import time

# from anyio import Path

from libs.commons import fitz, get_delta_time, get_img_s3_client
import json
import os
import math
from loguru import logger
from layout.bbox_sort import (
    prepare_bboxes_for_layout_split,
)
from layout.layout_sort import LAYOUT_UNPROC, get_bboxes_layout, get_columns_cnt_of_layout, sort_text_block
from libs.drop_reason import DropReason
from libs.markdown_utils import escape_special_markdown_char
from libs.safe_filename import sanitize_filename
from libs.vis_utils import draw_bbox_on_page, draw_layout_bbox_on_page
from pre_proc.detect_images import parse_images
from pdf2text_recogTable import parse_tables  # 获取tables的bbox
from pre_proc.detect_equation import parse_equations  # 获取equations的bbox
from pdf2text_recogHeader import parse_headers  # 获取headers的bbox
from pdf2text_recogPageNo import parse_pageNos  # 获取pageNos的bbox
from pre_proc.detect_footnote import parse_footnotes_by_model, parse_footnotes_by_rule  # 获取footnotes的bbox
from pre_proc.detect_footer_by_model import parse_footers  # 获取footers的bbox

from pdf2text_recogPara import (
    ParaProcessPipeline,
    TitleDetectionException,
    TitleLevelException,
    ParaSplitException,
    ParaMergeException,
    DenseSingleLineBlockException,
)
from pre_proc.main_text_font import get_main_text_font
from pre_proc.remove_colored_strip_bbox import remove_colored_strip_textblock
from pre_proc.remove_footer_header import remove_headder_footer_one_page

'''
from para.para_pipeline import ParaProcessPipeline
from para.exceptions import (
    TitleDetectionException,
    TitleLevelException,
    ParaSplitException,
    ParaMergeException,
    DenseSingleLineBlockException,
)
'''

from libs.commons import read_file, join_path
from libs.pdf_image_tools import save_images_by_bboxes
from post_proc.remove_footnote import merge_footnote_blocks, remove_footnote_blocks
from pre_proc.citationmarker_remove import remove_citation_marker
from pre_proc.equations_replace import combine_chars_to_pymudict, remove_chars_in_text_blocks, replace_equations_in_textblock
from pre_proc.pdf_pre_filter import pdf_filter
from pre_proc.detect_footer_header_by_statistics import drop_footer_header
from pre_proc.construct_paras import construct_page_component
from pre_proc.fix_image import combine_images, fix_image_vertical, fix_seperated_image, include_img_title
from post_proc.pdf_post_filter import pdf_post_filter
from pre_proc.remove_rotate_bbox import get_side_boundry, remove_rotate_side_textblock, remove_side_blank_block
from pre_proc.resolve_bbox_conflict import check_text_block_horizontal_overlap, resolve_bbox_overlap_conflict
from pre_proc.fix_table import fix_table_text_block, fix_tables, include_table_title

denseSingleLineBlockException_msg = DenseSingleLineBlockException().message
titleDetectionException_msg = TitleDetectionException().message
titleLevelException_msg = TitleLevelException().message
paraSplitException_msg = ParaSplitException().message
paraMergeException_msg = ParaMergeException().message


def get_docx_model_output(pdf_model_output, pdf_model_s3_profile, page_id):
    if isinstance(pdf_model_output, str):
        model_output_json_path = join_path(pdf_model_output, f"page_{page_id + 1}.json")  # 模型输出的页面编号从1开始的
        if os.path.exists(model_output_json_path):
            json_from_docx = read_file(model_output_json_path, pdf_model_s3_profile)
            model_output_json = json.loads(json_from_docx)
        else:
            try:
                model_output_json_path = join_path(pdf_model_output, "model.json")
                with open(model_output_json_path, "r", encoding="utf-8") as f:
                    model_output_json = json.load(f)
                    model_output_json = model_output_json["doc_layout_result"][page_id]
            except:
                s3_model_output_json_path = join_path(pdf_model_output, f"page_{page_id + 1}.json")
                s3_model_output_json_path = join_path(pdf_model_output, f"{page_id}.json")
                #s3_model_output_json_path = join_path(pdf_model_output, f"page_{page_id }.json")
                # logger.warning(f"model_output_json_path: {model_output_json_path} not found. try to load from s3: {s3_model_output_json_path}")

