""" OASIS Reddit模拟预设脚本 此脚本读取配置文件中的参数来执行模拟，实现全程自动化 使用方式: python run_reddit_simulation.py --config /path/to/simulation_config.json """ import argparse import asyncio import json import os import random import sys from datetime import datetime from typing import Dict, Any, List # 添加项目路径 sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) try: from camel.models import ModelFactory from camel.types import ModelPlatformType import oasis from oasis import ( ActionType, LLMAction, ManualAction, generate_reddit_agent_graph ) except ImportError as e: print(f"错误: 缺少依赖 {e}") print("请先安装: pip install oasis-ai camel-ai") sys.exit(1) class RedditSimulationRunner: """Reddit模拟运行器""" # Reddit可用动作 AVAILABLE_ACTIONS = [ ActionType.LIKE_POST, ActionType.DISLIKE_POST, ActionType.CREATE_POST, ActionType.CREATE_COMMENT, ActionType.LIKE_COMMENT, ActionType.DISLIKE_COMMENT, ActionType.SEARCH_POSTS, ActionType.SEARCH_USER, ActionType.TREND, ActionType.REFRESH, ActionType.DO_NOTHING, ActionType.FOLLOW, ActionType.MUTE, ] def __init__(self, config_path: str): """ 初始化模拟运行器 Args: config_path: 配置文件路径 (simulation_config.json) """ self.config_path = config_path self.config = self._load_config() self.simulation_dir = os.path.dirname(config_path) def _load_config(self) -> Dict[str, Any]: """加载配置文件""" with open(self.config_path, 'r', encoding='utf-8') as f: return json.load(f) def _get_profile_path(self) -> str: """获取Profile文件路径""" return os.path.join(self.simulation_dir, "reddit_profiles.json") def _get_db_path(self) -> str: """获取数据库路径""" return os.path.join(self.simulation_dir, "reddit_simulation.db") def _create_model(self): """ 创建LLM模型 OASIS使用camel-ai的ModelFactory，配置方式： - 标准OpenAI: 只需设置 OPENAI_API_KEY 环境变量 - 自定义API: 设置 OPENAI_API_KEY 和 OPENAI_API_BASE_URL 环境变量 """ import os llm_model = self.config.get("llm_model", "gpt-4o-mini") llm_base_url = self.config.get("llm_base_url", "") # 如果配置了base_url，设置环境变量 if llm_base_url: os.environ["OPENAI_API_BASE_URL"] = llm_base_url return ModelFactory.create( model_platform=ModelPlatformType.OPENAI, model_type=llm_model, ) def _get_active_agents_for_round( self, env, current_hour: int, round_num: int ) -> List: """ 根据时间和配置决定本轮激活哪些Agent """ time_config = self.config.get("time_config", {}) agent_configs = self.config.get("agent_configs", []) base_min = time_config.get("agents_per_hour_min", 5) base_max = time_config.get("agents_per_hour_max", 20) peak_hours = time_config.get("peak_hours", [9, 10, 11, 14, 15, 20, 21, 22]) off_peak_hours = time_config.get("off_peak_hours", [0, 1, 2, 3, 4, 5]) if current_hour in peak_hours: multiplier = time_config.get("peak_activity_multiplier", 1.5) elif current_hour in off_peak_hours: multiplier = time_config.get("off_peak_activity_multiplier", 0.3) else: multiplier = 1.0 target_count = int(random.uniform(base_min, base_max) * multiplier) candidates = [] for cfg in agent_configs: agent_id = cfg.get("agent_id", 0) active_hours = cfg.get("active_hours", list(range(8, 23))) activity_level = cfg.get("activity_level", 0.5) if current_hour not in active_hours: continue if random.random() < activity_level: candidates.append(agent_id) selected_ids = random.sample( candidates, min(target_count, len(candidates)) ) if candidates else [] active_agents = [] for agent_id in selected_ids: try: agent = env.agent_graph.get_agent(agent_id) active_agents.append((agent_id, agent)) except Exception: pass return active_agents async def run(self): """运行Reddit模拟""" print("=" * 