modelhub-submit-agent/main.py

"""
ModelHub 全云端提交智能体
部署在平台容器中，直接从内网提交验证任务

功能：
- POST /run    → 触发一次完整流程（搜索→筛选→提交）
- GET /status  → 查看当前状态
- GET /health  → 健康检查
"""

import json
import os
import signal
import sqlite3
import threading
import time
import traceback
from datetime import datetime
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from urllib.parse import urlparse, parse_qs

import requests
import yaml

# ============================================================
# 配置
# ============================================================

HOST = "0.0.0.0"
PORT = 8080
STRATEGY_ID = os.getenv("STRATEGY_ID", "")

# 四个账号的 Token
ACCOUNTS = {
    'MetaX_c-500': 'f8e60d1dac7f4472967e7ca40145747b',
    'Kunlunxin_p-800': 'f45f1aae2c094426be237c88b1085015',
    'Ascend_910-b4': 'f3c05879e7c34bbba92f399f12884183',
    'hygon_k100-ai': 'b88507029b884ad3b4bad8ba09e6546e',
}

# GPU 引擎配置
GPU_CONFIGS = {
    'MetaX_c-500': {
        'framework': 'vllm',
        'docker_image': 'modelhubxc-4pd.tencentcloudcr.com/enginex/enginex-metax/vllm:0.9.1',
    },
    'Kunlunxin_p-800': {
        'framework': 'vllm',
        'docker_image': 'modelhubxc-4pd.tencentcloudcr.com/enginex/sunjichen/xc-llm-kunlun:latest',
    },
    'Ascend_910-b4': {
        'framework': 'vllm',
        'docker_image': 'git.modelhub.org.cn:9443/enginex-ascend/vllm-ascend:v0.11.0rc0',
    },
    'hygon_k100-ai': {
        'framework': 'llama.cpp',
        'docker_image': 'modelhubxc-4pd.tencentcloudcr.com/enginex/enginex-hygon/hygon-llama.cpp:b7516',
    },
}

# 架构白名单
SUPPORTED_ARCH_KEYWORDS = ['Qwen', 'Qwen2', 'Qwen3']
SUPPORTED_MODEL_TYPES = [
    'qwen', 'qwen2', 'qwen2_vl', 'qwen2_5_vl', 'qwen2_audio',
    'qwen3', 'qwen3_vl', 'qwen3_5', 'qwen3_5_moe',
]
SUPPORTED_SPECIAL_ARCHS = ['Eagle3Speculator', 'LlamaForCausalLMEagle3']

MODELSCOPE_API = "https://modelscope.cn/api/v1"
MODELHUB_API = "https://modelhub.org.cn/api"

# 搜索关键词
SEARCH_KEYWORDS = ['qwen', 'Qwen2', 'Qwen3', 'Qwen3.5', 'Qwen1.5', 'Qwen-']

# ============================================================
# 全局状态
# ============================================================

state = {
    'running': False,
    'last_run': None,
    'last_result': None,
    'logs': [],
}
state_lock = threading.Lock()


def log(msg: str):
    ts = datetime.now().strftime('%H:%M:%S')
    line = f"[{ts}] {msg}"
    print(line, flush=True)
    with state_lock:
        state['logs'].append(line)
        if len(state['logs']) > 500:
            state['logs'] = state['logs'][-300:]


# ============================================================
# 数据库（内存 SQLite）
# ============================================================

db_conn = None


def init_db():
    global db_conn
    db_conn = sqlite3.connect(':memory:', check_same_thread=False)
    db_conn.execute('''CREATE TABLE IF NOT EXISTS queue (
        model_id TEXT, gpu TEXT, url TEXT, downloads INTEGER,
        params TEXT, category TEXT, score REAL,
        PRIMARY KEY(model_id, gpu)
    )''')
    db_conn.execute('''CREATE TABLE IF NOT EXISTS submitted (
        model_id TEXT, gpu TEXT, task_id TEXT, submitted_at TEXT,
        PRIMARY KEY(model_id, gpu)
    )''')
    db_conn.commit()


