"""投顾 Agent HTTP 契约入口与本地业务编排。"""
from __future__ import annotations

import json
import re
from typing import Literal

from fastapi import APIRouter, BackgroundTasks, Depends, Query, Request
from fastapi.responses import StreamingResponse
from sqlalchemy.ext.asyncio import AsyncSession

from agent.advisor_agent.auth import ensure_customer_access
from agent.advisor_agent.intent.fund_analysis import build_fund_analysis
from agent.advisor_agent.intent.talk_script import build_talk_script
from agent.advisor_agent.llm import generate_text
from agent.advisor_agent.intent.generation_flow import (
    generate_rebalance_draft,
    generate_recommendation_draft,
)
from agent.advisor_agent.protocol import agent_failure, agent_success
from common.common_const import (
    AGENT_INTENT_RECOMMEND,
    CUSTOMER_REL_STATUS_SIGNED,
    ERR_CODE_DRAFT_NOT_FOUND,
    ERR_CODE_FORBIDDEN_CUSTOMER,
    ERR_CODE_LLM_ERROR,
    ERR_CODE_NOT_SIGNED_REBALANCE,
    DRAFT_STATUS_DISCARDED,
    DRAFT_STATUS_DRAFT,
    SSE_EVENT_TYPE_DONE,
    SSE_EVENT_TYPE_ERROR,
    SSE_EVENT_TYPE_META,
    SSE_EVENT_TYPE_TEXT,
)
from api.deps import audited_advisor
from config.deps import get_db
from config.database import mysql, redis as redis_db
from model.sys_user import SysUser
from repositories.advisor_draft import AdvisorDraftRepo
from repositories.customer_relation import CustomerRelationRepo
from service.advisor_agent.context import (
    load_fund_analysis_context,
    load_customer_risk,
    load_rebalance_context,
    load_recommendation_context,
)
from service.event_publisher import publish_event
from schemas.advisor_agent import (
    AdvisorDraftOperateReq,
    AdvisorDraftSaveReq,
    AdvisorChatReq,
    AdvisorFundAnalysisReq,
    AdvisorRebalanceRunReq,
    AdvisorTalkScriptReq,
)
from service.advisor_agent.draft import (
    detail_draft,
    discard_draft,
    ensure_draft_owner,
    get_draft as get_draft_service,
    list_drafts as list_drafts_service,
    save_draft as save_draft_service,
)
from utils.exceptions import ApiError
from utils.request_id import get_request_id, new_request_id
from utils.logger import get_logger


router = APIRouter(prefix="/advisor-agent")
logger = get_logger("advisor_agent.router")

_NOT_READY_CODE = ERR_CODE_LLM_ERROR
_NOT_READY_MESSAGE = "投顾 Agent 核心能力尚未初始化"
_DRAFT_NOT_FOUND_CODE = ERR_CODE_DRAFT_NOT_FOUND
_DRAFT_NOT_FOUND_MESSAGE = "草稿不存在或者已废弃"


def _trace_id(request: Request) -> str:
    return request.headers.get("X-Trace-Id") or get_request_id() or new_request_id()


def _not_ready(request: Request):
    return agent_failure(_NOT_READY_CODE, _NOT_READY_MESSAGE, trace_id=_trace_id(request))


def _advisor_runtime(request: Request):
    app = request.scope.get("app")
    return getattr(getattr(app, "state", None), "advisor_agent_runtime", None)


def _infer_chat_intent(query: str) -> str | None:
    """从自然语言问题推断投顾意图；无法确定时保留通用问答。"""
    if any(word in query for word in ("调仓", "再平衡", "组合偏离")):
        return "rebalance"
    if any(word in query for word in ("沟通话术", "怎么和客户说", "解释给客户")):
        return "dialogue-script"
    if any(word in query for word in ("基金分析", "分析这只基金", "分析产品")):
        return "fund_analysis"
    if any(word in query for word in ("推荐", "产品建议", "买什么基金", "适合的基金")):
        return AGENT_INTENT_RECOMMEND
    return None


async def _resolve_customer_from_query(db, *, advisor_id: int, query: str) -> tuple[int | None, str | None]:
    """解析问题中的客户编号或姓名，并限制在当前投顾客户范围内。"""
    number_match = re.search(r"(?:客户|用户)\s*[#编号号:]?\s*(\d+)", query)
    relation_repo = CustomerRelationRepo(db)
    if number_match:
        customer_id = int(number_match.group(1))
        relation = await relation_repo.get_active_relation(
            customer_id=customer_id,
            advisor_id=advisor_id,
        )
        if relation is None:
            return None, "问题中的客户不在当前投顾的授权范围内"
        return customer_id, None

    rows = await relation_repo.list_customer_rows(advisor_id=advisor_id, limit=100)
    matched = {
        int(account.id)
        for _relation, account, _profile in rows
        if account.real_name and account.real_name in query
    }
    if len(matched) == 1:
        return next(iter(matched)), None
    if len(matched) > 1:
        return None, "问题中的客户姓名无法唯一确定，请补充客户编号"
    if "客户" in query or "用户" in query:
        return None, "请在问题中补充客户编号或客户姓名"
    return None, None


async def _recall_advisor_memories(
    request: Request, *, customer_id: int, query: str
) -> list[dict]:
    """从应用共享 runtime 读取记忆；未装配或故障时安全降级为空。"""
    app = request.scope.get("app")
    state = getattr(app, "state", None)
    runtime = getattr(state, "advisor_agent_runtime", None)
    provider = getattr(runtime, "memory_provider", None)
    if provider is None:
        return []
    try:
        return await provider.recall(customer_id=customer_id, query=query)
    except Exception:
        logger.warning(
            "advisor memory recall failed: customer_id=%s", customer_id, exc_info=True
        )
        return []


async def _ensure_draft_access(db, draft, advisor_id: int) -> None:
    ensure_draft_owner(draft, advisor_id=advisor_id)
    await ensure_customer_access(
        db,
        advisor_id=advisor_id,
        customer_id=draft.customer_id,
    )


async def _run_rebalance_background(
    *, advisor_id: int, customer_id: int, trace_id: str
) -> None:
    """后台任务使用独立会话，避免请求返回后复用已关闭的请求会话。"""
    try:
        async with mysql.get_session_factory()() as task_db:
            relation = await ensure_customer_access(
                task_db, advisor_id=advisor_id, customer_id=customer_id
            )
            if relation.status != CUSTOMER_REL_STATUS_SIGNED:
                return
            context = await load_rebalance_context(task_db, customer_id=customer_id)
            if context is None:
                return
            await generate_rebalance_draft(
                draft_repo=AdvisorDraftRepo(task_db),
                publish=lambda **kwargs: publish_event(redis_db.client(), task_db, **kwargs),
                advisor_id=advisor_id,
                trace_id=trace_id,
                **context,
            )
    except Exception:
        logger.warning("advisor rebalance background task failed", exc_info=True)


@router.post("/chat/stream")
async def chat_stream(
    request: Request,
    body: AdvisorChatReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    trace_id = _trace_id(request)
    chat_request = body
    customer_id = chat_request.customer_id
    inferred_intent = chat_request.intent or _infer_chat_intent(chat_request.query)

    # 请求体只传问题时，从问题中解析客户；解析结果仍必须经过投顾关系授权校验。
    if customer_id is None:
        customer_id, resolve_error = await _resolve_customer_from_query(
            db,
            advisor_id=user.id,
            query=chat_request.query,
        )
        if resolve_error:
            payload = agent_failure(
                ERR_CODE_FORBIDDEN_CUSTOMER,
                resolve_error,
                trace_id=trace_id,
            )
            async def resolve_error_events():
                yield f"data: {json.dumps({'type': SSE_EVENT_TYPE_ERROR, **payload}, ensure_ascii=False)}\n\n"

            return StreamingResponse(
                resolve_error_events(),
                media_type="text/event-stream",
                headers={"X-Trace-Id": trace_id},
            )
        else:
            payload = None

    # 不带客户编号时只提供通用基金问答，不读取客户画像，也不生成个性化草稿。
    if customer_id is None:
        if inferred_intent in {
            AGENT_INTENT_RECOMMEND,
            "rebalance",
            "fund_analysis",
            "dialogue-script",
        }:
            if payload is None:
                payload = agent_failure(
                    ERR_CODE_FORBIDDEN_CUSTOMER,
                    "个性化投顾分析需要在问题中明确客户编号或姓名",
                    trace_id=trace_id,
                )
        else:
            runtime = _advisor_runtime(request)
            llm_client = getattr(runtime, "llm_client", None)
            if llm_client is None:
                answer = "已收到问题。当前未配置通用投顾模型，请选择客户后使用个性化分析，或联系管理员配置 Agent 服务。"
            else:
                answer = await generate_text(
                    llm_client,
                    system_prompt="你是基金投顾助手，只回答通用基金知识和产品分析问题，不读取或推断任何客户信息，不承诺收益，不代客交易。",
                    user_prompt=chat_request.query,
                    fallback=lambda: "当前模型暂时不可用，请稍后重试。",
                    timeout=5.0,
                )

