""" File processing utilities for handling paper files and related operations. """ import json import os import re from typing import Dict, List, Optional, Union class FileProcessor: """ A class to handle file processing operations including path extraction and file reading. """ @staticmethod def extract_file_path(file_info: Union[str, Dict]) -> Optional[str]: """ Extract paper directory path from the input information. Args: file_info: Either a JSON string or a dictionary containing file information Returns: Optional[str]: The extracted paper directory path or None if not found """ try: # Handle direct file path input if isinstance(file_info, str): # Check if it's a file path (existing or not) if file_info.endswith( (".md", ".pdf", ".txt", ".docx", ".doc", ".html", ".htm") ): # It's a file path, return the directory return os.path.dirname(os.path.abspath(file_info)) elif os.path.exists(file_info): if os.path.isfile(file_info): return os.path.dirname(os.path.abspath(file_info)) elif os.path.isdir(file_info): return os.path.abspath(file_info) # Try to parse as JSON try: info_dict = json.loads(file_info) except json.JSONDecodeError: # 尝试从文本中提取JSON info_dict = FileProcessor.extract_json_from_text(file_info) if not info_dict: # If not JSON and doesn't look like a file path, raise error raise ValueError( f"Input is neither a valid file path nor JSON: {file_info}" ) else: info_dict = file_info # Extract paper path from dictionary paper_path = info_dict.get("paper_path") if not paper_path: raise ValueError("No paper_path found in input dictionary") # Get the directory path instead of the file path paper_dir = os.path.dirname(paper_path) # Convert to absolute path if relative if not os.path.isabs(paper_dir): paper_dir = os.path.abspath(paper_dir) return paper_dir except (AttributeError, TypeError) as e: raise ValueError(f"Invalid input format: {str(e)}") @staticmethod def find_markdown_file(directory: str) -> Optional[str]: """ Find the first markdown file in the given directory. Args: directory: Directory path to search Returns: Optional[str]: Path to the markdown file or None if not found """ if not os.path.isdir(directory): return None for file in os.listdir(directory): if file.endswith(".md"): return os.path.join(directory, file) return None @staticmethod def parse_markdown_sections(content: str) -> List[Dict[str, Union[str, int, List]]]: """ Parse markdown content and organize it by sections based on headers. Args: content: The markdown content to parse Returns: List[Dict]: A list of sections, each containing: - level: The header level (1-6) - title: The section title - content: The section content - subsections: List of subsections """ # Split content into lines lines = content.split("\n") sections = [] current_section = None current_content = [] for line in lines: # Check if line is a header header_match = re.match(r"^(#{1,6})\s+(.+)$", line) if header_match: # If we were building a section, save its content if current_section is not None: current_section["content"] = "\n".join(current_content).strip() sections.append(current_section) # Start a new section level = len(header_match.group(1)) title = header_match.group(2).strip() current_section = { "level": level, "title": title, "content": "", "subsections": [], } current_content = [] elif current_section is not None: current_content.append(line) # Don't forget to save the last section if current_section is not None: current_section["content"] = "\n".join(current_content).strip() sections.append(current_section) return FileProcessor._organize_sections(sections) @staticmethod def _organize_sections(sections: List[Dict]) -> List[Dict]: """ Organize sections into a hierarchical structure based on their levels. Args: sections: List of sections with their levels Returns: List[Dict]: Organized hierarchical structure of sections """ result = [] section_stack = [] for section in sections: while section_stack and section_stack[-1]["level"] >= section["level"]: section_stack.pop() if section_stack: section_stack[-1]["subsections"].append(section) else: result.append(section) section_stack.append(section) return result @staticmethod async def read_file_content(file_path: str) -> str: """ Read the content of a file asynchronously. Args: file_path: Path to the file to read Returns: str: The content of the file Raises: FileNotFoundError: If the file doesn't exist IOError: If there's an error reading the file """ try: # Ensure the file exists if not os.path.exists(file_path): raise FileNotFoundError(f"File not found: {file_path}") # Check if file is actually a PDF by reading the first few bytes with open(file_path, "rb") as f: header = f.read(8) if header.startswith(b"%PDF"): raise IOError( f"File {file_path} is a PDF file, not a text file. Please convert it to markdown format or use PDF processing tools." ) # Read file content # Note: Using async with would be better for large files # but for simplicity and compatibility, using regular file reading with open(file_path, "r", encoding="utf-8") as f: content = f.read() return content except UnicodeDecodeError as e: raise IOError( f"Error reading file {file_path}: File encoding is not UTF-8. Original error: {str(e)}" ) except Exception as e: raise IOError(f"Error reading file {file_path}: {str(e)}") @staticmethod def format_section_content(section: Dict) -> str: """ Format a section's content with standardized spacing and structure. Args: section: Dictionary containing section information Returns: str: Formatted section content """ # Start with section title formatted = f"\n{'#' * section['level']} {section['title']}\n" # Add section content if it exists if section["content"]: formatted += f"\n{section['content'].strip()}\n" # Process subsections if section["subsections"]: # Add a separator before subsections if there's content if section["content"]: formatted += "\n---\n" # Process each subsection for subsection in section["subsections"]: formatted += FileProcessor.format_section_content(subsection) # Add section separator formatted += "\n" + "=" * 80 + "\n" return formatted @staticmethod def standardize_output(sections: List[Dict]) -> str: """ Convert structured sections into a standardized string format. Args: sections: List of section dictionaries Returns: str: Standardized string output """ output = [] # Process each top-level section for section in sections: output.append(FileProcessor.format_section_content(section)) # Join all sections with clear separation return "\n".join(output) @classmethod async def process_file_input( cls, file_input: Union[str, Dict], base_dir: str = None ) -> Dict: """ Process file input information and return the structured content. Args: file_input: File input information (JSON string, dict, or direct file path) base_dir: Optional base directory to use for creating paper directories (for sync support) Returns: Dict: The structured content with sections and standardized text """ try: # 首先尝试从字符串中提取markdown文件路径 if isinstance(file_input, str): import re file_path_match = re.search(r"`([^`]+\.md)`", file_input) if file_path_match: paper_path = file_path_match.group(1) file_input = {"paper_path": paper_path} # Extract paper directory path paper_dir = cls.extract_file_path(file_input) # If base_dir is provided, adjust paper_dir to be relative to base_dir if base_dir and paper_dir: # If paper_dir is using default location, move it to base_dir if paper_dir.endswith(("deepcode_lab", "agent_folders")): paper_dir = base_dir else: # Extract the relative part and combine with base_dir paper_name = os.path.basename(paper_dir) # 保持原始目录名不变,不做任何替换 paper_dir = os.path.join(base_dir, "papers", paper_name) # Ensure the directory exists os.makedirs(paper_dir, exist_ok=True) if not paper_dir: raise ValueError("Could not determine paper directory path") # Get the actual file path file_path = None if isinstance(file_input, str): # 尝试解析为JSON(处理下载结果) try: parsed_json = json.loads(file_input) if isinstance(parsed_json, dict) and "paper_path" in parsed_json: file_path = parsed_json.get("paper_path") # 如果文件不存在,尝试查找markdown文件 if file_path and not os.path.exists(file_path): paper_dir = os.path.dirname(file_path) if os.path.isdir(paper_dir): file_path = cls.find_markdown_file(paper_dir) if not file_path: raise ValueError( f"No markdown file found in directory: {paper_dir}" ) else: raise ValueError("Invalid JSON format: missing paper_path") except json.JSONDecodeError: # 尝试从文本中提取JSON(处理包含额外文本的下载结果) extracted_json = cls.extract_json_from_text(file_input) if extracted_json and "paper_path" in extracted_json: file_path = extracted_json.get("paper_path") # 如果文件不存在,尝试查找markdown文件 if file_path and not os.path.exists(file_path): paper_dir = os.path.dirname(file_path) if os.path.isdir(paper_dir): file_path = cls.find_markdown_file(paper_dir) if not file_path: raise ValueError( f"No markdown file found in directory: {paper_dir}" ) else: # 不是JSON,按文件路径处理 # Check if it's a file path (existing or not) if file_input.endswith( (".md", ".pdf", ".txt", ".docx", ".doc", ".html", ".htm") ): if os.path.exists(file_input): file_path = file_input else: # File doesn't exist, try to find markdown in the directory file_path = cls.find_markdown_file(paper_dir) if not file_path: raise ValueError( f"No markdown file found in directory: {paper_dir}" ) elif os.path.exists(file_input): if os.path.isfile(file_input): file_path = file_input elif os.path.isdir(file_input): # If it's a directory, find the markdown file file_path = cls.find_markdown_file(file_input) if not file_path: raise ValueError( f"No markdown file found in directory: {file_input}" ) else: raise ValueError(f"Invalid input: {file_input}") else: # Dictionary input file_path = file_input.get("paper_path") # If the file doesn't exist, try to find markdown in the directory if file_path and not os.path.exists(file_path): paper_dir = os.path.dirname(file_path) if os.path.isdir(paper_dir): file_path = cls.find_markdown_file(paper_dir) if not file_path: raise ValueError( f"No markdown file found in directory: {paper_dir}" ) if not file_path: raise ValueError("No valid file path found") # Read file content content = await cls.read_file_content(file_path) # Parse and structure the content structured_content = cls.parse_markdown_sections(content) # Generate standardized text output standardized_text = cls.standardize_output(structured_content) return { "paper_dir": paper_dir, "file_path": file_path, "sections": structured_content, "standardized_text": standardized_text, } except Exception as e: raise ValueError(f"Error processing file input: {str(e)}") @staticmethod def extract_json_from_text(text: str) -> Optional[Dict]: """ Extract JSON from text that may contain markdown code blocks or other content. Args: text: Text that may contain JSON Returns: Optional[Dict]: Extracted JSON as dictionary or None if not found """ import re # Try to find JSON in markdown code blocks json_pattern = r"```json\s*(\{.*?\})\s*```" match = re.search(json_pattern, text, re.DOTALL) if match: try: return json.loads(match.group(1)) except json.JSONDecodeError: pass # Try to find standalone JSON json_pattern = r"(\{[^{}]*(?:\{[^{}]*\}[^{}]*)*\})" matches = re.findall(json_pattern, text, re.DOTALL) for match in matches: try: parsed = json.loads(match) if isinstance(parsed, dict) and "paper_path" in parsed: return parsed except json.JSONDecodeError: continue return None