# 创建根目录
mkdir -p ~/.openclaw

# 启动openclaw容器
docker run -d \
  --name openclaw \
  --restart unless-stopped \
  --memory="3g" \
  --memory-swap="6g" \
  --memory-reservation="1g" \
  --shm-size="2gb" \
  -e TZ=Asia/Shanghai \
  -v ~/.openclaw:/home/node/.openclaw \
  -p 3000:3000 \
  ghcr.io/openclaw/openclaw:latest

# 进行openclaw配置
docker exec -it openclaw openclaw onboard

# 安装微信插件
docker exec -it -u node openclaw npx -y @tencent-weixin/openclaw-weixin-cli@latest install

# 1. 创建一个 2GB 的交换文件 (可以根据需要把 2G 改为 4G)
sudo fallocate -l 2G /swapfile

# 2. 设置正确的权限（仅 root 可读写，出于安全考虑）
sudo chmod 600 /swapfile

# 3. 将文件格式化为交换分区
sudo mkswap /swapfile

# 4. 启用交换文件
sudo swapon /swapfile

# 5. 验证是否成功
sudo swapon --show

# 6. 设置开机自动挂载
echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab

gateway connect failed: Error: gateway closed (1000): 
◇  
Gateway not reachable. Is it running and accessible?
Gateway target: ws://127.0.0.1:18789
Source: local loopback
Config: /home/node/.openclaw/openclaw.json
Bind: loopback

# 创建根目录
mkdir -p ~/.hermes

# 启动容器，配置模型/消息通道
docker run -it --rm \
  -v ~/.hermes:/opt/data \
  nousresearch/hermes-agent setup

# 启动gateway
docker run -d \
  --name hermes \
  --restart unless-stopped \
  -v ~/.hermes:/opt/data \
  nousresearch/hermes-agent gateway run

Hi~ I don't recognize you yet!

Here's your pairing code: `RLU2WUYX`

Ask the bot owner to run:
`hermes pairing approve weixin RLU2WUYX`

auxiliary:
  # Image analysis (vision_analyze tool + browser screenshots)
  vision:
    provider: "auto"           # "auto", "openrouter", "nous", "codex", "main", etc.
    model: ""                  # e.g. "openai/gpt-4o", "google/gemini-2.5-flash"
    base_url: ""               # Custom OpenAI-compatible endpoint (overrides provider)
    api_key: ""                # API key for base_url (falls back to OPENAI_API_KEY)
    timeout: 120               # seconds — LLM API call timeout; vision payloads need generous timeout
    download_timeout: 30       # seconds — image HTTP download; increase for slow connections

def _handle_vision_analyze(args: Dict[str, Any], **kw: Any) -> Awaitable[str]:
    image_url = args.get("image_url", "")
    question = args.get("question", "")
    full_prompt = (
        "Fully describe and explain everything about this image, then answer the "
        f"following question:\n\n{question}"
    )
    // 从env文件获取vision模型
    model = os.getenv("AUXILIARY_VISION_MODEL", "").strip() or None
    return vision_analyze_tool(image_url, full_prompt, model)

// 注册工具
registry.register(
    name="vision_analyze",
    toolset="vision",
    schema=VISION_ANALYZE_SCHEMA,
    handler=_handle_vision_analyze,
    check_fn=check_vision_requirements,
    is_async=True,
    emoji="👁️",
)

    """
    Analyze an image from a URL or local file path using vision AI.
    
    This tool accepts either an HTTP/HTTPS URL or a local file path. For URLs,
    it downloads the image first. In both cases, the image is converted to base64
    and processed using Gemini 3 Flash Preview via OpenRouter API.
    
    The user_prompt parameter is expected to be pre-formatted by the calling
    function (typically model_tools.py) to include both full description
    requests and specific questions.
    
