大多数场景 暂时使用pro32

app/ai/model_config.py

@@ -15,11 +15,11 @@ class SkillGapModel:
     # 经历描述优化：针对目标岗位优化单条经历的 description
     EXPERIENCE = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
     # Agent规划：解析用户自然语言指令，拆解为原子编辑操作列表
-    AGENT_PLAN = LLM.ZM_GPT_5_4.create(temperature=0)
+    AGENT_PLAN = LLM.DOUBAO_LITE_32K.create(temperature=0)
     # Agent执行-修改：按指令修改简历中的单条记录
-    AGENT_EDIT = LLM.ZM_GPT_5_4.create(temperature=0.3)
+    AGENT_EDIT = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
     # Agent执行-新增：按指令生成一条新的简历记录
-    AGENT_ADD  = LLM.ZM_GPT_5_4.create(temperature=0.3)
+    AGENT_ADD  = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
 
 
 class JobAgentModel:
@@ -27,15 +27,15 @@ class JobAgentModel:
     # 多轮对话：理解用户求职意图，返回结构化回复(message+tool调用)
     CHAT       = LLM.ZM_GPT_5_4.create(temperature=0.7)
     # 岗位简历-summary优化：针对具体岗位JD优化个人概述
-    SUMMARY    = LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
+    SUMMARY    = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
     # 岗位简历-经历优化：针对具体岗位JD优化单条经历描述
-    EXPERIENCE = LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
+    EXPERIENCE = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
 
 
 class NovaChatModel:
     """Nova智能聊天模块"""
     # 通用对话：基于简历和岗位上下文的自由问答，返回Markdown文本
-    CHAT = LLM.ZM_GPT_5_2.create(temperature=0.7)
+    CHAT = LLM.DOUBAO_LITE_32K.create(temperature=0.7)
 
 
 class ResumeExtractorModel:
@@ -47,11 +47,11 @@ class ResumeExtractorModel:
 class DiagnoserModel:
     """简历诊断模块"""
     # 模块诊断：逐条分析经历记录的问题(错别字/无量化/弱相关等)
-    MODULE  = LLM.ZM_GPT_5_4_MINI.create(temperature=0)
+    MODULE  = LLM.DOUBAO_LITE_32K.create(temperature=0)
     # 整体评价：汇总所有诊断结果生成总结性评语
-    SUMMARY = LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
+    SUMMARY = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
     # 内容润色：用户编辑后的文本做专业润色
-    POLISH  = LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    POLISH  = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
 
 
 class BrowserPlugModel: