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crazy_functions/rag_fns/arxiv_fns/arxiv_splitter.py

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+import os
+import re
+import time
+import aiohttp
+import asyncio
+import requests
+import tarfile
+import logging
+from pathlib import Path
+from typing import Generator, List, Tuple, Optional, Dict, Set
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from crazy_functions.rag_fns.arxiv_fns.tex_processor import TexProcessor
+from crazy_functions.rag_fns.arxiv_fns.arxiv_fragment import ArxivFragment
+
+
+
+def save_fragments_to_file(fragments, output_dir: str = "fragment_outputs"):
+        """
+        将所有fragments保存为单个结构化markdown文件
+
+        Args:
+            fragments: fragment列表
+            output_dir: 输出目录
+        """
+        from datetime import datetime
+        from pathlib import Path
+        import re
+
+        # 创建输出目录
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        output_path = Path(output_dir)
+        output_path.mkdir(parents=True, exist_ok=True)
+
+        # 生成文件名
+        filename = f"fragments_{timestamp}.md"
+        file_path = output_path / filename
+
+        current_section = ""
+        section_count = {}  # 用于跟踪每个章节的片段数量
+
+        with open(file_path, "w", encoding="utf-8") as f:
+            # 写入文档头部
+            f.write("# Document Fragments Analysis\n\n")
+            f.write("## Overview\n")
+            f.write(f"- Total Fragments: {len(fragments)}\n")
+            f.write(f"- Generated Time: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
+
+            # 如果有标题和摘要，添加到开头
+            if fragments and (fragments[0].title or fragments[0].abstract):
+                f.write("\n## Paper Information\n")
+                if fragments[0].title:
+                    f.write(f"### Title\n{fragments[0].title}\n")
+                if fragments[0].abstract:
+                    f.write(f"\n### Abstract\n{fragments[0].abstract}\n")
+
+            # 生成目录
+            f.write("\n## Table of Contents\n")
+
+            # 首先收集所有章节信息
+            sections = {}
+            for fragment in fragments:
+                section = fragment.section or "Uncategorized"
+                if section not in sections:
+                    sections[section] = []
+                sections[section].append(fragment)
+
+            # 写入目录
+            for section, section_fragments in sections.items():
+                clean_section = section.strip()
+                if not clean_section:
+                    clean_section = "Uncategorized"
+                f.write(
+                    f"- [{clean_section}](#{clean_section.lower().replace(' ', '-')}) ({len(section_fragments)} fragments)\n")
+
+            # 写入正文内容
+            f.write("\n## Content\n")
+
+            # 按章节组织内容
+            for section, section_fragments in sections.items():
+                clean_section = section.strip() or "Uncategorized"
+                f.write(f"\n### {clean_section}\n")
+
+                # 写入每个fragment
+                for i, fragment in enumerate(section_fragments, 1):
+                    f.write(f"\n#### Fragment {i} ({fragment.segment_type})\n")
+
+                    # 元数据
+                    f.write("**Metadata:**\n")
+                    f.write(f"- Type: {fragment.segment_type}\n")
+                    f.write(f"- Length: {len(fragment.content)} chars\n")
+                    f.write(f"- Importance: {fragment.importance:.2f}\n")
+                    f.write(f"- Is Appendix: {fragment.is_appendix}\n")
+                    f.write(f"- File: {fragment.rel_path}\n")
+
+                    # 内容
+                    f.write("\n**Content:**\n")
+                    f.write("```tex\n")
+                    f.write(fragment.content)
+                    f.write("\n```\n")
+
+                    # 添加分隔线
+                    if i < len(section_fragments):
+                        f.write("\n---\n")
+
+            # 添加统计信息
+            f.write("\n## Statistics\n")
+            f.write("\n### Fragment Type Distribution\n")
+            type_stats = {}
+            for fragment in fragments:
+                type_stats[fragment.segment_type] = type_stats.get(fragment.segment_type, 0) + 1
+
+            for ftype, count in type_stats.items():
+                percentage = (count / len(fragments)) * 100