                s = read_file(s3_model_output_json_path, pdf_model_s3_profile)
                return json.loads(s)

    elif isinstance(pdf_model_output, list):
        model_output_json = pdf_model_output[page_id]

    return model_output_json


def parse_pdf_by_model(
    s3_pdf_path,
    s3_pdf_profile,
    pdf_model_output,
    save_path,
    book_name,
    pdf_model_profile=None,
    image_s3_config=None,
    start_page_id=0,
    end_page_id=None,
    junk_img_bojids=[],
    debug_mode=False,
):
    pdf_bytes = read_file(s3_pdf_path, s3_pdf_profile)
    save_tmp_path = os.path.join(os.path.dirname(__file__), "../..", "tmp", "unittest")
    md_bookname_save_path = ""
    book_name = sanitize_filename(book_name)
    if debug_mode:
        save_path = join_path(save_tmp_path, "md")
        pdf_local_path = join_path(save_tmp_path, "download-pdfs", book_name)

        if not os.path.exists(os.path.dirname(pdf_local_path)):
            # 如果目录不存在，创建它
            os.makedirs(os.path.dirname(pdf_local_path))

        md_bookname_save_path = join_path(save_tmp_path, "md", book_name)
        if not os.path.exists(md_bookname_save_path):
            # 如果目录不存在，创建它
            os.makedirs(md_bookname_save_path)

        with open(pdf_local_path + ".pdf", "wb") as pdf_file:
            pdf_file.write(pdf_bytes)

    pdf_docs = fitz.open("pdf", pdf_bytes)
    pdf_info_dict = {}
    img_s3_client = get_img_s3_client(save_path, image_s3_config)  # 更改函数名和参数，避免歧义
    # img_s3_client = "img_s3_client"  #不创建这个对象，直接用字符串占位

    start_time = time.time()

    """通过统计pdf全篇文字,识别正文字体"""
    main_text_font = get_main_text_font(pdf_docs)


    end_page_id = end_page_id if end_page_id else len(pdf_docs) - 1
    for page_id in range(start_page_id, end_page_id + 1):
        page = pdf_docs[page_id]
        page_width = page.rect.width
        page_height = page.rect.height

        if debug_mode:
            time_now = time.time()
            logger.info(f"page_id: {page_id}, last_page_cost_time: {get_delta_time(start_time)}")
            start_time = time_now
        """
        # 通过一个规则，过滤掉单页超过1500非junkimg的pdf
        # 对单页面非重复id的img数量做统计,如果当前页超过1500则直接return need_drop
        """
        page_imgs = page.get_images()
        img_counts = 0
        for img in page_imgs:
            img_bojid = img[0]
            if img_bojid in junk_img_bojids:  # 判断这个图片在不在junklist中
                continue  # 如果在junklist就不用管了，跳过
            else:
                recs = page.get_image_rects(img, transform=True)
                if recs:  # 如果这张图在当前页面有展示
                    img_counts += 1
        if img_counts >= 1500:  # 如果去除了junkimg的影响，单页img仍然超过1500的话，就排除当前pdf
            logger.warning(
                f"page_id: {page_id}, img_counts: {img_counts}, drop this pdf: {book_name}, drop_reason: {DropReason.HIGH_COMPUTATIONAL_lOAD_BY_IMGS}"
            )
            result = {"need_drop": True, "drop_reason": DropReason.HIGH_COMPUTATIONAL_lOAD_BY_IMGS}
            if not debug_mode:
                return result

        """
        ==================================================================================================================================
        首先获取基本的block数据，对pdf进行分解，获取图片、表格、公式、text的bbox
        """
        # 解析pdf原始文本block
        text_raw_blocks = page.get_text(
            "dict",
            flags=fitz.TEXTFLAGS_TEXT,
        )["blocks"]
        model_output_json = get_docx_model_output(pdf_model_output, pdf_model_profile, page_id)

        # 解析图片
        image_bboxes = parse_images(page_id, page, model_output_json, junk_img_bojids)
        image_bboxes = fix_image_vertical(image_bboxes, text_raw_blocks)  # 修正图片的位置
        image_bboxes = fix_seperated_image(image_bboxes)  # 合并有边重合的图片
        image_bboxes = include_img_title(text_raw_blocks, image_bboxes)  # 向图片上方和下方寻找title，使用规则进行匹配，暂时只支持英文规则
        """此时image_bboxes中可能出现这种情况，水平并列的2个图片，下方分别有各自的子标题，2个子标题下方又有大标题（形如Figxxx)，会出现2个图片的bbox都包含了这个大标题，这种情况需要把图片合并"""
        image_bboxes = combine_images(image_bboxes)  # 合并图片

