[全量] 初始化项目代码、配置、文档及Agent协同harness

langchain-chat/document_loaders/mypptloader.py

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+from langchain.document_loaders.unstructured import UnstructuredFileLoader
+from typing import List
+import tqdm
+
+
+class RapidOCRPPTLoader(UnstructuredFileLoader):
+    def _get_elements(self) -> List:
+        def ppt2text(filepath):
+            from pptx import Presentation
+            from PIL import Image
+            import numpy as np
+            from io import BytesIO
+            from rapidocr_onnxruntime import RapidOCR
+            ocr = RapidOCR()
+            prs = Presentation(filepath)
+            resp = ""
+
+            def extract_text(shape):
+                nonlocal resp
+                if shape.has_text_frame:
+                    resp += shape.text.strip() + "\n"
+                if shape.has_table:
+                    for row in shape.table.rows:
+                        for cell in row.cells:
+                            for paragraph in cell.text_frame.paragraphs:
+                                resp += paragraph.text.strip() + "\n"
+                if shape.shape_type == 13:  # 13 表示图片
+                    image = Image.open(BytesIO(shape.image.blob))
+                    result, _ = ocr(np.array(image))
+                    if result:
+                        ocr_result = [line[1] for line in result]
+                        resp += "\n".join(ocr_result)
+                elif shape.shape_type == 6:  # 6 表示组合
+                    for child_shape in shape.shapes:
+                        extract_text(child_shape)
+
+            b_unit = tqdm.tqdm(total=len(prs.slides),
+                               desc="RapidOCRPPTLoader slide index: 1")
+            # 遍历所有幻灯片
+            for slide_number, slide in enumerate(prs.slides, start=1):
+                b_unit.set_description(
+                    "RapidOCRPPTLoader slide index: {}".format(slide_number))
+                b_unit.refresh()
+                sorted_shapes = sorted(slide.shapes,
+                                       key=lambda x: (x.top, x.left))  # 从上到下、从左到右遍历
+                for shape in sorted_shapes:
+                    extract_text(shape)
+                b_unit.update(1)
+            return resp
+
+        text = ppt2text(self.file_path)
+        from unstructured.partition.text import partition_text
+        return partition_text(text=text, **self.unstructured_kwargs)
+
+
+if __name__ == '__main__':
+    loader = RapidOCRPPTLoader(file_path="../tests/samples/ocr_test.pptx")
+    docs = loader.load()
+    print(docs)