# -*- coding: utf-8 -*-
from .__load__ import *
#from langchain_community.document_loaders import PyPDFLoader
import fitz
#from PIL import Image
class Pdf(Base):
    # 提取为json格式
    def json(self):
        if not self.file:
            return False
        self.getPath()
        doc = fitz.open(self.file)
        page = doc.page_count
        result = {'page': page, 'content': []}

        for page_num in range(len(doc)):
            page = doc.load_page(page_num)
            page_height = page.rect.height
            blocks = page.get_text("dict", sort=True)["blocks"]
            page_items = []

            for i, b in enumerate(blocks):
                # 去除页眉页脚：bbox[1] 是顶部Y坐标，bbox[3] 是底部Y坐标
                y_top = b["bbox"][1]
                y_bottom = b["bbox"][3]
                if y_top < page_height * 0.05 or y_bottom > page_height * 0.95:
                    continue

                if b['type'] == 0:
                    text_content = ""
                    for line in b["lines"]:
                        for span in line["spans"]:
                            span_text = span["text"]
                            text_content += span_text
                        text_content += "\n"
                    text_content = text_content.strip()
                    text_content = self.removeDomains(text_content)
                    if text_content:
                        page_items.append({
                            "type": "text",
                            "pos": b["bbox"],
                            "content": text_content,
                            "page": page_num + 1
                        })

                elif b['type'] == 1:  # 图片块
                    image_bytes = b.get("image", b"")
                    if not image_bytes or len(image_bytes) < 100:
                        continue
                    try:
                        pix = fitz.Pixmap(doc, b["image"])
                        if pix.width < 10 or pix.height < 10:
                            continue
                    except Exception:
                        pass
                    image_ext = "png"
                    file = f"{self.param['path']}page{page_num+1}_img_{i}.{image_ext}"
                    with open(file, "wb") as f:
                        f.write(image_bytes)

                    if 'host' in self.param and self.param['host']:
                        file = file.replace(Demeter.path + 'runtime/', self.param['host'])
                    page_items.append({
                        "type": "image",
                        "pos": b["bbox"],
                        "ext": image_ext,
                        "file": file,
                        "page": page_num + 1,
                    })

            result['content'].extend(page_items)
        return result

    # 提取为langchain的Document格式
    def doc(self):
        if not self.file:
            return False
        #loader = PyPDFLoader(self.file, extract_images=False)
        #return loader.load()
        doc = fitz.open(self.file)
        result = {'page': page, 'content': []}
        for page_num in range(len(doc)):
            page = doc.load_page(page_num)
            
            # 提取文本
            text = page.get_text()

            # 提取图片中的文字
            image_texts = []
            for img in page.get_images(full=True):
                xref = img[0]
                base_image = doc.extract_image(xref)
                image_bytes = base_image["image"]
                image = Image.open(io.BytesIO(image_bytes))

                #result = Demeter.service('loader', 'extract').get(image)

                ocr_result = ocr.ocr(image)
                for line in ocr_result[0]:
                    image_texts.append(line[1])

                '''
                # OCR 识别
                ocr_result = ocr_reader.readtext(image)
                image_texts = " ".join([line[1] for line in ocr_result]).strip()
                '''

            # 合并文字 + 图片文字
            full_text = text.strip() + "\n" + "\n".join(image_texts)
            document = langchain.schema.Document(page_content=full_text)
            result['content'].append(document)
        return result