{"repo": "aihubmix/skills", "files": {"skills/aihubmixApi/scripts/aihubmixApi.py": {"53938717da78fb7d59acd3309791aca792326c13": {"t": 1785674652.5670595, "n": 114387, "h": "ffa0f7d6056a0a20", "c": "#!/usr/bin/env python3\n\"\"\"\nSmall AIHubMix API helper for Codex skills.\n\nThe script intentionally keeps volatile model data out of the skill. It reads\nmodel metadata from the live models API by default, or from a caller-provided\nJSON file for local validation.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport argparse\nfrom datetime import datetime\nimport io\nimport json\nimport os\nimport platform\nimport re\nimport shutil\nimport subprocess\nimport sys\nimport tarfile\nimport textwrap\nimport urllib.error\nimport urllib.request\nfrom pathlib import Path\nfrom typing import Any\n\n\n# Force UTF-8 stdout/stderr so Chinese output is not mangled to GBK mojibake\n# on Windows or when the stream is redirected/piped (default code page there\n# is cp936, not UTF-8).\nfor _stream in (sys.stdout, sys.stderr):\n    try:\n        _stream.reconfigure(encoding=\"utf-8\")\n    except (AttributeError, ValueError):  # non-reconfigurable stream\n        pass\n\n\n# Output language for status lines/labels: \"en\" (default, neutral) or \"zh\".\n# Set via the global --lang flag or AIHUBMIX_LANG; main() resolves it into _LANG.\n_LANG = (os.environ.get(\"AIHUBMIX_LANG\") or \"en\").strip().lower()\nif _LANG not in (\"en\", \"zh\"):\n    _LANG = \"en\"\n\n\ndef _t(en: str, zh: str) -> str:\n    \"\"\"Pick output text by the resolved language (data values are never translated).\"\"\"\n    return zh if _LANG == \"zh\" else en\n\n\nDEFAULT_MODELS_URL = \"https://aihubmix.com/api/v1/models\"\nDEFAULT_SERVER_URL = \"https://aihubmix.com\"\nDEFAULT_PRICE_UNIT = \"USD / 1M tokens\"\nSDK_PACKAGE_NAME = \"@aihubmix/ai-sdk-provider\"\nSDK_RECOMMENDED_VERSION = \"2.1.0\"\nSDK_REGISTRY_URL = \"https://registry.npmjs.org/@aihubmix%2Fai-sdk-provider\"\nOPENAPI_REPO_URL = \"https://github.com/AIhubmix/aihubmix-openapi\"\nOPENAPI_JSON_URL = \"https://aihubmix.com/openapi.json\"\nCONTRACT_JSON_URL = \"https://aihubmix.com/contract.json\"\nGATEWAY_ERRORS_URL = \"https://github.com/AIhubmix/aihubmix-openapi/blob/main/gateway/errors.yml\"\n\n# Companion `aihubmix` CLI. The repo URL is the durable anchor shown everywhere\n# (stable even if the install scripts move); the raw install scripts are the\n# per-OS executable entrypoints, derived from the same repo path so there is a\n# single source of truth and the CLI can always be re-found.\nCLI_BIN = \"aihubmix\"\nCLI_REPO = \"AIhubmix/platfrom-cli\"\nCLI_REPO_URL = f\"https://github.com/{CLI_REPO}\"\nCLI_RAW_BASE = f\"https://raw.githubusercontent.com/{CLI_REPO}/main\"\nCLI_INSTALL_PS1 = f\"{CLI_RAW_BASE}/install.ps1\"\nCLI_INSTALL_SH = f\"{CLI_RAW_BASE}/install.sh\"\n\nPROTOCOL_ALIASES = {\n    \"chat\": \"chat\",\n    \"chat-completions\": \"chat\",\n    \"model-response\": \"responses\",\n    \"model-responses\": \"responses\",\n    \"response\": \"responses\",\n    \"completion\": \"completions\",\n    \"embedding\": \"embeddings\",\n    \"image\": \"images\",\n    \"image-generation\": \"images\",\n    \"video\": \"videos\",\n    \"retrieve-video\": \"video-retrieve\",\n    \"download-video\": \"video-content\",\n    \"video-download\": \"video-content\",\n    \"remix-video\": \"video-remix\",\n    \"speech\": \"audio-speech\",\n    \"tts\": \"audio-speech\",\n    \"transcription\": \"audio-transcriptions\",\n    \"translation\": \"audio-translations\",\n    \"moderation\": \"moderations\",\n    \"message\": \"messages\",\n    \"anthropic\": \"messages\",\n    \"generate-content\": \"gemini\",\n    \"vertex\": \"gemini\",\n    \"google\": \"gemini\",\n}\n\nPROTOCOL_SPECS: dict[str, dict[str, Any]] = {\n    \"chat\": {\n        \"label\": \"OpenAI-Compatible Chat\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/chat/completions\",\n        \"family\": \"openai\",\n    },\n    \"responses\": {\n        \"label\": \"OpenAI Model Responses\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/responses\",\n        \"family\": \"openai\",\n    },\n    \"completions\": {\n        \"label\": \"OpenAI-Compatible Legacy Completion\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/completions\",\n        \"family\": \"openai\",\n    },\n    \"embeddings\": {\n        \"label\": \"OpenAI-Compatible Embeddings\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/embeddings\",\n        \"family\": \"openai\",\n    },\n    \"images\": {\n        \"label\": \"OpenAI-Compatible Image Generation\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/images/generations\",\n        \"family\": \"openai\",\n    },\n    \"videos\": {\n        \"label\": \"OpenAI-Compatible Video Creation\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/videos\",\n        \"family\": \"openai\",\n    },\n    \"video-retrieve\": {\n        \"label\": \"OpenAI-Compatible Video Retrieval\",\n        \"method\": \"GET\",\n        \"path\": \"/v1/videos/{video_id}\",\n        \"family\": \"openai\",\n        \"needs_video_id\": True,\n    },\n    \"video-delete\": {\n        \"label\": \"OpenAI-Compatible Video Deletion\",\n        \"method\": \"DELETE\",\n        \"path\": \"/v1/videos/{video_id}\",\n        \"family\": \"openai\",\n        \"needs_video_id\": True,\n    },\n    \"video-content\": {\n        \"label\": \"OpenAI-Compatible Video Content Download\",\n        \"method\": \"GET\",\n        \"path\": \"/v1/videos/{video_id}/content\",\n        \"family\": \"openai\",\n        \"needs_video_id\": True,\n    },\n    \"video-remix\": {\n        \"label\": \"OpenAI-Compatible Video Remix\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/videos/{video_id}/remix\",\n        \"family\": \"openai\",\n        \"needs_video_id\": True,\n    },\n    \"audio-speech\": {\n        \"label\": \"OpenAI-Compatible Speech\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/audio/speech\",\n        \"family\": \"openai\",\n        \"binary_response\": True,\n    },\n    \"audio-transcriptions\": {\n        \"label\": \"OpenAI-Compatible Audio Transcription\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/audio/transcriptions\",\n        \"family\": \"openai\",\n        \"multipart\": True,\n    },\n    \"audio-translations\": {\n        \"label\": \"OpenAI-Compatible Audio Translation\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/audio/translations\",\n        \"family\": \"openai\",\n        \"multipart\": True,\n    },\n    \"moderations\": {\n        \"label\": \"OpenAI-Compatible Moderation\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/moderations\",\n        \"family\": \"openai\",\n    },\n    \"messages\": {\n        \"label\": \"Claude/Anthropic-Compatible Messages\",\n        \"method\": \"POST\",\n        \"path\": \"/v1/messages\",\n        \"family\": \"anthropic\",\n    },\n    \"gemini\": {\n        \"label\": \"Google Vertex/Gemini-Compatible Generate Content\",\n        \"method\": \"POST\",\n        \"path\": \"/gemini/v1beta/models/{model}:generateContent\",\n        \"family\": \"gemini\",\n    },\n}\n\n\ndef display_models_source() -> str:\n    return DEFAULT_MODELS_URL\n\n\ndef display_openapi_source(filename: str = \"openapi.json\") -> str:\n    if filename == \"openapi.json\":\n        return OPENAPI_JSON_URL\n    if filename == \"contract.json\":\n        return CONTRACT_JSON_URL\n    return OPENAPI_REPO_URL\n\n\ndef display_error_contract_source() -> str:\n    return OPENAPI_JSON_URL\n\n\ndef load_json_source(source: str | None) -> Any:\n    # Always fetch live (no caching): every lookup hits the source directly.\n    source = source or os.environ.get(\"AIHUBMIX_MODELS_URL\") or DEFAULT_MODELS_URL\n    if source == \"-\":\n        return json.load(sys.stdin)\n    if source.startswith((\"http://\", \"https://\")):\n        request = urllib.request.Request(\n            source,\n            headers={\n                \"Accept\": \"application/json\",\n                \"User-Agent\": \"aihubmixApi-skill/0.1\",\n            },\n        )\n        try:\n            with urllib.request.urlopen(request, timeout=20) as response:\n                return json.load(response)\n        except urllib.error.HTTPError as exc:\n            detail = exc.read().decode(\"utf-8\", errors=\"replace\")\n            raise SystemExit(f\"HTTP {exc.code} while fetching {source}: {detail}\") from exc\n        except urllib.error.URLError as exc:\n            raise SystemExit(f\"Could not fetch {source}: {exc.reason}\") from exc\n\n    path = Path(source).expanduser()\n    with path.open(\"r\", encoding=\"utf-8\") as handle:\n        return json.load(handle)\n\n\ndef extract_models(payload: Any) -> list[dict[str, Any]]:\n    return sorted(extract_models_in_source_order(payload), key=lambda item: model_id(item).lower())\n\n\ndef extract_models_in_source_order(payload: Any) -> list[dict[str, Any]]:\n    if isinstance(payload, list):\n        candidates = payload\n    elif isinstance(payload, dict):\n        candidates = None\n        for key in (\"data\", \"models\", \"items\", \"list\", \"result\"):\n            value = payload.get(key)\n            if isinstance(value, list):\n                candidates = value\n                break\n            if isinstance(value, dict):\n                nested = extract_models_in_source_order(value)\n                if nested:\n                    candidates = nested\n                    break\n        if candidates is None:\n            candidates = [payload] if any(k in payload for k in (\"id\", \"model\", \"model_id\")) else []\n    else:\n        candidates = []\n\n    return [item for item in candidates if isinstance(item, dict)]\n\n\ndef model_id(model: dict[str, Any]) -> str:\n    for key in (\"model_id\", \"id\", \"model\", \"name\", \"slug\"):\n        value = model.get(key)\n        if value is not None:\n            return str(value)\n    return \"\"\n\n\ndef model_label(model: dict[str, Any]) -> str:\n    for key in (\"model_name\", \"name\", \"display_name\", \"label\", \"title\"):\n        value = model.get(key)\n        if value:\n            return str(value)\n    return model_id(model)\n\n\ndef developer(model: dict[str, Any]) -> str:\n    for key in (\"developer\", \"provider\", \"developer_id\", \"provider_id\", \"owned_by\"):\n        value = model.get(key)\n        if value:\n            return str(value)\n    return \"-\"\n\n\ndef context_length(model: dict[str, Any]) -> str:\n    for key in (\n        \"context_length\",\n        \"context_window\",\n        \"max_context\",\n        \"max_context_length\",\n        \"input_context_length\",\n    ):\n        value = model.get(key)\n        if value is not None:\n            return str(value)\n    return \"-\"\n\n\ndef max_output(model: dict[str, Any]) -> str:\n    for key in (\"max_output\", \"max_output_tokens\", \"output_context_length\"):\n        value = model.get(key)\n        if value is not None:\n            return str(value)\n    return \"-\"\n\n\ndef format_tokens(value: str) -> str:\n    if value in {\"\", \"-\"}:\n        return \"-\"\n    try:\n        number = int(float(value))\n    except ValueError:\n        return value\n    if number == 0:\n        return \"0\"\n    if number >= 1_000_000 and number % 1_000_000 == 0:\n        return f\"{number // 1_000_000}M\"\n    if number >= 1_000_000:\n        compact_value = number / 1_000_000\n        return f\"{compact_value:.2f}\".rstrip(\"0\").rstrip(\".\") + \"M\"\n    if number >= 1_000 and number % 1_000 == 0:\n        return f\"{number // 1_000}K\"\n    if number >= 1_000:\n        compact_value = number / 1_000\n        return f\"{compact_value:.1f}\".rstrip(\"0\").rstrip(\".