aiagent/backend/app/services/knowledge_sharing.py

"""
Agent 间知识共享服务 — 父 Agent 经验继承、跨 Agent 知识流通

子 Agent 创建时可继承父 Agent 的知识条目、学习模式和全局知识，
避免自主学习创建的 Agent 从零开始。
"""
from __future__ import annotations

import logging
from typing import Any, Dict, List, Optional

from sqlalchemy.orm import Session

from app.core.database import SessionLocal

logger = logging.getLogger(__name__)


def inherit_knowledge_from_parent(
    child_agent_id: str,
    parent_agent_id: str,
    db: Optional[Session] = None,
) -> Dict[str, Any]:
    """
    从父 Agent 继承知识到子 Agent。

    拷贝内容：
    1. KnowledgeEntry 条目（知识沉淀）
    2. GlobalKnowledge 条目（全局知识，标记为子 Agent 可见）
    3. AgentLearningPattern 模式（工具使用经验）
    """
    should_close = False
    if db is None:
        db = SessionLocal()
        should_close = True

    result = {
        "child_agent_id": child_agent_id,
        "parent_agent_id": parent_agent_id,
        "knowledge_entries_copied": 0,
        "global_knowledge_shared": 0,
        "learning_patterns_copied": 0,
    }

    try:
        # 1. 拷贝 KnowledgeEntry
        from app.models.knowledge_entry import KnowledgeEntry

        parent_entries = (
            db.query(KnowledgeEntry)
            .filter(
                KnowledgeEntry.is_active == True,
            )
            .filter(
                (KnowledgeEntry.agent_id == parent_agent_id)
                | (KnowledgeEntry.source_agent_name == parent_agent_id)
            )
            .all()
        )

        import uuid
        for entry in parent_entries:
            new_entry = KnowledgeEntry(
                id=str(uuid.uuid4()),
                agent_id=child_agent_id,
                title=f"[继承] {entry.title}",
                category=entry.category,
                tags=(entry.tags or []) + ["inherited"],
                situation=entry.situation,
                solution=entry.solution,
                caveats=entry.caveats,
                source_execution_ids=entry.source_execution_ids,
                source_agent_name=entry.source_agent_name,
                source_model=entry.source_model,
                retrieval_count=0,
                success_rate=entry.success_rate,
                confidence=(entry.confidence or 0.5) * 0.8,  # 继承降低置信度
                is_active=True,
            )
            db.add(new_entry)
            result["knowledge_entries_copied"] += 1

        # 2. 拷贝 GlobalKnowledge 标记（来源标记关联，不复制内容）
        from app.models.agent import GlobalKnowledge
        from datetime import datetime, timedelta

        # 查找父 Agent 贡献的全局知识
        parent_knowledge = (
            db.query(GlobalKnowledge)
            .filter(GlobalKnowledge.source_agent_id == parent_agent_id)
            .all()
        )
        # 将父 Agent 的全局知识也关联到子 Agent（scope）
        for gk in parent_knowledge:
            # 不直接修改，而是创建新的 scope 关联（scope_kind=agent, scope_id=child）
            # 如果已有相同内容的记录则跳过
            existing = (
                db.query(GlobalKnowledge)
                .filter(
                    GlobalKnowledge.content == gk.content,
                    GlobalKnowledge.scope_kind == "agent",
                    GlobalKnowledge.scope_id == child_agent_id,
                )
                .first()
            )
            if not existing:
                shared = GlobalKnowledge(
                    id=str(uuid.uuid4()),
                    content=gk.content,
                    embedding=gk.embedding,
                    source_agent_id=parent_agent_id,
                    source_user_id=gk.source_user_id,
                    tags=(gk.tags or []) + ["inherited_from_parent"],
                    confidence=gk.confidence or "medium",
                    scope_kind="agent",
                    scope_id=child_agent_id,
                    created_at=datetime.utcnow(),
                )
                db.add(shared)
                result["global_knowledge_shared"] += 1

        # 3. 拷贝 AgentLearningPattern
        from app.models.agent_learning_pattern import AgentLearningPattern

        parent_patterns = (
            db.query(AgentLearningPattern)
            .filter(
                AgentLearningPattern.scope_kind == "agent",
                AgentLearningPattern.scope_id == parent_agent_id,
            )
            .all()
        )

        for pattern in parent_patterns:
            new_pattern = AgentLearningPattern(
                id=str(uuid.uuid4()),
                scope_kind="agent",
                scope_id=child_agent_id,
                task_category=pattern.task_category,
                task_keywords=pattern.task_keywords,
                suggested_tools=pattern.suggested_tools,
                effectiveness_score=pattern.effectiveness_score,
                total_runs=1,  # 重置计数
                successful_runs=0,
                avg_iterations=pattern.avg_iterations,
                avg_tool_calls=pattern.avg_tool_calls,
                created_at=datetime.utcnow(),
                updated_at=datetime.utcnow(),
            )
            db.add(new_pattern)
            result["learning_patterns_copied"] += 1

        db.commit()
        logger.info(
            "Agent 知识继承完成: parent=%s → child=%s, entries=%d, global=%d, patterns=%d",
            parent_agent_id,
            child_agent_id,
            result["knowledge_entries_copied"],
            result["global_knowledge_shared"],
            result["learning_patterns_copied"],
        )

    except Exception as e:
        db.rollback()
        logger.error("Agent 知识继承失败: %s", e)
        raise
    finally:
        if should_close and db:
            db.close()

    return result


def get_parent_knowledge_context(
    agent_id: str,
    max_entries: int = 5,
    db: Optional[Session] = None,
) -> str:
    """
    获取 Agent 的父级知识上下文（用于注入 system prompt）。
    先查直接父 Agent，再查祖父 Agent（最多上溯 3 层）。
    """
    should_close = False
    if db is None:
        db = SessionLocal()
        should_close = True

    try:
        from app.models.agent import Agent
        from app.models.knowledge_entry import KnowledgeEntry

        # 收集祖先 Agent ID 列表（向上追溯最多 3 层）
        ancestor_ids: List[str] = []
        current_id = agent_id
        for _ in range(3):
            agent = db.query(Agent).filter(Agent.id == current_id).first()
            if not agent or not getattr(agent, "parent_agent_id", None):
                break
            parent_id = agent.parent_agent_id
            if parent_id in ancestor_ids:  # 防止循环引用
                break
            ancestor_ids.append(parent_id)
            current_id = parent_id

        if not ancestor_ids:
            return ""

        # 查询祖先 Agent 的高质量知识
        entries = (
            db.query(KnowledgeEntry)
            .filter(
                KnowledgeEntry.agent_id.in_(ancestor_ids),
                KnowledgeEntry.is_active == True,
                KnowledgeEntry.confidence >= 0.6,
            )
            .order_by(KnowledgeEntry.retrieval_count.desc())
            .limit(max_entries)
            .all()
        )

        if not entries:
            return ""

        lines = [f"## 父级 Agent 经验 ({len(entries)} 条)"]
        for i, entry in enumerate(entries, 1):
            tag_str = f"[{entry.category}]" if entry.category else ""
            sol = (entry.solution or "")[:300]
            lines.append(f"{i}. {tag_str} {entry.title}: {sol}")

        return "\n".join(lines)

    except Exception as e:
        logger.warning("获取父级知识上下文失败: %s", e)
        return ""
    finally:
        if should_close and db:
            db.close()