From b6d3f390810a8064d780edda63fc2bebf5140190 Mon Sep 17 00:00:00 2001 From: wangmeihua <13383952685@163.com> Date: Fri, 12 Sep 2025 15:34:36 +0800 Subject: [PATCH] rag --- rag/folderinfo.py | 544 ++++++++++++++++++++++---------------------- rag/ragapi.py | 81 +++++-- rag/service_opts.py | 35 +-- 3 files changed, 352 insertions(+), 308 deletions(-) diff --git a/rag/folderinfo.py b/rag/folderinfo.py index ae60e95..ec66736 100644 --- a/rag/folderinfo.py +++ b/rag/folderinfo.py @@ -14,7 +14,7 @@ import time import uuid from datetime import datetime import traceback -from filetxt.loader import fileloader +from filetxt.loader import fileloader,File2Text from ahserver.serverenv import get_serverenv from typing import List, Dict, Any from rag.service_opts import get_service_params, sor_get_service_params @@ -44,6 +44,206 @@ where a.orgid = b.orgid return r.quota, r.expired_date return None, None + async def get_doucment_chunks(self, realpath, timings): + """加载文件并进行文本分片""" + debug(f"加载文件: {realpath}") + start_load = time.time() + supported_formats = File2Text.supported_types() + debug(f"支持的文件格式:{supported_formats}") + ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else '' + if ext not in supported_formats: + raise ValueError(f"不支持的文件格式: {ext}, 支持的格式: {', '.join(supported_formats)}") + text = fileloader(realpath) + text = re.sub(r'[^\u4e00-\u9fa5a-zA-Z0-9\s.;,\n/]', '', text) + timings["load_file"] = time.time() - start_load + debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}") + + if not text or not text.strip(): + raise ValueError(f"文件 {realpath} 加载为空") + + document = Document(page_content=text) + text_splitter = RecursiveCharacterTextSplitter( + chunk_size=500, + chunk_overlap=100, + length_function=len + ) + debug("开始分片文件内容") + start_split = time.time() + chunks = text_splitter.split_documents([document]) + timings["split_text"] = time.time() - start_split + debug(f"文本分片耗时: {timings['split_text']:.2f} 秒, 分片数量: {len(chunks)}") + + if not chunks: + raise ValueError(f"文件 {realpath} 未生成任何文档块") + + return chunks + + async def docs_embedding(self, request, chunks, service_params, userid, timings): + """调用嵌入服务生成向量""" + debug("调用嵌入服务生成向量") + start_embedding = time.time() + texts = [chunk.page_content for chunk in chunks] + embeddings = [] + for i in range(0, len(texts), 10): + batch_texts = texts[i:i + 10] + batch_embeddings = await APIService().get_embeddings( + request=request, + texts=batch_texts, + upappid=service_params['embedding'], + apiname="BAAI/bge-m3", + user=userid + ) + embeddings.extend(batch_embeddings) + + if not embeddings or not all(len(vec) == 1024 for vec in embeddings): + raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表") + + timings["generate_embeddings"] = time.time() - start_embedding + debug(f"生成嵌入向量耗时: {timings['generate_embeddings']:.2f} 秒, 嵌入数量: {len(embeddings)}") + return embeddings + + async def embedding_2_vdb(self, request, chunks, embeddings, realpath, orgid, fiid, id, service_params, userid, + db_type, timings): + """准备数据并插入 Milvus""" + debug(f"准备数据并调用插入文件端点: {realpath}") + filename = os.path.basename(realpath).rsplit('.', 1)[0] + ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else '' + upload_time = datetime.now().isoformat() + + chunks_data = [ + { + "userid": orgid, + "knowledge_base_id": fiid, + "text": chunk.page_content, + "vector": embeddings[i], + "document_id": id, + "filename": filename + '.' + ext, + "file_path": realpath, + "upload_time": upload_time, + "file_type": ext, + } + for