优化 Elasticsearch 更新逻辑，支持批量位置更新，调整匹配结果处理，新增位置整数格式返回

src/add_chunk_cli_pdf_img.py

@@ -9,6 +9,8 @@ import tempfile
 from elasticsearch import Elasticsearch
 from minio import Minio
 from minio.error import S3Error
+from find_text_in_pdf_enhanced import find_text_in_pdf
+import time
 
 # from get_pos_pdf import smart_fuzzy_find_text_batch, find_text_positions_batch
 
@@ -47,7 +49,7 @@ MINIO_CONFIG = {
     "secure": False
 }
 
-def update_positon_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, position, new_img_id):
+def update_positon_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, positions, new_img_id):
     """
     在 Elasticsearch 中更新指定文档块的position and img_id。
     
@@ -88,29 +90,32 @@ def update_positon_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, position
         # 构建更新请求 - 只更新存在的字段
         update_body = {"doc": {}}
         
-        # 只有当 new_img_id 存在时才更新 img_id
+        #只有当 new_img_id 存在时才更新 img_id
         if new_img_id is not None:
             update_body["doc"]["img_id"] = new_img_id
             
         # 只有当 position 存在时才更新 positions
-        if position is not None:
-            # 如果传入的是嵌套字典格式的 position
-            if isinstance(position, list) and all(isinstance(p, dict) for p in position):
-                # 将字典格式转换为整数列表格式
-                formatted_positions = []
-                for pos in position:
-                    pos_list = [
-                        pos.get('page', 0),  # 页码
-                        int(round(float(pos.get('x0', 0)))),  # x0
-                        int(round(float(pos.get('x1', 0)))),  # x1
-                        int(round(float(pos.get('y0', 0)))),  # y0
-                        int(round(float(pos.get('y1', 0))))   # y1
-                    ]
-                    formatted_positions.append(pos_list)
-                update_body["doc"]["positions"] = formatted_positions
-            # 如果已经是整数列表格式
-            elif isinstance(position, list):
-                update_body["doc"]["positions"] = position
+        if positions :
+
+            position_int = []
+
+            for pos in positions:
+                if len(pos) != 5:
+                    continue  # Skip invalid positions
+                    
+                pn, left, right, top, bottom = pos
+                # 使用元组格式，与原始RAGFlow保持一致
+                position_int.append((int(pn + 1), int(left), int(right), int(top), int(bottom)))
+            if position_int:
+                update_body["doc"]["position_int"] = position_int
+                update_body["doc"]["page_num_int"] = [position_int[0][0]]
+                update_body["doc"]["top_int"] = [position_int[0][3]]
+
+
+
+
+            
+
 
         # 如果没有需要更新的字段，直接返回成功
         if not update_body["doc"]:
@@ -127,32 +132,32 @@ def update_positon_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, position
         
         print(f"Elasticsearch 更新结果: index={index_name}, id={doc_id_in_es}, result={update_result}")
 
-        # 验证更新
-        verify_doc = es.get(index=index_name, id=doc_id_in_es)
+    #     # 验证更新
+    #     verify_doc = es.get(index=index_name, id=doc_id_in_es)
 
-        # 检查 img_id 是否已更新（如果提供了 new_img_id）
-        img_id_updated = True
-        if new_img_id is not None:
-            img_id_updated = verify_doc['_source'].get('img_id') == new_img_id
-            if img_id_updated:
-                print(f"成功更新 img_id 为: {new_img_id}")
-            else:
-                print(f"更新验证失败，当前 img_id: {verify_doc['_source'].get('img_id')}")
+    #     # 检查 img_id 是否已更新（如果提供了 new_img_id）
+    #     img_id_updated = True
+    #     if new_img_id is not None:
+    #         img_id_updated = verify_doc['_source'].get('img_id') == new_img_id
+    #         if img_id_updated:
+    #             print(f"成功更新 img_id 为: {new_img_id}")
+    #         else:
+    #             print(f"更新验证失败，当前 img_id: {verify_doc['_source'].get('img_id')}")
 