        # 解析表格并对table_bboxes进行位置的微调,防止表格周围的文字被截断
        table_bboxes = parse_tables(page_id, page, model_output_json)
        table_bboxes = fix_tables(page, table_bboxes, include_table_title=True, scan_line_num=2)  # 修正
        table_bboxes = fix_table_text_block(text_raw_blocks, table_bboxes)  # 修正与text block的关系,某些table修正与pymupdf获取到的table内textblock没有完全包含，因此要进行一次修正。
        #debug_show_bbox(pdf_docs, page_id, table_bboxes, [], [b['bbox'] for b in text_raw_blocks], join_path(save_path, book_name, f"{book_name}_debug.pdf"), 7)
        table_bboxes = include_table_title(text_raw_blocks, table_bboxes)  # 向table上方和下方寻找title，使用规则进行匹配，暂时只支持英文规则

        # 解析公式
        equations_inline_bboxes, equations_interline_bboxes = parse_equations(page_id, page, model_output_json)

        """
        ==================================================================================================================================
        进入预处理-1阶段
        -------------------
        # # 解析标题
        # title_bboxs = parse_titles(page_id, page, model_output_json)
        # # 评估Layout是否规整、简单
        # isSimpleLayout_flag, fullColumn_cnt, subColumn_cnt, curPage_loss = evaluate_pdf_layout(page_id, page, model_output_json)
        接下来开始进行预处理过程
        """
        
        """去掉每页的页码、页眉、页脚"""
        page_no_bboxs = parse_pageNos(page_id, page, model_output_json)
        header_bboxs = parse_headers(page_id, page, model_output_json)
        footer_bboxs = parse_footers(page_id, page, model_output_json)
        image_bboxes, table_bboxes, remain_text_blocks, removed_hdr_foot_txt_block, removed_hdr_foot_img_block, removed_hdr_foot_table = remove_headder_footer_one_page(text_raw_blocks, image_bboxes, table_bboxes, header_bboxs, footer_bboxs, page_no_bboxs, page_width, page_height)

        """去除页面上半部分长条色块内的文本块"""
        remain_text_blocks, removed_colored_narrow_strip_background_text_block = remove_colored_strip_textblock(remain_text_blocks, page)

        #debug_show_bbox(pdf_docs, page_id, footnote_bboxes_by_model, [b['bbox'] for b in remain_text_blocks], header_bboxs, join_path(save_path, book_name, f"{book_name}_debug.pdf"), 7)

        """去掉旋转的文字：水印、垂直排列的文字"""
        remain_text_blocks, removed_non_horz_text_block = remove_rotate_side_textblock(
            remain_text_blocks, page_width, page_height
        )  # 去掉水印，非水平文字
        remain_text_blocks, removed_empty_side_block = remove_side_blank_block(remain_text_blocks, page_width, page_height) # 删除页面四周可能会留下的完全空白的textblock，这种block形成原因未知

        """出现在图片、表格上的文字块去掉，把层叠的图片单独分离出来，不参与layout的计算"""
        (
            image_bboxes,
            table_bboxes,
            equations_interline_bboxes,
            equations_inline_bboxes,
            remain_text_blocks,
            text_block_on_image_removed,
            images_overlap_backup,
            interline_eq_temp_text_block
        ) = resolve_bbox_overlap_conflict(
            image_bboxes, table_bboxes, equations_interline_bboxes, equations_inline_bboxes, remain_text_blocks
        )

        # """去掉footnote, 从文字和图片中"""
        # # 通过模型识别到的footnote
        # footnote_bboxes_by_model = parse_footnotes_by_model(page_id, page, model_output_json, md_bookname_save_path,
        #                                                     debug_mode=debug_mode)
        # # 通过规则识别到的footnote
        # footnote_bboxes_by_rule = parse_footnotes_by_rule(remain_text_blocks, page_height, page_id)
        """
        ==================================================================================================================================
        """
        if debug_mode:  # debugmode截图到本地
            save_path = join_path(save_tmp_path, "md")

