{"repo": "478201622/plugins", "files": {"astrbot_plugin_gemini_image_generation/tl/api/sensenova.py": {"8c3cecfe5267332ca9713fc70ab6c3d09677c9d4": {"t": 1785768260.8589282, "n": 8302, "h": "4d7976962410102b", "c": "\"\"\"SenseNova（商汤日日新）图像生成供应商实现。\n\n支持模型：\n- ``sensenova-u1-fast``：基于 SenseNova U1 的加速版本，专供信息图（Infographics）生成场景。\n\n\"\"\"\n\nfrom __future__ import annotations\n\nfrom typing import Any\n\nimport aiohttp\nfrom astrbot.api import logger\n\nfrom ..api_types import APIError, ApiRequestConfig\nfrom ..tl_utils import save_base64_image\nfrom .base import ProviderRequest\n\n# 官方默认 API Base\n_DEFAULT_API_BASE: str = \"https://token.sensenova.cn\"\n\n# 默认模型\n_DEFAULT_MODEL: str = \"sensenova-u1-fast\"\n\n# 11 种官方支持的尺寸（width x height）\n_ALLOWED_SIZES: tuple[str, ...] = (\n    \"1664x2496\",  # 2:3\n    \"2496x1664\",  # 3:2\n    \"1760x2368\",  # 3:4\n    \"2368x1760\",  # 4:3\n    \"1824x2272\",  # 4:5\n    \"2272x1824\",  # 5:4\n    \"2048x2048\",  # 1:1\n    \"2752x1536\",  # 16:9\n    \"1536x2752\",  # 9:16\n    \"3072x1376\",  # 21:9\n    \"1344x3136\",  # 9:21\n)\n\n# aspect_ratio → size 映射（覆盖插件配置中所有 aspect_ratio 选项）\n_ASPECT_TO_SIZE: dict[str, str] = {\n    \"1:1\": \"2048x2048\",\n    \"2:3\": \"1664x2496\",\n    \"3:2\": \"2496x1664\",\n    \"3:4\": \"1760x2368\",\n    \"4:3\": \"2368x1760\",\n    \"4:5\": \"1824x2272\",\n    \"5:4\": \"2272x1824\",\n    \"16:9\": \"2752x1536\",\n    \"9:16\": \"1536x2752\",\n    \"21:9\": \"3072x1376\",\n    \"9:21\": \"1344x3136\",\n}\n\n_DEFAULT_SIZE: str = \"2752x1536\"\n\n# prompt 最大 token 数\n_PROMPT_CHAR_SOFT_LIMIT: int = 4096\n\n\ndef _normalize_aspect_ratio(value: Any) -> str | None:\n    \"\"\"将 'WxH' / 'W×H' / 'W:H' 归一化为 'W:H'。\"\"\"\n    if value is None:\n        return None\n    text = str(value).strip().lower().replace(\"×\", \":\").replace(\"x\", \":\")\n    if \":\" not in text:\n        return None\n    parts = text.split(\":\", 1)\n    try:\n        w = int(parts[0].strip())\n        h = int(parts[1].strip())\n    except (TypeError, ValueError):\n        return None\n    if w <= 0 or h <= 0:\n        return None\n    return f\"{w}:{h}\"\n\n\ndef _resolve_size(\n    *,\n    explicit_size: Any,\n    aspect_ratio: str | None,\n    default_size: str | None,\n) -> str:\n    \"\"\"决定最终 size。\n\n    优先级：\n    1. ``explicit_size`` 合法且在白名单 → 直接使用\n    2. ``aspect_ratio`` 能映射到白名单 → 使用映射结果\n    3. ``default_size`` 合法且在白名单 → 使用\n    4. 兜底使用 ``_DEFAULT_SIZE``\n    \"\"\"\n    if explicit_size:\n        text = str(explicit_size).strip().lower().replace(\"×\", \"x\")\n        if text in _ALLOWED_SIZES:\n            return text\n        logger.warning(\n            \"[sensenova] 显式 size=%s 不在官方支持列表，将根据 aspect_ratio 重选\",\n            explicit_size,\n        )\n\n    ratio = _normalize_aspect_ratio(aspect_ratio)\n    if ratio and ratio in _ASPECT_TO_SIZE:\n        return _ASPECT_TO_SIZE[ratio]\n    if ratio:\n        logger.info(\n            \"[sensenova] aspect_ratio=%s 不在官方支持列表，将回退到默认尺寸\", ratio\n        )\n\n    if default_size:\n        text = str(default_size).strip().lower().replace(\"×\", \"x\")\n        if text in _ALLOWED_SIZES:\n            return text\n        logger.warning(\n            \"[sensenova] sensenova_settings.default_size=%s 非法，已忽略\", default_size\n        )\n\n    return _DEFAULT_SIZE\n\n\ndef _coerce_n(value: Any, default: int = 1) -> int:\n    try:\n        n = int(value)\n    except (TypeError, ValueError):\n        return default\n    return max(1, min(n, 4))\n\n\ndef _ensure_v1_endpoint(api_base: str) -> str:\n    base = (api_base or \"\").strip().rstrip(\"/\")\n    if not base:\n        base = _DEFAULT_API_BASE\n    if base.endswith(\"/v1\"):\n        return f\"{base}/images/generations\"\n    return f\"{base}/v1/images/generations\"\n\n\nclass SenseNovaProvider:\n    \"\"\"SenseNova ``/v1/images/generations`` 端点实现。