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feat(relationship): 重构关系信息提取系统并集成聊天流印象

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- 在 RelationshipFetcher 中添加 build_chat_stream_impression 方法，支持聊天流印象信息构建
- 扩展数据库模型，为 ChatStreams 表添加聊天流印象相关字段（stream_impression_text、stream_chat_style、stream_topic_keywords、stream_interest_score）
- 为 UserRelationships 表添加用户别名和偏好关键词字段（user_aliases、preference_keywords）
- 在 DefaultReplyer、Prompt 和 S4U PromptBuilder 中集成用户关系信息和聊天流印象的组合输出
- 重构工具系统，为 BaseTool 添加 chat_stream 参数支持上下文感知
- 移除旧的 ChatterRelationshipTracker 及相关关系追踪逻辑，统一使用评分API
- 在 AffinityChatterPlugin 中添加 UserProfileTool 和 ChatStreamImpressionTool 支持
- 优化计划执行器，移除关系追踪相关代码并改进错误处理

BREAKING CHANGE: 移除了 ChatterRelationshipTracker 类及相关的关系追踪功能，现在统一使用 scoring_api 进行关系管理。BaseTool 构造函数现在需要 chat_stream 参数。
This commit is contained in:
Windpicker-owo
2025-10-30 16:58:26 +08:00
parent 9372f6d31c
commit 60b3a2ba4f
17 changed files with 1264 additions and 989 deletions
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74
src/chat/replyer/default_generator.py
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@@ -1947,42 +1947,64 @@ class DefaultReplyer:
logger.warning(f"未找到用户 {sender} 的ID，跳过信息提取")
return f"你完全不认识{sender}，不理解ta的相关信息。"
# 使用统一评分API获取关系信息
# 使用 RelationshipFetcher 获取完整关系信息（包含新字段）
try:
from src.plugin_system.apis.scoring_api import scoring_api
from src.person_info.relationship_fetcher import relationship_fetcher_manager
# 获取用户信息以获取真实的user_id
user_info = await person_info_manager.get_values(person_id, ["user_id", "platform"])
user_id = user_info.get("user_id", "unknown")
# 获取 chat_id
chat_id = self.chat_stream.stream_id
# 从统一API获取关系数据
relationship_data = await scoring_api.get_user_relationship_data(user_id)
if relationship_data:
relationship_text = relationship_data.get("relationship_text", "")
relationship_score = relationship_data.get("relationship_score", 0.3)
# 获取 RelationshipFetcher 实例
relationship_fetcher = relationship_fetcher_manager.get_fetcher(chat_id)
# 构建丰富的关系信息描述
if relationship_text:
# 转换关系分数为描述性文本
if relationship_score >= 0.8:
relationship_level = "非常亲密的朋友"
elif relationship_score >= 0.6:
relationship_level = "好朋友"
elif relationship_score >= 0.4:
relationship_level = "普通朋友"
elif relationship_score >= 0.2:
relationship_level = "认识的人"
else:
relationship_level = "陌生人"
# 构建用户关系信息（包含别名、偏好关键词等新字段）
user_relation_info = await relationship_fetcher.build_relation_info(person_id, points_num=5)
return f"你与{sender}的关系：{relationship_level}（关系分：{relationship_score:.2f}/1.0）。{relationship_text}"
else:
return f"你与{sender}是初次见面，关系分：{relationship_score:.2f}/1.0。"
# 构建聊天流印象信息
stream_impression = await relationship_fetcher.build_chat_stream_impression(chat_id)
# 组合两部分信息
if user_relation_info and stream_impression:
return "\n\n".join([user_relation_info, stream_impression])
elif user_relation_info:
return user_relation_info
elif stream_impression:
return stream_impression
else:
return f"你完全不认识{sender}，这是第一次互动。"
except Exception as e:
logger.error(f"获取关系信息失败: {e}")
# 降级到基本信息
try:
from src.plugin_system.apis.scoring_api import scoring_api
user_info = await person_info_manager.get_values(person_id, ["user_id", "platform"])
user_id = user_info.get("user_id", "unknown")
relationship_data = await scoring_api.get_user_relationship_data(user_id)
if relationship_data:
relationship_text = relationship_data.get("relationship_text", "")
relationship_score = relationship_data.get("relationship_score", 0.3)
if relationship_text:
if relationship_score >= 0.8:
relationship_level = "非常亲密的朋友"
elif relationship_score >= 0.6:
relationship_level = "好朋友"
elif relationship_score >= 0.4:
relationship_level = "普通朋友"
elif relationship_score >= 0.2:
relationship_level = "认识的人"
else:
relationship_level = "陌生人"
return f"你与{sender}的关系：{relationship_level}（关系分：{relationship_score:.2f}/1.0）。{relationship_text}"
else:
return f"你与{sender}是初次见面，关系分：{relationship_score:.2f}/1.0。"
except Exception:
pass
return f"你与{sender}是普通朋友关系。"
async def _store_chat_memory_async(self, reply_to: str, reply_message: dict[str, Any] | None = None):