        # 把图、表、公式都进行截图，保存到存储上，返回图片路径作为内容
        image_info, image_backup_info, table_info, inline_eq_info, interline_eq_info = save_images_by_bboxes(
            book_name,
            page_id,
            page,
            save_path,
            image_bboxes,
            images_overlap_backup,
            table_bboxes,
            equations_inline_bboxes,
            equations_interline_bboxes,
            # 传入img_s3_client
            img_s3_client,
        )  # 只要表格和图片的截图
        
        """"以下进入到公式替换环节 """
        char_level_text_blocks = page.get_text("rawdict", flags=fitz.TEXTFLAGS_TEXT)['blocks']
        remain_text_blocks = combine_chars_to_pymudict(remain_text_blocks, char_level_text_blocks)# 合并chars
        remain_text_blocks = replace_equations_in_textblock(remain_text_blocks, inline_eq_info, interline_eq_info)
        remain_text_blocks = remove_citation_marker(remain_text_blocks) # 公式替换之后去角标，防止公式无法替换成功。但是这样也会带来个问题就是把角标当公式。各有优劣。
        remain_text_blocks = remove_chars_in_text_blocks(remain_text_blocks) # 减少中间态数据体积
        #debug_show_bbox(pdf_docs, page_id, [b['bbox'] for b in inline_eq_info], [b['bbox'] for b in interline_eq_info], [], join_path(save_path, book_name, f"{book_name}_debug.pdf"), 3)

        """去掉footnote, 从文字和图片中(先去角标再去footnote试试)"""
        # 通过模型识别到的footnote
        footnote_bboxes_by_model = parse_footnotes_by_model(page_id, page, model_output_json, md_bookname_save_path, debug_mode=debug_mode)
        # 通过规则识别到的footnote
        footnote_bboxes_by_rule = parse_footnotes_by_rule(remain_text_blocks, page_height, page_id, main_text_font)

        """进入pdf过滤器，去掉一些不合理的pdf"""
        is_good_pdf, err = pdf_filter(page, remain_text_blocks, table_bboxes, image_bboxes)
        if not is_good_pdf:
            logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {err}")
            if not debug_mode:
                return err

        """
        ==================================================================================================================================
        进行版面布局切分和过滤
        """
        """在切分之前，先检查一下bbox是否有左右重叠的情况，如果有，那么就认为这个pdf暂时没有能力处理好，这种左右重叠的情况大概率是由于pdf里的行间公式、表格没有被正确识别出来造成的 """

        is_text_block_horz_overlap = check_text_block_horizontal_overlap(remain_text_blocks, header_bboxs, footer_bboxs)

        if is_text_block_horz_overlap:
            # debug_show_bbox(pdf_docs, page_id, [b['bbox'] for b in remain_text_blocks], [], [], join_path(save_path, book_name, f"{book_name}_debug.pdf"), 0)
            logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {DropReason.TEXT_BLCOK_HOR_OVERLAP}")
            result = {"need_drop": True, "drop_reason": DropReason.TEXT_BLCOK_HOR_OVERLAP}
            if not debug_mode:
                return result

        """统一格式化成一个数据结构用于计算layout"""
        page_y0 = 0 if len(header_bboxs) == 0 else max([b[3] for b in header_bboxs])
        page_y1 = page_height if len(footer_bboxs) == 0 else min([b[1] for b in footer_bboxs])
        left_x, right_x = get_side_boundry(removed_non_horz_text_block, page_width, page_height)
        page_boundry = [math.floor(left_x), page_y0 + 1, math.ceil(right_x), page_y1 - 1]
        # 返回的是一个数组，每个元素[x0, y0, x1, y1, block_content, idx_x, idx_y], 初始时候idx_x, idx_y都是None. 对于图片、公式来说，block_content是图片的地址， 对于段落来说，block_content是段落的内容
        
        all_bboxes = prepare_bboxes_for_layout_split(
            image_info, image_backup_info, table_info, inline_eq_info, interline_eq_info, remain_text_blocks, page_boundry, page)
        #debug_show_bbox(pdf_docs, page_id, [], [], all_bboxes, join_path(save_path, book_name, f"{book_name}_debug.pdf"), 1)
        """page_y0, page_y1能够过滤掉页眉和页脚，不会算作layout内"""
        layout_bboxes, layout_tree = get_bboxes_layout(all_bboxes, page_boundry, page_id)
        
        if len(remain_text_blocks)>0 and len(all_bboxes)>0 and len(layout_bboxes)==0:
            logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {DropReason.CAN_NOT_DETECT_PAGE_LAYOUT}")
            result = {"need_drop": True, "drop_reason": DropReason.CAN_NOT_DETECT_PAGE_LAYOUT}
            if not debug_mode:
                return result