\"\"\"\n\n    name = \"sensenova\"\n\n    async def build_request(\n        self, *, client: Any, config: ApiRequestConfig\n    ) -> ProviderRequest:  # noqa: ANN401\n        settings: dict[str, Any] = (\n            getattr(config, \"provider_settings\", None)\n            or getattr(client, \"sensenova_settings\", None)\n            or {}\n        )\n\n        api_base = config.api_base or settings.get(\"api_base\") or _DEFAULT_API_BASE\n        url = _ensure_v1_endpoint(str(api_base))\n\n        if not config.api_key:\n            raise APIError(\n                \"SenseNova 缺少 API Key，请在 provider_overrides.sensenova.api_keys 中配置\",\n                None,\n                \"missing_api_key\",\n                retryable=False,\n            )\n\n        # 参考图不支持，给出明确日志而非静默\n        if config.reference_images:\n            logger.info(\n                \"[sensenova] U1 Fast 不支持图像输入，已忽略 %d 张参考图\",\n                len(config.reference_images),\n            )\n\n        prompt = (config.prompt or \"\").strip()\n        if not prompt:\n            raise APIError(\n                \"SenseNova 需要非空 prompt\", None, \"empty_prompt\", retryable=False\n            )\n        if len(prompt) > _PROMPT_CHAR_SOFT_LIMIT:\n            logger.warning(\n                \"[sensenova] prompt 长度 %d 超过软上限 %d，可能被服务端截断\",\n                len(prompt),\n                _PROMPT_CHAR_SOFT_LIMIT,\n            )\n\n        model = (\n            config.model or settings.get(\"model\") or _DEFAULT_MODEL\n        ).strip() or _DEFAULT_MODEL\n\n        size = _resolve_size(\n            explicit_size=settings.get(\"size\"),\n            aspect_ratio=config.aspect_ratio,\n            default_size=settings.get(\"default_size\"),\n        )\n\n        n = _coerce_n(settings.get(\"n\", 1))\n\n        payload: dict[str, Any] = {\n            \"model\": model,\n            \"prompt\": prompt,\n            \"size\": size,\n            \"n\": n,\n        }\n\n        headers = {\n            \"Authorization\": f\"Bearer {config.api_key}\",\n            \"Content-Type\": \"application/json\",\n        }\n\n        logger.debug(\n            \"[sensenova] build_request: url=%s model=%s size=%s n=%s prompt_len=%s\",\n            url,\n            model,\n            size,\n            n,\n            len(prompt),\n        )\n        return ProviderRequest(url=url, headers=headers, payload=payload)\n\n    async def parse_response(\n        self,\n        *,\n        client: Any,\n        response_data: dict[str, Any],\n        session: aiohttp.ClientSession,\n        api_base: str | None = None,\n        http_status: int | None = None,\n        request_config: ApiRequestConfig | None = None,\n    ) -> tuple[list[str], list[str], str | None, str | None]:  # noqa: ANN401\n        image_urls: list[str] = []\n        image_paths: list[str] = []\n\n        data = response_data.get(\"data\")\n        if not isinstance(data, list) or not data:\n            error_obj = response_data.get(\"error\")\n            if error_obj:\n                error_msg = (\n                    error_obj.get(\"message\", \"未知错误\")\n                    if isinstance(error_obj, dict)\n                    else str(error_obj)\n                )\n                raise APIError(\n                    f\"SenseNova 图像生成失败: {error_msg}\",\n                    http_status,\n                    \"api_error\",\n                    error_obj.get(\"code\") if isinstance(error_obj, dict) else None,\n                    retryable=False,\n                )\n            raise APIError(\n                \"SenseNova 响应缺少 data 字段\",\n                http_status,\n                \"invalid_response\",\n                retryable=True,\n            )\n\n        for item in data:\n            if not isinstance(item, dict):\n                continue\n            url = item.get(\"url\")\n            if isinstance(url, str) and url:\n                if client._request_has_proxy(request_config):\n                    _, image_path = await client._download_image(\n                        url,\n                        session,\n                        use_cache=False,\n                        proxy=client._request_http_proxy(request_config),\n                    )\n                    if image_path:\n                        image_urls.append(image_path)\n                        image_paths.append(image_path)\n                    continue\n                image_urls.append(url)\n                logger.debug(\"[sensenova] 图片 URL: %s...\", url[:80])\n                continue\n            b64 = item.get(\"b64_json\")\n            if isinstance(b64, str) and b64:\n                saved = await save_base64_image(b64, \"png\")\n                if saved:\n                    image_urls.append(saved)\n                    image_paths.append(saved)\n\n        if not image_urls:\n            raise APIError(\n                \"SenseNova 未返回图片数据\",\n                http_status,\n                \"no_image\",\n                retryable=False,\n            )\n\n        logger.debug(\"[sensenova] 共 %d 张图片\", len(image_urls))\n        return image_urls, image_paths, None, None\n"}}}}