-        # 检查 position 是否已更新（如果提供了 position）
-        position_updated = True
-        if position is not None:
-            position_updated = verify_doc['_source'].get('positions') == position
-            if position_updated:
-                print(f"成功更新 position 为: {position}")
-            else:
-                print(f"更新验证失败，当前 position: {verify_doc['_source'].get('positions')}")
+    #     # 检查 position 是否已更新（如果提供了 position）
+    #     position_updated = True
+    #     if position is not None:
+    #         position_updated = verify_doc['_source'].get('positions') == position
+    #         if position_updated:
+    #             print(f"成功更新 position 为: {position}")
+    #         else:
+    #             print(f"更新验证失败，当前 position: {verify_doc['_source'].get('positions')}")
 
-        # 统一返回结果
-        if img_id_updated and position_updated:
-            return {"code": 0, "message": ""}
-        else:
-            return {"code": 100, "message": "Failed to verify update"}
+    #     # 统一返回结果
+    #     if img_id_updated and position_updated:
+    #         return {"code": 0, "message": ""}
+    #     else:
+    #         return {"code": 100, "message": "Failed to verify update"}
         
 
     except Exception as e:
@@ -160,6 +165,7 @@ def update_positon_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, position
         return {"code": 101, "message": f"Error updating img_id: {str(e)}"}
 
 
+
 def get_minio_client():
     """创建MinIO客户端"""
     return Minio(
@@ -444,43 +450,57 @@ def get_positions_from_chunk(pdf_path, chunks_info):
     try:
         # 提取所有chunk的文本内容用于批量查找
         chunk_texts = [chunk_info['text'] for chunk_info in chunks_info]
+        print(f"批量查找文本块: {chunk_texts}")
         
         # 使用智能模糊查找获取位置信息
-        batch_positions = smart_fuzzy_find_text_batch(pdf_path, chunk_texts, similarity_threshold=0.7)
+        matches = find_text_in_pdf(
+            pdf_path,
+            chunk_texts,  
+            threshold=60
+        )
+        print(f"匹配结果: {matches}")
         
         # 将位置信息与chunks_info关联，并确保数据类型正确
         for i, chunk_info in enumerate(chunks_info):
-            positions = batch_positions[i] if i < len(batch_positions) else []
-            
-            # 处理位置信息
-            processed_positions = []
-            for pos in positions:
-                if isinstance(pos, dict):
-                    # 创建新的位置字典，确保所有坐标都是整数
-                    processed_pos = {
-                        'x0': int(round(float(pos['x0']))) if pos.get('x0') is not None else 0,
-                        'y0': int(round(float(pos['y0']))) if pos.get('y0') is not None else 0,
-                        'x1': int(round(float(pos['x1']))) if pos.get('x1') is not None else 0,
-                        'y1': int(round(float(pos['y1']))) if pos.get('y1') is not None else 0,
-                        'page': int(pos['page']) if pos.get('page') is not None else 0
-                    }
-                    processed_positions.append(processed_pos)
-            
-            # 更新chunk_info中的positions
-            chunk_info['positions'] = processed_positions
+            # 确保 chunk_info 包含 'positions' 键
+            if 'positions' not in chunk_info:
+                chunk_info['positions'] = []
+                
+            print(f"处理第 {i+1} 个chunk: {chunk_info['text']}")
+            print(f"更新前位置: {chunk_info['positions']}")
             
+            if isinstance(matches, list) and i < len(matches):
+                chunk_info['positions']=[mat['position_int'] for mat in matches[i] if 'position_int' in mat]
+
+                # # 如果matches是列表且索引有效
+                # if isinstance(matches[i], dict) and 'position_int' in matches[i]:
+                #     chunk_info['positions'] = matches[i]['position_int']
+                #     print(f"更新后位置: {chunk_info['positions']}")
+                # else:
+                #     chunk_info['positions'] = []
+                #     print(f"未找到有效位置信息，设置为空列表")
+            else:
+                chunk_info['positions'] = []
+                print(f"匹配结果无效或索引越界，设置为空列表")
+                
+        # 验证更新结果
+        print("最终chunks_info状态:")
+        for i, chunk_info in enumerate(chunks_info):
+            print(f"  Chunk {i+1}: ID={chunk_info['id']}, Positions={chunk_info['positions']}")
+                
         return chunks_info
         