        """以下去掉复杂的布局和超过2列的布局"""
        if any([lay["layout_label"] == LAYOUT_UNPROC for lay in layout_bboxes]):  # 复杂的布局
            logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {DropReason.COMPLICATED_LAYOUT}")
            result = {"need_drop": True, "drop_reason": DropReason.COMPLICATED_LAYOUT}
            if not debug_mode:
                return result

        layout_column_width = get_columns_cnt_of_layout(layout_tree)
        if layout_column_width > 2:  # 去掉超过2列的布局pdf
            logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {DropReason.TOO_MANY_LAYOUT_COLUMNS}")
            result = {
                "need_drop": True,
                "drop_reason": DropReason.TOO_MANY_LAYOUT_COLUMNS,
                "extra_info": {"column_cnt": layout_column_width},
            }
            if not debug_mode:
                return result


        """
        ==================================================================================================================================
        构造出下游需要的数据结构
        """
        remain_text_blocks = remain_text_blocks + interline_eq_temp_text_block # 把计算layout时候临时删除的行间公式再放回去，防止行间公式替换的时候丢失。
        removed_text_blocks = []
        removed_text_blocks.extend(removed_hdr_foot_txt_block)
        # removed_text_blocks.extend(removed_footnote_text_block)
        removed_text_blocks.extend(text_block_on_image_removed)
        removed_text_blocks.extend(removed_non_horz_text_block)
        removed_text_blocks.extend(removed_colored_narrow_strip_background_text_block)

        removed_images = []
        # removed_images.extend(footnote_imgs)
        removed_images.extend(removed_hdr_foot_img_block)

        images_backup = []
        images_backup.extend(image_backup_info)
        remain_text_blocks = escape_special_markdown_char(remain_text_blocks) # 转义span里的text
        sorted_text_remain_text_block = sort_text_block(remain_text_blocks, layout_bboxes)

        footnote_bboxes_tmp = []
        footnote_bboxes_tmp.extend(footnote_bboxes_by_model)
        footnote_bboxes_tmp.extend(footnote_bboxes_by_rule)
        

        page_info = construct_page_component(
            page_id,
            image_info,
            table_info,
            sorted_text_remain_text_block,
            layout_bboxes,
            inline_eq_info,
            interline_eq_info,
            page.get_text("dict", flags=fitz.TEXTFLAGS_TEXT)["blocks"],
            removed_text_blocks=removed_text_blocks,
            removed_image_blocks=removed_images,
            images_backup=images_backup,
            droped_table_block=[],
            table_backup=[],
            layout_tree=layout_tree,
            page_w=page.rect.width,
            page_h=page.rect.height,
            footnote_bboxes_tmp=footnote_bboxes_tmp
        )
        pdf_info_dict[f"page_{page_id}"] = page_info

    # end page for

    '''计算后处理阶段耗时'''
    start_time = time.time()

    """
    ==================================================================================================================================
    去掉页眉和页脚，这里需要用到一定的统计量，所以放到最后
    页眉和页脚主要从文本box和图片box中去除，位于页面的四周。
    下面函数会直接修改pdf_info_dict,从文字块中、图片中删除属于页眉页脚的内容，删除内容做相对应记录
    """
    # 去页眉页脚
    header, footer = drop_footer_header(pdf_info_dict)

    """对单个layout内footnote和他下面的所有textbbox合并"""

    for page_key, page_info in pdf_info_dict.items():
        page_info = merge_footnote_blocks(page_info, main_text_font)
        page_info = remove_footnote_blocks(page_info)
        pdf_info_dict[page_key] = page_info

