简历诊断添加日志

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()
 
 

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}