import os import json from datetime import datetime import time class MemoryManager: def __init__(self, persistence_file="memory.json"): self.persistence_file = persistence_file self._load_memory() print("MemoryManager initialized.") def initialize_user_profile(self, user_id: str): if user_id not in self.memory: self.memory[user_id] = { "created_at": datetime.now().isoformat(), "conversations": [] } self._save_memory() return self.memory[user_id] def store_conversation(self, user_id: str, message: str, role: str): if user_id in self.memory: self.memory[user_id]["conversations"].append({ "timestamp": datetime.now().isoformat(), "role": role, "message": message }) self._save_memory() def get_relevant_memories(self, user_id: str, query: str, limit: int = 5) -> list: print(f"Placeholder: Searching for relevant memories for user '{user_id}' with query '{query}'") return [] def get_user_profile(self, user_id: str) -> dict: print(f"Placeholder: Retrieving user profile for '{user_id}'") return self.memory.get(user_id, {}).get("profile", {}) def store_learned_traits(self, user_id: str, traits: dict): if user_id in self.memory: self.memory[user_id]["profile"] = self.memory.get(user_id, {}).get("profile", {}) self.memory[user_id]["profile"]["learned_traits"] = json.dumps(traits) self._save_memory() def get_conversation_count(self, user_id: str) -> int: return len(self.memory.get(user_id, {}).get("conversations", [])) def _load_memory(self): if os.path.exists(self.persistence_file): with open(self.persistence_file, 'r') as f: self.memory = json.load(f) else: self.memory = {} def _save_memory(self): with open(self.persistence_file, 'w') as f: json.dump(self.memory, f, indent=2)