\") + \"K\"\n    return str(number)\n\n\ndef context_display(model: dict[str, Any]) -> str:\n    return format_tokens(context_length(model))\n\n\ndef max_output_display(model: dict[str, Any]) -> str:\n    return format_tokens(max_output(model))\n\n\ndef compact(value: Any) -> str:\n    if value is None:\n        return \"-\"\n    if isinstance(value, (str, int, float, bool)):\n        return str(value)\n    if isinstance(value, list):\n        return \",\".join(compact(item) for item in value[:8]) or \"-\"\n    if isinstance(value, dict):\n        parts = []\n        for key in sorted(value):\n            item = value[key]\n            if item is not None:\n                parts.append(f\"{key}={compact(item)}\")\n        return \"; \".join(parts) or \"-\"\n    return str(value)\n\n\ndef pricing(model: dict[str, Any]) -> str:\n    value = model.get(\"pricing\") or model.get(\"price\") or model.get(\"prices\")\n    return compact(value)\n\n\ndef price_unit() -> str:\n    return os.environ.get(\"AIHUBMIX_PRICE_UNIT\", DEFAULT_PRICE_UNIT)\n\n\ndef query_time_label() -> str:\n    now = datetime.now().astimezone()\n    offset = now.strftime(\"%z\")\n    if offset:\n        offset_label = f\"UTC{offset[:3]}:{offset[3:]}\"\n    else:\n        offset_label = \"local timezone\"\n    stamp = now.strftime(\"%Y-%m-%d %H:%M:%S\")\n    return _t(f\"{stamp} (local time, {offset_label})\", f\"{stamp} (本地时间，{offset_label})\")\n\n\ndef types(model: dict[str, Any]) -> str:\n    value = model.get(\"types\") or model.get(\"type\") or model.get(\"endpoints\")\n    return compact(value)\n\n\ndef features(model: dict[str, Any]) -> str:\n    value = model.get(\"features\") or model.get(\"capabilities\") or model.get(\"input_modalities\")\n    return compact(value)\n\n\ndef endpoint_display(model: dict[str, Any]) -> str:\n    raw = str(model.get(\"endpoints\") or \"\").strip()\n    if not raw:\n        model_type = str(model.get(\"types\") or \"\")\n        if \"llm\" in model_type and \"image_generation\" not in model_type:\n            return \"not declared; use OpenAI-compatible chat example by default\"\n        return \"not declared; choose endpoint by model type and verify against contract\"\n    labels = {\n        \"chat_completions\": \"OpenAI-compatible chat\",\n        \"responses\": \"OpenAI Responses\",\n        \"gemini_api\": \"Gemini native\",\n        \"claude_api\": \"Claude/Anthropic-compatible\",\n        \"embeddings\": \"Embeddings\",\n        \"image_generation\": \"Image generation\",\n        \"audio\": \"Audio\",\n        \"moderations\": \"Moderation\",\n        \"videos\": \"Video\",\n    }\n    parts = [part.strip() for part in raw.replace(\";\", \",\").split(\",\") if part.strip()]\n    mapped = [labels.get(part, part) for part in parts]\n    return \"; \".join(mapped) if mapped else raw\n\n\ndef endpoint_note(model: dict[str, Any]) -> str:\n    raw = str(model.get(\"endpoints\") or \"\").strip()\n    return raw if raw else \"-\"\n\n\ndef suggested_protocol(model: dict[str, Any]) -> str | None:\n    raw_endpoint = compact(model.get(\"endpoints\")).lower()\n    raw_type = compact(model.get(\"types\") or model.get(\"type\")).lower()\n    searchable = model_search_text(model).lower()\n\n    if \"gemini_api\" in raw_endpoint:\n        return \"gemini\"\n    if \"claude_api\" in raw_endpoint:\n        return \"messages\"\n    if \"responses\" in raw_endpoint:\n        return \"responses\"\n    if \"chat_completions\" in raw_endpoint:\n        return \"chat\"\n    if \"embedding\" in raw_endpoint or \"embedding\" in raw_type:\n        return \"embeddings\"\n    if any(value in raw_endpoint or value in raw_type for value in (\"image_generation\", \"image\")):\n        return \"images\"\n    if any(value in raw_endpoint or value in raw_type for value in (\"video\", \"videos\")):\n        return \"videos\"\n    if any(value in raw_endpoint or value in raw_type for value in (\"speech\", \"tts\")):\n        return \"audio-speech\"\n    if \"transcription\" in raw_endpoint or \"transcription\" in raw_type:\n        return \"audio-transcriptions\"\n    if \"translation\" in raw_endpoint or \"translation\" in raw_type:\n        return \"audio-translations\"\n    if \"moderation\" in raw_endpoint or \"moderation\" in raw_type:\n        return \"moderations\"\n    if \"audio\" in raw_endpoint or \"audio\" in raw_type:\n        return \"audio-transcriptions\"\n    if \"llm\" in raw_type or \"chat\" in raw_type:\n        return \"chat\"\n    if any(value in searchable for value in (\"gemini\", \"claude\", \"anthropic\")):\n        if \"gemini\" in searchable:\n            return \"gemini\"\n        return \"messages\"\n    return \"chat\"\n\n\ndef protocol_name(protocol: str) -> str:\n    protocol = normalize_protocol(protocol)\n    return PROTOCOL_SPECS[protocol][\"label\"]\n\n\ndef protocol_auth_label(protocol: str) -> str:\n    header_name, header_value = auth_header(protocol)\n    return f\"{header_name}: {header_value}\"\n\n\ndef print_user_overview(selected: list[dict[str, Any]], query: str | None = None) -> None:\n    print(\"## Quick Start Overview\")\n    print()\n    if query:\n        print(f\"- Searched: `{query}`\")\n    print(f\"- Models shown: `{len(selected)}`\")\n    print(f\"- Price unit: `{price_unit()}`\")\n    print(\"- How to use: copy a `model_id`, check context/price, then run the example below.\")\n    print()\n    print(\"| model_id | protocol | context | max_output | price |\")\n    print(\"|---|---|---:|---:|---|\")\n    for item in selected[:5]:\n        protocol = suggested_protocol(item)\n        protocol_label = protocol_name(protocol) if protocol else \"verify endpoint by model type\"\n        print(\n            \"| \"\n            + \" | \".join(\n                [\n                    f\"`{model_id(item)}`\",\n                    protocol_label,\n                    context_display(item),\n                    max_output_display(item),\n                    pricing(item).replace(\"|\", \"\\\\|\"),\n                ]\n            )\n            + \" |\"\n        )\n    print()\n    print(\"## Technical Details\")\n    print()\n\n\ndef example_intro(kind: str, os_name: str | None = None) -> str:\n    if kind == \"command\":\n        shell_name = \"Windows PowerShell\" if os_name == \"windows\" else \"macOS/Linux shell\"\n        return (\n            f\"Use this {shell_name} example when you want to test the model directly from a terminal. \"\n            \"It asks for `AIHUBMIX_API_KEY`, sends one request, and prints the model reply.\"\n        )\n    if kind == \"js\":\n        return (\n            \"Use this JavaScript example inside a Node.js project or service. \"\n            \"Run the environment setup command below before starting the script.\"\n        )\n    if kind == \"python\":\n        return (\n            \"Use this Python example for a quick backend or script test. \"\n            \"Run the environment setup command below before starting the script.\"\n        )\n    return \"Use this example as a minimal starting point.