优化 agent 定制简历生成速度

app/ai/job_agent/resume_optimizer.py

@@ -1,9 +1,11 @@
 """求职助手 - 岗位简历优化 AI 引擎
 
-针对目标岗位并发优化简历（summary + 经历子表）。
+针对目标岗位并发优化简历（summary + 经历子表，按单条记录粒度并发）。
 依赖：LLM 枚举、job_agent/prompts、parse_llm_json
 """
 
+import time
+
 from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate
 
@@ -16,40 +18,46 @@ from app.tool.json_helper import parse_llm_json
 
 _summary_chain = (
     ChatPromptTemplate.from_messages([("system", RESUME_SUMMARY_OPTIMIZE_PROMPT), ("human", "请开始优化。")])
-    | LLM.ZM_GPT_5_4.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
     | StrOutputParser()
 )
 
 
 async def optimize_summary(job_title: str, job_description: str, original_summary: str) -> str:
     """针对岗位优化个人概述"""
+    t0 = time.monotonic()
     try:
-        return await _summary_chain.ainvoke({
+        result = await _summary_chain.ainvoke({
             "job_title": job_title, "job_description": job_description or "",
             "original_summary": original_summary or "暂无",
         })
+        log.info(f"岗位简历summary优化完成 ({round(time.monotonic() - t0, 2)}s)")
+        return result
     except Exception as e:
-        log.warning(f"岗位简历summary优化失败: {e}")
+        log.warning(f"岗位简历summary优化失败: {e} ({round(time.monotonic() - t0, 2)}s)")
         return original_summary
 
 
-# ===== 经历优化 =====
+# ===== 单条经历优化 =====
 
 _experience_chain = (
     ChatPromptTemplate.from_messages([("system", RESUME_EXPERIENCE_OPTIMIZE_PROMPT), ("human", "请开始优化。")])
-    | LLM.ZM_GPT_5_4.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
     | StrOutputParser()
 )
 
 
-async def optimize_experience(job_title: str, job_description: str, module_data: str) -> list | dict | None:
-    """针对岗位优化经历模块描述，返回修改后的完整模块数据"""
+async def optimize_experience_record(job_title: str, job_description: str, record_json: str) -> dict | None:
+    """针对岗位优化单条经历记录，返回修改后的记录数据"""
+    t0 = time.monotonic()
     try:
         raw = await _experience_chain.ainvoke({
             "job_title": job_title, "job_description": job_description or "",
-            "original_module_data": module_data,
+            "original_module_data": record_json,
         })
-        return parse_llm_json(raw)
+        result = parse_llm_json(raw)
+        log.info(f"岗位简历经历记录优化完成 ({round(time.monotonic() - t0, 2)}s)")
+        return result
     except Exception as e:
-        log.warning(f"岗位简历经历优化失败: {e}")
+        log.warning(f"岗位简历经历记录优化失败: {e} ({round(time.monotonic() - t0, 2)}s)")
         return None