# ============================================================
# ModelScope 搜索
# ============================================================

def search_models(keyword: str, limit: int = 100) -> list:
    """从 ModelScope 搜索模型"""
    url = "https://modelscope.cn/openapi/v1/models"
    params = {
        'search': keyword,
        'page_size': limit,
        'page_number': 1,
        'sort': 'downloads',
    }
    try:
        resp = requests.get(url, params=params, timeout=20,
                            headers={'User-Agent': 'Mozilla/5.0'})
        data = resp.json()
        if data.get('success'):
            models = data.get('data', {}).get('models', [])
            log(f"  搜索 [{keyword}]: status={resp.status_code} models={len(models)}")
            return models
        else:
            log(f"  搜索 [{keyword}]: success=false, data={str(data)[:200]}")
    except Exception as e:
        log(f"  搜索失败 [{keyword}]: {e}")
    return []


def check_architecture(model_id: str) -> tuple:
    """检查模型架构"""
    try:
        cfg_url = f"{MODELSCOPE_API}/models/{model_id}/repo?Revision=master&FilePath=config.json"
        resp = requests.get(cfg_url, timeout=10)
        if resp.status_code == 200:
            cfg = resp.json()
            archs = cfg.get('architectures', [])
            mtype = cfg.get('model_type', '')
            arch_str = str(archs)
            for special in SUPPORTED_SPECIAL_ARCHS:
                if special in arch_str:
                    return True, special
            for kw in SUPPORTED_ARCH_KEYWORDS:
                if kw in arch_str:
                    return True, kw
            if mtype in SUPPORTED_MODEL_TYPES:
                return True, mtype
            return False, f"arch={archs} type={mtype}"
        mid_upper = model_id.upper()
        if 'QWEN3' in mid_upper or 'QWEN2' in mid_upper:
            return True, "GGUF"
        return False, "no config, not Qwen"
    except Exception as e:
        return True, f"check error: {e}"


def normalize_model_url(model_url: str) -> str:
    """标准化 URL 格式"""
    if '/models/' in model_url:
        return model_url
    if 'modelscope.cn/' in model_url:
        parts = model_url.split('modelscope.cn/')
        if len(parts) == 2:
            return f"https://www.modelscope.cn/models/{parts[1]}"
    return model_url


# ============================================================
# 平台 API
# ============================================================

def check_platform_verify(model_id: str) -> dict:
    """查询全平台验证状态"""
    headers = {'Xc-Token': list(ACCOUNTS.values())[0], 'Accept': 'application/json'}
    url = f"{MODELHUB_API}/computility/models/search-by-model-id"
    try:
        resp = requests.get(url, headers=headers, params={'modelId': model_id}, timeout=10)
        data = resp.json()
        if data.get('code') == 0:
            return data.get('data', {}).get('verifyResult', {})
    except Exception:
        pass
    return {}


def check_my_submitted(model_id: str, gpu: str, token: str) -> bool:
    """检查自己是否已提交"""
    headers = {'Xc-Token': token, 'Accept': 'application/json'}
    url = f"{MODELHUB_API}/adapt/task/page"
    try:
        resp = requests.get(url, headers=headers, params={
            'current': 1, 'pageSize': 100, 'onlyMine': 'true',
            'gpuType': gpu, 'modelId': model_id,
        }, timeout=10)
        data = resp.json()
        if data.get('code') == 0:
            records = data.get('data', {}).get('records', [])
            for r in records:
                if r.get('modelId') == model_id and r.get('gpuType') == gpu:
                    status = r.get('status', '')
                    if status in ('waiting', 'running', 'success'):
                        return True
    except Exception:
        pass
    return False


def check_queue_available(gpu: str, token: str) -> int:
    """查询队列可用位置"""
    headers = {'Xc-Token': token, 'Accept': 'application/json'}
    url = f"{MODELHUB_API}/adapt/task/page"
    try:
        resp = requests.get(url, headers=headers, params={
            'current': 1, 'pageSize': 1, 'onlyMine': 'true',
            'gpuType': gpu, 'status': 'waiting',
        }, timeout=10)
        data = resp.json()
        if data.get('code') == 0:
            waiting = int(data['data'].get('total', 0))
            return max(0, 100 - waiting)
    except Exception:
        pass
    return -1


def build_config_params(gpu: str) -> str:
    """构建 YAML 配置"""
    config = GPU_CONFIGS.get(gpu, {})
    framework = config.get('framework', 'vllm')
    docker_image = config.get('docker_image', '')