\"\n\n\ndef env_setup_block(kind: str, os_name: str | None = None) -> tuple[str, str]:\n    if kind == \"command\":\n        return \"\", \"\"\n    if os_name == \"windows\":\n        return (\n            \"PowerShell\",\n            '$env:AIHUBMIX_API_KEY = Read-Host \"Paste AIHubMix API Key\"',\n        )\n    if kind == \"js\":\n        return (\n            \"bash\",\n            'export AIHUBMIX_API_KEY=\"sk-...\"',\n        )\n    return (\n        \"bash\",\n        'export AIHUBMIX_API_KEY=\"sk-...\"',\n    )\n\n\ndef print_env_setup(kind: str, os_name: str | None = None) -> None:\n    lang, command = env_setup_block(kind, os_name)\n    if not command:\n        return\n    print(\"先设置环境变量，把 `sk-...` 换成你的 AIHubMix API Key：\")\n    print()\n    print(f\"```{lang}\")\n    print(command)\n    print(\"```\")\n    print()\n\n\ndef print_model_switch_hint(selected: list[dict[str, Any]]) -> None:\n    if len(selected) <= 1:\n        return\n    shown = \", \".join(f\"`{model_id(item)}`\" for item in selected[:6])\n    print(f\"可选模型 ID：{shown}\")\n    print(\"想切换模型时，直接把示例里的 `model` / `model_id` 换成对应 ID 即可。\")\n    print()\n\n\ndef availability_note(model: dict[str, Any]) -> str:\n    desc = str(model.get(\"desc\") or \"\")\n    lowered = desc.lower()\n    notes = []\n    if \"temporarily suspended\" in lowered or \"suspended\" in lowered:\n        notes.append(\"access note in desc\")\n    if \"expensive\" in lowered or \"high price\" in lowered:\n        notes.append(\"cost note in desc\")\n    return \", \".join(notes) if notes else \"-\"\n\n\nLATEST_QUERY_TERMS = (\"latest\", \"newest\", \"recent\", \"最新\", \"新模型\", \"最近\")\n\nGENERIC_QUERY_TOKENS = {\n    \"aihubmix\",\n    \"api\",\n    \"info\",\n    \"interface\",\n    \"latest\",\n    \"model\",\n    \"models\",\n    \"newest\",\n    \"price\",\n    \"pricing\",\n    \"recent\",\n}\n\nMODEL_ALIAS_GROUPS: list[tuple[tuple[str, ...], tuple[str, ...]]] = [\n    ((\"月之暗面\", \"moonshot\", \"kimi\"), (\"moonshot\", \"kimi\")),\n    ((\"谷歌\", \"google\", \"gemini\"), (\"google\", \"gemini\")),\n    ((\"claude\", \"anthropic\"), (\"claude\", \"anthropic\")),\n    ((\"opus\",), (\"opus\",)),\n    ((\"sonnet\",), (\"sonnet\",)),\n    ((\"haiku\",), (\"haiku\",)),\n    ((\"openai\", \"chatgpt\", \"gpt\"), (\"openai\", \"gpt\")),\n    ((\"qwen\", \"通义\", \"通义千问\", \"千问\", \"alibaba\", \"阿里\"), (\"qwen\", \"通义\", \"千问\", \"alibaba\")),\n    ((\"deepseek\", \"深度求索\"), (\"deepseek\", \"深度求索\")),\n    ((\"zhipu\", \"智谱\", \"glm\"), (\"zhipu\", \"智谱\", \"glm\")),\n    ((\"doubao\", \"豆包\", \"字节\", \"火山\", \"volcengine\"), (\"doubao\", \"volcengine\", \"字节\", \"火山\")),\n    ((\"minimax\", \"海螺\"), (\"minimax\", \"hailuo\", \"海螺\")),\n    ((\"零一万物\", \"01ai\", \"01-ai\", \"yi\"), (\"01-ai\", \"yi\", \"零一\")),\n    ((\"baichuan\", \"百川\"), (\"baichuan\", \"百川\")),\n    ((\"mistral\",), (\"mistral\",)),\n    ((\"llama\", \"meta\"), (\"llama\", \"meta\")),\n    ((\"grok\", \"xai\", \"x.ai\"), (\"grok\", \"xai\", \"x.ai\")),\n]\n\n\ndef normalize_search_text(value: str) -> str:\n    return re.sub(r\"[\\W_]+\", \"\", value.lower(), flags=re.UNICODE)\n\n\ndef query_wants_latest(query: str) -> bool:\n    lowered = query.lower()\n    return any(term in lowered for term in LATEST_QUERY_TERMS)\n\n\ndef model_search_text(model: dict[str, Any]) -> str:\n    keys = (\n        \"model_id\",\n        \"id\",\n        \"model\",\n        \"model_name\",\n        \"name\",\n        \"display_name\",\n        \"label\",\n        \"title\",\n        \"developer\",\n        \"provider\",\n        \"developer_id\",\n        \"provider_id\",\n        \"owned_by\",\n        \"desc\",\n        \"description\",\n        \"types\",\n        \"type\",\n        \"endpoints\",\n        \"features\",\n        \"capabilities\",\n        \"input_modalities\",\n    )\n    return \" \".join(compact(model.get(key)) for key in keys if model.get(key) is not None)\n\n\ndef add_query_group(\n    groups: list[list[str]],\n    labels: list[str],\n    seen: set[tuple[str, ...]],\n    label: str,\n    terms: tuple[str, ...] | list[str],\n) -> None:\n    cleaned = tuple(dict.fromkeys(term.strip().lower() for term in terms if term.strip()))\n    if not cleaned:\n        return\n    key = tuple(sorted(normalize_search_text(term) for term in cleaned if normalize_search_text(term)))\n    if not key or key in seen:\n        return\n    groups.append(list(cleaned))\n    labels.append(f\"{label} -> {', '.join(cleaned)}\" if label else \", \".join(cleaned))\n    seen.add(key)\n\n\ndef build_query_plan(query: str) -> dict[str, Any]:\n    lowered = query.lower()\n    compact_query = normalize_search_text(query)\n    groups: list[list[str]] = []\n    labels: list[str] = []\n    seen: set[tuple[str, ...]] = set()\n    matched_alias_triggers: set[str] = set()\n\n    for triggers, terms in MODEL_ALIAS_GROUPS:\n        matched_trigger = None\n        for trigger in triggers:\n            trigger_lower = trigger.lower()\n            trigger_compact = normalize_search_text(trigger)\n            if trigger_lower in lowered or (trigger_compact and trigger_compact in compact_query):\n                matched_trigger = trigger\n                matched_alias_triggers.update(normalize_search_text(item) for item in triggers)\n                break\n        if matched_trigger:\n            add_query_group(groups, labels, seen, matched_trigger, terms)\n\n    for token in re.findall(r\"[a-z0-9]+(?:[._-]?[a-z0-9]+)*\", lowered):\n        token_compact = normalize_search_text(token)\n        if not token_compact or token in GENERIC_QUERY_TOKENS or token_compact in matched_alias_triggers:\n            continue\n        add_query_group(groups, labels, seen, token, (token,))\n\n    if not groups and query.strip():\n        add_query_group(groups, labels, seen, \"raw query\", (query.strip(),))\n\n    return {\n        \"groups\": groups,\n        \"labels\": labels,\n        \"wants_latest\": query_wants_latest(query),\n        \"compact_query\": compact_query,\n    }\n\n\ndef term_match_score(model: dict[str, Any], raw_text: str, compact_text: str, term: str) -> int:\n    term_lower = term.lower()\n    term_compact = normalize_search_text(term)\n    model_id_lower = model_id(model).lower()\n    model_id_compact = normalize_search_text(model_id(model))\n\n    if term_lower == model_id_lower or (term_compact and term_compact == model_id_compact):\n        return 100\n    if term_lower and term_lower in raw_text:\n        return 25\n    if term_compact and term_compact in