'commit'

dsRag/Test/TestReadWordContent.py

@@ -0,0 +1,37 @@
+import os
+import docx
+from docx.oxml.ns import nsmap
+
+def read_word_content(docx_path):
+    """遍历Word文档的每个段落，输出文字或图片标识"""
+    try:
+        doc = docx.Document(docx_path)
+        
+        for paragraph in doc.paragraphs:
+            has_image = False
+            # 检查段落中是否有图片
+            for run in paragraph.runs:
+                for element in run._element:
+                    if element.tag.endswith('drawing'):
+                        # 找到图片元素
+                        has_image = True
+                        break
+                if has_image:
+                    break
+            
+            if has_image:
+                print("【图片】")
+            elif paragraph.text.strip():
+                print(paragraph.text.strip())
+
+    except Exception as e:
+        print(f"处理Word文档时出错: {str(e)}")
+
+if __name__ == "__main__":
+    # 示例用法
+    # 请将 'your_document.docx' 替换为你的Word文档路径
+    word_document_path = "d:\\dsWork\\dsProject\\dsRag\\static\\Test\\带图的WORD文档_MATH_3.docx"
+    if os.path.exists(word_document_path):
+        read_word_content(word_document_path)
+    else:
+        print(f"文件不存在: {word_document_path}")

dsRag/Test/TestReadWordTextAndImage.py

@@ -1,168 +0,0 @@
-import os
-
-import docx
-
-from Util.WordImageUtil import extract_images_from_docx
-
-# 定义常量
-BLOCK_START_KEYWORDS = ('问题', '话题')
-OUTPUT_IMAGE_DIR = "D:\\dsWork\\dsProject\\dsRag\\static\\Images"
-OUTPUT_TXT_DIR = "D:\\dsWork\\dsProject\\dsRag\\Txt"
-
-
-def read_docx(file_path):
-    """读取docx文件内容，返回包含段落索引和文本的列表"""
-    try:
-        doc = docx.Document(file_path)
-        return [(i, para.text) for i, para in enumerate(doc.paragraphs) if para.text]
-    except Exception as e:
-        print(f"读取docx文件出错: {str(e)}")
-        return []
-
-
-def is_new_block_start(para_text):
-    """判断段落是否是新块的开始"""
-    return para_text.startswith(BLOCK_START_KEYWORDS) and any(c.isdigit() for c in para_text[:5])
-
-def split_into_blocks(paragraphs):
-    """按段落遍历文本，发现'问题X'或'话题X'时开始分割，保留段落索引和内容"""
-    blocks = []
-    current_block = []
-    current_indices = []
-    in_block = False
-
-    for para_idx, para_text in paragraphs:
-        if is_new_block_start(para_text):
-            if in_block:
-                blocks.append((current_indices, '\n'.join(current_block)))
-                print(
-                    f"问题/话题 {len(blocks)} 管辖段落范围: {current_indices[0]} - {current_indices[-1]} (段落数: {len(current_block)})")
-                print(f"当前段落块内容: {''.join(current_block)}")
-                print(f"当前段落块索引: {current_indices}")
-            current_block = [para_text]
-            current_indices = [para_idx]
-            in_block = True
-        elif not current_block and (para_text.strip() or para_idx == 0):
-            # 处理文档开头没有明确标记的问题/话题
-            current_block = [para_text]
-            current_indices = [para_idx]
-        
-        if in_block and para_text.strip():  # 只添加非空段落
-            # 检查当前段落是否与前一个段落重复，避免重复添加
-            if not current_block or para_text.strip() != current_block[-1].strip():
-                current_block.append(para_text)
-            # 确保 current_indices 包含所有属于当前块的段落索引
-            if para_idx not in current_indices:
-                current_indices.append(para_idx)
-
-    if current_block:
-        blocks.append((current_indices, '\n'.join(current_block)))
-        print(
-            f"问题/话题 {len(blocks)} 管辖段落范围: {current_indices[0]} - {current_indices[-1]} (段落数: {len(current_block)})")
-        print(f"当前段落块内容: {''.join(current_block)}")
-        print(f"当前段落块索引: {current_indices}")
-
-    return blocks
-
-
-def process_images(images, blocks):
-    """处理图片与段落块的关联，并将图片信息写入对应的段落块文本中"""
-    for img in images:
-        img_para_idx = img['location']['paragraph_index']
-        img_name = os.path.basename(img['image_path'])
-        img_path = img['image_path']
-
-        assigned = False
-        for block_idx, (para_indices, block_text) in enumerate(blocks, 1):
-            # 检查图片所在的段落索引是否直接包含在段落块的索引列表中
-            if img_para_idx in para_indices:
-                print(f"图片 {img_name} 属于段落块 {block_idx} (段落索引: {para_indices})")
-                # 将图片信息添加到对应的段落块文本中
-                blocks[block_idx - 1] = (para_indices, block_text + f"\n[图片: {img_name}, 路径: {img_path}]")
-                assigned = True
-                break
-        
-        # 如果图片未被分配到任何特定段落块，则将其添加到最后一个段落块
-        if not assigned:
-            if blocks:
-                last_block_idx = len(blocks) - 1
-                last_para_indices, last_block_text = blocks[last_block_idx]
-                blocks[last_block_idx] = (last_para_indices, last_block_text + f"\n[图片: {img_name}, 路径: {img_path}]")
-                print(f"图片 {img_name} 未找到精确匹配的段落块，已添加到最后一个段落块。")
-            else:
-                print(f"图片 {img_name} 未找到匹配的段落块，且没有可用的段落块。")
-
-def save_blocks_to_txt(blocks, file_prefix, output_dir):
-    """将段落块保存到TXT文件"""
-    saved_count = 0
-    for block_idx, (para_indices, block_text) in enumerate(blocks, 1):
-        block_text = block_text.strip()
-        output_file = os.path.join(output_dir, f"{file_prefix}_{block_idx}.txt")
-        if save_to_txt(block_text, output_file):
-            saved_count += 1
-    print(f"处理完成，共保存{saved_count}个文件到目录: {output_dir}")
-    return saved_count > 0
-
-def process_document(input_path):
-    """处理文档主函数"""
-    paragraphs = read_docx(input_path)
-
-    print("段落块信息:" + str(paragraphs))
-
-    if not paragraphs:
-        print("无法读取输入文件内容")
-        return False
-
-    os.makedirs(OUTPUT_IMAGE_DIR, exist_ok=True)
-    print(f"图片将保存到目录: {OUTPUT_IMAGE_DIR}")
-    images = extract_images_from_docx(input_path, OUTPUT_IMAGE_DIR)
-    print(f"共提取到{len(images)}张图片")
-    for img in images:
-        print(f"图片保存至: {img['image_path']}")
-        loc = img['location']
-        print(f"位置信息: 段落 {loc['paragraph_index']}")
-
-    blocks = split_into_blocks(paragraphs)
-    print(f"共分割出{len(blocks)}个段落块")
-
-    # 处理图片
-    process_images(images, blocks)
-
-    file_prefix = os.path.basename(input_path).split('.')[0].split('_')[-2] + '_' + \
-                  os.path.basename(input_path).split('.')[0].split('_')[-1]
-    return save_blocks_to_txt(blocks, file_prefix, OUTPUT_TXT_DIR)
-
-
-# 保留原有的save_to_txt函数
-def save_to_txt(content, file_path, mode='w'):
-    """将内容保存到文本文件"""
-    try:
-        with open(file_path, mode, encoding='utf-8') as f:
-            f.write(content)
-        return True
-    except Exception as e:
-        print(f"保存文件{file_path}时出错: {str(e)}")
-        return False
-
-
-def process_directory(input_dir):
-    """处理指定目录下的所有docx文件"""
-    docx_files = [f for f in os.listdir(input_dir) if f.lower().endswith('.docx')]
-    if not docx_files:
-        print(f"目录中没有找到docx文件: {input_dir}")
-        return False
-
-    success_count = 0
-    for docx_file in docx_files:
-        input_path = os.path.join(input_dir, docx_file)
-        print(f"正在处理文件: {docx_file}")
-        if process_document(input_path):
-            success_count += 1
-
-    print(f"处理完成，共处理{success_count}/{len(docx_files)}个文件")
-    return success_count > 0
-
-
-if __name__ == "__main__":
-    input_dir = '../static/Test'
-    process_directory(input_dir)

