初始化：记忆系统源代码上传（已脱敏）

- 排除 .env / *.bak / 内部运维文档（README_INTERNAL.html）
- config.py 默认密码已替换为占位符 CHANGE_ME_*
- init_db.sql 移除生产数据库用户 GRANT 段
- README.html 数据库用户名已脱敏
- 保留：源码 + 公网 API 文档 + 建表 SQL（无授权语句）

lifecycle/persona_generator.py

@@ -0,0 +1,80 @@
+"""Persona Generator - Generate user persona from scenarios and memories."""
+import json
+import logging
+from typing import Optional
+
+from lifecycle.llm_parse import parse_llm_json_object
+
+logger = logging.getLogger(__name__)
+
+PERSONA_SYSTEM_PROMPT = """你是JSON生成器。直接输出JSON对象，禁止分析、思考、解释、markdown。
+
+根据记忆和场景生成用户画像。
+
+输出格式（第一个字符必须是{，最后一个字符必须是}）：
+{"preferences":["偏好1"],"habits":["习惯1"],"expertise":["擅长1"],"communication_style":"风格","summary":"100字以内摘要"}
+
+只输出JSON，不要有任何其他文字。"""
+
+
+class PersonaGenerator:
+    """Generate user persona from memories and scenarios."""
+
+    def __init__(self, mysql_store, llm_client):
+        self.mysql = mysql_store
+        self.llm = llm_client
+
+    def generate(self, agent_id: str, team_id: str,
+                 max_items: int = 30) -> dict:
+        if not self.llm.available:
+            return {"error": "LLM not configured. Set LLM_API_URL, LLM_API_KEY, LLM_MODEL environment variables."}
+
+        memories = self.mysql.get_personal_memories_by_agent(agent_id, limit=max_items)
+        scenarios = self.mysql.get_scenarios_by_agent(agent_id)
+
+        if not memories and not scenarios:
+            return {"error": "No memories or scenarios found for this agent"}
+
+        context_parts = []
+        if memories:
+            mem_lines = [f"- {m.get('content', '')[:100]}" for m in memories]
+            context_parts.append("历史记忆：\n" + "\n".join(mem_lines))
+        if scenarios:
+            scene_lines = [f"- [{s.get('name', '')}] {s.get('summary', '')}" for s in scenarios]
+            context_parts.append("已识别场景：\n" + "\n".join(scene_lines))
+
+        user_prompt = "请根据以下内容生成用户画像JSON：\n\n" + "\n\n".join(context_parts)
+
+        try:
+            persona = parse_llm_json_object(
+                self.llm, PERSONA_SYSTEM_PROMPT, user_prompt,
+                temperature=0.3, context="generate-persona",
+                max_tokens=2000,
+            )
+        except ValueError as e:
+            return {"error": str(e)}
+
+        if not isinstance(persona, dict):
+            logger.warning("LLM returned non-dict persona: %r", persona)
+            return {"error": "LLM returned invalid persona format"}
+
+        pid = self.mysql.add_persona(
+            team_id=team_id,
+            agent_id=agent_id,
+            preferences=persona.get("preferences", []),
+            habits=persona.get("habits", []),
+            expertise=persona.get("expertise", []),
+            communication_style=persona.get("communication_style", ""),
+            summary=persona.get("summary", ""),
+        )
+        persona["id"] = pid
+        return {"persona": persona}
+
+    def get_persona(self, agent_id: str):
+        return self.mysql.get_persona_by_agent(agent_id)
+
+    def delete_persona(self, persona_id: str, team_id: str) -> bool:
+        persona = self.mysql.get_persona(persona_id)
+        if not persona or persona["team_id"] != team_id:
+            return False
+        return self.mysql.delete_persona(persona_id)