    if framework == 'llama.cpp':
        params = {
            'framework': 'llama.cpp',
            'docker_image': docker_image,
            'nv_docker_image': docker_image,
            'api': 'completion',
            'max_tokens': 1024,
            'temperature': 0.7,
            'repetition_penalty': 1.2,
            'top_p': 0.9,
            'lang': 'zh',
            'max_model_len': 4096,
            'modelFormat': 'GGUF',
            'sut_config': {
                'values': {
                    'gpu_num': 1,
                    'command': [
                        '/bin/bash', '-ic',
                        'llama-server --model /model --alias llm --threads 20 '
                        '--n-gpu-layers 999 --prio 3 --min_p 0.01 '
                        '--ctx-size 4096 --host 0.0.0.0 --port 8000 --jinja --flash-attn off'
                    ]
                }
            },
            'ref_config': {
                'values': {
                    'cpu_num': 2, 'gpu_num': 1,
                    'command': [
                        'llama-server', '--model', '/model', '--alias', 'llm',
                        '--threads', '20', '--n-gpu-layers', '999',
                        '--ctx-size', '4096', '--host', '0.0.0.0', '--port', '8000',
                    ]
                }
            },
            'model': 'llm',
        }
    else:
        params = {
            'framework': 'vllm',
            'docker_image': docker_image,
            'nv_docker_image': docker_image,
            'api': 'completion',
            'max_tokens': 1024,
            'temperature': 0.7,
            'repetition_penalty': 1.2,
            'top_p': 0.9,
            'lang': 'zh',
            'max_model_len': 2048,
            'modelFormat': 'HuggingFace',
            'sut_config': {
                'values': {
                    'gpu_num': 1,
                    'command': [
                        '/bin/bash', '-ic',
                        'vllm serve /model --port 8000 --served-model-name llm '
                        '--max-model-len 2048 --dtype auto --gpu-memory-utilization 0.95 '
                        '-tp 1 --enforce-eager --trust-remote-code'
                    ]
                }
            },
            'ref_config': {
                'values': {
                    'cpu_num': 2, 'gpu_num': 1,
                    'command': [
                        'vllm', 'serve', '/model', '--port', '8000',
                        '--served-model-name', 'llm', '--max-model-len', '2048',
                        '--dtype', 'auto', '--gpu-memory-utilization', '0.95',
                        '-tp', '1', '--enforce-eager', '--trust-remote-code',
                    ]
                }
            },
            'model': 'llm',
        }
    return yaml.dump(params, default_flow_style=False, allow_unicode=True)


def submit_model(model_url: str, gpu: str, token: str) -> tuple:
    """提交单个模型"""
    headers = {
        'Xc-Token': token,
        'Accept': 'application/json',
        'Content-Type': 'application/json',
    }
    url = f"{MODELHUB_API}/adapt/task/add"
    config = GPU_CONFIGS.get(gpu, {})
    payload = {
        'modelAddress': normalize_model_url(model_url),
        'taskType': 'text-generation',
        'targetGpu': gpu,
        'framework': config.get('framework', 'vllm'),
        'strategyId': STRATEGY_ID,
        'configParams': build_config_params(gpu),
    }
    try:
        resp = requests.post(url, headers=headers, json=payload, timeout=30)
        data = resp.json()
        if data.get('code') == 0:
            task_id = data.get('data', {}).get('id')
            return True, task_id, 'success'
        return False, None, data.get('message', 'unknown error')
    except Exception as e:
        return False, None, str(e)


# ============================================================
# 主流程
# ============================================================

def run_pipeline(gpus: list = None, submit_limit: int = 30):
    """完整流程：搜索→筛选→提交"""
    if gpus is None:
        gpus = list(GPU_CONFIGS.keys())

    init_db()
    log("=" * 50)
    log("开始执行流程")
    log(f"目标GPU: {', '.join(gpus)}")
    log(f"提交限制: 每GPU {submit_limit} 个")

