238 lines
7.9 KiB
Python
238 lines
7.9 KiB
Python
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"""
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Agent 间知识共享服务 — 父 Agent 经验继承、跨 Agent 知识流通
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子 Agent 创建时可继承父 Agent 的知识条目、学习模式和全局知识，
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避免自主学习创建的 Agent 从零开始。
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"""
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from __future__ import annotations
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import logging
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from typing import Any, Dict, List, Optional
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from sqlalchemy.orm import Session
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from app.core.database import SessionLocal
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logger = logging.getLogger(__name__)
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def inherit_knowledge_from_parent(
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child_agent_id: str,
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parent_agent_id: str,
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db: Optional[Session] = None,
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) -> Dict[str, Any]:
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"""
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从父 Agent 继承知识到子 Agent。
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拷贝内容：
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1. KnowledgeEntry 条目（知识沉淀）
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2. GlobalKnowledge 条目（全局知识，标记为子 Agent 可见）
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3. AgentLearningPattern 模式（工具使用经验）
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"""
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should_close = False
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if db is None:
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db = SessionLocal()
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should_close = True
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result = {
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"child_agent_id": child_agent_id,
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"parent_agent_id": parent_agent_id,
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"knowledge_entries_copied": 0,
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"global_knowledge_shared": 0,
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"learning_patterns_copied": 0,
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}
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try:
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# 1. 拷贝 KnowledgeEntry
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from app.models.knowledge_entry import KnowledgeEntry
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parent_entries = (
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db.query(KnowledgeEntry)
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.filter(
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KnowledgeEntry.is_active == True,
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)
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.filter(
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(KnowledgeEntry.agent_id == parent_agent_id)
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| (KnowledgeEntry.source_agent_name == parent_agent_id)
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)
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.all()
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)
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import uuid
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for entry in parent_entries:
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new_entry = KnowledgeEntry(
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id=str(uuid.uuid4()),
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agent_id=child_agent_id,
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title=f"[继承] {entry.title}",
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category=entry.category,
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tags=(entry.tags or []) + ["inherited"],
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situation=entry.situation,
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solution=entry.solution,
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caveats=entry.caveats,
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source_execution_ids=entry.source_execution_ids,
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source_agent_name=entry.source_agent_name,
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source_model=entry.source_model,
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retrieval_count=0,
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success_rate=entry.success_rate,
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confidence=(entry.confidence or 0.5) * 0.8, # 继承降低置信度
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is_active=True,
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)
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db.add(new_entry)
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result["knowledge_entries_copied"] += 1
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# 2. 拷贝 GlobalKnowledge 标记（来源标记关联，不复制内容）
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from app.models.agent import GlobalKnowledge
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from datetime import datetime, timedelta
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# 查找父 Agent 贡献的全局知识
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parent_knowledge = (
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db.query(GlobalKnowledge)
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.filter(GlobalKnowledge.source_agent_id == parent_agent_id)
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.all()
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)
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# 将父 Agent 的全局知识也关联到子 Agent（scope）
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for gk in parent_knowledge:
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# 不直接修改，而是创建新的 scope 关联（scope_kind=agent, scope_id=child）
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# 如果已有相同内容的记录则跳过
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existing = (
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db.query(GlobalKnowledge)
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.filter(
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GlobalKnowledge.content == gk.content,
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GlobalKnowledge.scope_kind == "agent",
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GlobalKnowledge.scope_id == child_agent_id,
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)
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.first()
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)
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if not existing:
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shared = GlobalKnowledge(
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id=str(uuid.uuid4()),
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content=gk.content,
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embedding=gk.embedding,
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source_agent_id=parent_agent_id,
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source_user_id=gk.source_user_id,
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tags=(gk.tags or []) + ["inherited_from_parent"],
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confidence=gk.confidence or "medium",
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scope_kind="agent",
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scope_id=child_agent_id,
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created_at=datetime.utcnow(),
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)
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db.add(shared)
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result["global_knowledge_shared"] += 1
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# 3. 拷贝 AgentLearningPattern
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from app.models.agent_learning_pattern import AgentLearningPattern
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parent_patterns = (
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db.query(AgentLearningPattern)
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.filter(
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AgentLearningPattern.scope_kind == "agent",
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AgentLearningPattern.scope_id == parent_agent_id,
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)
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.all()
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)
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for pattern in parent_patterns:
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new_pattern = AgentLearningPattern(
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id=str(uuid.uuid4()),
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scope_kind="agent",
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scope_id=child_agent_id,
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task_category=pattern.task_category,
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task_keywords=pattern.task_keywords,
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suggested_tools=pattern.suggested_tools,
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effectiveness_score=pattern.effectiveness_score,
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total_runs=1, # 重置计数
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successful_runs=0,
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avg_iterations=pattern.avg_iterations,
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avg_tool_calls=pattern.avg_tool_calls,
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created_at=datetime.utcnow(),
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updated_at=datetime.utcnow(),
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)
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db.add(new_pattern)
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result["learning_patterns_copied"] += 1
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db.commit()
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logger.info(
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"Agent 知识继承完成: parent=%s → child=%s, entries=%d, global=%d, patterns=%d",
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parent_agent_id,
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child_agent_id,
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result["knowledge_entries_copied"],
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result["global_knowledge_shared"],
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result["learning_patterns_copied"],
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)
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except Exception as e:
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db.rollback()
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logger.error("Agent 知识继承失败: %s", e)
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raise
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finally:
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if should_close and db:
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db.close()
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return result
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def get_parent_knowledge_context(
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agent_id: str,
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max_entries: int = 5,
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db: Optional[Session] = None,
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) -> str:
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"""
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获取 Agent 的父级知识上下文（用于注入 system prompt）。
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先查直接父 Agent，再查祖父 Agent（最多上溯 3 层）。
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"""
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should_close = False
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if db is None:
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db = SessionLocal()
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should_close = True
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try:
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from app.models.agent import Agent
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from app.models.knowledge_entry import KnowledgeEntry
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# 收集祖先 Agent ID 列表（向上追溯最多 3 层）
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ancestor_ids: List[str] = []
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current_id = agent_id
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for _ in range(3):
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agent = db.query(Agent).filter(Agent.id == current_id).first()
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if not agent or not getattr(agent, "parent_agent_id", None):
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break
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parent_id = agent.parent_agent_id
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if parent_id in ancestor_ids: # 防止循环引用
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break
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ancestor_ids.append(parent_id)
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current_id = parent_id
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if not ancestor_ids:
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return ""
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# 查询祖先 Agent 的高质量知识
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entries = (
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db.query(KnowledgeEntry)
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.filter(
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KnowledgeEntry.agent_id.in_(ancestor_ids),
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KnowledgeEntry.is_active == True,
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KnowledgeEntry.confidence >= 0.6,
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)
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.order_by(KnowledgeEntry.retrieval_count.desc())
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.limit(max_entries)
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.all()
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)
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if not entries:
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return ""
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lines = [f"## 父级 Agent 经验 ({len(entries)} 条)"]
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for i, entry in enumerate(entries, 1):
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tag_str = f"[{entry.category}]" if entry.category else ""
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sol = (entry.solution or "")[:300]
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lines.append(f"{i}. {tag_str} {entry.title}: {sol}")
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return "\n".join(lines)
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except Exception as e:
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logger.warning("获取父级知识上下文失败: %s", e)
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return ""
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finally:
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if should_close and db:
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db.close()
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