compact_text:\n        return 20\n    return 0\n\n\ndef model_query_score(model: dict[str, Any], plan: dict[str, Any]) -> int:\n    raw_text = model_search_text(model).lower()\n    compact_text = normalize_search_text(raw_text)\n    groups = plan[\"groups\"]\n    if not groups:\n        return 0\n\n    score = 0\n    for group in groups:\n        group_score = max(term_match_score(model, raw_text, compact_text, term) for term in group)\n        if group_score == 0:\n            return 0\n        score += group_score\n\n    compact_query = plan[\"compact_query\"]\n    model_id_compact = normalize_search_text(model_id(model))\n    if compact_query and compact_query == model_id_compact:\n        score += 200\n    elif compact_query and compact_query in model_id_compact:\n        score += 80\n    return score\n\n\ndef rank_matching_models(\n    models: list[dict[str, Any]],\n    query: str,\n    limit: int | None = None,\n    preserve_source_order: bool = False,\n) -> tuple[list[dict[str, Any]], dict[str, Any]]:\n    plan = build_query_plan(query)\n    scored = [\n        (index, model_query_score(item, plan), item)\n        for index, item in enumerate(models)\n    ]\n    matches = [(index, score, item) for index, score, item in scored if score > 0]\n    if preserve_source_order:\n        ordered = sorted(matches, key=lambda row: row[0])\n    else:\n        ordered = sorted(matches, key=lambda row: (-row[1], model_id(row[2]).lower()))\n    selected = [item for _, _, item in ordered]\n    if limit is not None:\n        selected = selected[:limit]\n    return selected, plan\n\n\ndef find_model(models: list[dict[str, Any]], target: str) -> dict[str, Any] | None:\n    selected, _ = rank_matching_models(models, target, limit=1)\n    return selected[0] if selected else None\n\n\ndef print_table(headers: list[str], rows: list[list[str]]) -> None:\n    widths = [len(header) for header in headers]\n    for row in rows:\n        for idx, cell in enumerate(row):\n            widths[idx] = max(widths[idx], len(cell))\n    print(\" | \".join(header.ljust(widths[idx]) for idx, header in enumerate(headers)))\n    print(\"-+-\".join(\"-\" * width for width in widths))\n    for row in rows:\n        print(\" | \".join(cell.ljust(widths[idx]) for idx, cell in enumerate(row)))\n\n\ndef cmd_list(args: argparse.Namespace) -> None:\n    models = extract_models(load_json_source(args.source))\n    if args.query:\n        models, _ = rank_matching_models(models, args.query)\n    if args.json:\n        print(json.dumps(models[: args.limit], ensure_ascii=False, indent=2))\n        return\n    rows = []\n    for item in models[: args.limit]:\n        rows.append(\n            [\n                model_id(item),\n                model_label(item),\n                developer(item),\n                context_display(item),\n                max_output_display(item),\n                types(item),\n            ]\n        )\n    print_table([\"model_id\", \"name\", \"provider\", \"context\", \"max_output\", \"types\"], rows)\n    print(f\"\\nsource: {display_models_source()}\")\n\n\ndef cmd_get(args: argparse.Namespace) -> None:\n    models = extract_models(load_json_source(args.source))\n    item = find_model(models, args.model)\n    if not item:\n        raise SystemExit(f\"Model not found: {args.model}\")\n    if args.json:\n        print(json.dumps(item, ensure_ascii=False, indent=2))\n        return\n    rows = [\n        [\"model_id\", model_id(item)],\n        [\"name\", model_label(item)],\n        [\"provider\", developer(item)],\n        [\"context_length\", context_display(item)],\n        [\"max_output\", max_output_display(item)],\n        [\"pricing\", pricing(item)],\n        [\"price_unit\", price_unit()],\n        [\"types/endpoints\", types(item)],\n        [\"features/modalities\", features(item)],\n    ]\n    print_table([\"field\", \"value\"], rows)\n    print(\"\\nRaw model data is available with --json.\")\n\n\ndef cmd_compare(args: argparse.Namespace) -> None:\n    models = extract_models(load_json_source(args.source))\n    selected = []\n    missing = []\n    for target in args.models:\n        item = find_model(models, target)\n        if item:\n            selected.append(item)\n        else:\n            missing.append(target)\n    if args.json:\n        print(json.dumps({\"models\": selected, \"missing\": missing}, ensure_ascii=False, indent=2))\n        return\n    rows = []\n    for item in selected:\n        rows.append(\n            [\n                model_id(item),\n                developer(item),\n                context_display(item),\n                max_output_display(item),\n                pricing(item),\n                features(item),\n            ]\n        )\n    print_table([\"model_id\", \"provider\", \"context\", \"max_output\", \"pricing\", \"features\"], rows)\n    if missing:\n        print(\"\\nmissing: \" + \", \".join(missing))\n    print(f\"\\nPricing units: {price_unit()}. Values are displayed exactly as returned by the models API.\")\n\n\ndef cmd_latest_report(args: argparse.Namespace) -> None:\n    payload = load_json_source(args.source)\n    models = extract_models_in_source_order(payload)\n    selected = models[: args.limit]\n    if not selected:\n        raise SystemExit(\"No models found in the selected source.\")\n\n    source = display_models_source()\n    unit = price_unit()\n    now = query_time_label()\n\n    print(f\"# AIHubMix Latest Models Report\")\n    print()\n    print(f\"- Data source: `{source}`\")\n    print(f\"- Query time: `{now}`\")\n    print(\"- Latest definition: first records returned by `/api/v1/models` in source order; no model_id sorting is applied.\")\n    print(f\"- Price unit: `{unit}`\")\n    print(\"- Price values: displayed exactly as returned in each model's `pricing` object.