60) print("OASIS Reddit模拟") print(f"配置文件: {self.config_path}") print(f"模拟ID: {self.config.get('simulation_id', 'unknown')}") print("=" * 60) time_config = self.config.get("time_config", {}) total_hours = time_config.get("total_simulation_hours", 72) minutes_per_round = time_config.get("minutes_per_round", 30) total_rounds = (total_hours * 60) // minutes_per_round print(f"\n模拟参数:") print(f" - 总模拟时长: {total_hours}小时") print(f" - 每轮时间: {minutes_per_round}分钟") print(f" - 总轮数: {total_rounds}") print(f" - Agent数量: {len(self.config.get('agent_configs', []))}") print("\n初始化LLM模型...") model = self._create_model() print("加载Agent Profile...") profile_path = self._get_profile_path() if not os.path.exists(profile_path): print(f"错误: Profile文件不存在: {profile_path}") return agent_graph = await generate_reddit_agent_graph( profile_path=profile_path, model=model, available_actions=self.AVAILABLE_ACTIONS, ) db_path = self._get_db_path() if os.path.exists(db_path): os.remove(db_path) print(f"已删除旧数据库: {db_path}") print("创建OASIS环境...") env = oasis.make( agent_graph=agent_graph, platform=oasis.DefaultPlatformType.REDDIT, database_path=db_path, ) await env.reset() print("环境初始化完成\n") # 执行初始事件 event_config = self.config.get("event_config", {}) initial_posts = event_config.get("initial_posts", []) if initial_posts: print(f"执行初始事件 ({len(initial_posts)}条初始帖子)...") initial_actions = {} for post in initial_posts: agent_id = post.get("poster_agent_id", 0) content = post.get("content", "") try: agent = env.agent_graph.get_agent(agent_id) if agent in initial_actions: if not isinstance(initial_actions[agent], list): initial_actions[agent] = [initial_actions[agent]] initial_actions[agent].append(ManualAction( action_type=ActionType.CREATE_POST, action_args={"content": content} )) else: initial_actions[agent] = ManualAction( action_type=ActionType.CREATE_POST, action_args={"content": content} ) except Exception as e: print(f" 警告: 无法为Agent {agent_id}创建初始帖子: {e}") if initial_actions: await env.step(initial_actions) print(f" 已发布 {len(initial_actions)} 条初始帖子") # 主模拟循环 print("\n开始模拟循环...") start_time = datetime.now() for round_num in range(total_rounds): simulated_minutes = round_num * minutes_per_round simulated_hour = (simulated_minutes // 60) % 24 simulated_day = simulated_minutes // (60 * 24) + 1 active_agents = self._get_active_agents_for_round( env, simulated_hour, round_num ) if not active_agents: continue actions = { agent: LLMAction() for _, agent in active_agents } await env.step(actions) if (round_num + 1) % 10 == 0 or round_num == 0: elapsed = (datetime.now() - start_time).total_seconds() progress = (round_num + 1) / total_rounds * 100 print(f" [Day {simulated_day}, {simulated_hour:02d}:00] " f"Round {round_num + 1}/{total_rounds} ({progress:.1f}%) " f"- {len(active_agents)} agents active " f"- elapsed: {elapsed:.1f}s") await env.close() total_elapsed = (datetime.now() - start_time).total_seconds() print(f"\n模拟完成!") print(f" - 总耗时: {total_elapsed:.1f}秒") print(f" - 数据库: {db_path}") print("=" * 60) async def main(): parser = argparse.ArgumentParser(description='OASIS Reddit模拟') parser.add_argument( '--config', type=str, required=True, help='配置文件路径 (simulation_config.json)' ) args = parser.parse_args() if not os.path.exists(args.config): print(f"错误: 配置文件不存在: {args.config}") sys.exit(1) runner = RedditSimulationRunner(args.config) await runner.run() if __name__ == "__main__": asyncio.run(main())