i, chunk in enumerate(chunks) + ] + + start_milvus = time.time() + for i in range(0, len(chunks_data), 10): + batch_chunks = chunks_data[i:i + 10] + result = await APIService().milvus_insert_document( + request=request, + chunks=batch_chunks, + db_type=db_type, + upappid=service_params['vdb'], + apiname="milvus/insertdocument", + user=userid + ) + if result.get("status") != "success": + raise ValueError(result.get("message", "Milvus 插入失败")) + + timings["insert_milvus"] = time.time() - start_milvus + debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒") + return chunks_data + + async def get_triples(self, request, chunks, service_params, userid, timings): + """调用三元组抽取服务""" + debug("调用三元组抽取服务") + start_triples = time.time() + chunk_texts = [doc.page_content for doc in chunks] + triples = [] + for i, chunk in enumerate(chunk_texts): + result = await APIService().extract_triples( + request=request, + text=chunk, + upappid=service_params['triples'], + apiname="Babelscape/mrebel-large", + user=userid + ) + if isinstance(result, list): + triples.extend(result) + debug(f"分片 {i + 1} 抽取到 {len(result)} 个三元组") + else: + error(f"分片 {i + 1} 处理失败: {str(result)}") + + unique_triples = [] + seen = set() + for t in triples: + identifier = (t['head'].lower(), t['tail'].lower(), t['type'].lower()) + if identifier not in seen: + seen.add(identifier) + unique_triples.append(t) + else: + for existing in unique_triples: + if (existing['head'].lower() == t['head'].lower() and + existing['tail'].lower() == t['tail'].lower() and + len(t['type']) > len(existing['type'])): + unique_triples.remove(existing) + unique_triples.append(t) + debug(f"替换三元组为更具体类型: {t}") + break + + timings["extract_triples"] = time.time() - start_triples + debug(f"三元组抽取耗时: {timings['extract_triples']:.2f} 秒, 抽取到 {len(unique_triples)} 个三元组") + return unique_triples + + async def triple2graphdb(self, request, unique_triples, id, fiid, orgid, service_params, userid, timings): + """调用 Neo4j 插入三元组""" + debug(f"插入 {len(unique_triples)} 个三元组到 Neo4j") + start_neo4j = time.time() + if unique_triples: + for i in range(0, len(unique_triples), 30): + batch_triples = unique_triples[i:i + 30] + neo4j_result = await APIService().neo4j_insert_triples( + request=request, + triples=batch_triples, + document_id=id, + knowledge_base_id=fiid, + userid=orgid, + upappid=service_params['gdb'], + apiname="neo4j/inserttriples", + user=userid + ) + if neo4j_result.get("status") != "success": + raise ValueError(f"Neo4j 三元组插入失败: {neo4j_result.get('message', '未知错误')}") + info(f"文件三元组成功插入 Neo4j: {neo4j_result.get('message')}") + timings["insert_neo4j"] = time.time() - start_neo4j + debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒") + else: + debug("未抽取到三元组") + timings["insert_neo4j"] = 0.0 + + async def delete_from_milvus(self, request, orgid, realpath, fiid, id, service_params, userid, db_type): + """调用 Milvus 删除文档""" + debug(f"调用删除文件端点: userid={orgid}, file_path={realpath}, knowledge_base_id={fiid}, document_id={id}") + milvus_result = await APIService().milvus_delete_document( + request=request, + userid=orgid, + file_path=realpath, + knowledge_base_id=fiid, + document_id=id, + db_type=db_type, + upappid=service_params['vdb'], + apiname="milvus/deletedocument", + user=userid + ) + if milvus_result.get("status") != "success": + raise ValueError(milvus_result.get("message", "Milvus 删除失败")) + + async def delete_from_neo4j(self, request, id, service_params, userid): + """调用 Neo4j 删除文档""" + debug(f"调用 Neo4j 删除文档端点: document_id={id}") + neo4j_result = await APIService().neo4j_delete_document( + request=request, + document_id=id, + upappid=service_params['gdb'], + apiname="neo4j/deletedocument", + user=userid + ) + if neo4j_result.get("status") != "success": + raise ValueError(neo4j_result.get("message", "Neo4j 删除失败")) + nodes_deleted = neo4j_result.get("nodes_deleted", 0) + rels_deleted = neo4j_result.get("rels_deleted", 0) + info(f"成功删除 document_id={id} 的 {nodes_deleted} 个 Neo4j 节点和 {rels_deleted} 个关系") + return nodes_deleted, rels_deleted + async def file_uploaded(self, request, ns, userid): """将文档插入 Milvus 并抽取三元组到 Neo4j""" debug(f'Received ns: {ns=}') @@ -52,23 +252,13 @@ where a.orgid = b.orgid fiid = ns.get('fiid', '') id = ns.get('id', '') orgid = ns.get('ownerid', '') - hashvalue = ns.get('hashvalue', '') db_type = '' - api_service = APIService() - debug( - f'Inserting document: file_path={realpath}, userid={orgid}, db_type={db_type}, knowledge_base_id={fiid}, document_id={id}') + debug(f'Inserting document: file_path={realpath}, userid={orgid}, db_type={db_type}, knowledge_base_id={fiid}, document_id={id}') timings = {} start_total = time.time() - service_params = await get_service_params(orgid) - chunks = await self.get_doucment_chunks(realpath) - embeddings = await self.docs_embedding(chunks) - await self.embedding_2_vdb(id, fiid, orgid, realpath, embedding) - triples = await self.get_triples(chunks) - await self.triple2graphdb(id, fiid, orgid, realpath, triples) - return try: if not orgid or not fiid or not id: raise ValueError("orgid、fiid 和 id 不能为空") @@ -82,217 +272,41 @@ where a.orgid = b.orgid if not service_params: raise ValueError("无法获取服务参数") - supported_formats = {'pdf', 'docx', 'xlsx', 'pptx', 'csv', 'txt'} - ext = realpath.rsplit('.', 1)[1].lower() if '.' in realpath else '' - if ext not in supported_formats: - raise ValueError(f"不支持的文件格式: {ext}, 支持的格式: {', '.join(supported_formats)}") - - debug(f"加载文件: {realpath}") - start_load = time.time() - text = fileloader(realpath) - # debug(f"处理后的文件内容是：{text=}") - text = re.sub(r'[^\u4e00-\u9fa5a-zA-Z0-9\s.;,\n/]', '', text) - timings["load_file"] = time.time() - start_load - debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}") - if not text or not text.strip(): - raise ValueError(f"文件 {realpath} 加载为空") - - document = Document(page_content=text) - text_splitter = RecursiveCharacterTextSplitter( - chunk_size=500, - chunk_overlap=100, - length_function=len) - debug("开始分片文件内容") - start_split = time.time() - chunks = text_splitter.split_documents([document]) - timings["split_text"] = time.time() - start_split - debug( - f"文本分片耗时: {timings['split_text']:.2f} 秒, 分片数量: {len(chunks)}, 分片内容: {[chunk.page_content[:50] for chunk in chunks[:5]]}") - debug(f"分片内容: {[chunk.page_content[:100] + '...' for chunk in chunks]}") - if not chunks: - raise ValueError(f"文件 {realpath} 未生成任何文档块") - - filename = os.path.basename(realpath).rsplit('.', 1)[0] - upload_time = datetime.now().isoformat() - - debug("调用嵌入服务生成向量") - start_embedding = time.time() - texts = [chunk.page_content for chunk in chunks] - embeddings = [] - for i in range(0, len(texts), 10): # 每次处理 10 个文本块 - batch_texts = texts[i:i + 10] - batch_embeddings = await api_service.get_embeddings( - request=request, - texts=batch_texts, - upappid=service_params['embedding'], - apiname="BAAI/bge-m3", - user=userid - ) - embeddings.extend(batch_embeddings) - if not embeddings or not all(len(vec) == 1024 for vec in embeddings): - raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表") - timings["generate_embeddings"] = time.time() - start_embedding - debug(f"生成嵌入向量耗时: {timings['generate_embeddings']:.2f} 秒, 嵌入数量: {len(embeddings)}") - - chunks_data = [] - for i, chunk in enumerate(chunks): - chunks_data.append({ - "userid": orgid, - "knowledge_base_id": fiid, - "text": chunk.page_content, - "vector": embeddings[i], - "document_id": id, - "filename": filename + '.' + ext, - "file_path": realpath, - "upload_time": upload_time, - "file_type": ext, - }) - - debug(f"调用插入文件端点: {realpath}") - start_milvus = time.time() - for i in range(0, len(chunks_data), 10): # 每次处理 10 条数据 - batch_chunks = chunks_data[i:i + 10] - result = await api_service.milvus_insert_document( - request=request, - chunks=batch_chunks, - db_type=db_type, - upappid=service_params['vdb'], - apiname="milvus/insertdocument", - user=userid - ) - if result.get("status") != "success": - raise ValueError(result.get("message", "Milvus 插入失败")) - timings["insert_milvus"] = time.time() - start_milvus - debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒") - - if result.get("status") != "success": - timings["total"] = time.time() - start_total - return {"status": "error", "document_id": id, "timings": timings, - "message": result.get("message", "未知错误"), "status_code": 400} - - debug("调用三元组抽取服务") - start_triples = time.time() - unique_triples = [] - try: - chunk_texts = [doc.page_content for doc in chunks] - debug(f"处理 {len(chunk_texts)} 个分片进行三元组抽取") - triples = [] - for i, chunk in enumerate(chunk_texts): - result = await api_service.extract_triples( - request=request, - text=chunk, - upappid=service_params['triples'], - apiname="Babelscape/mrebel-large", - user=userid - ) - if isinstance(result, list): - triples.extend(result) - debug(f"分片 {i + 1} 抽取到 {len(result)} 个三元组: {result[:5]}") - else: - error(f"分片 {i + 1} 处理失败: {str(result)}") - - seen = set() - for t in triples: - identifier = (t['head'].lower(), t['tail'].lower(), t['type'].lower()) - if identifier not in seen: - seen.add(identifier) - unique_triples.append(t) - else: - for existing in unique_triples: - if (existing['head'].lower() == t['head'].lower() and - existing['tail'].lower() == t['tail'].lower() and - len(t['type']) > len(existing['type'])): - unique_triples.remove(existing) - unique_triples.append(t) - debug(f"替换三元组为更具体类型: {t}") - break - - timings["extract_triples"] = time.time() - start_triples - debug( - f"三元组抽取耗时: {timings['extract_triples']:.2f} 秒, 抽取到 {len(unique_triples)} 个三元组: {unique_triples[:5]}") - - if unique_triples: - debug(f"抽取到 {len(unique_triples)} 个三元组，调用 Neo4j 服务插入") - start_neo4j = time.time() - for i in range(0, len(unique_triples), 30): # 每次插入 30 个三元组 - batch_triples = unique_triples[i:i + 30] - neo4j_result = await api_service.neo4j_insert_triples( - request=request, - triples=batch_triples, - document_id=id, - knowledge_base_id=fiid, - userid=orgid, - upappid=service_params['gdb'], - apiname="neo4j/inserttriples", - user=userid - ) - debug(f"Neo4j 服务响应: {neo4j_result}") - if neo4j_result.get("status") != "success": - timings["insert_neo4j"] = time.time() - start_neo4j - timings["total"] = time.time() - start_total - return { - "status": "error", - "document_id": id, - "collection_name": "ragdb", - "timings": timings, - "message": f"Neo4j 三元组插入失败: {neo4j_result.get('message', '未知错误')}", - "status_code": 400 - } - info(f"文件 {realpath} 三元组成功插入 Neo4j: {neo4j_result.get('message')}") - timings["insert_neo4j"] = time.time() - start_neo4j - debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒") - else: - debug(f"文件 {realpath} 未抽取到三元组") - timings["insert_neo4j"] = 0.0 - - except Exception as e: - timings["extract_triples"] = time.time() - start_triples if "extract_triples" not in timings else \ - timings["extract_triples"] - timings["insert_neo4j"] = time.time() - start_neo4j if "insert_neo4j" not in timings else timings[ - "insert_neo4j"] - debug(f"处理三元组或 Neo4j 插入失败: {str(e)}, 堆栈: {traceback.format_exc()}") - timings["total"] = time.time() - start_total - return { - "status": "success", - "document_id": id, - "collection_name": "ragdb", - "timings": timings, - "unique_triples": unique_triples, - "message": f"文件 {realpath} 成功嵌入，但三元组处理或 Neo4j 插入失败: {str(e)}", - "status_code": 200 - } + chunks = await self.get_doucment_chunks(realpath, timings) + embeddings = await self.docs_embedding(request, chunks, service_params, userid, timings) + await self.embedding_2_vdb(request, chunks, embeddings, realpath, orgid, fiid, id, service_params, userid,db_type, timings) + triples = await self.get_triples(request, chunks, service_params, userid, timings) + await self.triple2graphdb(request, triples, id, fiid, orgid, service_params, userid, timings) timings["total"] = time.time() - start_total debug(f"总耗时: {timings['total']:.2f} 秒") return { - "status": "success", - "userid": orgid, - "document_id": id, - "collection_name": "ragdb", - "timings": timings, - "unique_triples": unique_triples, - "message": f"文件 {realpath} 成功嵌入并处理三元组", - "status_code": 200 + "status": "success", + "userid": orgid, + "document_id": id, + "collection_name": "ragdb", + "timings": timings, + "unique_triples": triples, + "message": f"文件 {realpath} 成功嵌入并处理三元组", + "status_code": 200 } - except Exception as e: error(f"插入文档失败: {str(e)}, 堆栈: {traceback.format_exc()}") timings["total"] = time.time() - start_total return { - "status": "error", - "document_id": id, - "collection_name": "ragdb", - "timings": timings, - "message": f"插入文档失败: {str(e)}", - "status_code": 400 + "status": "error", + "document_id": id, + "collection_name": "ragdb", + "timings": timings, + "message": f"插入文档失败: {str(e)}", + "status_code": 400 } async def file_deleted(self, request, recs, userid): """删除用户指定文件数据，包括 Milvus 和 Neo4j 中的记录""" if not isinstance(recs, list): - recs = [recs] # 确保 recs 是列表，即使传入单个记录 + recs = [recs] results = [] - api_service = APIService() total_nodes_deleted = 0 total_rels_deleted = 0 @@ -310,46 +324,24 @@ where a.orgid = b.orgid if missing_fields: raise ValueError(f"缺少必填字段: {', '.join(missing_fields)}") - # 获取服务参数 service_params = await get_service_params(orgid) if not service_params: raise ValueError("无法获取服务参数") - debug(f"调用删除文件端点: userid={orgid}, file_path={realpath}, knowledge_base_id={fiid}, document_id={id}") - milvus_result = await api_service.milvus_delete_document( - request=request, - userid=orgid, - file_path=realpath, - knowledge_base_id=fiid, - document_id=id, - db_type=db_type, - upappid=service_params['vdb'], - apiname="milvus/deletedocument", - user=userid - ) - - if milvus_result.get("status") != "success": - raise ValueError(milvus_result.get("message", "Milvus 删除失败")) + # 调用 Milvus 删除 + await self.delete_from_milvus(request, orgid, realpath, fiid, id, service_params, userid, db_type) + # 调用 Neo4j 删除 neo4j_deleted_nodes = 0 neo4j_deleted_rels = 0 - debug(f"调用 Neo4j 删除文档端点: document_id={id}") - neo4j_result = await api_service.neo4j_delete_document( - request=request, - document_id=id, - upappid=service_params['gdb'], - apiname="neo4j/deletedocument", - user=userid - ) - if neo4j_result.get("status") != "success": - raise ValueError(neo4j_result.get("message", "Neo4j 删除失败")) - nodes_deleted = neo4j_result.get("nodes_deleted", 0) - rels_deleted = neo4j_result.get("rels_deleted", 0) - neo4j_deleted_nodes += nodes_deleted - neo4j_deleted_rels += rels_deleted - total_nodes_deleted += nodes_deleted - total_rels_deleted += rels_deleted - info(f"成功删除 document_id={id} 的 {nodes_deleted} 个 Neo4j 节点和 {rels_deleted} 个关系") + try: + nodes_deleted, rels_deleted = await self.delete_from_neo4j(request, id, service_params, userid) + neo4j_deleted_nodes += nodes_deleted + neo4j_deleted_rels += rels_deleted + total_nodes_deleted += nodes_deleted + total_rels_deleted += rels_deleted + except Exception as e: + error(f"删除 document_id={id} 的 Neo4j 数据失败: {str(e)}") results.append({ "status": "success", @@ -361,13 +353,13 @@ where a.orgid = b.orgid except Exception as e: error(f"删除文档 {realpath} 失败: {str(e)}, 堆栈: {traceback.format_exc()}") - results.append({ - "status": "error", - "collection_name": collection_name, - "document_id": id, - "message": f"删除文档 {realpath} 失败: {str(e)}", - "status_code": 400 - }) + results.append({ + "status": "error", + "collection_name": collection_name, + "document_id": id, + "message": f"删除文档 {realpath} 失败: {str(e)}", + "status_code": 400 + }) return { "status": "success" if all(r["status"] == "success" for r in results) else "partial", @@ -378,31 +370,31 @@ where a.orgid = b.orgid "status_code": 200 if all(r["status"] == "success" for r in results) else 207 } -async def test_ragfilemgr(): - """测试 RagFileMgr 类的 get_service_params""" - print("初始化数据库连接池...") - dbs = { - "kyrag": { - "driver": "aiomysql", - "async_mode": True, - "coding": "utf8", - "maxconn": 100, - "dbname": "kyrag", - "kwargs": { - "user": "test", - "db": "kyrag", - "password": "QUZVcXg5V1p1STMybG5Ia6mX9D0v7+g=", - "host": "db" - } - } - } - DBPools(dbs) - - ragfilemgr = RagFileMgr() - orgid = "04J6VbxLqB_9RPMcgOv_8" - result = await ragfilemgr.get_service_params(orgid) - print(f"get_service_params 结果: {result}") - - -if __name__ == "__main__": - asyncio.run(test_ragfilemgr()) +# async def test_ragfilemgr(): +# """测试 RagFileMgr 类的 get_service_params""" +# print("初始化数据库连接池...") +# dbs = { +# "kyrag": { +# "driver": "aiomysql", +# "async_mode": True, +# "coding": "utf8", +# "maxconn": 100, +# "dbname": "kyrag", +# "kwargs": { +# "user": "test", +# "db": "kyrag", +# "password": "QUZVcXg5V1p1STMybG5Ia6mX9D0v7+g=", +# "host": "db" +# } +# } +# } +# DBPools(dbs) +# +# ragfilemgr = RagFileMgr() +# orgid = "04J6VbxLqB_9RPMcgOv_8" +# result = await get_service_params(orgid) +# print(f"get_service_params 结果: {result}") +# +# +# if __name__ == "__main__": +# asyncio.run(test_ragfilemgr()) diff --git a/rag/ragapi.py b/rag/ragapi.py index 5c3c4da..e4520de 100644 --- a/rag/ragapi.py +++ b/rag/ragapi.py @@ -1,11 +1,11 @@ from rag.uapi_service import APIService -from rag.folderinfo import RagFileMgr from sqlor.dbpools import DBPools from appPublic.log import debug, error, info import time import traceback import json import math +from rag.service_opts import get_service_params, sor_get_service_params helptext = """kyrag API: @@ -82,7 +82,7 @@ async def fusedsearch(request, params_kw, *params, **kw): # orgid = "04J6VbxLqB_9RPMcgOv_8" # userid = "04J6VbxLqB_9RPMcgOv_8" query = params_kw.get('query', '') - # 统一模式处理 limit 参数 + # 统一模式处理 limit 参数,为了对接dify和coze raw_limit = params_kw.get('limit') or ( params_kw.get('retrieval_setting', {}).get('top_k') if isinstance(params_kw.get('retrieval_setting'), dict) @@ -103,7 +103,7 @@ async def fusedsearch(request, params_kw, *params, **kw): else: limit = 5 # 其他意外类型使用默认值 debug(f"limit: {limit}") - raw_fiids = params_kw.get('fiids') or params_kw.get('knowledge_id') + raw_fiids = params_kw.get('fiids') or params_kw.get('knowledge_id') # # 标准化为列表格式 if raw_fiids is None: @@ -111,8 +111,18 @@ async def fusedsearch(request, params_kw, *params, **kw): elif isinstance(raw_fiids, list): fiids = [str(item).strip() for item in raw_fiids] # 已经是列表 elif isinstance(raw_fiids, str): - # 处理逗号分隔的字符串或单个ID字符串 - fiids = [f.strip() for f in raw_fiids.split(',') if f.strip()] + # fiids = [f.strip() for f in raw_fiids.split(',') if f.strip()] + try: + # 尝试解析 JSON 字符串 + parsed = json.loads(raw_fiids) + if isinstance(parsed, list): + fiids = [str(item).strip() for item in parsed] # JSON 数组转为字符串列表 + else: + # 处理逗号分隔的字符串或单个 ID 字符串 + fiids = [f.strip() for f in raw_fiids.split(',') if f.strip()] + except json.JSONDecodeError: + # 如果不是合法 JSON，按逗号分隔 + fiids = [f.strip() for f in raw_fiids.split(',') if f.strip()] elif isinstance(raw_fiids, (int, float)): fiids = [str(int(raw_fiids))] # 数值类型转为字符串列表 else: @@ -140,8 +150,7 @@ async def fusedsearch(request, params_kw, *params, **kw): except Exception as e: error(f"orgid 验证失败: {str(e)}") return json.dumps({"status": "error", "message": str(e)}) - ragfilemgr = RagFileMgr("fiids[0]") - service_params = await ragfilemgr.get_service_params(orgid) + service_params = await get_service_params(orgid) api_service = APIService() start_time = time.time() @@ -276,9 +285,19 @@ async def fusedsearch(request, params_kw, *params, **kw): timing_stats["total_time"] = time.time() - start_time info(f"融合搜索完成，返回 {len(unique_results)} 条结果，总耗时: {timing_stats['total_time']:.3f} 秒") - # debug(f"results: {unique_results[:limit]},timing: {timing_stats}") - # return {"results": unique_results[:limit], "timing": timing_stats} - + # dify_result = [] + # for res in unique_results[:limit]: + # content = res.get('text', '') + # title = res.get('metadata', {}).get('filename', 'Untitled') + # document_id = res.get('metadata', {}).get('document_id', '') + # dify_result.append({ + # 'metadata': {'document_id': document_id}, + # 'title': title, + # 'content': content + # }) + # info(f"融合搜索完成，返回 {len(dify_result)} 条结果，总耗时: {(time.time() - start_time):.3f} 秒") + # debug(f"result: {dify_result}") + # return dify_result dify_records = [] dify_result = [] @@ -291,18 +310,50 @@ async def fusedsearch(request, params_kw, *params, **kw): document_id = res.get('metadata', {}).get('document_id', '') dify_records.append({ "content": content, - "score": score, - "title": title + "title": title, + "metadata": {"document_id": document_id, "score": score}, }) dify_result.append({ "content": content, "title": title, - "metadata": {"document_id": document_id} + "metadata": {"document_id": document_id, "score": score}, }) - info(f"融合搜索完成，返回 {len(dify_records)} 条结果，总耗时: {(time.time() - start_time):.3f} 秒") debug(f"records: {dify_records}, result: {dify_result}") - return {"records": dify_records, "result": dify_result, "own":{"results": unique_results[:limit], "timing": timing_stats}} + # return {"records": dify_records, "result": dify_result,"own": {"results": unique_results[:limit], "timing": timing_stats}} + return {"records": dify_records} + + # dify_result = [] + # for res in unique_results[:limit]: + # rerank_score = res.get('rerank_score', 0) + # score = 1 / (1 + math.exp(-rerank_score)) if rerank_score is not None else 1 - res.get('distance', 0) + # score = max(0.0, min(1.0, score)) + # content = res.get('text', '') + # title = res.get('metadata', {}).get('filename', 'Untitled') + # document_id = res.get('metadata', {}).get('document_id', '') + # dify_result.append({ + # "metadata": { + # "_source": "konwledge", + # "dataset_id":"111111", + # "dataset_name": "NVIDIA_GPU性能参数-RAG-V1.xlsx", + # "document_id": document_id, + # "document_name": "test.docx", + # "data_source_type": "upload_file", + # "segment_id": "7b391707-93bc-4654-80ae-7989f393b045", + # "retriever_from": "workflow", + # "score": score, + # "segment_hit_count": 7, + # "segment_word_count": 275, + # "segment_position": 5, + # "segment_index_node_hash": "1cd60b478221c9d4831a0b2af3e8b8581d94ecb53e8ffd46af687e8fc3077b73", + # "doc_metadata": None, + # "position":1 + # }, + # "title": title, + # "content": content + # }) + # return {"result": dify_result} + except Exception as e: error(f"融合搜索失败: {str(e)}, 堆栈: {traceback.format_exc()}") return {"results": [], "timing": timing_stats} diff --git a/rag/service_opts.py b/rag/service_opts.py index 72c1833..6e07d3b 100644 --- a/rag/service_opts.py +++ b/rag/service_opts.py @@ -1,4 +1,5 @@ from ahserver.serverenv import get_serverenv +from sqlor.dbpools import DBPools async def sor_get_service_params(sor, orgid): """ 根据 orgid 从数据库获取服务参数 (仅 upappid)，假设 service_opts 表返回单条记录。 """ @@ -16,8 +17,8 @@ async def sor_get_service_params(sor, orgid): # 收集服务 ID service_ids = set() for key in ['embedding_id', 'vdb_id', 'reranker_id', 'triples_id', 'gdb_id', 'entities_id']: - if opts[key]: - service_ids.add(opts[key]) + if opts[key]: + service_ids.add(opts[key]) # 检查 service_ids 是否为空 if not service_ids: @@ -25,7 +26,7 @@ async def sor_get_service_params(sor, orgid): return None # 手动构造 IN 子句的 ID 列表 - id_list = ','.join([f"'{id}'" for id in service_ids]) # 确保每个 ID 被单引号包裹 + id_list = [id for id in service_ids] # 确保每个 ID 被单引号包裹 sql_services = """ SELECT id, name, upappid FROM ragservices @@ -46,19 +47,19 @@ async def sor_get_service_params(sor, orgid): 'entities': None } for service in services_result: - name = service['name'] - if name == 'bgem3嵌入': - service_params['embedding'] = service['upappid'] - elif name == 'milvus向量检索': - service_params['vdb'] = service['upappid'] - elif name == 'bgem2v3重排': - service_params['reranker'] = service['upappid'] - elif name == 'mrebel三元组抽取': - service_params['triples'] = service['upappid'] - elif name == 'neo4j删除知识库': - service_params['gdb'] = service['upappid'] - elif name == 'small实体抽取': - service_params['entities'] = service['upappid'] + name = service['name'] + if name == 'bgem3嵌入': + service_params['embedding'] = service['upappid'] + elif name == 'milvus向量检索': + service_params['vdb'] = service['upappid'] + elif name == 'bgem2v3重排': + service_params['reranker'] = service['upappid'] + elif name == 'mrebel三元组抽取': + service_params['triples'] = service['upappid'] + elif name == 'neo4j删除知识库': + service_params['gdb'] = service['upappid'] + elif name == 'small实体抽取': + service_params['entities'] = service['upappid'] # 检查是否所有服务参数都已填充 missing_services = [k for k, v in service_params.items() if v is None] @@ -71,5 +72,5 @@ async def get_service_params(orgid): db = DBPools() dbname = get_serverenv('get_module_dbname')('rag') async with db.sqlorContext(dbname) as sor: - return await sor_get_server_params(sor, orgid) + return await sor_get_service_params(sor, orgid) return None