\")\n    print()\n    print_user_overview(selected)\n    print(\"| # | model_id | name | developer_id | pricing | context_length(tokens) | max_output(tokens) | types/endpoints | features | notes |\")\n    print(\"|---:|---|---|---:|---|---:|---:|---|---|---|\")\n    for index, item in enumerate(selected, start=1):\n        type_endpoint = types(item)\n        endpoints = compact(item.get(\"endpoints\"))\n        if endpoints != \"-\" and endpoints not in type_endpoint:\n            type_endpoint = f\"{type_endpoint}; endpoints={endpoints}\" if type_endpoint != \"-\" else f\"endpoints={endpoints}\"\n        print(\n            \"| \"\n            + \" | \".join(\n                [\n                    str(index),\n                    f\"`{model_id(item)}`\",\n                    model_label(item).replace(\"|\", \"\\\\|\"),\n                    developer(item),\n                    pricing(item).replace(\"|\", \"\\\\|\"),\n                    context_display(item),\n                    max_output_display(item),\n                    type_endpoint.replace(\"|\", \"\\\\|\"),\n                    features(item).replace(\"|\", \"\\\\|\"),\n                    availability_note(item).replace(\"|\", \"\\\\|\"),\n                ]\n            )\n            + \" |\"\n        )\n    print()\n    print_model_switch_hint(selected)\n\n    first_model = model_id(selected[0])\n    protocol = suggested_protocol(selected[0])\n    print()\n    if protocol is None:\n        print(\"## Example\")\n        print()\n        print(\"The first selected model is not a plain text/chat model. Choose the endpoint by model type and verify it with `protocols` before generating a call example.\")\n        return\n\n    print(f\"## Suggested {protocol_name(protocol)} Call Example\")\n    print()\n    print(f\"- URL: `{base_url()}{endpoint_path(protocol, first_model)}`\")\n    print(f\"- Auth: `{protocol_auth_label(protocol)}`\")\n    print(\"- Replace `model` with any compatible `model_id` from the table when needed.\")\n    print()\n    os_name = detect_os(args.os)\n    print(f\"### Command Line ({'Windows PowerShell' if os_name == 'windows' else 'macOS/Linux shell'})\")\n    print()\n    print(example_intro(\"command\", os_name))\n    print()\n    print(\"```\" + (\"powershell\" if os_name == \"windows\" else \"bash\"))\n    print(render_cmd_example(protocol, first_model, os_name))\n    print(\"```\")\n    print()\n    print(\"### JavaScript\")\n    print()\n    print(example_intro(\"js\"))\n    print()\n    print_env_setup(\"js\", os_name)\n    print(\"```js\")\n    print(render_js_example(protocol, first_model))\n    print(\"```\")\n\n\ndef cmd_report(args: argparse.Namespace) -> None:\n    payload = load_json_source(args.source)\n    wants_latest = query_wants_latest(args.query)\n    models = extract_models_in_source_order(payload) if wants_latest else extract_models(payload)\n    selected, query_plan = rank_matching_models(\n        models,\n        args.query,\n        limit=args.limit,\n        preserve_source_order=wants_latest,\n    )\n    if not selected:\n        raise SystemExit(f\"No models matched query: {args.query}\")\n\n    source = display_models_source()\n    now = query_time_label()\n    matched_terms = \"; \".join(query_plan[\"labels\"]) if query_plan[\"labels\"] else \"raw query\"\n\n    print(\"# AIHubMix Model Interface Report\")\n    print()\n    print(f\"- Query: `{args.query}`\")\n    print(f\"- Normalized query terms: `{matched_terms}`\")\n    if query_plan[\"wants_latest\"]:\n        print(\"- Latest intent: `detected`; matched rows keep `/api/v1/models` source order.\")\n    print(f\"- Data source: `{source}`\")\n    print(f\"- Query time: `{now}`\")\n    print(f\"- Matched models shown: `{len(selected)}`\")\n    print(f\"- Price unit: `{price_unit()}`\")\n    print(\"- Price values: displayed exactly as returned in each model's `pricing` object.\")\n    print()\n    print_user_overview(selected, args.query)\n    print(\"| model_id | name | developer_id | pricing | context | max_output | type | callable entrypoints | raw endpoints | features | modalities | notes |\")\n    print(\"|---|---|---:|---|---:|---:|---|---|---|---|---|---|\")\n    for item in selected:\n        print(\n            \"| \"\n            + \" | \".join(\n                [\n                    f\"`{model_id(item)}`\",\n                    model_label(item).replace(\"|\", \"\\\\|\"),\n                    developer(item),\n                    pricing(item).replace(\"|\", \"\\\\|\"),\n                    context_display(item),\n                    max_output_display(item),\n                    compact(item.get(\"types\")).replace(\"|\", \"\\\\|\"),\n                    endpoint_display(item).replace(\"|\", \"\\\\|\"),\n                    endpoint_note(item).replace(\"|\", \"\\\\|\"),\n                    compact(item.get(\"features\")).replace(\"|\", \"\\\\|\"),\n                    compact(item.get(\"input_modalities\")).replace(\"|\", \"\\\\|\"),\n                    availability_note(item).replace(\"|\", \"\\\\|\"),\n                ]\n            )\n            + \" |\"\n        )\n    print()\n    print_model_switch_hint(selected)\n\n    first_model = model_id(selected[0])\n    protocol = suggested_protocol(selected[0])\n    print()\n    if protocol is None:\n        print(\"## Example\")\n        print()\n        print(\"The matched model is not a plain text/chat model. Choose the endpoint by model type and verify it with `protocols` before generating a call example.\")\n        return\n\n    print(f\"## Suggested {protocol_name(protocol)} Endpoint\")\n    print()\n    print(\"- Method: `POST`\")\n    print(f\"- URL: `{base_url()}{endpoint_path(protocol, first_model)}`\")\n    print(f\"- Auth: `{protocol_auth_label(protocol)}`\")\n    print()\n    print(\"## Example\")\n    print()\n    os_name = detect_os(args.os)\n    print(f\"### Command Line ({'Windows PowerShell' if os_name == 'windows' else 'macOS/Linux shell'})\")\n    print()\n    print(example_intro(\"command\", os_name))\n    print()\n    print(\"```\" + (\"powershell\" if os_name == \"windows\" else \"bash\"))\n    print(render_cmd_example(protocol, first_model, os_name))\n    print(\"```\")\n    print()\n    print(\"### JavaScript\")\n    print()\n    print(example_intro(\"js\"))\n    print()\n    print_env_setup(\"js\", os_name)\n    print(\"```js\")\n    print(render_js_example(protocol, first_model))\n    print(\"```\")\n\n\ndef load_openapi() -> dict[str, Any] | None:\n    \"\"\"Fetch the live OpenAPI spec from the remote endpoint (no local checkout).\"\"\"\n    url = os.environ.get(\"AIHUBMIX_OPENAPI_URL\") or OPENAPI_JSON_URL\n    try:\n        return json.loads(read_url_bytes(url).decode(\"utf-8\", errors=\"replace\"))\n    except ValueError:\n        return None\n\n\ndef _error_statuses_from_spec(spec: dict[str, Any]) -> dict[str, dict[str, str]]:\n    \"\"\"Collect declared 4XX/5XX responses (code -> description/schema) from the spec.