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feat(i18n): replace remaining Chinese in config generator and profile generator

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Also update simulation prompts to be locale-neutral for timezone/schedule.
This commit is contained in:
ghostubborn
2026-04-01 17:19:12 +08:00
parent 7c07237544
commit 0e55e4cf6b
4 changed files with 107 additions and 15 deletions
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2
backend/app/services/oasis_profile_generator.py
View File

@@ -1022,7 +1022,7 @@ class OasisProfileGenerator:
output_lines = [
f"\n{separator}",
f"[已生成] {entity_name} ({entity_type})",
t('progress.profileGenerated', name=entity_name, type=entity_type),
f"{separator}",
f"用户名: {profile.user_name}",
f"",

16
backend/app/services/simulation_config_generator.py
View File

@@ -297,13 +297,13 @@ class SimulationConfigGenerator:
num_entities = len(entities)
time_config_result = self._generate_time_config(context, num_entities)
time_config = self._parse_time_config(time_config_result, num_entities)
reasoning_parts.append(f"时间配置: {time_config_result.get('reasoning', '成功')}")
reasoning_parts.append(f"{t('progress.timeConfigLabel')}: {time_config_result.get('reasoning', t('common.success'))}")
# ========== 步骤2: 生成事件配置 ==========
report_progress(2, t('progress.generatingEventConfig'))
event_config_result = self._generate_event_config(context, simulation_requirement, entities)
event_config = self._parse_event_config(event_config_result)
reasoning_parts.append(f"事件配置: {event_config_result.get('reasoning', '成功')}")
reasoning_parts.append(f"{t('progress.eventConfigLabel')}: {event_config_result.get('reasoning', t('common.success'))}")
# ========== 步骤3-N: 分批生成Agent配置 ==========
all_agent_configs = []
@@ -325,13 +325,13 @@ class SimulationConfigGenerator:
)
all_agent_configs.extend(batch_configs)
reasoning_parts.append(f"Agent配置: 成功生成 {len(all_agent_configs)} 个")
reasoning_parts.append(t('progress.agentConfigResult', count=len(all_agent_configs)))
# ========== 为初始帖子分配发布者 Agent ==========
logger.info("为初始帖子分配合适的发布者 Agent...")
event_config = self._assign_initial_post_agents(event_config, all_agent_configs)
assigned_count = len([p for p in event_config.initial_posts if p.get("poster_agent_id") is not None])
reasoning_parts.append(f"初始帖子分配: {assigned_count} 个帖子已分配发布者")
reasoning_parts.append(t('progress.postAssignResult', count=assigned_count))
# ========== 最后一步: 生成平台配置 ==========
report_progress(total_steps, t('progress.generatingPlatformConfig'))
@@ -548,7 +548,7 @@ class SimulationConfigGenerator:
请生成时间配置JSON。
### 基本原则（仅供参考，需根据具体事件和参与群体灵活调整）：
- 用户群体为中国人，需符合北京时间作息习惯
- 请根据模拟场景推断目标用户群体所在时区和作息习惯，以下为东八区(UTC+8)的参考示例
- 凌晨0-5点几乎无人活动（活跃度系数0.05）
- 早上6-8点逐渐活跃（活跃度系数0.4）
- 工作时间9-18点中等活跃（活跃度系数0.7）
@@ -585,7 +585,7 @@ class SimulationConfigGenerator:
- work_hours (int数组): 工作时段
- reasoning (string): 简要说明为什么这样配置"""
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。"
system_prompt = "你是社交媒体模拟专家。返回纯JSON格式，时间配置需符合模拟场景中目标用户群体的作息习惯。"
system_prompt = f"{system_prompt}\n\n{get_language_instruction()}"
try:
@@ -841,7 +841,7 @@ class SimulationConfigGenerator:
## 任务
为每个实体生成活动配置，注意：
- **时间符合中国人作息**：凌晨0-5点几乎不活动，晚间19-22点最活跃
- **时间符合目标用户群体作息**：以下为参考（东八区），请根据模拟场景调整
- **官方机构**（University/GovernmentAgency）：活跃度低(0.1-0.3)，工作时间(9-17)活动，响应慢(60-240分钟)，影响力高(2.5-3.0)
- **媒体**（MediaOutlet）：活跃度中(0.4-0.6)，全天活动(8-23)，响应快(5-30分钟)，影响力高(2.0-2.5)
- **个人**（Student/Person/Alumni）：活跃度高(0.6-0.9)，主要晚间活动(18-23)，响应快(1-15分钟)，影响力低(0.8-1.2)
@@ -866,7 +866,7 @@ class SimulationConfigGenerator:
]
}}"""
system_prompt = "你是社交媒体行为分析专家。返回纯JSON，配置需符合中国人作息习惯。"
system_prompt = "你是社交媒体行为分析专家。返回纯JSON，配置需符合模拟场景中目标用户群体的作息习惯。"
system_prompt = f"{system_prompt}\n\n{get_language_instruction()}\nIMPORTANT: The 'stance' field value MUST be one of the English strings: 'supportive', 'opposing', 'neutral', 'observer'. All JSON field names and numeric values must remain unchanged. Only natural language text fields should use the specified language."
try: