"""样本中心 API 客户端服务。"""

import httpx
import time
from typing import Any

from app.config import get_settings
from app.core.logging import logger

settings = get_settings()

# Token 缓存（内存中）
_token_cache: dict[str, Any] = {}


def _get_base_url() -> str:
    if not settings.sample_center_base_url:
        raise ValueError("样本中心地址未配置，请检查 SAMPLE_CENTER_BASE_URL 环境变量")
    return settings.sample_center_base_url.rstrip("/")


def _get_credentials() -> tuple[str, str]:
    if not settings.sample_center_app_id or not settings.sample_center_app_secret:
        raise ValueError("样本中心凭证未配置，请检查 SAMPLE_CENTER_APP_ID 和 SAMPLE_CENTER_APP_SECRET")
    return settings.sample_center_app_id, settings.sample_center_app_secret


def _check_token_valid() -> bool:
    if not _token_cache.get("access_token"):
        return False
    expires_at = _token_cache.get("expires_at", 0)
    return time.time() < expires_at - 300  # 提前 5 分钟过期


async def get_token() -> str:
    if _check_token_valid():
        return _token_cache["access_token"]

    app_id, app_secret = _get_credentials()
    base_url = _get_base_url()

    async with httpx.AsyncClient(timeout=30) as client:
        resp = await client.post(
            f"{base_url}/api/v1/auth/token",
            json={"app_id": app_id, "app_secret": app_secret},
        )
        resp.raise_for_status()
        body = resp.json()

    if body.get("code") != "000000":
        raise RuntimeError(f"获取样本中心 Token 失败: {body.get('message')}")

    data = body["data"]
    _token_cache["access_token"] = data["access_token"]
    _token_cache["expires_in"] = data.get("expires_in", 7200)
    _token_cache["expires_at"] = time.time() + data.get("expires_in", 7200)
    _token_cache["token_type"] = data.get("token_type", "Bearer")

    return data["access_token"]


def _auth_headers() -> dict[str, str]:
    app_id, _ = _get_credentials()
    token = _token_cache.get("access_token", "")
    return {
        "Authorization": f"Bearer {token}",
        "X-App-Id": app_id,
        "Content-Type": "application/json",
    }


async def list_knowledge_bases(page: int = 1, page_size: int = 20) -> dict[str, Any]:
    """获取知识库列表。"""
    token = await get_token()
    base_url = _get_base_url()

    async with httpx.AsyncClient(timeout=30) as client:
        resp = await client.get(
            f"{base_url}/api/v1/knowledge-bases",
            params={"page": page, "page_size": page_size},
            headers=_auth_headers(),
        )
        resp.raise_for_status()
        body = resp.json()

    if body.get("code") != "000000":
        raise RuntimeError(f"获取知识库列表失败: {body.get('message')}")

    return body["data"]


async def get_knowledge_base_detail(kb_id: str) -> dict[str, Any]:
    """获取知识库详情。"""
    token = await get_token()
    base_url = _get_base_url()

    async with httpx.AsyncClient(timeout=30) as client:
        resp = await client.get(
            f"{base_url}/api/v1/knowledge-bases/{kb_id}",
            headers=_auth_headers(),
        )
        resp.raise_for_status()
        body = resp.json()

    if body.get("code") != "000000":
        raise RuntimeError(f"获取知识库详情失败: {body.get('message')}")

    return body["data"]


async def batch_import(kb_id: str, parents: list[dict], children: list[dict] | None = None,
                       callback_url: str | None = None) -> dict[str, Any]:
    """提交批量入库任务。"""
    import uuid

    token = await get_token()
    base_url = _get_base_url()
    task_no = f"IMP{int(time.time())}{uuid.uuid4().hex[:8]}"

    payload: dict[str, Any] = {
        "task_no": task_no,
        "parents": parents,
    }
    if children:
        payload["children"] = children
    if callback_url:
        payload["callback_url"] = callback_url

    async with httpx.AsyncClient(timeout=60) as client:
        resp = await client.post(
            f"{base_url}/api/v1/knowledge-bases/{kb_id}/batch-import",
            json=payload,
            headers=_auth_headers(),
        )
        resp.raise_for_status()
        body = resp.json()

    if body.get("code") != "000000":
        raise RuntimeError(f"批量入库提交失败: {body.get('message')}")

    return body["data"]


async def query_import_task(task_id: str) -> dict[str, Any]:
    """查询批量入库任务状态。"""
    token = await get_token()
    base_url = _get_base_url()

    async with httpx.AsyncClient(timeout=30) as client:
        resp = await client.get(
            f"{base_url}/api/v1/knowledge-bases/batch-import/{task_id}",
            headers=_auth_headers(),
        )
        resp.raise_for_status()
        body = resp.json()

    if body.get("code") != "000000":
        raise RuntimeError(f"查询任务失败: {body.get('message')}")

    return body["data"]


async def import_kb_to_dataset(kb_id: str, kb_name: str) -> dict[str, Any]:
    """从知识库导入数据：查询知识库详情，将数据转为训练格式并保存为数据集。

    由于样本中心的批量入库是异步任务，这里采用直接查询知识库内容的方式。
    先获取知识库详情，然后根据 metadata_schema 构建训练数据集。
    """
    kb_detail = await get_knowledge_base_detail(kb_id)

    # 这里返回知识库信息，前端可据此展示给用户
    # 实际的数据导入由批量入库 API 完成
    return {
        "kb_id": kb_id,
        "kb_name": kb_name or kb_detail.get("name", ""),
        "document_count": kb_detail.get("document_count", 0),
        "metadata_schema": kb_detail.get("metadata_schema", []),
        "parent_table": kb_detail.get("parent_table", ""),
        "child_table": kb_detail.get("child_table", ""),
    }