+                f.write(f"- {ftype}: {count} ({percentage:.1f}%)\n")
+
+            # 长度分布
+            f.write("\n### Length Distribution\n")
+            lengths = [len(f.content) for f in fragments]
+            f.write(f"- Minimum: {min(lengths)} chars\n")
+            f.write(f"- Maximum: {max(lengths)} chars\n")
+            f.write(f"- Average: {sum(lengths) / len(lengths):.1f} chars\n")
+
+        print(f"Fragments saved to: {file_path}")
+        return file_path
+
+
+
+class ArxivSplitter:
+    """Arxiv论文智能分割器"""
+
+    def __init__(self,
+                 char_range: Tuple[int, int],
+                 root_dir: str = "gpt_log/arxiv_cache",
+                 proxies: Optional[Dict[str, str]] = None,
+                 cache_ttl: int = 7 * 24 * 60 * 60):
+        """
+        初始化分割器
+
+        Args:
+            char_range: 字符数范围(最小值, 最大值)
+            root_dir: 缓存根目录
+            proxies: 代理设置
+            cache_ttl: 缓存过期时间(秒)
+        """
+        self.min_chars, self.max_chars = char_range
+        self.root_dir = Path(root_dir)
+        self.root_dir.mkdir(parents=True, exist_ok=True)
+        self.proxies = proxies or {}
+        self.cache_ttl = cache_ttl
+
+        # 动态计算最优线程数
+        import multiprocessing
+        cpu_count = multiprocessing.cpu_count()
+        # 根据CPU核心数动态设置，但设置上限防止过度并发
+        self.max_workers = min(32, cpu_count * 2)
+
+        # 初始化TeX处理器
+        self.tex_processor = TexProcessor(char_range)
+
+        # 配置日志
+        self._setup_logging()
+
+
+
+    def _setup_logging(self):
+        """配置日志"""
+        logging.basicConfig(
+            level=logging.INFO,
+            format='%(asctime)s - %(levelname)s - %(message)s'
+        )
+        self.logger = logging.getLogger(__name__)
+
+    def _normalize_arxiv_id(self, input_str: str) -> str:
+        """规范化ArXiv ID"""
+        if 'arxiv.org/' in input_str.lower():
+            # 处理URL格式
+            if '/pdf/' in input_str:
+                arxiv_id = input_str.split('/pdf/')[-1]
+            else:
+                arxiv_id = input_str.split('/abs/')[-1]
+            # 移除版本号和其他后缀
+            return arxiv_id.split('v')[0].strip()
+        return input_str.split('v')[0].strip()
+
+
+    def _check_cache(self, paper_dir: Path) -> bool:
+        """
+        检查缓存是否有效，包括文件完整性检查
+
+        Args:
+            paper_dir: 论文目录路径
+
+        Returns:
+            bool: 如果缓存有效返回True，否则返回False
+        """
+        if not paper_dir.exists():
+            return False
+
+        # 检查目录中是否存在必要文件
+        has_tex_files = False
+        has_main_tex = False
+
+        for file_path in paper_dir.rglob("*"):
+            if file_path.suffix == '.tex':
+                has_tex_files = True
+                content = self.tex_processor.read_file(str(file_path))
+                if content and r'\documentclass' in content:
+                    has_main_tex = True
+                    break
+
+        if not (has_tex_files and has_main_tex):
+            return False
+
+        # 检查缓存时间
+        cache_time = paper_dir.stat().st_mtime
+        if (time.time() - cache_time) < self.cache_ttl:
+            self.logger.info(f"Using valid cache for {paper_dir.name}")
+            return True
+
+        return False
+
+    async def download_paper(self, arxiv_id: str, paper_dir: Path) -> bool:
+        """
+        异步下载论文，包含重试机制和临时文件处理
+
+        Args:
+            arxiv_id: ArXiv论文ID
+            paper_dir: 目标目录路径
+
+        Returns:
+            bool: 下载成功返回True，否则返回False
+        """
+        from crazy_functions.rag_fns.arxiv_fns.arxiv_downloader import ArxivDownloader
+        temp_tar_path = paper_dir / f"{arxiv_id}_temp.tar.gz"
+        final_tar_path = paper_dir / f"{arxiv_id}.tar.gz"
+
+        # 确保目录存在
+        paper_dir.mkdir(parents=True, exist_ok=True)
+
+        # 尝试使用 ArxivDownloader 下载
+        try:
+            downloader = ArxivDownloader(root_dir=str(paper_dir), proxies=self.proxies)
+            downloaded_dir = downloader.download_paper(arxiv_id)
+            if downloaded_dir:
+                self.logger.info(f"Successfully downloaded using ArxivDownloader to {downloaded_dir}")
+                return True
+        except Exception as e:
+            self.logger.warning(f"ArxivDownloader failed: {str(e)}. Falling back to direct download.")