    # 1. 搜索
    log("\n--- 阶段1: 搜索 ModelScope ---")
    seen = set()
    all_models = []
    for kw in SEARCH_KEYWORDS:
        models = search_models(kw, limit=100)
        for m in models:
            mid = m.get('id', '')
            if mid and mid not in seen:
                seen.add(mid)
                downloads = m.get('downloads', 0)
                if downloads >= 50:
                    all_models.append({
                        'model_id': mid,
                        'url': f"https://modelscope.cn/{mid}",
                        'downloads': downloads,
                        'params': m.get('params', ''),
                        'category': 'quantized' if 'GGUF' in mid.upper() else 'standard',
                    })
        time.sleep(0.3)
    log(f"搜索完成: {len(seen)} 个唯一模型, {len(all_models)} 个下载量>=50")

    # 2. 架构筛选
    log("\n--- 阶段2: 架构筛选 ---")
    arch_passed = []
    arch_rejected = 0
    for m in all_models:
        ok, reason = check_architecture(m['model_id'])
        if ok:
            arch_passed.append(m)
        else:
            arch_rejected += 1
            log(f"  ✗ {m['model_id']}: {reason}")
        time.sleep(0.15)
    log(f"架构筛选: {len(arch_passed)} 通过, {arch_rejected} 拒绝")

    # 3. 按 GPU 筛选并提交
    log("\n--- 阶段3: 筛选并提交 ---")
    total_submitted = 0
    for gpu in gpus:
        token = ACCOUNTS.get(gpu)
        if not token:
            continue

        log(f"\n[{gpu}]")

        # 检查队列
        available = check_queue_available(gpu, token)
        if available <= 0:
            log(f"  队列满，跳过")
            continue
        log(f"  队列可用: {available}")

        # 筛选
        to_submit = []
        for m in arch_passed:
            model_id = m['model_id']

            # hygon 只接受 GGUF
            if gpu == 'hygon_k100-ai' and 'GGUF' not in model_id.upper():
                continue

            # 检查全平台验证状态
            verify = check_platform_verify(model_id)
            if gpu in verify:
                continue  # 已有记录，跳过

            # 检查自己是否已提交
            if check_my_submitted(model_id, gpu, token):
                continue

            to_submit.append(m)
            if len(to_submit) >= min(submit_limit, available):
                break
            time.sleep(0.2)

        log(f"  待提交: {len(to_submit)}")

        # 提交
        submitted = 0
        for m in to_submit:
            ok, task_id, msg = submit_model(m['url'], gpu, token)
            if ok:
                submitted += 1
                log(f"  ✅ {m['model_id']}")
                db_conn.execute(
                    'INSERT OR REPLACE INTO submitted VALUES (?,?,?,?)',
                    (m['model_id'], gpu, str(task_id), datetime.now().isoformat())
                )
            else:
                log(f"  ❌ {m['model_id']}: {msg}")
            time.sleep(0.5)

        log(f"  提交完成: {submitted}/{len(to_submit)}")
        total_submitted += submitted

    db_conn.commit()
    log(f"\n{'=' * 50}")
    log(f"流程完成，共提交 {total_submitted} 个模型")
    return total_submitted


# ============================================================
# HTTP 服务
# ============================================================

class AgentHandler(BaseHTTPRequestHandler):
    def do_GET(self):
        parsed = urlparse(self.path)
        path = parsed.path

        if path == '/health':
            self._json({'status': 'ok'})
        elif path == '/':
            self._json({
                'name': 'modelhub-submit-agent',
                'strategy_id': STRATEGY_ID,
                'status': 'running' if state['running'] else 'idle',
                'last_run': state['last_run'],
                'last_result': state['last_result'],
            })
        elif path == '/test':
            self._json(self._run_connectivity_test())
        elif path == '/status':
            self._json({
                'running': state['running'],
                'last_run': state['last_run'],
                'last_result': state['last_result'],
                'queue_count': db_conn.execute('SELECT COUNT(*) FROM queue').fetchone()[0] if db_conn else 0,
                'submitted_count': db_conn.execute('SELECT COUNT(*) FROM submitted').fetchone()[0] if db_conn else 0,
            })
        elif path == '/logs':
            lines = int(parse_qs(parsed.query).get('lines', ['50'])[0])
            self._json({'logs': state['logs'][-lines:]})
        else:
            self._json({'error': 'not found'}, 404)

    def do_POST(self):
        parsed = urlparse(self.path)
        path = parsed.path

        if path == '/run':
            if state['running']:
                self._json({'error': 'already running'}, 409)
                return

