from __future__ import annotations

from typing import Any

from app.agents.schemas.learning import SessionRetrospective


def _classify_task_type(query_text: str) -> str:
    normalized = (query_text or "").lower()
    if any(token in normalized for token in ("总结", "分析", "对比", "report", "analyze")):
        return "analysis"
    if any(token in normalized for token in ("安排", "提醒", "日程", "todo", "task")):
        return "planning_or_execution"
    if any(token in normalized for token in ("文档", "资料", "年报", "search", "查")):
        return "retrieval"
    return "general"


def build_session_retrospective(
    *,
    request_id: str,
    session_id: str,
    user_query: str,
    state: dict[str, Any] | None,
    runtime_context: dict[str, Any] | None = None,
) -> SessionRetrospective:
    state = state or {}
    if hasattr(runtime_context, "model_dump"):
        runtime_context = runtime_context.model_dump(mode="json")
    runtime_context = runtime_context or {}
    skill_shortlist = state.get("skill_shortlist") or []
    used_skill_names = [
        item.get("skill_name")
        for item in skill_shortlist
        if isinstance(item, dict) and item.get("skill_name")
    ]

    task_refs = []
    for task in (state.get("completed_tasks") or [])[:4]:
        if isinstance(task, dict):
            task_refs.append(
                {
                    "task_id": task.get("task_id"),
                    "title": task.get("title"),
                    "status": task.get("status"),
                }
            )

    event_refs = []
    for event in (state.get("event_trace") or [])[:8]:
        if isinstance(event, dict):
            event_refs.append(
                {
                    "event_type": event.get("event_type"),
                    "task_id": event.get("task_id"),
                    "agent_id": event.get("agent_id"),
                }
            )

    verification_evidence = []
    for evidence in (state.get("verification_evidence") or [])[:6]:
        if isinstance(evidence, dict):
            verification_evidence.append(evidence)

    verification_status = state.get("verification_status")
    execution_mode = state.get("execution_mode")
    primary_agent = state.get("current_agent") or "master"
    retrospective_shortlist = state.get("retrospective_shortlist") or []

    summary_parts = [
        f"本轮请求按 {execution_mode or 'unknown'} 模式处理",
        f"主要负责 agent 为 {primary_agent}",
    ]
    if verification_status:
        summary_parts.append(f"验证结果为 {verification_status}")
    if used_skill_names:
        summary_parts.append(f"命中技能候选 {', '.join(used_skill_names[:3])}")
    if retrospective_shortlist:
        summary_parts.append(f"参考了 {len(retrospective_shortlist)} 条历史复盘")

    final_response = state.get("final_response")
    outcome = "completed" if final_response else "failed"
    if not final_response and verification_status == "passed":
        outcome = "completed"
    if final_response and verification_status == "skipped":
        outcome = "partial"

    return SessionRetrospective(
        retrospective_id=request_id,
        user_id=str(runtime_context.get("user_id") or ""),
        conversation_id=session_id,
        response_message_id=request_id,
        query_text=user_query,
        final_response=final_response,
        summary="；".join(summary_parts) + "。",
        task_type=_classify_task_type(user_query),
        execution_mode=execution_mode,
        primary_agent=primary_agent,
        verification_status=verification_status,
        verification_summary=state.get("verification_summary"),
        used_skill_names=used_skill_names,
        evidence_refs=verification_evidence,
        task_refs=task_refs,
        event_refs=event_refs,
        context_snapshot={
            "runtime_request_context": runtime_context,
            "recommended_runtime_mode": runtime_context.get("recommended_runtime_mode"),
            "parallel_worthiness": state.get("parallel_worthiness"),
            "retrospective_shortlist_count": len(retrospective_shortlist),
            "scheduled_subtask_count": len(state.get("scheduled_subtasks") or []),
            "merge_report": dict(state.get("merge_report") or {}),
            "verification_report": dict(state.get("verification_report") or {}),
        },
        outcome=outcome,
    )