+
+        # 如果 ArxivDownloader 失败，使用原有的下载方式作为备选
+        urls = [
+            f"https://arxiv.org/src/{arxiv_id}",
+            f"https://arxiv.org/e-print/{arxiv_id}"
+        ]
+
+        max_retries = 3
+        retry_delay = 1  # 初始重试延迟（秒）
+
+        for url in urls:
+            for attempt in range(max_retries):
+                try:
+                    self.logger.info(f"Downloading from {url} (attempt {attempt + 1}/{max_retries})")
+                    async with aiohttp.ClientSession() as session:
+                        async with session.get(url, proxy=self.proxies.get('http')) as response:
+                            if response.status == 200:
+                                content = await response.read()
+
+                                # 写入临时文件
+                                temp_tar_path.write_bytes(content)
+
+                                try:
+                                    # 验证tar文件完整性并解压
+                                    loop = asyncio.get_event_loop()
+                                    await loop.run_in_executor(None, self._process_tar_file, temp_tar_path, paper_dir)
+
+                                    # 下载成功后移动临时文件到最终位置
+                                    temp_tar_path.rename(final_tar_path)
+                                    return True
+
+                                except Exception as e:
+                                    self.logger.warning(f"Invalid tar file: {str(e)}")
+                                    if temp_tar_path.exists():
+                                        temp_tar_path.unlink()
+
+                except Exception as e:
+                    self.logger.warning(f"Download attempt {attempt + 1} failed from {url}: {str(e)}")
+                    await asyncio.sleep(retry_delay * (attempt + 1))  # 指数退避
+                    continue
+
+        return False
+
+    def _process_tar_file(self, tar_path: Path, extract_path: Path):
+        """处理tar文件的同步操作"""
+        with tarfile.open(tar_path, 'r:gz') as tar:
+            tar.testall()  # 验证文件完整性
+            tar.extractall(path=extract_path)  # 解压文件
+
+    def _process_single_tex(self, file_path: str) -> List[ArxivFragment]:
+        """处理单个TeX文件"""
+        try:
+            content = self.tex_processor.read_file(file_path)
+            if not content:
+                return []
+
+            # 提取元数据
+            is_main = r'\documentclass' in content
+            title, abstract = "", ""
+            if is_main:
+                title, abstract = self.tex_processor.extract_metadata(content)
+
+            # 分割内容
+            segments = self.tex_processor.split_content(content)
+            fragments = []
+
+            for i, (segment_content, section, is_appendix) in enumerate(segments):
+                if not segment_content.strip():
+                    continue
+
+                segment_type = self.tex_processor.detect_segment_type(segment_content)
+                importance = self.tex_processor.calculate_importance(
+                    segment_content, segment_type, is_main
+                )
+                fragments.append(ArxivFragment(
+                    file_path=file_path,
+                    content=segment_content,
+                    segment_index=i,
+                    total_segments=len(segments),
+                    rel_path=str(Path(file_path).relative_to(self.root_dir)),
+                    segment_type=segment_type,
+                    title=title,
+                    abstract=abstract,
+                    section=section,
+                    is_appendix=is_appendix,
+                    importance=importance
+                ))
+
+            return fragments
+
+        except Exception as e:
+            self.logger.error(f"Error processing {file_path}: {str(e)}")
+            return []
+
