bugfix
This commit is contained in:
parent
8c134b7ca5
commit
2435b8dca0
@ -113,7 +113,7 @@ class APIService:
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error(f"Request #{request_id} failed, status: {response.status}, response: {error_text}")
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raise RuntimeError(f"三元组抽取服务调用失败: {response.status}, {error_text}")
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result = await response.json()
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if result.get("object") != "list" or not result.get("data"):
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if result.get("object") != "list":
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error(f"Request #{request_id} invalid response format: {result}")
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raise RuntimeError("三元组抽取服务响应格式错误")
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triples = result["data"]
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@ -231,6 +231,13 @@ class APIService:
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"chunks": chunks,
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"dbtype": db_type
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}
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# 计算请求体大小
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payload = json.dumps(params) # 转换为 JSON 字符串
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payload_bytes = payload.encode() # 编码为字节
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payload_size = len(payload_bytes) # 获取字节数
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debug(f"Request payload size for insertdocument: {payload_size} bytes")
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return await self._make_request("https://vectordb.opencomputing.net:10443/v1/insertdocument", "insertdocument", params)
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async def milvus_delete_document(self, userid: str, file_path: str, knowledge_base_id: str, document_id:str, db_type: str = "") -> Dict[str, Any]:
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103
rag/file.py
103
rag/file.py
@ -1,4 +1,4 @@
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from api_service import APIService
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from rag.api_service import APIService
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from appPublic.registerfunction import RegisterFunction
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from appPublic.log import debug, error, info
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from sqlor.dbpools import DBPools
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@ -14,6 +14,9 @@ from datetime import datetime
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import traceback
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from filetxt.loader import fileloader
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from ahserver.serverenv import get_serverenv
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from typing import List, Dict, Any
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api_service = APIService()
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async def get_orgid_by_id(kdb_id):
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"""
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@ -38,7 +41,6 @@ async def get_orgid_by_id(kdb_id):
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async def file_uploaded(params_kw):
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"""将文档插入 Milvus 并抽取三元组到 Neo4j"""
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debug(f'Received params: {params_kw=}')
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api_service = APIService()
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realpath = params_kw.get('realpath', '')
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fiid = params_kw.get('fiid', '')
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id = params_kw.get('id', '')
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@ -52,6 +54,7 @@ async def file_uploaded(params_kw):
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try:
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if not orgid or not fiid or not id:
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raise ValueError("orgid、fiid 和 id 不能为空")
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debug(f'orgid、fiid 和 id 不能为空')
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if len(orgid) > 32 or len(fiid) > 255:
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raise ValueError("orgid 或 fiid 的长度超出限制")
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if not os.path.exists(realpath):
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@ -90,7 +93,11 @@ async def file_uploaded(params_kw):
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debug("调用嵌入服务生成向量")
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start_embedding = time.time()
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texts = [chunk.page_content for chunk in chunks]
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embeddings = await api_service.get_embeddings(texts)
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embeddings = []
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for i in range(0, len(texts), 10): # 每次处理 10 个文本块
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batch_texts = texts[i:i + 10]
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batch_embeddings = await api_service.get_embeddings(batch_texts)
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embeddings.extend(batch_embeddings)
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if not embeddings or not all(len(vec) == 1024 for vec in embeddings):
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raise ValueError("所有嵌入向量必须是长度为 1024 的浮点数列表")
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timings["generate_embeddings"] = time.time() - start_embedding
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@ -112,7 +119,11 @@ async def file_uploaded(params_kw):
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debug(f"调用插入文件端点: {realpath}")
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start_milvus = time.time()
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result = await api_service.milvus_insert_document(chunks_data, db_type)
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for i in range(0, len(chunks_data), 10): # 每次处理 10 条数据
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batch_chunks = chunks_data[i:i + 10]
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result = await api_service.milvus_insert_document(batch_chunks, db_type)
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if result.get("status") != "success":
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raise ValueError(result.get("message", "Milvus 插入失败"))
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timings["insert_milvus"] = time.time() - start_milvus
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debug(f"Milvus 插入耗时: {timings['insert_milvus']:.2f} 秒")
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@ -158,8 +169,9 @@ async def file_uploaded(params_kw):
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debug(f"抽取到 {len(unique_triples)} 个三元组，调用 Neo4j 服务插入")
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start_neo4j = time.time()
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if unique_triples:
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neo4j_result = await api_service.neo4j_insert_triples(unique_triples, id, fiid, orgid)
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for i in range(0, len(unique_triples), 30): # 每次插入 30 个三元组