dsRag/Txt/MATH_3_1.txt

@@ -1,4 +1,5 @@
 问题1 教学建议与意义
 在教学过程中，引导学生构建和理解模型，不仅能提升他们分析和解决问题的能力，还能激发他们发现问题和提出问题的意识。例如，在认识路程模型时，教师可通过生活化情境让学生理解速度的概念及其单位表示。
 模型思想是《义务教育数学课程标准》中强调的核心素养之一，它帮助学生建立从现实世界抽象出数学问题的能力，并通过数学语言进行描述和解释。
-因此，在“综合与实践”类教学内容中，应加强模型的应用训练，以培养学生应用数学知识解决实际问题的能力。
+因此，在“综合与实践”类教学内容中，应加强模型的应用训练，以培养学生应用数学知识解决实际问题的能力。
+【图片】

dsRag/Txt/MATH_3_2.txt

@@ -1,3 +1 @@
-问题2 我随便写点什么
+问题2 我随便写点什么
-[图片: edc7cfaa93dc4759b2adbd73fb764989.png, 路径: D:\dsWork\dsProject\dsRag\static\Images\edc7cfaa93dc4759b2adbd73fb764989.png]
-[图片: 373866967dbc4c1fbc23c71caa4357e1.png, 路径: D:\dsWork\dsProject\dsRag\static\Images\373866967dbc4c1fbc23c71caa4357e1.png]