    Args:
        image_url (str): The URL or local file path of the image to analyze.
                         Accepts http://, https:// URLs or absolute/relative file paths.
        user_prompt (str): The pre-formatted prompt for the vision model
        model (str): The vision model to use (default: google/gemini-3-flash-preview)
    
    Returns:
        str: JSON string containing the analysis results with the following structure:
             {
                 "success": bool,
                 "analysis": str (defaults to error message if None)
             }
    
    Raises:
        Exception: If download fails, analysis fails, or API key is not set
        
    Note:
        - For URLs, temporary images are stored in ./temp_vision_images/ and cleaned up
        - For local file paths, the file is used directly and NOT deleted
        - Supports common image formats (JPEG, PNG, GIF, WebP, etc.)
    """

def _read_main_model() -> str:
    """Read the user's configured main model from config.yaml.

    config.yaml model.default is the single source of truth for the active
    model. Environment variables are no longer consulted.
    """
    try:
        from hermes_cli.config import load_config
        cfg = load_config()
        model_cfg = cfg.get("model", {})
        if isinstance(model_cfg, str) and model_cfg.strip():
            return model_cfg.strip()
        if isinstance(model_cfg, dict):
            default = model_cfg.get("default", "")
            if isinstance(default, str) and default.strip():
                return default.strip()
    except Exception:
        pass
    return ""


def _read_main_provider() -> str:
    """Read the user's configured main provider from config.yaml.

    Returns the lowercase provider id (e.g. "alibaba", "openrouter") or ""
    if not configured.
    """
    try:
        from hermes_cli.config import load_config
        cfg = load_config()
        model_cfg = cfg.get("model", {})
        if isinstance(model_cfg, dict):
            provider = model_cfg.get("provider", "")
            if isinstance(provider, str) and provider.strip():
                return provider.strip().lower()
    except Exception:
        pass
    return ""

_VISION_AUTO_PROVIDER_ORDER = (
    "openrouter",
    "nous",
)

def _resolve_strict_vision_backend(provider: str) -> Tuple[Optional[Any], Optional[str]]:
    provider = _normalize_vision_provider(provider)
    if provider == "openrouter":
        return _try_openrouter()
    if provider == "nous":
        return _try_nous(vision=True)
    if provider == "openai-codex":
        return _try_codex()
    if provider == "anthropic":
        return _try_anthropic()
    if provider == "custom":
        return _try_custom_endpoint()
    return None, None

def _try_openrouter() -> Tuple[Optional[OpenAI], Optional[str]]:
    pool_present, entry = _select_pool_entry("openrouter")
    if pool_present:
        or_key = _pool_runtime_api_key(entry)
        if not or_key:
            return None, None
        base_url = _pool_runtime_base_url(entry, OPENROUTER_BASE_URL) or OPENROUTER_BASE_URL
        logger.debug("Auxiliary client: OpenRouter via pool")
        return OpenAI(api_key=or_key, base_url=base_url,
                       default_headers=_OR_HEADERS), _OPENROUTER_MODEL

    or_key = os.getenv("OPENROUTER_API_KEY")
    if not or_key:
        return None, None
    logger.debug("Auxiliary client: OpenRouter")
    return OpenAI(api_key=or_key, base_url=OPENROUTER_BASE_URL,
                   default_headers=_OR_HEADERS), _OPENROUTER_MODEL

# Default auxiliary models per provider
_OPENROUTER_MODEL = "google/gemini-3-flash-preview"
_NOUS_MODEL = "google/gemini-3-flash-preview"
_NOUS_FREE_TIER_VISION_MODEL = "xiaomi/mimo-v2-omni"
_NOUS_FREE_TIER_AUX_MODEL = "xiaomi/mimo-v2-pro"
_NOUS_DEFAULT_BASE_URL = "https://inference-api.nousresearch.com/v1"
_ANTHROPIC_DEFAULT_BASE_URL = "https://api.anthropic.com"
_AUTH_JSON_PATH = get_hermes_home() / "auth.json"