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batch_triples = unique_triples[i:i + 30]
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neo4j_result = await api_service.neo4j_insert_triples(batch_triples, id, fiid, orgid)
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debug(f"Neo4j 服务响应: {neo4j_result}")
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if neo4j_result.get("status") != "success":
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timings["insert_neo4j"] = time.time() - start_neo4j
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@ -194,7 +206,6 @@ async def file_uploaded(params_kw):
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async def file_deleted(params_kw):
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"""删除用户指定文件数据，包括 Milvus 和 Neo4j 中的记录"""
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api_service = APIService()
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id = params_kw.get('id', '')
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realpath = params_kw.get('realpath', '')
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fiid = params_kw.get('fiid', '')
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@ -246,6 +257,72 @@ async def file_deleted(params_kw):
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"status_code": 400
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}
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async def _search_query(query: str, userid: str, knowledge_base_ids: List[str], limit: int = 5,
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offset: int = 0, use_rerank: bool = True, db_type: str = "") -> Dict[str, Any]:
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"""纯向量搜索，调用服务化端点"""
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start_time = time.time()
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collection_name = "ragdb" if not db_type else f"ragdb_{db_type}"
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timing_stats = {}
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try:
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info(
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f"开始纯向量搜索: query={query}, userid={userid}, db_type={db_type}, knowledge_base_ids={knowledge_base_ids}, limit={limit}, offset={offset}, use_rerank={use_rerank}")
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if not query:
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raise ValueError("查询文本不能为空")
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if not userid:
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raise ValueError("userid 不能为空")
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if limit <= 0 or limit > 16384:
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raise ValueError("limit 必须在 1 到 16384 之间")
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if offset < 0:
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raise ValueError("offset 不能为负数")
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if limit + offset > 16384:
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raise ValueError("limit + offset 不能超过 16384")
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if not knowledge_base_ids:
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raise ValueError("knowledge_base_ids 不能为空")
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for kb_id in knowledge_base_ids:
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if not isinstance(kb_id, str):
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raise ValueError(f"knowledge_base_id 必须是字符串: {kb_id}")
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if len(kb_id) > 100:
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raise ValueError(f"knowledge_base_id 长度超出 100 个字符: {kb_id}")
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# 将查询文本转换为向量
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vector_start = time.time()
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query_vector = await api_service.get_embeddings([query])
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if not query_vector or not all(len(vec) == 1024 for vec in query_vector):
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raise ValueError("查询向量必须是长度为 1024 的浮点数列表")
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query_vector = query_vector[0] # 取第一个向量
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timing_stats["vector_generation"] = time.time() - vector_start
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debug(f"生成查询向量耗时: {timing_stats['vector_generation']:.3f} 秒")
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# 调用纯向量搜索端点
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search_start = time.time()
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result = await api_service.milvus_search_query(query_vector, userid, knowledge_base_ids, limit, offset)
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timing_stats["vector_search"] = time.time() - search_start
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debug(f"向量搜索耗时: {timing_stats['vector_search']:.3f} 秒")
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if result.get("status") != "success":
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error(f"纯向量搜索失败: {result.get('message', '未知错误')}")
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return {"results": [], "timing": timing_stats}
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unique_results = result.get("results", [])
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if use_rerank and unique_results:
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rerank_start = time.time()
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debug("开始重排序")
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unique_results = await api_service.rerank_results(query, unique_results, limit)
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unique_results = sorted(unique_results, key=lambda x: x.get('rerank_score', 0), reverse=True)
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timing_stats["reranking"] = time.time() - rerank_start
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debug(f"重排序耗时: {timing_stats['reranking']:.3f} 秒")
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debug(f"重排序分数分布: {[round(r.get('rerank_score', 0), 3) for r in unique_results]}")
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else:
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unique_results = [{k: v for k, v in r.items() if k != 'rerank_score'} for r in unique_results]
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timing_stats["total_time"] = time.time() - start_time
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info(f"纯向量搜索完成，返回 {len(unique_results)} 条结果，总耗时: {timing_stats['total_time']:.3f} 秒")
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return {"results": unique_results[:limit], "timing": timing_stats}
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except Exception as e:
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error(f"纯向量搜索失败: {str(e)}, 堆栈: {traceback.format_exc()}")
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return {"results": [], "timing": timing_stats}
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async def main():
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dbs = {
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@ -286,6 +363,18 @@ async def main():
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# delete_result = await file_deleted(test_params_delete)
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# print(f"file_deleted 结果: {delete_result}")
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# # 测试 _search_query
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# print("测试 _search_query...")
