简历提取 插值分析 依然使用 pro32

app/ai/model_config.py

@@ -9,9 +9,9 @@ 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.DEEPSEEK_V4_FLASH.create(temperature=0)
+    ANALYSIS = LLM.DOUBAO_PRO_32K.create(temperature=0)
     # 个人概述优化：将缺失技能关键词融入 summary
-    SUMMARY    = LLM.DEEPSEEK_V4_FLASH.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.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
@@ -19,15 +19,15 @@ class SkillGapModel:
     # Agent执行-修改：按指令修改简历中的单条记录
     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.DEEPSEEK_V4_FLASH.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.DEEPSEEK_V4_FLASH.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.DEEPSEEK_V4_FLASH.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.DEEPSEEK_V4_FLASH.create(temperature=0.3)
 
@@ -41,17 +41,17 @@ class NovaChatModel:
 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.DEEPSEEK_V4_FLASH.create(temperature=0)
+    PARSE = LLM.DOUBAO_PRO_32K.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.DEEPSEEK_V4_FLASH.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.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.DEEPSEEK_V4_FLASH.create(temperature=0.3)
+    POLISH = LLM.DEEPSEEK_V4_FLASH.create(temperature=0.3)
 
 
 class BrowserPlugModel:

app/ai/models.py

@@ -15,9 +15,6 @@ from app.config import settings
 
 # 供应商连接配置
 _VOLCENGINE = (lambda: settings.volcengine_api_key, lambda: settings.volcengine_base_url)
-_JIAYU = (lambda: settings.jiayu_api_key, lambda: settings.jiayu_base_url)
-_JIEKOU = (lambda: settings.jiekou_api_key, lambda: settings.jiekou_base_url)
-
 _ZM = (lambda: settings.zm_api_key, lambda: settings.zm_base_url)
 
 
@@ -36,19 +33,6 @@ class LLM(Enum):
     DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", *_VOLCENGINE)
     DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", *_VOLCENGINE)
 
-    # jiekou
-    GPT_4O = ("gpt-4o", *_JIAYU)
-    GPT_4O_MINI = ("gpt-4o-mini", *_JIEKOU)
-    GEMINI_FLASH = ("gemini-2.5-flash", *_JIEKOU)
-
-    # 加鱼
-    JIAYU_CLAUDE_SONNET_4_5 = ("claude-sonnet-4.5", *_JIAYU)
-    JIAYU_CLAUDE_HAIKU_4_5 = ("claude-haiku-4.5", *_JIAYU)
-    JIAYU_DEEPSEEK_3_2 = ("deepseek-3.2", *_JIAYU)
-    JIAYU_GLM_5 = ("glm-5", *_JIAYU)
-    JIAYU_QWEN3_CODER_NEXT = ("qwen3-coder-next", *_JIAYU)
-    JIAYU_MINIMAX_M2_5 = ("minimax-m2.5", *_JIAYU)
-
 
     # ZM
     ZM_GPT_5_5 = ("gpt-5.5", *_ZM)

app/config/settings.py

@@ -38,21 +38,10 @@ class Settings(BaseSettings):
     volcengine_api_key: str = "fd065993-bee2-4f31-8bf2-56d5d3012c02"
     volcengine_base_url: str = "https://ark.cn-beijing.volces.com/api/v3"
 
-    # jiekou
-    jiekou_api_key: str = "sk_4BXi4_yvwx-NW4_zuVt2LufrrlGyhs2q9qMN5Vq_j7Q"
-    jiekou_base_url: str = "https://api.jiekou.ai/openai"
-
-    # jiayu
-    jiayu_api_key: str = "Aa123123"
-    jiayu_base_url: str = "http://192.168.31.133:8800/v1"
-
     #zm
     zm_api_key: str = "3-chatgpt-is-free-free-free"
     zm_base_url: str = "http://re.94xy.cn/v1"
 
-
-
-
     # JWT
     jwt_secret: str = "Aa123123"
     token_expire_seconds: int = 5184000