Enhance simulation configuration and management features
- Added support for a `max_rounds` parameter in simulation API, allowing users to limit the number of simulation rounds, improving control over simulation duration. - Updated README.md to reflect the new `max_rounds` parameter and its usage in simulation requests. - Enhanced error handling for `max_rounds` input validation to ensure it is a positive integer. - Modified simulation runner and related scripts to incorporate `max_rounds` functionality, ensuring consistent application across Twitter and Reddit simulations. - Improved logging to indicate when the number of rounds is truncated due to the `max_rounds` setting, enhancing traceability during simulation execution.
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666ghj
@@ -85,8 +85,8 @@ class TimeSimulationConfig:
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# 模拟总时长（模拟小时数）
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total_simulation_hours: int = 72 # 默认模拟72小时（3天）
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# 每轮代表的时间（模拟分钟）
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minutes_per_round: int = 30
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# 每轮代表的时间（模拟分钟）- 默认60分钟（1小时），加快时间流速
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minutes_per_round: int = 60
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# 每小时激活的Agent数量范围
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agents_per_hour_min: int = 5
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@@ -205,7 +205,7 @@ class SimulationConfigGenerator:
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采用分步生成策略：
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1. 生成时间配置和事件配置（轻量级）
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2. 分批生成Agent配置（每批10-15个）
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2. 分批生成Agent配置（每批10-20个）
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3. 生成平台配置
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"""
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@@ -214,6 +214,13 @@ class SimulationConfigGenerator:
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# 每批生成的Agent数量
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AGENTS_PER_BATCH = 15
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# 各步骤的上下文截断长度（字符数）
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TIME_CONFIG_CONTEXT_LENGTH = 10000 # 时间配置
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EVENT_CONFIG_CONTEXT_LENGTH = 8000 # 事件配置
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ENTITY_SUMMARY_LENGTH = 300 # 实体摘要
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AGENT_SUMMARY_LENGTH = 300 # Agent配置中的实体摘要
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ENTITIES_PER_TYPE_DISPLAY = 20 # 每类实体显示数量
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def __init__(
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self,
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api_key: Optional[str] = None,
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@@ -286,8 +293,9 @@ class SimulationConfigGenerator:
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# ========== 步骤1: 生成时间配置 ==========
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report_progress(1, "生成时间配置...")
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time_config_result = self._generate_time_config(context, len(entities))
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time_config = self._parse_time_config(time_config_result)
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num_entities = len(entities)
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time_config_result = self._generate_time_config(context, num_entities)
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time_config = self._parse_time_config(time_config_result, num_entities)
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reasoning_parts.append(f"时间配置: {time_config_result.get('reasoning', '成功')}")
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# ========== 步骤2: 生成事件配置 ==========
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@@ -411,11 +419,14 @@ class SimulationConfigGenerator:
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for entity_type, type_entities in by_type.items():
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lines.append(f"\n### {entity_type} ({len(type_entities)}个)")
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for e in type_entities[:10]: # 每类最多显示10个
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summary_preview = (e.summary[:100] + "...") if len(e.summary) > 100 else e.summary
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# 使用配置的显示数量和摘要长度
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display_count = self.ENTITIES_PER_TYPE_DISPLAY
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summary_len = self.ENTITY_SUMMARY_LENGTH
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for e in type_entities[:display_count]:
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summary_preview = (e.summary[:summary_len] + "...") if len(e.summary) > summary_len else e.summary
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lines.append(f"- {e.name}: {summary_preview}")
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if len(type_entities) > 10:
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lines.append(f" ... 还有 {len(type_entities) - 10} 个")
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if len(type_entities) > display_count:
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lines.append(f" ... 还有 {len(type_entities) - display_count} 个")
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return "\n".join(lines)
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@@ -522,33 +533,56 @@ class SimulationConfigGenerator:
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def _generate_time_config(self, context: str, num_entities: int) -> Dict[str, Any]:
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"""生成时间配置"""
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# 使用配置的上下文截断长度
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context_truncated = context[:self.TIME_CONFIG_CONTEXT_LENGTH]
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# 计算最大允许值（80%的agent数）
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max_agents_allowed = max(1, int(num_entities * 0.9))
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prompt = f"""基于以下模拟需求，生成时间模拟配置。
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{context[:5000]}
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{context_truncated}
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## 任务
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请生成时间配置JSON，注意：
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请生成时间配置JSON。
