from langchain_text_splitters import MarkdownHeaderTextSplitter, CharacterTextSplitter
import requests
import json

from openai import OpenAI

def _split_markdown(text, chunk_size=2048, chunk_overlap=50):
    """
    根据 max_level 动态生成 headers_to_split_on 配置
    规则：
    - max_level=1 → 只按 # 分割
    - max_level=2 → 按 # 和 ## 分割
    - 以此类推
    """
    # 动态生成 headers_to_split_on 配置（目前固定为 Header_1）
    headers_to_split_on = [("#", "Header_1")]

    # 初始化分割器
    splitter = MarkdownHeaderTextSplitter(
        headers_to_split_on=headers_to_split_on,
        strip_headers=True
    )
    chunks = splitter.split_text(text)

    char_splitter = CharacterTextSplitter(
        chunk_size=chunk_size,
        chunk_overlap=chunk_overlap,
        length_function=len,
        separator="\n\n"  # 更合理的分隔符
    )

    final_chunks = []
    start_chars = ["1", "2", "3", "4", "5", "6", "7", "8", "9", "0", "第", "十",
                   "一", "二", "三", "四", "五", "六", "七", "八", "九"]
    new_header = []

    # 提取所有 Header_1 并筛选出“有效标题”
    for chunk in chunks:
        header_1 = chunk.metadata.get('Header_1', '')
        if header_1 and header_1[0] in start_chars:
            new_header.append(header_1)

    new_header_set = set(new_header)

    # 构建带标题前缀的 final_chunks
    for chunk in chunks:
        header_1 = chunk.metadata.get('Header_1', '')
        content = chunk.page_content
        if len(content) <= 20000:
            chunk_with_header = f"{header_1}\n{content}" if header_1 else content
            final_chunks.append(chunk_with_header)
        else:
            split_texts = char_splitter.split_documents([chunk])
            for split_chunk in split_texts:
                chunk_with_header = f"{header_1}\n{split_chunk.page_content}" if header_1 else split_chunk.page_content
                final_chunks.append(chunk_with_header)

    # ===== 重新分组，并记录每个组的 header =====
    rechunked = []
    rechunked_headers = []  # 新增：每个 rechunked 块对应的 header
    current = ""
    current_header = ""  # 当前正在构建的块所属的标题

    for chunk in final_chunks:
        is_new_section = False
        matched_header = ""

        # 检查是否以某个 new_header 开头
        for h in new_header_set:
            if chunk.startswith(h + "\n"):
                is_new_section = True
                matched_header = h
                break

        if is_new_section:
            # 保存上一段
            if current:
                rechunked.append(current)
                rechunked_headers.append(current_header)
            # 开启新段
            current = chunk
            current_header = matched_header
        else:
            # 合并到当前段
            if current:
                current += "\n" + chunk
            else:
                current = chunk
                current_header = ""  # 如果开头无标题，则 header 为空

    # 添加最后一段
    if current:
        rechunked.append(current)
        rechunked_headers.append(current_header)

    return rechunked, rechunked_headers

def read_markdown_file(file_path):
    """
    读取 Markdown 文件并返回其全部内容作为字符串。

    参数:
        file_path (str): Markdown 文件的路径（支持相对或绝对路径）

    返回:
        str 或 None: 成功时返回文件内容；出错时返回 None
    """
    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            content = f.read()
        return content
    except FileNotFoundError:
        print(f"错误：文件未找到 - {file_path}")
    except PermissionError:
        print(f"错误：没有权限读取文件 - {file_path}")
    except UnicodeDecodeError:
        print(f"错误：文件编码不是 UTF-8，无法读取 - {file_path}")
    except Exception as e:
        print(f"读取文件时发生未知错误: {e}")
    return None






# if __name__ == "__main__":


#     # 测试代码
#     file_path = "F:\zklnlp\HJ\code\output.md"  # 替换为你的 Markdown 文件路径
#     markdown_content = read_markdown_file(file_path)
#     content, headers = _split_markdown(markdown_content, chunk_size=3000, chunk_overlap=100)
#     for ins in content:
#         print(ins)
#         print(1111111111111111111111111)