统一抽象 封装 模型配置配置管理

app/ai/job_agent/chat.py

@@ -5,7 +5,7 @@
 """
 
 from app.ai.job_agent.prompts import SYSTEM_PROMPT
-from app.ai.models import LLM
+from app.ai.model_config import JobAgentModel
 from app.core.logger import log
 from app.tool.json_helper import parse_llm_json
 
@@ -32,8 +32,7 @@ async def agent_chat(resume_text: str, message: str, history: list[dict],
 
     # 3. 调 LLM
     try:
-        llm = LLM.ZM_GPT_5_4.create(temperature=0.7)
-        result = await llm.ainvoke(messages)
+        result = await JobAgentModel.CHAT.ainvoke(messages)
         raw = result.content
     except Exception as e:
         log.error(f"求职助手AI调用失败: {e}")

app/ai/job_agent/resume_optimizer.py

@@ -10,7 +10,7 @@ from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate
 
 from app.ai.job_agent.prompts import RESUME_SUMMARY_OPTIMIZE_PROMPT, RESUME_EXPERIENCE_OPTIMIZE_PROMPT
-from app.ai.models import LLM
+from app.ai.model_config import JobAgentModel
 from app.core.logger import log
 from app.tool.json_helper import parse_llm_json
 
@@ -18,7 +18,7 @@ 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.ZM_GPT_5_4_MINI.create(temperature=0.3)
+    | JobAgentModel.SUMMARY
     | StrOutputParser()
 )
 
@@ -42,7 +42,7 @@ 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.ZM_GPT_5_4_MINI.create(temperature=0.3)
+    | JobAgentModel.EXPERIENCE
     | StrOutputParser()
 )