            async def events():
                for event in (
                    {"type": SSE_EVENT_TYPE_META, "intent": "general_question"},
                    {"type": SSE_EVENT_TYPE_TEXT, "content": answer},
                    {"type": SSE_EVENT_TYPE_DONE},
                ):
                    yield f"data: {json.dumps(event, ensure_ascii=False)}\n\n"

            return StreamingResponse(
                events(),
                media_type="text/event-stream",
                headers={"X-Trace-Id": trace_id},
            )
    else:
        relation = await ensure_customer_access(
            db, advisor_id=user.id, customer_id=int(customer_id)
        )
        if inferred_intent == AGENT_INTENT_RECOMMEND:
            memories = await _recall_advisor_memories(
                request,
                customer_id=int(customer_id),
                query=chat_request.query,
            )
            runtime = _advisor_runtime(request)
            context = await load_recommendation_context(
                db, customer_id=int(customer_id)
            )
            if context is not None:
                draft = await generate_recommendation_draft(
                    draft_repo=AdvisorDraftRepo(db),
                    advisor_id=user.id,
                    relation_status=relation.status,
                    trace_id=trace_id,
                    memories=memories,
                    llm_client=getattr(runtime, "llm_client", None),
                    **context,
                )

                async def events():
                    for event in (
                        {
                            "type": SSE_EVENT_TYPE_META,
                            "draft_id": draft.draft_id,
                            "intent": draft.intent,
                            "status": draft.status,
                        },
                        {"type": SSE_EVENT_TYPE_TEXT, "content": draft.content},
                        {"type": SSE_EVENT_TYPE_DONE, "draft_id": draft.draft_id},
                    ):
                        yield f"data: {json.dumps(event, ensure_ascii=False)}\n\n"

                return StreamingResponse(
                    events(),
                    media_type="text/event-stream",
                    headers={"X-Trace-Id": trace_id},
                )
        payload = agent_failure(_NOT_READY_CODE, _NOT_READY_MESSAGE, trace_id=trace_id)

    async def events():
        yield f"data: {json.dumps({'type': SSE_EVENT_TYPE_ERROR, **payload}, ensure_ascii=False)}\n\n"

    return StreamingResponse(
        events(),
        media_type="text/event-stream",
        headers={"X-Trace-Id": trace_id},
    )


@router.get("/draft/list")
async def list_drafts(
    request: Request,
    advisor_id: int | None = Query(default=None),
    customer_id: int | None = Query(default=None),
    status: Literal[DRAFT_STATUS_DRAFT, DRAFT_STATUS_DISCARDED] | None = Query(default=None),
    page: int = Query(default=1, ge=1),
    page_size: int = Query(default=10, ge=1, le=100),
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    if advisor_id is not None and advisor_id != user.id:
        raise ApiError(ERR_CODE_FORBIDDEN_CUSTOMER, "无权操作该客户数据")
    if customer_id is not None:
        await ensure_customer_access(db, advisor_id=user.id, customer_id=customer_id)
    result = await list_drafts_service(
        AdvisorDraftRepo(db),
        advisor_id=user.id,
        customer_id=customer_id,
        status=status,
        page=page,
        page_size=page_size,
    )
    return agent_success(result, trace_id=_trace_id(request))


@router.get("/draft/{draft_id}")
async def get_draft(
    draft_id: str,
    request: Request,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    draft = await get_draft_service(AdvisorDraftRepo(db), draft_id)
    await _ensure_draft_access(db, draft, user.id)
    return agent_success(detail_draft(draft), trace_id=_trace_id(request))


@router.put("/draft/{draft_id}/save")
async def save_draft(
    draft_id: str,
    request: Request,
    body: AdvisorDraftSaveReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    repo = AdvisorDraftRepo(db)
    draft = await get_draft_service(repo, draft_id)
    await _ensure_draft_access(db, draft, user.id)
    customer_risk = await load_customer_risk(db, customer_id=draft.customer_id)
    result = await save_draft_service(
        repo,
        draft_id,
        title=body.title,
        content=body.content,
        structured_data=body.structured_data,
        customer_risk=customer_risk,
    )
    return agent_success(result, trace_id=_trace_id(request))


