"""SSH 远程执行模块 — 在算力节点上运行 GPU 任务。"""
import json
import os
import subprocess
from typing import Any

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

settings = get_settings()


def _get_ssh_prefix() -> list[str]:
    """构建 ssh/scp 命令前缀，支持密钥或密码登录。"""
    prefix = ["-o", "StrictHostKeyChecking=no", "-o", "ConnectTimeout=10"]
    return prefix


def scp_to_remote(local_path: str, remote_path: str) -> tuple[int, str, str]:
    """通过 SCP 把本地文件复制到远端主机，返回 (exit_code, stdout, stderr)。"""
    target = f"{settings.compute_node_ssh_user}@{settings.compute_node_host}"
    scp_args = ["scp", *_get_ssh_prefix(), "-P", str(settings.compute_node_ssh_port)]
    if settings.compute_node_ssh_key:
        scp_args += ["-i", settings.compute_node_ssh_key]
    elif settings.compute_node_ssh_password:
        scp_args = ["sshpass", "-p", settings.compute_node_ssh_password] + scp_args
    scp_args += [local_path, f"{target}:{remote_path}"]

    try:
        proc = subprocess.run(scp_args, capture_output=True, text=True, timeout=30)
        clean_stderr = "\n".join(line for line in proc.stderr.split("\n")
                                  if not line.startswith("Warning:"))
        return proc.returncode, proc.stdout, clean_stderr
    except Exception as e:
        logger.error(f"SCP failed: {e}")
        return -1, "", str(e)


def ssh_exec(cmd: str, timeout: int | None = None) -> tuple[int, str, str]:
    """通过 SSH 在算力节点执行命令，返回 (exit_code, stdout, stderr)。"""
    if not settings.use_remote_compute:
        raise RuntimeError("未配置算力节点（compute_node_host 为空）")

    target = f"{settings.compute_node_ssh_user}@{settings.compute_node_host}"
    ssh_args = [
        "ssh", *_get_ssh_prefix(),
        "-p", str(settings.compute_node_ssh_port),
        target,
        cmd,
    ]

    # sshpass 需要包裹 ssh 命令，而不是作为 ssh 的参数
    if settings.compute_node_ssh_key:
        ssh_args = ["ssh", "-i", settings.compute_node_ssh_key] + ssh_args[1:]
    elif settings.compute_node_ssh_password:
        ssh_args = ["sshpass", "-p", settings.compute_node_ssh_password] + ssh_args

    timeout = timeout or settings.compute_node_ssh_timeout
    try:
        proc = subprocess.run(
            ssh_args,
            capture_output=True,
            text=True,
            timeout=timeout,
        )
        # 过滤 known_hosts 警告，这些不算真正的错误
        clean_stderr = "\n".join(line for line in proc.stderr.split("\n")
                                  if not line.startswith("Warning:"))
        return proc.returncode, proc.stdout, clean_stderr
    except subprocess.TimeoutExpired:
        logger.error(f"SSH command timeout after {timeout}s: {cmd[:100]}")
        return -1, "", f"Command timed out after {timeout}s"
    except Exception as e:
        logger.error(f"SSH exec failed: {e}")
        return -1, "", str(e)


def run_training_remote(
    job_id: str,
    model_id: str,
    model_type: str,
    dataset_id: str,
    config: dict[str, Any],
) -> str | None:
    """在算力节点启动训练任务（通过 docker exec，后台执行）。

    通过 docker exec -i 将配置传入容器内，避免宿主机/容器路径混淆。
    """
    import base64

    config_json = json.dumps(config, ensure_ascii=False)
    config_b64 = base64.b64encode(config_json.encode()).decode()
    config_file = f"/tmp/config_{job_id}.json"

    # 通过 docker exec -i 把配置传入容器内，在容器里写入临时文件并启动训练
    remote_cmd = (
        f"echo '{config_b64}' | base64 -d | "
        f"docker exec -i {settings.compute_node_docker_container} bash -c '"
        f"cat > {config_file} && "
        f"cd {settings.compute_node_workdir} && "
        f"nohup {settings.compute_node_python} -m app.engines.remote_train "
        f"{job_id} {model_id} {model_type} {dataset_id} {config_file} "
        f">/tmp/train_{job_id}.log 2>&1 & echo $!'"
    )

    code, stdout, stderr = ssh_exec(remote_cmd, timeout=30)

    if code != 0:
        logger.error(f"Remote training launch failed: {stderr}")
        return None

    pid = stdout.strip()
    logger.info(f"Remote training launched in container: job={job_id}, container_pid={pid}")
    return pid


def is_process_running(pid: str) -> bool:
    """检查远程训练进程是否还在运行。

    通过 docker exec 进入容器检查 PID 是否存在。
    """
    cmd = f"docker exec {settings.compute_node_docker_container} bash -c 'kill -0 {pid} 2>/dev/null && echo running || echo stopped'"
    code, stdout, stderr = ssh_exec(cmd, timeout=10)
    return code == 0 and "running" in stdout


def run_inference_remote(
    model_id: str,
    adapter_id: str,
    prompt: str,
    max_new_tokens: int,
    temperature: float,
    top_p: float,
    repetition_penalty: float,
    do_sample: bool,
) -> dict[str, Any] | None:
    """在算力节点执行推理。"""
    safe_prompt = prompt.replace('"', '\\"').replace("'", "\\'").replace("\n", "\\n")

    remote_cmd = (
        f"docker exec {settings.compute_node_docker_container} "
        f"{settings.compute_node_python} -c \""
        "import asyncio, json; "
        "from app.config import get_settings; "
        "settings = get_settings(); "
        "from app.services.inference_service import run_inference_single; "
        f"result = asyncio.run(run_inference_single("
        f"'{model_id}', '{adapter_id}', '{safe_prompt}', "
        f"{max_new_tokens}, {temperature}, {top_p}, {repetition_penalty}, {str(do_sample).lower()}"
        ")); "
        "print(json.dumps(result, ensure_ascii=False))\" 2>&1"
    )

    code, stdout, stderr = ssh_exec(remote_cmd, timeout=600)

    if code != 0:
        logger.error(f"Remote inference failed: {stderr}")
        return {"error": stderr.strip() or "Remote inference failed"}

    # 提取最后一行 JSON
    for line in reversed(stdout.strip().split("\n")):
        line = line.strip()
        if line.startswith("{"):
            try:
                return json.loads(line)
            except json.JSONDecodeError:
                continue

    return {"error": f"Invalid JSON response: {stdout[:500]}"}