\"\"\"\n    statuses: dict[str, dict[str, str]] = {}\n    for _method, _path, operation in iter_operations(spec):\n        for code, response in (operation.get(\"responses\") or {}).items():\n            code = str(code)\n            if code in statuses or not re.match(r\"^[45]\\d\\d$|^[45]XX$\", code, re.IGNORECASE):\n                continue\n            if not isinstance(response, dict):\n                continue\n            schema_ref = \"#/components/schemas/GatewayError\"\n            for media in (response.get(\"content\") or {}).values():\n                ref = ((media or {}).get(\"schema\") or {}).get(\"$ref\")\n                if ref:\n                    schema_ref = ref\n                    break\n            statuses[code] = {\n                \"description\": str(response.get(\"description\", \"\")).strip(),\n                \"schema\": schema_ref,\n            }\n    return statuses\n\n\ndef load_error_contract() -> dict[str, Any]:\n    \"\"\"Derive the GatewayError contract from the live OpenAPI spec (no local checkout).\"\"\"\n    spec = load_openapi()\n    if not spec:\n        raise SystemExit(\n            f\"Could not load the OpenAPI spec from {OPENAPI_JSON_URL} to derive the error contract.\"\n        )\n    return {\n        \"source\": display_error_contract_source(),\n        \"schema_name\": \"GatewayError\",\n        \"envelope\": {\n            \"top_level\": \"error\",\n            \"required\": [\"error.message\"],\n            \"fields\": {\n                \"error.message\": \"Human-readable error message.\",\n                \"error.type\": \"OpenAI-compatible category; upstream value may pass through and enum is not fixed.\",\n                \"error.param\": \"Offending field name, when applicable.\",\n                \"error.code\": \"Sub-error code; may be string or integer.\",\n            },\n        },\n        \"request_id\": \"Use the X-Request-Id response header. It is not in the JSON body.\",\n        \"legacy_upstream\": \"The legacy upstream field is no longer emitted.\",\n        \"statuses\": _error_statuses_from_spec(spec),\n    }\n\n\ndef iter_operations(spec: dict[str, Any]) -> list[tuple[str, str, dict[str, Any]]]:\n    ops = []\n    for path, path_item in (spec.get(\"paths\") or {}).items():\n        if not isinstance(path_item, dict):\n            continue\n        for method, operation in path_item.items():\n            if method.lower() not in {\"get\", \"post\", \"put\", \"patch\", \"delete\"}:\n                continue\n            if isinstance(operation, dict):\n                ops.append((method.upper(), path, operation))\n    return ops\n\n\ndef cmd_protocols(args: argparse.Namespace) -> None:\n    spec = load_openapi()\n    if not spec:\n        raise SystemExit(f\"Could not load the OpenAPI spec from {OPENAPI_JSON_URL}.\")\n    operations = iter_operations(spec)\n    if args.json:\n        print(json.dumps({\"source\": display_openapi_source(), \"operations\": operations}, ensure_ascii=False, indent=2))\n        return\n    rows = []\n    for method, endpoint, operation in operations:\n        security = operation.get(\"security\") or spec.get(\"security\") or []\n        rows.append(\n            [\n                method,\n                endpoint,\n                operation.get(\"operationId\", \"-\"),\n                compact(security),\n                \"yes\" if operation.get(\"requestBody\") else \"no\",\n            ]\n        )\n    print_table([\"method\", \"path\", \"operation_id\", \"security\", \"request_body\"], rows)\n    print(f\"\\nsource: {display_openapi_source()}\")\n\n\ndef cmd_error_contract(args: argparse.Namespace) -> None:\n    contract = load_error_contract()\n    if args.json:\n        print(json.dumps(contract, ensure_ascii=False, indent=2))\n        return\n\n    print(\"# AIHubMix Gateway Error Contract\")\n    print()\n    print(f\"- Source: `{display_error_contract_source()}`\")\n    print(f\"- Schema: `{contract['schema_name']}`\")\n    print(\"- Body shape: top-level `error` object.\")\n    print(\"- Required body field: `error.message`.\")\n    print(f\"- Request ID: `{contract['request_id']}`\")\n    print(f\"- Legacy upstream field: `{contract['legacy_upstream']}`\")\n    print()\n    print(\"## GatewayError Fields\")\n    print()\n    rows = [[field, description] for field, description in contract[\"envelope\"][\"fields\"].items()]\n    print_table([\"field\", \"meaning\"], rows)\n    print()\n    print(\"## Status Responses\")\n    print()\n    status_order = [\"400\", \"401\", \"403\", \"404\", \"429\", \"5XX\"]\n    rows = []\n    statuses = contract[\"statuses\"]\n    for status in status_order:\n        item = statuses.get(status, {})\n        rows.append([status, item.get(\"description\", \"-\"), item.get(\"schema\", \"#/components/schemas/GatewayError\")])\n    print_table([\"status\", \"description\", \"schema\"], rows)\n    print()\n    print(\"## Troubleshooting Rule\")\n    print()\n    print(\"Use the live HTTP status, JSON error body, and `X-Request-Id` as the observed evidence.\")\n    print(\"Use this contract to verify the error envelope and status category; do not assume `error.type` is a fixed enum.\")\n\n\ndef load_package_json(path: Path) -> dict[str, Any] | None:\n    if not path.exists():\n        return None\n    with path.open(\"r\", encoding=\"utf-8\") as handle:\n        data = json.load(handle)\n    return data if isinstance(data, dict) else None\n\n\ndef find_installed_sdk_package(start: str | None = None) -> tuple[dict[str, Any] | None, Path | None]:\n    explicit = os.environ.get(\"AIHUBMIX_SDK_PACKAGE_JSON\")\n    candidates: list[Path] = []\n    if explicit:\n        candidates.append(Path(explicit).expanduser())\n    cwd = Path(start).expanduser() if start else Path.cwd()\n    for path in [cwd, *cwd.parents]:\n        candidates.append(path / \"node_modules\" / \"@aihubmix\" / \"ai-sdk-provider\" / \"package.json\")\n    seen: set[str] = set()\n    for candidate in candidates:\n        try:\n            resolved = candidate.resolve()\n        except OSError:\n            resolved = candidate\n        key = str(resolved).lower()\n        if key in seen:\n            continue\n        