@router.post("/draft/{draft_id}/operate")
async def operate_draft(
    draft_id: str,
    request: Request,
    body: AdvisorDraftOperateReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    if body.operation != "discard":
        raise ApiError(_DRAFT_NOT_FOUND_CODE, "不支持的草稿操作")
    repo = AdvisorDraftRepo(db)
    draft = await get_draft_service(repo, draft_id)
    await _ensure_draft_access(db, draft, user.id)
    result = await discard_draft(repo, draft_id)
    return agent_success(detail_draft(result), trace_id=_trace_id(request))


@router.post("/rebalance/run")
async def run_rebalance(
    request: Request,
    body: AdvisorRebalanceRunReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
    background_tasks: BackgroundTasks = None,
):
    customer_id = body.customer_id
    relation = await ensure_customer_access(
        db, advisor_id=user.id, customer_id=int(customer_id)
    )
    if relation.status != CUSTOMER_REL_STATUS_SIGNED:
        return agent_failure(
            ERR_CODE_NOT_SIGNED_REBALANCE,
            "客户尚未签约，禁止生成调仓草稿",
            trace_id=_trace_id(request),
        )
    if background_tasks is None:
        background_tasks = BackgroundTasks()
    background_tasks.add_task(
        _run_rebalance_background,
        advisor_id=user.id,
        customer_id=customer_id,
        trace_id=_trace_id(request),
    )
    return agent_success(
        {"accepted": True, "status": "queued"},
        trace_id=_trace_id(request),
    )


@router.post("/fund-analysis")
async def fund_analysis(
    request: Request,
    body: AdvisorFundAnalysisReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    memories: list[dict] = []
    if body.customer_id is not None:
        await ensure_customer_access(
            db, advisor_id=user.id, customer_id=body.customer_id
        )
        memories = await _recall_advisor_memories(
            request,
            customer_id=body.customer_id,
            query=f"基金分析 {','.join(body.fund_codes)}",
        )
    fund = body.fund
    performance = body.performance
    if fund is None or performance is None:
        contexts = await load_fund_analysis_context(
            db,
            fund_codes=[str(code) for code in body.fund_codes],
        )
        if not contexts:
            return _not_ready(request)
        if len(contexts) == 1:
            fund = contexts[0]["fund"]
            performance = contexts[0]["performance"]
        else:
            return agent_success(
                {"items": [build_fund_analysis(item["fund"], item["performance"]) for item in contexts]},
                trace_id=_trace_id(request),
            )
    result = build_fund_analysis(fund, performance)
    runtime = _advisor_runtime(request)
    if getattr(runtime, "llm_client", None) is not None:
        result["analysis_text"] = await generate_text(
            runtime.llm_client,
            system_prompt="你是基金投顾助手，只基于给定历史数据生成谨慎的内部分析，不承诺收益。",
            user_prompt=json.dumps(
                {"analysis": result, "customer_memories": memories},
                ensure_ascii=False,
            ),
            fallback=lambda: result["analysis_text"],
            timeout=5.0,
        )
    return agent_success(result, trace_id=_trace_id(request))


@router.post("/generate-talk-script")
async def generate_talk_script(
    request: Request,
    body: AdvisorTalkScriptReq,
    user: SysUser = Depends(audited_advisor),
    db: AsyncSession = Depends(get_db),
):
    await ensure_customer_access(db, advisor_id=user.id, customer_id=body.customer_id)
    memories = await _recall_advisor_memories(
        request,
        customer_id=body.customer_id,
        query=f"沟通话术 {body.scene_type}",
    )
    try:
        result = build_talk_script(
            body.scene_type,
            customer_name=body.customer_name,
        )
    except ValueError as exc:
        raise ApiError(ERR_CODE_LLM_ERROR, str(exc)) from exc
    runtime = _advisor_runtime(request)
    if getattr(runtime, "llm_client", None) is not None:
        result["content"] = await generate_text(
            runtime.llm_client,
            system_prompt="你是合规的基金投顾助手，只生成谨慎沟通话术，不承诺收益、不代客交易。",
            user_prompt=json.dumps(
                {"script": result, "customer_memories": memories},
                ensure_ascii=False,
            ),
            fallback=lambda: result["content"],
            timeout=5.0,
        )
    return agent_success(result, trace_id=_trace_id(request))