adaptai / projects /ui /DeepCode /utils /file_processor.py
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"""
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