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# test_params_query = {
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# "query": "什么是关系抽取",
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# "userid": "04J6VbxLqB_9RPMcgOv_8",
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# "knowledge_base_ids": ["1"],
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# "limit": 5,
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# "offset": 0,
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# "use_rerank": True
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# }
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# query_result = await _search_query(query="什么是知识融合？", userid="testuser1", knowledge_base_ids=["kb1", "kb2"], limit=5, offset=0, use_rerank=True, db_type="")
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# print(f"file_uploaded 结果: {query_result}")
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if __name__ == "__main__":
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asyncio.run(main())
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@ -184,6 +184,7 @@ where a.orgid = b.orgid
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debug(f"加载文件: {realpath}")
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start_load = time.time()
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text = fileloader(realpath)
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# debug(f"处理后的文件内容是：{text=}")
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text = re.sub(r'[^\u4e00-\u9fa5a-zA-Z0-9\s.;,\n]', '', text)
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timings["load_file"] = time.time() - start_load
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debug(f"加载文件耗时: {timings['load_file']:.2f} 秒, 文本长度: {len(text)}")
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@ -249,7 +250,7 @@ where a.orgid = b.orgid
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chunks=batch_chunks,
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db_type=db_type,
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upappid=service_params['vdb'],
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apiname="milvus/insertdocument", # 固定 apiname
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apiname="milvus/insertdocument",
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user=userid
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)
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if result.get("status") != "success":
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@ -264,6 +265,7 @@ where a.orgid = b.orgid
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debug("调用三元组抽取服务")
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start_triples = time.time()
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unique_triples = []
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try:
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chunk_texts = [doc.page_content for doc in chunks]
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debug(f"处理 {len(chunk_texts)} 个分片进行三元组抽取")
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@ -272,7 +274,7 @@ where a.orgid = b.orgid
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request=request,
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text=chunk,
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upappid=service_params['triples'],
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apiname="Babelscape/mrebel-large", # 固定 apiname
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apiname="Babelscape/mrebel-large",
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user=userid
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) for chunk in chunk_texts
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]
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@ -285,7 +287,6 @@ where a.orgid = b.orgid
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else:
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error(f"分片 {i + 1} 处理失败: {str(result)}")
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unique_triples = []
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seen = set()
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for t in triples:
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identifier = (t['head'].lower(), t['tail'].lower(), t['type'].lower())
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@ -306,6 +307,7 @@ where a.orgid = b.orgid
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debug(
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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]}")
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if unique_triples:
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debug(f"抽取到 {len(unique_triples)} 个三元组，调用 Neo4j 服务插入")
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start_neo4j = time.time()
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for i in range(0, len(unique_triples), 30): # 每次插入 30 个三元组
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@ -317,47 +319,69 @@ where a.orgid = b.orgid
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knowledge_base_id=fiid,
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userid=orgid,
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upappid=service_params['gdb'],
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apiname="neo4j/inserttriples", # 固定 apiname
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apiname="neo4j/inserttriples",
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user=userid
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)
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debug(f"Neo4j 服务响应: {neo4j_result}")
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if neo4j_result.get("status") != "success":
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timings["insert_neo4j"] = time.time() - start_neo4j
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timings["total"] = time.time() - start_total
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return {"status": "error", "document_id": id, "collection_name": "ragdb",
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return {
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"status": "error",
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"document_id": id,
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"collection_name": "ragdb",
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"timings": timings,
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"message": f"Neo4j 三元组插入失败: {neo4j_result.get('message', '未知错误')}",
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"status_code": 400}
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"status_code": 400
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}
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info(f"文件 {realpath} 三元组成功插入 Neo4j: {neo4j_result.get('message')}")
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else:
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debug(f"文件 {realpath} 未抽取到三元组")
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timings["insert_neo4j"] = time.time() - start_neo4j
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debug(f"Neo4j 插入耗时: {timings['insert_neo4j']:.2f} 秒")
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else:
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debug(f"文件 {realpath} 未抽取到三元组")
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timings["insert_neo4j"] = 0.0
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except Exception as e:
