From a8f7b1aabb6be3ff1dba03ca9ef1715029e46011 Mon Sep 17 00:00:00 2001 From: zk Date: Tue, 26 May 2026 15:48:26 +0800 Subject: [PATCH] =?UTF-8?q?=E7=AE=80=E5=8E=86=E8=AF=8A=E6=96=AD=E6=B7=BB?= =?UTF-8?q?=E5=8A=A0=E6=97=A5=E5=BF=97?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- app/ai/resume_diagnoser/diagnoser.py | 9 ++++++++- app/api/resume_diagnose.py | 13 +++++++++++++ 2 files changed, 21 insertions(+), 1 deletion(-) diff --git a/app/ai/resume_diagnoser/diagnoser.py b/app/ai/resume_diagnoser/diagnoser.py index 8b8c999..fb50d60 100644 --- a/app/ai/resume_diagnoser/diagnoser.py +++ b/app/ai/resume_diagnoser/diagnoser.py @@ -1,6 +1,7 @@ """简历诊断 AI 引擎：并行诊断 + 汇总评价""" import asyncio +import time from langchain_core.output_parsers import StrOutputParser from langchain_core.prompts import ChatPromptTemplate @@ -94,12 +95,18 @@ async def polish_content(module_type: str, reference_content: list[dict] | str | async def _safe_invoke(task: dict) -> dict: """单条记录诊断，失败返回空结果""" + module_type = task.get("module_type", "unknown") + log.info(f"AI诊断[{module_type}]开始") + start = time.time() raw = "" try: raw = await _diagnose_chain.ainvoke(task) + elapsed = time.time() - start + log.info(f"AI诊断[{module_type}]完成, 耗时{elapsed:.2f}s") return parse_llm_json(raw) except Exception as e: - log.warning(f"AI诊断[{task.get('module_type', '')}]失败: {e}\n原始输出: {raw[:500]}") + elapsed = time.time() - start + log.warning(f"AI诊断[{module_type}]失败, 耗时{elapsed:.2f}s: {e}\n原始输出: {raw[:500]}") return _empty_result() diff --git a/app/api/resume_diagnose.py b/app/api/resume_diagnose.py index 6dc04d7..bae2aad 100644 --- a/app/api/resume_diagnose.py +++ b/app/api/resume_diagnose.py @@ -1,5 +1,7 @@ """简历诊断接口""" +import time + from fastapi import APIRouter, Depends from pydantic import BaseModel, Field @@ -7,6 +9,7 @@ from app.ai.resume_diagnoser.diagnoser import diagnose_all, generate_summary, po from app.core.auth import func_permission from app.core.context import RequestContext from app.core.database import get_db +from app.core.logger import log from app.services.resume_diagnose_service import ResumeDiagnoseService, aggregate_results router = APIRouter(prefix="/resume/diagnose", tags=["简历诊断"]) @@ -20,6 +23,7 @@ class DiagnoseParam(BaseModel): async def diagnose_resume(param: DiagnoseParam, _: None = Depends(func_permission("resume_diag"))): """触发简历AI诊断，返回报告ID""" user_id = RequestContext.user_id.get() + log.info(f"简历诊断开始, resumeId={param.resume_id}, userId={user_id}") # 1. 短事务：加载简历数据 async for session in get_db(): @@ -27,21 +31,29 @@ async def diagnose_resume(param: DiagnoseParam, _: None = Depends(func_permissio resume, tasks = await service.load_resume_data(param.resume_id, user_id) if not tasks: + log.warning(f"简历无可诊断内容, resumeId={param.resume_id}") raise ValueError("简历没有可诊断的描述内容") + log.info(f"加载简历数据完成, 待诊断任务数={len(tasks)}") + # 2. 并行 AI 诊断（不持有数据库连接） ai_tasks = [{k: v for k, v in t.items() if not k.startswith("_")} for t in tasks] + t0 = time.time() ai_results = await diagnose_all(ai_tasks) + log.info(f"AI诊断全部完成, 耗时{time.time() - t0:.2f}s") # 3. 统计 + 评级（纯计算） stats = aggregate_results(tasks, ai_results) + log.info(f"统计完成, grade={stats['grade']}, urgent={stats['urgent_total']}, important={stats['important_total']}, expression={stats['expression_total']}") # 4. AI 生成整体评价（不持有数据库连接） + t1 = time.time() summary = await generate_summary( grade=stats["grade"], urgent_total=stats["urgent_total"], important_total=stats["important_total"], expression_total=stats["expression_total"], target_position=resume.target_position or "", all_findings=stats["all_findings"], ) + log.info(f"AI生成整体评价完成, 耗时{time.time() - t1:.2f}s") # 5. 短事务：纯写入 async for session in get_db(): @@ -52,6 +64,7 @@ async def diagnose_resume(param: DiagnoseParam, _: None = Depends(func_permissio tasks, ai_results, ) + log.info(f"简历诊断完成, reportId={report_id}") return {"reportId": report_id}