     except Exception as e:
         print(f"获取PDF文本位置信息时出错: {str(e)}")
         # 出错时为每个chunk添加空的位置信息
         for chunk_info in chunks_info:
-            chunk_info['positions'] = []
+            # 确保 chunk_info 包含 'positions' 键
+            if 'positions' not in chunk_info:
+                chunk_info['positions'] = []
         return chunks_info
 
 
 
-
 def process_pdf_txt_pairs(pdf_dict, txt_dict, dataset):
     """处理PDF-TXT文件对"""
     for name, pdf_path in pdf_dict.items():
@@ -493,6 +513,8 @@ def process_pdf_txt_pairs(pdf_dict, txt_dict, dataset):
         txt_path = txt_dict.get(name)
         if txt_path:
             chunks_info=process_txt_chunks(dataset.id,document, txt_path)
+
+            time.sleep(1)
             if  chunks_info:
                 chunks_info=get_positions_from_chunk(pdf_path, chunks_info)
                 for chunk_info in chunks_info:

src/find_text_in_pdf_enhanced.py

@@ -161,9 +161,10 @@ def find_text_in_pdf(pdf_path,
                 if matched_lines:
                     _, merged_bbox = _merge_lines(matched_lines)
                     results.append({
-                        "page": p + 1,
+                        "page": p,
                         "bbox": merged_bbox,
-                        "matched_text": matched_text
+                        "matched_text": matched_text,
+                        "position_int":[p, merged_bbox[0], merged_bbox[2], merged_bbox[1], merged_bbox[3]]
                     })
             if results:
                 batch_results[idx].extend(results)
@@ -206,6 +207,7 @@ def highlight_matches(pdf_path, matches, output_path="highlighted.pdf"):
 if __name__ == "__main__":
     pdf_path = 'e:\\2\\2024深化智慧城市发展推进城市全域数字化转型的指导意见.pdf'
     pdf_path = 'G:\\SynologyDrive\\大模型\\RAG\\20250805党建\\中国共产党领导干部廉洁从业若干准则.pdf'
+    pdf_path ="F:\\Synology_nas\\SynologyDrive\\大模型\\RAG\\20250805党建\\中国共产党领导干部廉洁从业若干准则.pdf"
     query = [
         '''一、总体要求
 以习近平新时代中国特色社会主义思想为指导，完整、准确、全面贯彻新发展理念，统筹发展和安全，充分发挥数据的基础资源和创新引擎作用，整体性重塑智慧城市技术架构、系统性变革城市管理流程、一体化推动产城深度融合，全面提升城市全域数字化转型的整体性、系统性、协同性，不断满足人民日益增长的美好生活需要，为全面建设社会主义现代化国家提供强大动力。到2027年，全国城市全域数字化转型取得明显成效，形成一批横向打通、纵向贯通、各具特色的宜居、韧性、智慧城市，有力支撑数字中国建设。到2030年，全国城市全域数字化转型全面突破，人民群众的获得感、幸福感、安全感全面提升，涌现一批数字文明时代具有全球竞争力的中国式现代化城市。''',
@@ -271,7 +273,7 @@ if __name__ == "__main__":
     # 1. 找跨行正则匹配
     matches = find_text_in_pdf(
         pdf_path,
-        query,  # 你的正则
+        query,  
         threshold=60
         
     )
@@ -284,7 +286,7 @@ if __name__ == "__main__":
         
         #highlight_matches(pdf_path, query_matches, "example_highlighted.pdf")
         for m in query_matches:
-            print(f"第 {m['page']} 页 匹配: {m['matched_text'][:50]}... 位置: {m['bbox']}")
+            print(f"第 {m['page']} 页 匹配: {m['matched_text'][:50]}... 位置: {m['bbox']}, 位置_int: {m['position_int']}")
         print("------------------")