    """进入pdf后置过滤器，去掉一些不合理的pdf"""

    i = 0
    for page_info in pdf_info_dict.values():
        is_good_pdf, err = pdf_post_filter(page_info)
        if not is_good_pdf:
            logger.warning(f"page_id: {i}, drop this pdf: {book_name}, reason: {err}")
            if not debug_mode:
                return err
        i += 1

    if debug_mode:
        params_file_save_path = join_path(save_tmp_path, "md", book_name, "preproc_out.json")
        page_draw_rect_save_path = join_path(save_tmp_path, "md", book_name, "layout.pdf")
        # dir_path = os.path.dirname(page_draw_rect_save_path)
        # if not os.path.exists(dir_path):
        #     # 如果目录不存在，创建它
        #     os.makedirs(dir_path)

        with open(params_file_save_path, "w", encoding="utf-8") as f:
            json.dump(pdf_info_dict, f, ensure_ascii=False, indent=4)
        # 先检测本地 page_draw_rect_save_path 是否存在，如果存在则删除
        if os.path.exists(page_draw_rect_save_path):
            os.remove(page_draw_rect_save_path)
        # 绘制bbox和layout到pdf
        draw_bbox_on_page(pdf_docs, pdf_info_dict, page_draw_rect_save_path)
        draw_layout_bbox_on_page(pdf_docs, pdf_info_dict, header, footer, page_draw_rect_save_path)

    if debug_mode:
        # 打印后处理阶段耗时
        logger.info(f"post_processing_time: {get_delta_time(start_time)}")

    """
    ==================================================================================================================================
    进入段落处理-2阶段
    """
    start_time = time.time()

    para_process_pipeline = ParaProcessPipeline()

    def _deal_with_text_exception(error_info):
        logger.warning(f"page_id: {page_id}, drop this pdf: {book_name}, reason: {error_info}")
        if error_info == denseSingleLineBlockException_msg:
            logger.warning(f"Drop this pdf: {book_name}, reason: {DropReason.DENSE_SINGLE_LINE_BLOCK}")
            result = {"need_drop": True, "drop_reason": DropReason.DENSE_SINGLE_LINE_BLOCK}
            return result
        if error_info == titleDetectionException_msg:
            logger.warning(f"Drop this pdf: {book_name}, reason: {DropReason.TITLE_DETECTION_FAILED}")
            result = {"need_drop": True, "drop_reason": DropReason.TITLE_DETECTION_FAILED}
            return result
        elif error_info == titleLevelException_msg:
            logger.warning(f"Drop this pdf: {book_name}, reason: {DropReason.TITLE_LEVEL_FAILED}")
            result = {"need_drop": True, "drop_reason": DropReason.TITLE_LEVEL_FAILED}
            return result
        elif error_info == paraSplitException_msg:
            logger.warning(f"Drop this pdf: {book_name}, reason: {DropReason.PARA_SPLIT_FAILED}")
            result = {"need_drop": True, "drop_reason": DropReason.PARA_SPLIT_FAILED}
            return result
        elif error_info == paraMergeException_msg:
            logger.warning(f"Drop this pdf: {book_name}, reason: {DropReason.PARA_MERGE_FAILED}")
            result = {"need_drop": True, "drop_reason": DropReason.PARA_MERGE_FAILED}
            return result

    if debug_mode:
        input_pdf_file = f"{pdf_local_path}.pdf"
        output_dir = f"{save_path}/{book_name}"
        output_pdf_file = f"{output_dir}/pdf_annos.pdf"

        """
        Call the para_process_pipeline function to process the pdf_info_dict.
        
        Parameters:
        para_debug_mode: str or None
            If para_debug_mode is None, the para_process_pipeline will not keep any intermediate results.
            If para_debug_mode is "simple", the para_process_pipeline will only keep the annos on the pdf and the final results as a json file.
            If para_debug_mode is "full", the para_process_pipeline will keep all the intermediate results generated during each step.
        """
        pdf_info_dict, error_info = para_process_pipeline.para_process_pipeline(
            pdf_info_dict,
            para_debug_mode="simple",
            input_pdf_path=input_pdf_file,
            output_pdf_path=output_pdf_file,
        )
        # 打印段落处理阶段耗时
        logger.info(f"para_process_time: {get_delta_time(start_time)}")

        # debug的时候不return drop信息
        if error_info is not None:
            _deal_with_text_exception(error_info)
        return pdf_info_dict
    else:
        pdf_info_dict, error_info = para_process_pipeline.para_process_pipeline(pdf_info_dict)
        if error_info is not None:
            return _deal_with_text_exception(error_info)

    return pdf_info_dict
