重构简历优化

app/ai/resume_diagnoser/diagnoser.py

@@ -7,7 +7,7 @@ from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompts import ChatPromptTemplate
 
 from app.ai.model_config import DiagnoserModel
-from app.ai.resume_diagnoser.prompts import DIAGNOSE_MODULE_PROMPT, SUMMARY_PROMPT, POLISH_PROMPT
+from app.ai.resume_diagnoser.prompts import DIAGNOSE_MODULE_PROMPT, SUMMARY_PROMPT
 from app.core.logger import log
 from app.tool.json_helper import parse_llm_json
 
@@ -54,45 +54,6 @@ async def generate_summary(grade: str, urgent_total: int, important_total: int,
         return "简历诊断已完成，请查看各模块的详细诊断结果。"
 
 
-_polish_chain = (
-    ChatPromptTemplate.from_messages([("system", POLISH_PROMPT), ("human", "请开始优化。")])
-    | DiagnoserModel.POLISH
-    | StrOutputParser()
-)
-
-
-async def polish_content(module_type: str, reference_content: list[dict] | str | None,
-                         user_content: list[str], is_summary: bool) -> list[str]:
-    """润色用户编辑后的文本"""
-    ref_text = ""
-    if reference_content:
-        if isinstance(reference_content, list):
-            ref_text = "\n".join(
-                item.get("text", "") if isinstance(item, dict) else str(item)
-                for item in reference_content
-            )
-        else:
-            ref_text = str(reference_content)
-    if not ref_text:
-        ref_text = "无"
-
-    inp = {
-        "module_type": module_type,
-        "reference_content": ref_text,
-        "user_content": "\n".join(user_content),
-        "summary_constraint": "- 注意：此模块只能输出一个段落，数组只能有一个元素" if is_summary else "",
-    }
-    try:
-        raw = await _polish_chain.ainvoke(inp)
-        result = parse_llm_json(raw)
-        if isinstance(result, list):
-            return [str(item) for item in result]
-        return [str(result)]
-    except Exception as e:
-        log.warning(f"AI润色失败: {e}")
-        return user_content
-
-
 async def _safe_invoke(task: dict) -> dict:
     """单条记录诊断，失败返回空结果"""
     module_type = task.get("module_type", "unknown")