+    async def process(self, arxiv_id_or_url: str) -> List[ArxivFragment]:
+        """处理ArXiv论文"""
+        try:
+            arxiv_id = self._normalize_arxiv_id(arxiv_id_or_url)
+            paper_dir = self.root_dir / arxiv_id
+
+            # 检查缓存
+            if not self._check_cache(paper_dir):
+                paper_dir.mkdir(exist_ok=True)
+                if not await self.download_paper(arxiv_id, paper_dir):
+                    raise RuntimeError(f"Failed to download paper {arxiv_id}")
+
+            # 查找主TeX文件
+            main_tex = self.tex_processor.find_main_tex_file(str(paper_dir))
+            if not main_tex:
+                raise RuntimeError(f"No main TeX file found in {paper_dir}")
+
+            # 获取所有相关TeX文件
+            tex_files = self.tex_processor.resolve_includes(main_tex)
+            if not tex_files:
+                raise RuntimeError(f"No valid TeX files found for {arxiv_id}")
+
+            # 并行处理所有TeX文件
+            fragments = []
+            chunk_size = max(1, len(tex_files) // self.max_workers)  # 计算每个线程处理的文件数
+            loop = asyncio.get_event_loop()
+
+            async def process_chunk(chunk_files):
+                chunk_fragments = []
+                for file_path in chunk_files:
+                    try:
+                        result = await loop.run_in_executor(None, self._process_single_tex, file_path)
+                        chunk_fragments.extend(result)
+                    except Exception as e:
+                        self.logger.error(f"Error processing {file_path}: {str(e)}")
+                return chunk_fragments
+
+            # 将文件分成多个块
+            file_chunks = [tex_files[i:i + chunk_size] for i in range(0, len(tex_files), chunk_size)]
+            # 异步处理每个块
+            chunk_results = await asyncio.gather(*[process_chunk(chunk) for chunk in file_chunks])
+            for result in chunk_results:
+                fragments.extend(result)
+            # 重新计算片段索引并排序
+            fragments.sort(key=lambda x: (x.rel_path, x.segment_index))
+            total_fragments = len(fragments)
+
+            for i, fragment in enumerate(fragments):
+                fragment.segment_index = i
+                fragment.total_segments = total_fragments
+            # 在返回之前添加过滤
+            fragments = self.tex_processor.filter_fragments(fragments)
+            return fragments
+
+        except Exception as e:
+            self.logger.error(f"Failed to process {arxiv_id_or_url}: {str(e)}")
+            raise
+
+
+async def test_arxiv_splitter():
+    """测试ArXiv分割器的功能"""
+
+    # 测试配置
+    test_cases = [
+        {
+            "arxiv_id": "2411.03663",
+            "expected_title": "Large Language Models and Simple Scripts",
+            "min_fragments": 10,
+        },
+        # {
+        #     "arxiv_id": "1805.10988",
+        #     "expected_title": "RAG vs Fine-tuning",
+        #     "min_fragments": 15,
+        # }
+    ]
+
+    # 创建分割器实例
+    splitter = ArxivSplitter(
+        char_range=(800, 1800),
+        root_dir="test_cache"
+    )
+
+
+    for case in test_cases:
+        print(f"\nTesting paper: {case['arxiv_id']}")
+        try:
+            fragments = await splitter.process(case['arxiv_id'])
+
+            # 保存fragments
+            output_dir = save_fragments_to_file(fragments,output_dir="crazy_functions/rag_fns/arxiv_fns/gpt_log")
+            print(f"Output saved to: {output_dir}")
+            # 内容检查
+            for fragment in fragments:
+                # 长度检查
+
+                print((fragment.content))
+                print(len(fragment.content))
+                # 类型检查
+
+
+        except Exception as e:
+            print(f"✗ Test failed for {case['arxiv_id']}: {str(e)}")
+            raise
+
+
+if __name__ == "__main__":
+    asyncio.run(test_arxiv_splitter())