diff --git a/chunk_operations.py b/chunk_operations.py
new file mode 100644
index 0000000..e8b5751
--- /dev/null
+++ b/chunk_operations.py
@@ -0,0 +1,157 @@
+from elasticsearch import Elasticsearch
+
+# 初始化 Elasticsearch   用户名elastic，密码infini_rag_flow
+es = Elasticsearch(
+    [{'host': '192.168.107.165', 'port': 1200, 'scheme': 'http'}],
+    basic_auth=('elastic', 'infini_rag_flow')
+)
+
+def update_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id, new_img_id):
+    """
+    在 Elasticsearch 中更新指定文档块的 img_id。
+    如果img_id不存在，则增加一个新的 img_id。
+
+    :param tenant_id: 租户 ID
+    :param dataset_id: 数据集 ID
+    :param doc_id: 文档 ID
+    :param chunk_id: 文档块 ID
+    :param new_img_id: 新的 img_id
+    :return: 更新结果
+
+    """
+    # 构建索引名称
+    index_name = f"ragflow_{tenant_id}"  # 这里需要替换为实际的索引名称生成逻辑
+
+    # 构建查询条件
+    query = {
+        "bool": {
+            "must": [
+                {"term": {"doc_id": doc_id}},
+                {"term": {"_id": chunk_id}}
+            ]
+        }
+    }
+
+    # 搜索目标文档
+    result = es.search(index=index_name, body={"query": query})
+
+    # 检查是否找到目标文档
+    if result['hits']['total']['value'] == 0:
+        return {"code": 102, "message": f"Can't find this chunk {chunk_id}"}
+    
+
+    # 获取目标文档的 ID
+    hit = result['hits']['hits'][0]
+    doc_id_in_es = hit['_id']
+    # print(doc_id_in_es)
+    #print(hit)
+    #print(len(hit['_source']['img_id']))
+    # image_id = hit['_source'].get('img_id', None)
+
+    # if (image_id):
+    #     mapping = es.indices.get_mapping(index=index_name)
+    #     print(mapping)
+
+    # else:
+    #     # img_id 不存在，添加新的 img_id
+    #     # 获取索引的映射
+    #     mapping = es.indices.get_mapping(index=index_name)
+    #     mapping[index_name]['mappings']['properties']['img_id'] = {'type': 'text'}
+    #     es.indices.put_mapping(index="my_index", body=mapping)
+    #     print(mapping)
+
+    
+    #         # 构建更新请求
+    update_body = {
+        "doc": {
+            "img_id": new_img_id
+        }
+        }
+
+    # 更新文档
+    update_result = es.update(index=index_name, id=doc_id_in_es, body=update_body)
+    
+
+    if update_result['result'] == 'updated':
+        return {"code": 0, "message": ""}
+    else:
+        return {"code": 100, "message": "Failed to update img_id"}
+    
+
+def list_chunk_information(tenant_id, dataset_id, doc_id=None, chunk_id=None, size=1000):
+    """
+    列出指定条件下的 chunk 信息
+
+    :param tenant_id: 租户 ID
+    :param dataset_id: 数据集 ID
+    :param doc_id: 文档 ID（可选）
+    :param chunk_id: 文档块 ID（可选）
+    :param size: 返回的最大结果数
+    :return: chunk 信息列表
+    """
+    # 构建索引名称
+    index_name = f"ragflow_{tenant_id}"  # 需替换为实际索引名生成逻辑
+    
+    # 构建基础查询
+    query = {"bool": {"must": []}}
+    
+    # 添加可选过滤条件
+    if doc_id:
+        query["bool"]["must"].append({"term": {"doc_id": doc_id}})
+
+    
+    # 执行搜索
+    try:
+        result = es.search(
+            index=index_name,
+            body={"query": query, "size": size},
+            fields= ["_id"],
+            _source=["doc_id", "kb_id", "img_id", "content", "docnm_kwd"]  # 指定返回的字段
+        )
+        for d in result['hits']['hits']:
+            print(d['_id'])
+            
+        
+        # 提取并格式化结果
+        chunks = []
+        for hit in result['hits']['hits']:
+            source = hit['_source']
+            chunks.append({
+                'doc_id': source.get('doc_id'),
+                'kb_id': source.get('kb_id'),
+                'img_id': source.get('img_id'),
+                'content': source.get('content'),
+                'docnm_kwd': source.get('docnm_kwd')
+            })
+            
+        return {"code": 0, "message": "", "data": chunks}
+    
+    except Exception as e:
+        return {"code": 500, "message": str(e), "data": []}
+
+# 示例调用 - 列出特定文档的所有 chunks
+if __name__ == "__main__":
+    try:
+        print(es.info())
+    except Exception as e:
+        print("连接失败：", e)
+
+    tenant_id = "d669205e57a211f0b9e7324e7f243034"
+    dataset_id = "10345832587311f0919f3a2728512a4b"  #  dataset_id = kb_id
+    doc_id = "cbf576385bc911f08f23fedc3996e479"
+    doc_id = "4300e558609511f08b8bde4a87f78768"  
+    chunk_id = "f035247f7de579b0"  #  
+    chunk_id = "5b3445f7861ff772"  # 
+    new_img_id =    "10345832587311f0919f3a2728512a4b-f035247f7de579b0" #"new_img_id_12345"
+    #new_img_id ="c5142bce5ac611f0ae707a8b5ba029cb-thumbnail_fb3cbc165ac611f0b5897a8b5ba029cb.png"
+
+
+
+    #chunk_list = list_chunk_information(tenant_id, dataset_id, doc_id=doc_id)
+    update_img_id_in_elasticsearch(tenant_id, doc_id, chunk_id,new_img_id)
+    # if chunk_list["code"] == 0:
+    #     print(f"找到 {len(chunk_list['data'])} 个 chunks")
+    #     for chunk in chunk_list['data']:
+    #         print(f"Chunk ID: {chunk['kb_id']}, Img ID: {chunk['img_id']}","docnm_kwd:", chunk['docnm_kwd'])
+    # else:
+    #     print(f"Error: {chunk_list['message']}")
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