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timings["extract_triples"] = time.time() - start_triples if "extract_triples" not in timings else \
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timings[
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"extract_triples"]
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timings["insert_neo4j"] = time.time() - start_neo4j
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timings["extract_triples"]
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timings["insert_neo4j"] = time.time() - start_neo4j if "insert_neo4j" not in timings else timings[
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"insert_neo4j"]
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debug(f"处理三元组或 Neo4j 插入失败: {str(e)}, 堆栈: {traceback.format_exc()}")
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timings["total"] = time.time() - start_total
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return {"status": "success", "document_id": id, "collection_name": "ragdb", "timings": timings,
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return {
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"status": "success",
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"document_id": id,
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"collection_name": "ragdb",
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"timings": timings,
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"unique_triples": unique_triples,
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"message": f"文件 {realpath} 成功嵌入，但三元组处理或 Neo4j 插入失败: {str(e)}",
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"status_code": 200}
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"status_code": 200
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}
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timings["total"] = time.time() - start_total
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debug(f"总耗时: {timings['total']:.2f} 秒")
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return {"status": "success", "userid": orgid, "document_id": id, "collection_name": "ragdb",
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return {
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"status": "success",
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"userid": orgid,
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"document_id": id,
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"collection_name": "ragdb",
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"timings": timings,
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"unique_triples": unique_triples, "message": f"文件 {realpath} 成功嵌入并处理三元组",
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"status_code": 200}
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"unique_triples": unique_triples,
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"message": f"文件 {realpath} 成功嵌入并处理三元组",
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"status_code": 200
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}
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except Exception as e:
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error(f"插入文档失败: {str(e)}, 堆栈: {traceback.format_exc()}")
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timings["total"] = time.time() - start_total
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return {"status": "error", "document_id": id, "collection_name": "ragdb", "timings": timings,
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"message": f"插入文档失败: {str(e)}", "status_code": 400}
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return {
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"status": "error",
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"document_id": id,
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"collection_name": "ragdb",
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"timings": timings,
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"message": f"插入文档失败: {str(e)}",
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"status_code": 400
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}
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async def file_deleted(self, request, recs, userid):
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"""删除用户指定文件数据，包括 Milvus 和 Neo4j 中的记录"""
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@ -25,7 +25,7 @@
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}
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},
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{
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"widgettype":"text",
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"widgettype":"Text",
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"options":{
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"otext":"{{p.description}}",
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"i18n":true,
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@ -37,18 +37,18 @@
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{
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"widgettype":"HBox",
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"options":{
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"height":1.5
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"cheight":1.5
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},
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"subwidgets":[
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{
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"widgettype":"text",
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"widgettype":"Text",
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"options":{
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"otext":"可用磁盘容量",
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"i18n":true
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}
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},
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{
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"widgettype":"text",
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"widgettype":"Text",
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"options":{
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"text":"{{p.quota / 1000000}}M"
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}
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@ -58,18 +58,18 @@
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{
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||||
"widgettype":"HBox",
|
||||
"options":{
|
||||
"height":1.5
|
||||
"cheight":1.5
|
||||
},
|
||||
"subwidgets":[
|
||||
{
|
||||
"widgettype":"text",
|
||||
"widgettype":"Text",
|
||||
"options":{
|
||||
"otext":"时长（月)",
|
||||
"i18n":true
|
||||
}
|
||||
},
|
||||
{
|
||||
"widgettype":"text",
|
||||
"widgettype":"Text",
|
||||
"options":{
|
||||
"text":"{{p.term}}"
|
||||
}
|
||||
@ -79,18 +79,18 @@
|
||||
{
|
||||
"widgettype":"HBox",
|
||||
"options":{
|
||||
"height":1.5
|
||||
"cheight":1.5
|
||||
},
|
||||
"subwidgets":[
|
||||
{
|
||||
"widgettype":"text",
|
||||
"widgettype":"Text",
|
||||
"options":{
|
||||
"otext":"价格",
|
||||
"i18n":true
|
||||
}
|
||||
},
|
||||
{
|
||||
"widgettype":"text",
|
||||
"widgettype":"Text",
|
||||
"options":{
|
||||
"color":"red",
|
||||
"text":"{{p.price}}圆"
|
||||
@ -112,7 +112,7 @@
|
||||
},
|
||||
"options":{
|
||||
"params":{
|
||||
"selected_program":"p.id"
|
||||
"selected_program":"{{p.id}}"
|
||||
},
|
||||
"url":"{{entire_url('./program_selected.dspy')}}"
|
||||
}
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user