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### 基本原则（仅供参考，需根据具体事件和参与群体灵活调整）：
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- 用户群体为中国人，需符合北京时间作息习惯
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- 凌晨0-5点几乎无人活动（活跃度系数0.05）
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- 早上6-8点逐渐活跃（活跃度系数0.4）
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- 工作时间9-18点中等活跃（活跃度系数0.7）
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- 晚间19-22点是高峰期（活跃度系数1.5）
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- 23点后活跃度下降（活跃度系数0.5）
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- 一般规律：凌晨低活跃、早间渐增、工作时段中等、晚间高峰
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- **重要**：以下示例值仅供参考，你需要根据事件性质、参与群体特点来调整具体时段
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- 例如：学生群体高峰可能是21-23点；媒体全天活跃；官方机构只在工作时间
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- 例如：突发热点可能导致深夜也有讨论，off_peak_hours 可适当缩短
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当前实体数量: {num_entities}
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### 返回JSON格式（不要markdown）
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返回JSON格式（不要markdown）：
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示例：
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{{
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"total_simulation_hours": <72-168，根据事件性质决定>,
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"minutes_per_round": <15-60>,
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"agents_per_hour_min": <每小时最少激活Agent数>,
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"agents_per_hour_max": <每小时最多激活Agent数>,
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"total_simulation_hours": 72,
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"minutes_per_round": 60,
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"agents_per_hour_min": 5,
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"agents_per_hour_max": 50,
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"peak_hours": [19, 20, 21, 22],
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"off_peak_hours": [0, 1, 2, 3, 4, 5],
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"morning_hours": [6, 7, 8],
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"work_hours": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18],
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"reasoning": "<简要说明>"
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}}"""
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"reasoning": "针对该事件的时间配置说明"
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}}
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字段说明：
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- total_simulation_hours (int): 模拟总时长，24-168小时，突发事件短、持续话题长
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- minutes_per_round (int): 每轮时长，30-120分钟，建议60分钟
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- agents_per_hour_min (int): 每小时最少激活Agent数（取值范围: 1-{max_agents_allowed}）
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- agents_per_hour_max (int): 每小时最多激活Agent数（取值范围: 1-{max_agents_allowed}）
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- peak_hours (int数组): 高峰时段，根据事件参与群体调整
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- off_peak_hours (int数组): 低谷时段，通常深夜凌晨
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- morning_hours (int数组): 早间时段
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- work_hours (int数组): 工作时段
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- reasoning (string): 简要说明为什么这样配置"""
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system_prompt = "你是社交媒体模拟专家。返回纯JSON格式，时间配置需符合中国人作息习惯。"
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@@ -562,23 +596,41 @@ class SimulationConfigGenerator:
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"""获取默认时间配置（中国人作息）"""
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return {
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"total_simulation_hours": 72,
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"minutes_per_round": 30,
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"minutes_per_round": 60, # 每轮1小时，加快时间流速
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"agents_per_hour_min": max(1, num_entities // 15),
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"agents_per_hour_max": max(5, num_entities // 5),
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"peak_hours": [19, 20, 21, 22],
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"off_peak_hours": [0, 1, 2, 3, 4, 5],
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"morning_hours": [6, 7, 8],
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"work_hours": [9, 10, 11, 12, 13, 14, 15, 16, 17, 18],
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"reasoning": "使用默认中国人作息配置"
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"reasoning": "使用默认中国人作息配置（每轮1小时）"
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}
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def _parse_time_config(self, result: Dict[str, Any]) -> TimeSimulationConfig:
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"""解析时间配置结果"""
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def _parse_time_config(self, result: Dict[str, Any], num_entities: int) -> TimeSimulationConfig:
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"""解析时间配置结果，并验证agents_per_hour值不超过总agent数"""
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# 获取原始值
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agents_per_hour_min = result.get("agents_per_hour_min", max(1, num_entities // 15))
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agents_per_hour_max = result.get("agents_per_hour_max", max(5, num_entities // 5))
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# 验证并修正：确保不超过总agent数
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if agents_per_hour_min > num_entities:
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logger.warning(f"agents_per_hour_min ({agents_per_hour_min}) 超过总Agent数 ({num_entities})，已修正")
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agents_per_hour_min = max(1, num_entities // 10)
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if agents_per_hour_max > num_entities:
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logger.warning(f"agents_per_hour_max ({agents_per_hour_max}) 超过总Agent数 ({num_entities})，已修正")
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agents_per_hour_max = max(agents_per_hour_min + 1, num_entities // 2)
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# 确保 min < max
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if agents_per_hour_min >= agents_per_hour_max:
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agents_per_hour_min = max(1, agents_per_hour_max // 2)
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logger.warning(f"agents_per_hour_min >= max，已修正为 {agents_per_hour_min}")
