From 7ecafd2fbf6c51f4bd030c03075e35c962260050 Mon Sep 17 00:00:00 2001 From: "qinyong@9artedu.com" Date: Tue, 23 Jun 2026 17:21:48 +0800 Subject: [PATCH] update --- app/chat_qa_query/api/router/query_router.py | 2 ++ app/chat_qa_query/query_graph.py | 2 +- app/chat_qa_query/query_nodes/node_rewrite.py | 5 ++++- .../query_nodes/node_search_embedding.py | 2 +- app/repository/milvus/message_qa_repository.py | 13 ++++++++----- readme | 5 +++++ 6 files changed, 21 insertions(+), 8 deletions(-) create mode 100644 readme diff --git a/app/chat_qa_query/api/router/query_router.py b/app/chat_qa_query/api/router/query_router.py index 448f8f6..f191aed 100644 --- a/app/chat_qa_query/api/router/query_router.py +++ b/app/chat_qa_query/api/router/query_router.py @@ -7,11 +7,13 @@ from watchfiles import awatch from app.chat_qa_query.api.qa_dependencies import get_qa_query_service from app.chat_qa_query.api.schema.query_qa_schema import QueryQASchema from app.chat_qa_query.service.query_qa_service import QueryQAService +from app.core.log import logger query_qa_router = APIRouter() @query_qa_router.post("/api/qa/query") async def query_handler(query: QueryQASchema, query_service: Annotated[QueryQAService, Depends(get_qa_query_service)]): + logger.info(f"请求参数:{query.external_str},历史top15:{query.messages_top15}") return await query_service.query(query.external_str, query.messages_top15) diff --git a/app/chat_qa_query/query_graph.py b/app/chat_qa_query/query_graph.py index 44f2fa2..f974cc3 100644 --- a/app/chat_qa_query/query_graph.py +++ b/app/chat_qa_query/query_graph.py @@ -45,7 +45,7 @@ if __name__ == '__main__': archive_messages_mysql_repository = ArchiveMessagesRepository(db_session) qa_milvus_repository = QARepository() - state: QueryQAState = QueryQAState(original_query="培训的费用？") + state: QueryQAState = QueryQAState(original_query="暂时有点忙", history=['2026-05-26T13:14:59 EXTERNAL 暂时有点忙\n', '2026-05-26T12:48:09 INTERNAL 下午好呀 你这边怎么计划的呀 考虑跟咱们6月1号的班级学习嘛\n']) context = QueryQAContext(meta_mysql_repository=archive_messages_mysql_repository, qa_milvus_repository=qa_milvus_repository ) diff --git a/app/chat_qa_query/query_nodes/node_rewrite.py b/app/chat_qa_query/query_nodes/node_rewrite.py index 349136b..d4b463d 100644 --- a/app/chat_qa_query/query_nodes/node_rewrite.py +++ b/app/chat_qa_query/query_nodes/node_rewrite.py @@ -28,7 +28,6 @@ problem_rewriting_prompt = """ 4. **输出格式**： - 仅输出JSON，不要任何解释性文字 - - rewritten_query 必须是一个完整的疑问句（以"是什么"、"有哪些"、"怎么样"、"如何"等结尾，或以问号结尾） ## 改写示例 @@ -76,6 +75,9 @@ problem_rewriting_prompt = """ 历史会话： {history_text} +历史会话字段说明： +EXTERNAL：客户 +INTERNAL：销售 当前问题：{query} 请直接输出JSON： @@ -90,6 +92,7 @@ async def rewrite_query(state:QueryQAState): """ history_text = state.get("history", "") query = state.get("original_query", "") + logger.info(f"问题改写：{query},历史会话：{history_text}") prompt = PromptTemplate(template=problem_rewriting_prompt, input_variables=["history_text", "query"]) output = JsonOutputParser() chain = prompt | llm | output diff --git a/app/chat_qa_query/query_nodes/node_search_embedding.py b/app/chat_qa_query/query_nodes/node_search_embedding.py index 9889f19..88a2493 100644 --- a/app/chat_qa_query/query_nodes/node_search_embedding.py +++ b/app/chat_qa_query/query_nodes/node_search_embedding.py @@ -15,7 +15,7 @@ async def search_embed(state:QueryQAState) : batch_embeddings = await embedding_client.aembed_query(rewritten_query) qa_repository = QARepository() - result = await qa_repository.search_qa(query_text=batch_embeddings, top_k=3) + result = await qa_repository.search_qa(query_vector=batch_embeddings, top_k=3) logger.info(f"原始问题:{original_query},改写后的问题：{rewritten_query},匹配结果：{result}") if result: question = result[0]["question"] diff --git a/app/repository/milvus/message_qa_repository.py b/app/repository/milvus/message_qa_repository.py index ed6ecf8..8195f98 100644 --- a/app/repository/milvus/message_qa_repository.py +++ b/app/repository/milvus/message_qa_repository.py @@ -100,12 +100,12 @@ class QARepository: logger.error(f"QA数据入库失败: {str(e)}", exc_info=True) return [] - async def search_qa(self, query_text: List[float], top_k: int = 5) -> List[Dict[str, Any]]: + async def search_qa(self, query_vector: List[float], top_k: int = 5) -> List[Dict[str, Any]]: """ 根据查询文本搜索QA数据 Args: - query_text: 查询文本 + query_vector: 查询向量 top_k: 返回结果数量 Returns: @@ -114,13 +114,16 @@ class QARepository: res = milvus_client.client.search( collection_name=self.collection_name, anns_field="question_dense_vector", - data=[query_text], + data=[query_vector], limit=top_k, - search_params={"metric_type": "COSINE"}, + search_params={ + "metric_type": "COSINE", + "efSearch": 300 # 你配置 efSearch=200：检索时最多遍历 200 个候选节点，再从中选出相似度最高的结果。 + }, output_fields=["question", "answer", "created_at"] ) - score_threshold = 0.6 + score_threshold = 0.60 filter_results = [] # res 是二维结构：[ [单条结果列表] ] diff --git a/readme b/readme new file mode 100644 index 0000000..887019e --- /dev/null +++ b/readme @@ -0,0 +1,5 @@ + 启动：nohup uvicorn app.uvicorn_main:app --host 0.0.0.0 --port 8000 --workers 4 > uvicorn.log 2>&1 & + 打包：py package.py + 同步库+虚拟环境：uv sync + +