            # 读取请求体
            content_len = int(self.headers.get('Content-Length', 0))
            body = {}
            if content_len > 0:
                body = json.loads(self.rfile.read(content_len))

            gpus = body.get('gpus', list(GPU_CONFIGS.keys()))
            limit = body.get('limit', 30)

            self._json({'status': 'started', 'gpus': gpus, 'limit': limit})

            # 后台运行
            def _run():
                try:
                    state['running'] = True
                    state['last_run'] = datetime.now().isoformat()
                    count = run_pipeline(gpus=gpus, submit_limit=limit)
                    state['last_result'] = {'submitted': count, 'success': True}
                except Exception as e:
                    log(f"流程异常: {traceback.format_exc()}")
                    state['last_result'] = {'error': str(e), 'success': False}
                finally:
                    state['running'] = False

            threading.Thread(target=_run, daemon=True).start()
        else:
            self._json({'error': 'not found'}, 404)

    def _run_connectivity_test(self) -> dict:
        """测试各 API 连通性"""
        results = {}

        # 1. ModelScope 搜索 API
        try:
            resp = requests.get(
                'https://modelscope.cn/openapi/v1/models',
                params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
                timeout=10,
                headers={'User-Agent': 'Mozilla/5.0'}
            )
            results['modelscope_search'] = {
                'status': resp.status_code,
                'ok': resp.status_code == 200,
                'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
            }
        except Exception as e:
            results['modelscope_search'] = {'ok': False, 'error': str(e)}

        # 2. ModelScope config.json API
        try:
            resp = requests.get(
                'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
                timeout=10,
            )
            results['modelscope_config'] = {
                'status': resp.status_code,
                'ok': resp.status_code == 200,
                'body_preview': resp.text[:200] if resp.status_code == 200 else resp.text[:100],
            }
        except Exception as e:
            results['modelscope_config'] = {'ok': False, 'error': str(e)}

        # 3. ModelHub 查询 API
        try:
            token = list(ACCOUNTS.values())[0]
            resp = requests.get(
                'https://modelhub.org.cn/api/adapt/task/page',
                headers={'Xc-Token': token, 'Accept': 'application/json'},
                params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
                timeout=10,
            )
            data = resp.json()
            results['modelhub_query'] = {
                'ok': data.get('code') == 0,
                'code': data.get('code'),
                'total': data.get('data', {}).get('total'),
            }
        except Exception as e:
            results['modelhub_query'] = {'ok': False, 'error': str(e)}

        # 4. ModelHub 提交 API (dry test)
        try:
            token = list(ACCOUNTS.values())[0]
            resp = requests.post(
                'https://modelhub.org.cn/api/adapt/task/add',
                headers={'Xc-Token': token, 'Accept': 'application/json', 'Content-Type': 'application/json'},
                json={
                    'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
                    'taskType': 'text-generation',
                    'targetGpu': 'Kunlunxin_p-800',
                    'framework': 'vllm',
                    'strategyId': STRATEGY_ID,
                    'configParams': 'framework: vllm\n',
                },
                timeout=10,
            )
            data = resp.json()
            results['modelhub_submit'] = {
                'ok': data.get('code') == 0,
                'code': data.get('code'),
                'message': data.get('message', '')[:100],
            }
        except Exception as e:
            results['modelhub_submit'] = {'ok': False, 'error': str(e)}

        return results

    def _json(self, body: dict, status: int = 200):
        payload = json.dumps(body, ensure_ascii=False).encode()
        self.send_response(status)
        self.send_header('Content-Type', 'application/json; charset=utf-8')
        self.send_header('Content-Length', str(len(payload)))
        self.end_headers()
        self.wfile.write(payload)

    def log_message(self, fmt, *args):
        pass  # 静默 HTTP 日志


# ============================================================
# 启动
# ============================================================

shutdown_requested = False


def _handle_signal(signum, _frame):
    global shutdown_requested
    shutdown_requested = True
    log(f"收到信号 {signum}，准备关闭")


def main():
    signal.signal(signal.SIGTERM, _handle_signal)
    signal.signal(signal.SIGINT, _handle_signal)

    init_db()

    server = ThreadingHTTPServer((HOST, PORT), AgentHandler)
    server.timeout = 1

    log(f"智能体启动 | {HOST}:{PORT}")
    log(f"STRATEGY_ID: {STRATEGY_ID}")
    log(f"GPU: {', '.join(GPU_CONFIGS.keys())}")

