Files
abot/plugins/ai_auto_response/context_builder.py
2026-04-07 12:10:47 +08:00

116 lines
5.2 KiB
Python

from __future__ import annotations
from typing import Dict, List
class ContextBuilder:
def build(
self,
*,
room_id: str,
group_profile: Dict,
sender: str,
sender_name: str,
content: str,
recent_messages: List[Dict],
member_context: Dict,
trigger: Dict,
flow_state: str,
reply_mode: str,
vector_memories: List[Dict],
) -> Dict:
recent_lines = []
for item in recent_messages[-8:]:
msg_sender = item.get("sender_name") or item.get("sender") or "未知成员"
msg_content = item.get("content") or item.get("message") or ""
if msg_content:
recent_lines.append(f"{msg_sender}: {msg_content}")
return {
"group_profile": group_profile or {"room_id": room_id},
"speaker_profile": {
"wxid": sender,
"display_name": sender_name,
"member_context": member_context or {},
},
"recent_messages": recent_lines,
"recent_summary": "",
"trigger_type": trigger.get("trigger_type", "none"),
"reply_mode": reply_mode,
"flow_state": flow_state,
"memory_prompt": self._build_member_memory_prompt(member_context),
"vector_memory_prompt": self._build_vector_memory_prompt(vector_memories),
"group_profile_prompt": self._build_group_profile_prompt(group_profile or {}),
"current_message": f"{sender_name}: {content}",
}
@staticmethod
def _build_member_memory_prompt(member_context: Dict) -> str:
if not member_context:
return "暂无稳定成员画像。"
meta = member_context.get("meta", {}) or {}
topics = member_context.get("topics_of_interest", []) or []
recent_focus = member_context.get("recent_focus", []) or []
lines = [
f"成员摘要:{member_context.get('summary_text', '')}".strip(),
f"互动风格:{member_context.get('interaction_style', '')}".strip(),
f"回复偏好:{member_context.get('response_style_hint', '')}".strip(),
f"长期主题:{', '.join(topics[:5])}" if topics else "",
f"近期关注:{', '.join(recent_focus[:4])}" if recent_focus else "",
f"群内角色:{meta.get('group_role', '')}".strip(),
]
return "\n".join([line for line in lines if line])
@staticmethod
def _build_vector_memory_prompt(vector_memories: List[Dict]) -> str:
if not vector_memories:
return ""
lines = []
for item in vector_memories[:2]:
summary = item.get("content_summary") or item.get("summary_text") or item.get("text") or ""
memory_type = item.get("memory_type", "memory")
if summary:
lines.append(f"[{memory_type}] {summary}")
return "\n".join(lines)
@staticmethod
def _build_group_profile_prompt(group_profile: Dict) -> str:
if not group_profile:
return "当前群没有特殊知识域限制。"
focus = ", ".join(group_profile.get("knowledge_focus", [])[:6])
boundaries = ", ".join(group_profile.get("topic_boundaries", [])[:6])
summary = str(group_profile.get("group_memory_summary", "") or "").replace("\n", " ").strip()
if len(summary) > 120:
summary = summary[:117] + "..."
lines = [
f"群模式:{group_profile.get('mode', 'social')}",
f"知识域:{group_profile.get('knowledge_domain', 'general')}",
f"配置知识域:{group_profile.get('configured_domain', 'general')}",
f"历史推断知识域:{group_profile.get('group_memory_domain', 'general')}",
f"回答风格:{group_profile.get('reply_style', '自然短句')}",
f"互动调性:{group_profile.get('interaction_tone', '自然群友感')}",
f"幽默强度:{group_profile.get('humor_style', '轻微')}",
f"嘴硬程度:{group_profile.get('sharpness_style', '轻微嘴硬,不刻薄')}",
f"表达松弛度:{group_profile.get('expressiveness_style', '克制')}",
f"知识重点:{focus}" if focus else "",
f"群长期摘要:{summary}" if summary else "",
f"历史推断社交风格:{ContextBuilder._build_style_summary(group_profile.get('group_memory_style', {}))}"
if group_profile.get("group_memory_style")
else "",
f"边界提醒:{boundaries}" if boundaries else "",
f"人格叠加:{group_profile.get('persona_overlay', '')}".strip(),
]
return "\n".join([line for line in lines if line])
@staticmethod
def _build_style_summary(style_profile: Dict) -> str:
if not style_profile:
return ""
return " / ".join(
[
str(style_profile.get("interaction_tone", "") or "").strip(),
str(style_profile.get("humor_style", "") or "").strip(),
str(style_profile.get("sharpness_style", "") or "").strip(),
str(style_profile.get("expressiveness_style", "") or "").strip(),
]
).strip(" /")