模型全面切换值 ZM 模型

app/ai/job_agent/chat.py

@@ -32,7 +32,7 @@ async def agent_chat(resume_text: str, message: str, history: list[dict],
 
     # 3. 调 LLM
     try:
-        llm = LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.7)
+        llm = LLM.ZM_GPT_5_4.create(temperature=0.7)
         result = await llm.ainvoke(messages)
         raw = result.content
     except Exception as e:

app/ai/job_agent/resume_optimizer.py

@@ -16,7 +16,7 @@ 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.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4.create(temperature=0.3)
     | StrOutputParser()
 )
 
@@ -37,7 +37,7 @@ async def optimize_summary(job_title: str, job_description: str, original_summar
 
 _experience_chain = (
     ChatPromptTemplate.from_messages([("system", RESUME_EXPERIENCE_OPTIMIZE_PROMPT), ("human", "请开始优化。")])
-    | LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4.create(temperature=0.3)
     | StrOutputParser()
 )
 

app/ai/models.py

@@ -53,7 +53,6 @@ class LLM(Enum):
     ZM_GPT_5_4 = ("gpt-5.4", *_ZM)
     ZM_GPT_5_4_MINI = ("gpt-5.4-mini", *_ZM)
     ZM_GPT_5_2 = ("gpt-5.2", *_ZM)
-    ZM_GPT_4O = ("gpt-5.5", *_ZM)
 
 
 

app/ai/nova_chat/chat.py

@@ -24,7 +24,7 @@ async def nova_chat(resume_text: str, message: str, history: list[dict],
     messages.append(("human", message))
 
     try:
-        llm = LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.7)
+        llm = LLM.ZM_GPT_5_2.create(temperature=0.7)
         result = await llm.ainvoke(messages)
         return result.content.strip()
     except Exception as e:

app/ai/resume_diagnoser/diagnoser.py

@@ -14,14 +14,14 @@ from app.tool.json_helper import parse_llm_json
 # 诊断链（StrOutputParser 拿原始文本，再手动解析 JSON，避免 markdown 代码块导致解析失败）
 _diagnose_chain = (
     ChatPromptTemplate.from_messages([("system", DIAGNOSE_MODULE_PROMPT), ("human", "请开始诊断。")])
-    | LLM.ZM_GPT_5_5.create(temperature=0)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0)
     | StrOutputParser()
 )
 
 # 汇总评价链（纯文本输出）
 _summary_chain = (
     ChatPromptTemplate.from_messages([("system", SUMMARY_PROMPT), ("human", "请生成整体评价。")])
-    | LLM.ZM_GPT_5_5.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
     | StrOutputParser()
 )
 

app/ai/resume_diagnoser/prompts.py

@@ -81,7 +81,7 @@ SUMMARY_PROMPT = """你是一位资深简历顾问。请根据以下简历诊断
 3. 主要问题（最需要改进的方面）
 4. 一句鼓励或行动建议
 
-直接输出评价文本，不要输出JSON或其他格式标记。控制在300字以内。"""
+直接输出评价文本，不要输出JSON或其他格式标记。控制在200字以内。"""
 
 POLISH_PROMPT = """你是一位资深简历顾问。请对用户提供的简历描述文本进行润色优化，让语言更精练、更专业。
 

app/ai/skill_gap_analyzer/analyzer.py

@@ -119,7 +119,7 @@ async def plan_edit(job_title: str, job_description: str, resume_json: str,
 
 _record_edit_chain = (
     ChatPromptTemplate.from_messages([("system", AGENT_MODULE_EDIT_PROMPT), ("human", "请执行修改。")])
-    | LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
     | StrOutputParser()
 )
 
@@ -144,7 +144,7 @@ async def execute_record_edit(job_title: str, job_description: str, instruction:
 
 _record_add_chain = (
     ChatPromptTemplate.from_messages([("system", AGENT_MODULE_ADD_PROMPT), ("human", "请生成新记录。")])
-    | LLM.JIAYU_CLAUDE_SONNET_4_5.create(temperature=0.3)
+    | LLM.ZM_GPT_5_4_MINI.create(temperature=0.3)
     | StrOutputParser()
 )
 

app/ai/skill_gap_analyzer/prompts.py

@@ -85,9 +85,9 @@ AGENT_PLAN_PROMPT = """你是一个简历编辑助手。你的唯一职责是根
 
 操作类型：
 1. 删除记录：{{"type": "delete", "module": "模块名", "id": "记录id"}}
-2. 修改记录：{{"type": "update", "module": "模块名", "id": "记录id", "instruction": "修改说明(50字内)"}}
-3. 修改主表：{{"type": "update", "module": "resume", "instruction": "修改说明(50字内)"}}
-4. 新增记录：{{"type": "add", "module": "模块名", "instruction": "新增说明(50字内)"}}
+2. 修改记录：{{"type": "update", "module": "模块名", "id": "记录id", "instruction": "修改说明(30字内)"}}
+3. 修改主表：{{"type": "update", "module": "resume", "instruction": "修改说明(30字内)"}}
+4. 新增记录：{{"type": "add", "module": "模块名", "instruction": "新增说明(30字内)"}}
 
 模块名可选：resume(主表，包含 name、email、mobileNumber、city、wechatNumber、portfolioUrl、skills、certificates、summary、avatarUrl)、education(教育)、work(工作)、internship(实习)、project(项目)、competition(竞赛)