    # 启动后自动运行连通性测试
    def _startup_test():
        time.sleep(2)
        log("=" * 50)
        log("连通性测试开始")
        log("=" * 50)

        # 1. ModelScope 搜索
        try:
            resp = requests.get(
                'https://modelscope.cn/openapi/v1/models',
                params={'search': 'qwen', 'page_size': 2, 'sort': 'downloads'},
                timeout=10, headers={'User-Agent': 'Mozilla/5.0'}
            )
            if resp.status_code == 200:
                data = resp.json()
                models = data.get('data', {}).get('models', [])
                log(f"[ModelScope搜索] ✅ status={resp.status_code} models={len(models)}")
                for m in models[:2]:
                    log(f"  {m.get('id')} downloads={m.get('downloads')}")
            else:
                log(f"[ModelScope搜索] ❌ status={resp.status_code} body={resp.text[:100]}")
        except Exception as e:
            log(f"[ModelScope搜索] ❌ error={e}")

        # 2. ModelScope config.json
        try:
            resp = requests.get(
                'https://modelscope.cn/api/v1/models/Qwen/Qwen3-8B/repo?Revision=master&FilePath=config.json',
                timeout=10
            )
            if resp.status_code == 200:
                cfg = resp.json()
                log(f"[ModelScope配置] ✅ arch={cfg.get('architectures')} type={cfg.get('model_type')}")
            else:
                log(f"[ModelScope配置] ❌ status={resp.status_code}")
        except Exception as e:
            log(f"[ModelScope配置] ❌ error={e}")

        # 3. ModelHub 查询
        try:
            token = list(ACCOUNTS.values())[0]
            resp = requests.get(
                'https://modelhub.org.cn/api/adapt/task/page',
                headers={'Xc-Token': token, 'Accept': 'application/json'},
                params={'current': 1, 'pageSize': 1, 'onlyMine': 'true'},
                timeout=10
            )
            data = resp.json()
            if data.get('code') == 0:
                log(f"[ModelHub查询] ✅ total={data['data'].get('total')}")
            else:
                log(f"[ModelHub查询] ❌ code={data.get('code')} msg={data.get('message','')[:80]}")
        except Exception as e:
            log(f"[ModelHub查询] ❌ error={e}")

        # 4. ModelHub 提交
        try:
            token = list(ACCOUNTS.values())[0]
            resp = requests.post(
                'https://modelhub.org.cn/api/adapt/task/add',
                headers={'Xc-Token': token, 'Accept': 'application/json', 'Content-Type': 'application/json'},
                json={
                    'modelAddress': 'https://www.modelscope.cn/models/Qwen/Qwen3-8B',
                    'taskType': 'text-generation', 'targetGpu': 'Kunlunxin_p-800',
                    'framework': 'vllm', 'strategyId': STRATEGY_ID,
                    'configParams': 'framework: vllm\n',
                }, timeout=10
            )
            data = resp.json()
            log(f"[ModelHub提交] code={data.get('code')} msg={data.get('message','')[:80]}")
        except Exception as e:
            log(f"[ModelHub提交] ❌ error={e}")

        log("=" * 50)
        log("连通性测试完成")
        log("=" * 50)

        # 开始正式提交流程
        log("\n自动触发提交流程...")
        try:
            state['running'] = True
            state['last_run'] = datetime.now().isoformat()
            count = run_pipeline(submit_limit=30)
            state['last_result'] = {'submitted': count, 'success': True}
        except Exception as e:
            log(f"流程异常: {traceback.format_exc()}")
            state['last_result'] = {'error': str(e), 'success': False}
        finally:
            state['running'] = False

    threading.Thread(target=_startup_test, daemon=True).start()

    while not shutdown_requested:
        server.handle_request()

    server.server_close()
    log("智能体已关闭")


if __name__ == '__main__':
    main()