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return TimeSimulationConfig(
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total_simulation_hours=result.get("total_simulation_hours", 72),
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minutes_per_round=result.get("minutes_per_round", 30),
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agents_per_hour_min=result.get("agents_per_hour_min", 5),
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agents_per_hour_max=result.get("agents_per_hour_max", 20),
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minutes_per_round=result.get("minutes_per_round", 60), # 默认每轮1小时
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agents_per_hour_min=agents_per_hour_min,
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agents_per_hour_max=agents_per_hour_max,
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peak_hours=result.get("peak_hours", [19, 20, 21, 22]),
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off_peak_hours=result.get("off_peak_hours", [0, 1, 2, 3, 4, 5]),
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off_peak_activity_multiplier=0.05, # 凌晨几乎无人
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@@ -616,11 +668,14 @@ class SimulationConfigGenerator:
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for t, examples in type_examples.items()
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])
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# 使用配置的上下文截断长度
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context_truncated = context[:self.EVENT_CONFIG_CONTEXT_LENGTH]
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prompt = f"""基于以下模拟需求，生成事件配置。
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模拟需求: {simulation_requirement}
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{context[:3000]}
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{context_truncated}
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## 可用实体类型及示例
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{type_info}
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@@ -761,14 +816,15 @@ class SimulationConfigGenerator:
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) -> List[AgentActivityConfig]:
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"""分批生成Agent配置"""
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# 构建实体信息
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# 构建实体信息（使用配置的摘要长度）
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entity_list = []
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summary_len = self.AGENT_SUMMARY_LENGTH
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for i, e in enumerate(entities):
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entity_list.append({
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"agent_id": start_idx + i,
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"entity_name": e.name,
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"entity_type": e.get_entity_type() or "Unknown",
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"summary": e.summary[:150] if e.summary else ""
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"summary": e.summary[:summary_len] if e.summary else ""
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})
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prompt = f"""基于以下信息，为每个实体生成社交媒体活动配置。
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@@ -280,7 +280,8 @@ class SimulationRunner:
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def start_simulation(
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cls,
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simulation_id: str,
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platform: str = "parallel" # twitter / reddit / parallel
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platform: str = "parallel", # twitter / reddit / parallel
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max_rounds: int = None # 最大模拟轮数（可选，用于截断过长的模拟）
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) -> SimulationRunState:
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"""
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启动模拟
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@@ -288,6 +289,7 @@ class SimulationRunner:
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Args:
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simulation_id: 模拟ID
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platform: 运行平台 (twitter/reddit/parallel)
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max_rounds: 最大模拟轮数（可选，用于截断过长的模拟）
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Returns:
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SimulationRunState
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@@ -313,6 +315,13 @@ class SimulationRunner:
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minutes_per_round = time_config.get("minutes_per_round", 30)
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total_rounds = int(total_hours * 60 / minutes_per_round)
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# 如果指定了最大轮数，则截断
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if max_rounds is not None and max_rounds > 0:
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original_rounds = total_rounds
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total_rounds = min(total_rounds, max_rounds)
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if total_rounds < original_rounds:
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logger.info(f"轮数已截断: {original_rounds} -> {total_rounds} (max_rounds={max_rounds})")
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state = SimulationRunState(
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simulation_id=simulation_id,
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runner_status=RunnerStatus.STARTING,
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@@ -358,6 +367,10 @@ class SimulationRunner:
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"--config", config_path, # 使用完整配置文件路径
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]
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# 如果指定了最大轮数，添加到命令行参数
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if max_rounds is not None and max_rounds > 0:
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cmd.extend(["--max-rounds", str(max_rounds)])
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# 创建主日志文件，避免 stdout/stderr 管道缓冲区满导致进程阻塞
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main_log_path = os.path.join(sim_dir, "simulation.log")
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main_log_file = open(main_log_path, 'w', encoding='utf-8')
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