全部切换成 deepseek V4 flash

app/ai/model_config.py

@@ -9,52 +9,52 @@ from app.ai.models import LLM
 class SkillGapModel:
     """技能差距分析模块"""
     # 技能差距识别：对比简历与岗位技能标签，输出缺失技能列表
-    ANALYSIS   = LLM.DOUBAO_LITE_32K.create(temperature=0)
+    ANALYSIS   = LLM.DEEPSEEK_V4_FLASH.create(temperature=0)
     # 个人概述优化：将缺失技能关键词融入 summary
-    SUMMARY    = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
+    SUMMARY    = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)
     # 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)
+    EXPERIENCE = LLM.DEEPSEEK_V4_FLASH.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.DOUBAO_LITE_32K.create(temperature=0)
+    AGENT_PLAN = LLM.DEEPSEEK_V4_FLASH.create(temperature=0)
     # Agent执行-修改：按指令修改简历中的单条记录
-    AGENT_EDIT = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
+    AGENT_EDIT = LLM.DEEPSEEK_V4_FLASH.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.DOUBAO_LITE_32K.create(temperature=0.3)
+    AGENT_ADD  = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)
 
 
 class JobAgentModel:
     """求职助手Agent模块"""
     # 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)
+    CHAT       = LLM.DEEPSEEK_V4_FLASH.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.DOUBAO_LITE_32K.create(temperature=0.3)
+    SUMMARY    = LLM.DEEPSEEK_V4_FLASH.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.DOUBAO_LITE_32K.create(temperature=0.3)
+    EXPERIENCE = LLM.DEEPSEEK_V4_FLASH.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.DOUBAO_LITE_32K.create(temperature=0.7)
+    CHAT = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.7)
 
 
 class ResumeExtractorModel:
     """简历解析模块"""
     # 简历结构化提取：两阶段并行提取简历文本为JSON结构
-    PARSE = LLM.DOUBAO_LITE_32K.create(temperature=0)
+    PARSE = LLM.DEEPSEEK_V4_FLASH.create(temperature=0)
 
 
 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.DOUBAO_LITE_32K.create(temperature=0)
+    MODULE  = LLM.DEEPSEEK_V4_FLASH.create(temperature=0)
     # 整体评价：汇总所有诊断结果生成总结性评语
-    SUMMARY = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
+    SUMMARY = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)
     # 内容润色：用户编辑后的文本做专业润色
-    POLISH  = LLM.DOUBAO_LITE_32K.create(temperature=0.3)
+    POLISH  = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)
 
 
 class BrowserPlugModel:
     """浏览器插件模块"""
     # 表单自动填写：根据简历+岗位信息生成招聘网站表单字段的回答
-    FORM_FILL = LLM.DOUBAO_PRO_32K.create(temperature=0.3)
+    FORM_FILL = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)

app/ai/models.py

@@ -28,8 +28,10 @@ class LLM(Enum):
 
     DOUBAO_PRO_32K = ("doubao-1-5-pro-32k-250115", *_VOLCENGINE)
     DOUBAO_LITE_32K = ("doubao-1-5-lite-32k-250115", *_VOLCENGINE)
-    DEEPSEEK_V3 = ("deepseek-v3-250324", *_VOLCENGINE)
-    DEEPSEEK_R1 = ("deepseek-r1-250528", *_VOLCENGINE)
+
+    DEEPSEEK_V4_FLASH = ("deepseek-v4-flash-260425", *_VOLCENGINE)
+    DEEPSEEK_V4_PRO = ("deepseek-v4-pro-260425", *_VOLCENGINE)
+
     DOUBAO_SEED_MINI = ("doubao-seed-2-0-mini-260215", *_VOLCENGINE)
     DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", *_VOLCENGINE)
     DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", *_VOLCENGINE)