"""投顾意图结果到草稿与事件的编排。"""
from __future__ import annotations

from decimal import Decimal
import json

from agent.advisor_agent.intent.draft_generation import (
    build_rebalance_draft,
    build_recommendation_draft,
)
from common.common_const import EVENT_ADVISOR_REBALANCE_DRAFT_CREATED
from service.advisor_agent.draft import create_draft
from agent.advisor_agent.llm import generate_text


async def generate_rebalance_draft(
    *,
    draft_repo,
    publish,
    customer_id: int,
    advisor_id: int,
    customer_risk: str,
    relation_status: str,
    holdings: list[dict],
    target_allocation: dict[str, int | float | Decimal],
    threshold: Decimal,
    candidates: list[dict],
    trace_id: str,
) -> dict | None:
    draft_data = build_rebalance_draft(
        customer_id=customer_id,
        advisor_id=advisor_id,
        customer_risk=customer_risk,
        relation_status=relation_status,
        holdings=holdings,
        target_allocation=target_allocation,
        threshold=threshold,
        candidates=candidates,
    )
    if draft_data is None:
        return None

    draft = await create_draft(draft_repo, draft_data)
    event_id = await publish(
        event_name=EVENT_ADVISOR_REBALANCE_DRAFT_CREATED,
        trace_id=trace_id,
        trigger_user_id=advisor_id,
        customer_id=customer_id,
        payload={
            "draft_id": draft.draft_id,
            "customer_id": customer_id,
            "advisor_id": advisor_id,
            "deviation": float(draft.deviation or 0),
            "created_at": draft.create_time.isoformat()
            if draft.create_time
            else None,
        },
    )
    return {"draft": draft, "event_id": event_id}


async def generate_recommendation_draft(
    *,
    draft_repo,
    customer_id: int,
    advisor_id: int,
    customer_risk: str,
    relation_status: str,
    candidates: list[dict],
    trace_id: str,
    memories: list[dict] | None = None,
    llm_client=None,
    llm_timeout: float = 5.0,
):
    draft_data = build_recommendation_draft(
        customer_id=customer_id,
        advisor_id=advisor_id,
        customer_risk=customer_risk,
        candidates=candidates,
        relation_status=relation_status,
        memories=memories,
    )
    if llm_client is not None:
        draft_data["content"] = await generate_text(
            llm_client,
            system_prompt="你是基金投顾助手，只生成内部投顾草稿说明，不下单、不承诺收益。",
            user_prompt=(
                "请根据以下候选基金和客户记忆生成简洁推荐说明："
                + json.dumps(
                    {"candidates": candidates, "memories": memories or []},
                    ensure_ascii=False,
                )
            ),
            fallback=lambda: draft_data["content"],
            timeout=llm_timeout,
        )
    return await create_draft(draft_repo, draft_data)