feat: 生成回忆录agent结构封装

api/app/agents/memoir/narrative_agent.py

@@ -0,0 +1,78 @@
+"""
+NarrativeAgent：生成创意标题和叙事改写。
+对应现有逻辑：get_creative_title_prompt、get_narrative_prompt
+"""
+from __future__ import annotations
+
+from typing import Any, Dict, Optional
+
+from app.core.logging import get_logger
+
+from app.agents.prompts.memory_prompts import (
+    get_creative_title_prompt,
+    get_narrative_prompt,
+)
+
+logger = get_logger(__name__)
+
+
+class NarrativeAgent:
+    """生成章节标题和叙事正文"""
+
+    def generate_title(
+        self,
+        stage: str,
+        emotion: str,
+        slots: Dict[str, str],
+        user_profile: str = "",
+        birth_year: Optional[int] = None,
+        llm: Any = None,
+    ) -> str:
+        """生成创意标题。若无 LLM 则返回默认标题"""
+        if not llm:
+            return f"{stage} 回忆"
+        try:
+            prompt = get_creative_title_prompt(
+                stage=stage,
+                emotion=emotion,
+                slots=slots,
+                user_profile=user_profile,
+                birth_year=birth_year,
+            )
+            response = llm.invoke(prompt)
+            return (response.content or "").strip().strip('"')
+        except Exception as e:
+            logger.warning("NarrativeAgent 生成标题失败: %s", e)
+            return f"{stage} 回忆"
+
+    def generate_narrative(
+        self,
+        stage: str,
+        slots: Dict[str, str],
+        new_content: str,
+        existing_content: str = "",
+        user_profile: str = "",
+        birth_year: Optional[int] = None,
+        llm: Any = None,
+    ) -> str:
+        """将新对话改写为叙述。若无 LLM 则直接拼接"""
+        if not llm:
+            if existing_content:
+                return f"{existing_content}\n\n{new_content}"
+            return new_content
+        try:
+            prompt = get_narrative_prompt(
+                stage=stage,
+                slots=slots,
+                new_content=new_content,
+                existing_content=existing_content,
+                user_profile=user_profile,
+                birth_year=birth_year,
+            )
+            response = llm.invoke(prompt)
+            return (response.content or "").strip()
+        except Exception as e:
+            logger.warning("NarrativeAgent 生成叙事失败: %s", e)
+            if existing_content:
+                return f"{existing_content}\n\n{new_content}"
+            return new_content