.chains import RetrievalQA from ollama_embeding import CustomEmbeding from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler from langchain_community.document_loaders import ( TextLoader, PyPDFLoader, Docx2txtLoader, UnstructuredPowerPointLoader, UnstructuredExcelLoader, CSVLoader, UnstructuredHTMLLoader, UnstructuredMarkdownLoader, UnstructuredEmailLoader, UnstructuredFileLoader ) # 配置日志记录器 logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logger = logging.getLogger(__name__) # 创建 FastMCP 实例 mcp = FastMCP("VectorService") class VectorService: def __init__(self): self.embedding_function = CustomEmbeding('shaw/dmeta-embedding-zh') self.docstore = InMemoryDocstore() self.index = faiss.IndexFlatL2(768) self.vector_store = None self.existing_index_path = "E:/llm_rag/faiss_index/index.faiss" self.existing_index_pkl_path = "E:/llm_rag/faiss_index/index.pkl" self.is_processing = False self.last_processed_count = 0 self.initialized = asyncio.Event() # 使用异步事件标志 self.init_task = asyncio.create_task(self.async_init()) # 创建异步初始化任务 async def async_init(self): """异步初始化向量存储""" try: if os.path.exists(self.existing_index_path) and os.path.exists(self.existing_index_pkl_path): # 修复：使用绝对路径加载 self.vector_store = FAISS.load_local( "E:/llm_rag/faiss_index", embeddings=self.embedding_function, allow_dangerous_deserialization=True ) logger.info("Loaded existing vector store.") else: # 修复：正确初始化新的向量存储 self.vector_store = FAISS( embedding_function=self.embedding_function, index=self.index, docstore=self.docstore, index_to_docstore_id={} ) logger.info("Initialized new vector store.") self.initialized.set() # 标记初始化完成 except Exception as e: logger.error(f"Vector store initialization failed: {str(e)}") # 可根据需要添加重试逻辑 def get_id(self, file_path): """生成文件唯一ID""" return hashlib.md5(file_path.encode()).hexdigest() def load_document(self, file_path: str): """根据文件扩展名安全加载文档""" # 修复：添加路径安全性检查 if not os.path.exists(file_path) or not os.path.isfile(file_path): logger.error(f"Invalid file path: {file_path}") return None file_ext = file_path.split('.')[-1].lower() logger.info(f"Loading document from {file_path}") loader_map = { 'txt': TextLoader, 'pdf': PyPDFLoader, 'docx': Docx2txtLoader, 'pptx': UnstructuredPowerPointLoader, 'xlsx': UnstructuredExcelLoader, 'csv': CSVLoader, 'html': UnstructuredHTMLLoader, 'htm': UnstructuredHTMLLoader, 'md': UnstructuredMarkdownLoader, 'eml': UnstructuredEmailLoader, 'msg': UnstructuredEmailLoader } loader_class = loader_map.get(file_ext, UnstructuredFileLoader) try: loader = loader_class(file_path) return loader.load() except Exception as e: logger.error(f"Error loading {file_path}: {str(e)}") return None def _add_vector_metadata(self, file_name, file_path): """添加文件元数据并增强内容""" # 修复：增强路径验证 if not os.path.exists(file_path): logger.error(f"File not found: {file_path}") return [], [] try: docs, metadatas = [], [] file_stats = os.stat(file_path) file_size = file_stats.st_size documents = self.load_document(file_path) if not documents: return [], [] file_id = self.get_id(file_path) for doc in documents: metadata = doc.metadata.copy() metadata.update({ "source": file_name, "file_path": os.path.abspath(file_path), # 修复：使用绝对路径 "id": file_id, "upload_time": datetime.now().isoformat() }) # 增强内容：融入文件名提高权重 enhanced_content = f"文件名: {file_name}\n内容: {doc.page_content.strip()}" docs.append(enhanced_content) metadatas.append(metadata) logger.info(f"Processed {file_name} ({file_size / (1024 * 1024.0):.2f} MB)") return docs, metadatas except Exception as e: logger.error(f"Error processing {file_path}: {str(e)}") return [], [] async def process_documents(self, data_path: str): """批量处理文档并向量化""" # 修复：验证数据路径存在性 if not os.path.exists(data_path) or not os.path.isdir(data_path): return {"status": "error", "message": f"Invalid data path: {data_path}"} try: self.is_processing = True all_docs, all_metadatas = [], [] for root, _, files in os.walk(data_path): for file_name in files: file_path = os.path.join(root, file_name) docs, metas = self._add_vector_metadata(file_name, file_path) all_docs.extend(docs) all_metadatas.extend(metas) # 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确保初始化完成 if self.is_processing: return {"status": "processing", "message": "Documents are being processed"} elif os.path.exists(self.existing_index_path) and os.path.exists(self.existing_index_pkl_path): return { "status": "success", "message": "Vector store is updated", "last_processed_count": self.last_processed_count } else: return {"status": "empty", "message": "No vector store exists"} async def add_vector(self, file_path: str, file_name: str): """添加单个文件向量""" # 修复：验证文件路径 if not os.path.exists(file_path): return {"status": "error", "message": f"File not found: {file_path}"} try: self.is_processing = True docs, metas = self._add_vector_metadata(file_name, file_path) await self._save_data_vector(docs, metas) self.last_processed_count = len(docs) self.is_processing = False return {"status": "success", "message": "Vector added successfully"} except Exception as e: logger.error(f"Error adding vector: {str(e)}") self.is_processing = False return {"status": "error", "message": str(e)} vector_service = VectorService() @mcp.tool() async def process_documents(data_path: str): """处理指定路径下的文档并生成向量存储""" logger.info(f"Processing documents in {data_path}") return await vector_service.process_documents(data_path) @mcp.tool() async def check_process_status(): """检查处理状态""" logger.info("Checking process status") return await vector_service.check_process_status() @mcp.tool() async def add_vector(file_path: str, file_name: str): """添加单个文件向量""" logger.info(f"Adding vector for: {file_path}") return await vector_service.add_vector(file_path, file_name) @mcp.tool(name="searchfile", description=f"根据关键词搜索文件并返回匹配的内容") async def search_answer(query: str): """根据关键词搜索文件并返回匹配内容""" await vector_service.initialized.wait() # 确保初始化完成 try: # 修复：使用已初始化的向量存储而非重新加载 if not vector_service.vector_store: logger.error("Vector store not initialized") return {"status": "error", "message": "Vector store not initialized"} retriever = vector_service.vector_store.as_retriever(search_kwargs={"k": 10}) # 执行搜索 docs = retriever.get_relevant_documents(query) logger.info(f"Found {len(docs)} relevant documents") # 处理结果 results = [] allowed_dir = "E:\\llm_rag\\data\\" for doc in docs: metadata = doc.metadata file_path = metadata.get("file_path", "") # 修复：增强路径安全性验证 if not file_path or not os.path.exists(file_path): continue # 规范化为绝对路径 abs_path = os.path.abspath(file_path) # 验证文件是否在允许目录下 if abs_path.startswith(os.path.abspath(allowed_dir)): # 生成相对路径作为下载URL download_url = os.path.relpath(abs_path, os.path.abspath(allowed_dir)) results.append({ "content": doc.page_content, "download_url": download_url, "file_name": os.path.basename(file_path) }) return results except Exception as e: logger.error(f"Search error: {str(e)}") return {"status": "error", "message": str(e)} if __name__ == "__main__": mcp.settings.port = 8880 logger.info("Starting MCP server with SSE transport") mcp.run(transport="sse") 请修改
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