seen.add(key)\n        data = load_package_json(candidate)\n        if data:\n            return data, candidate\n    return None, None\n\n\ndef fetch_npm_package_metadata() -> dict[str, Any] | None:\n    request = urllib.request.Request(\n        SDK_REGISTRY_URL,\n        headers={\n            \"Accept\": \"application/json\",\n            \"User-Agent\": \"aihubmixApi-skill/0.1\",\n        },\n    )\n    try:\n        with urllib.request.urlopen(request, timeout=20) as response:\n            payload = json.load(response)\n    except urllib.error.HTTPError as exc:\n        detail = exc.read().decode(\"utf-8\", errors=\"replace\")\n        raise SystemExit(f\"HTTP {exc.code} while checking npm registry: {detail}\") from exc\n    except urllib.error.URLError as exc:\n        raise SystemExit(f\"Could not check npm registry: {exc.reason}\") from exc\n    return payload if isinstance(payload, dict) else None\n\n\ndef read_url_bytes(url: str) -> bytes:\n    request = urllib.request.Request(\n        url,\n        headers={\"User-Agent\": \"aihubmixApi-skill/0.1\"},\n    )\n    try:\n        with urllib.request.urlopen(request, timeout=30) as response:\n            return response.read()\n    except urllib.error.HTTPError as exc:\n        detail = exc.read().decode(\"utf-8\", errors=\"replace\")\n        raise SystemExit(f\"HTTP {exc.code} while fetching {url}: {detail}\") from exc\n    except urllib.error.URLError as exc:\n        raise SystemExit(f\"Could not fetch {url}: {exc.reason}\") from exc\n\n\ndef parse_sdk_package_texts(package_json: dict[str, Any], dts_text: str, js_text: str, source: str) -> dict[str, Any]:\n    method_candidates = [\n        \"languageModel\",\n        \"chat\",\n        \"responses\",\n        \"completion\",\n        \"embedding\",\n        \"embeddingModel\",\n        \"image\",\n        \"imageModel\",\n        \"textEmbedding\",\n        \"textEmbeddingModel\",\n        \"transcription\",\n        \"transcriptionModel\",\n        \"speech\",\n        \"speechModel\",\n    ]\n    tool_candidates = [\"codeInterpreter\", \"fileSearch\", \"imageGeneration\", \"webSearchPreview\", \"webSearch\"]\n    export_candidates = [\"aihubmix\", \"createAihubmix\"]\n    provider_methods = [name for name in method_candidates if re.search(rf\"\\b{name}\\b\", dts_text)]\n    tools = [name for name in tool_candidates if re.search(rf\"\\b{name}\\b\", dts_text)]\n    exports = [name for name in export_candidates if re.search(rf\"\\b{name}\\b\", dts_text)]\n    env_vars = sorted(set(re.findall(r'\"(AIHUBMIX_[A-Z0-9_]+)\"', js_text + dts_text)))\n    base_urls = sorted(set(re.findall(r'\"(https://aihubmix\\.com[^\"]*)\"', js_text + dts_text)))\n    header_candidates = [\"Authorization\", \"APP-Code\", \"Content-Type\", \"x-api-key\", \"x-goog-api-key\"]\n    headers = [name for name in header_candidates if name in js_text]\n    routing = []\n    if 'startsWith(\"claude-\")' in js_text:\n        routing.append(\"Claude model IDs starting with claude- use Anthropic-compatible messages with x-api-key.\")\n    if 'startsWith(\"gemini\")' in js_text or 'startsWith(\"imagen\")' in js_text:\n        routing.append(\"Gemini or Imagen model IDs use Gemini native base URL unless suffixed with -nothink or -search.\")\n    if \"OpenAICompatibleChatLanguageModel\" in js_text:\n        routing.append(\"Other chat models use OpenAI-compatible chat through https://aihubmix.com/v1.\")\n\n    return {\n        \"source\": source,\n        \"package\": str(package_json.get(\"name\") or SDK_PACKAGE_NAME),\n        \"version\": str(package_json.get(\"version\") or \"-\"),\n        \"exports\": exports,\n        \"provider_methods\": provider_methods,\n        \"tools\": tools,\n        \"environment_variable\": env_vars[0] if env_vars else \"-\",\n        \"base_urls\": base_urls,\n        \"headers\": headers,\n        \"routing\": routing,\n    }\n\n\ndef load_sdk_info_from_directory(package_dir: Path, source_label: str) -> dict[str, Any]:\n    package_json = load_package_json(package_dir / \"package.json\") or {}\n    dts_text = (package_dir / \"dist\" / \"index.d.ts\").read_text(encoding=\"utf-8\")\n    js_text = (package_dir / \"dist\" / \"index.js\").read_text(encoding=\"utf-8\")\n    return parse_sdk_package_texts(package_json, dts_text, js_text, source_label)\n\n\ndef load_sdk_info_from_tarball(tarball: bytes, source_label: str) -> dict[str, Any]:\n    with tarfile.open(fileobj=io.BytesIO(tarball), mode=\"r:gz\") as archive:\n        files: dict[str, bytes] = {}\n        for name in (\"package/package.json\", \"package/dist/index.d.ts\", \"package/dist/index.js\"):\n            member = archive.getmember(name)\n            extracted = archive.extractfile(member)\n            if not extracted:\n                raise SystemExit(f\"Could not read {name} from SDK tarball.\")\n            files[name] = extracted.read()\n    package_json = json.loads(files[\"package/package.json\"].decode(\"utf-8\"))\n    dts_text = files[\"package/dist/index.d.ts\"].decode(\"utf-8\")\n    js_text = files[\"package/dist/index.js\"].decode(\"utf-8\")\n    return parse_sdk_package_texts(package_json, dts_text, js_text, source_label)\n\n\ndef load_sdk_info(args: argparse.Namespace) -> dict[str, Any]:\n    if args.package_dir:\n        return load_sdk_info_from_directory(Path(args.package_dir).expanduser(), str(Path(args.package_dir).expanduser()))\n\n    installed, package_json_path = find_installed_sdk_package(args.project)\n    if package_json_path and args.source in {\"auto\", \"installed\"}:\n        return load_sdk_info_from_directory(package_json_path.parent, str(package_json_path.parent))\n    if args.source == \"installed\":\n        raise SystemExit(\"SDK package is not installed in the selected project path.\")\n\n    metadata = fetch_npm_package_metadata()\n    target_version = args.version or SDK_RECOMMENDED_VERSION\n    versions = metadata.get(\"versions\") or {}\n    package_meta = versions.get(target_version)\n    if not isinstance(package_meta, dict):\n        raise SystemExit(f\"Could not find {SDK_PACKAGE_NAME}@{target_version} in npm registry metadata.\")\n    tarball_url = ((package_meta.get(\"dist\") or {}).get(\"tarball\"))\n    if not tarball_url:\n        raise SystemExit(f\"No tarball URL found for {SDK_PACKAGE_NAME}@{target_version}.\")\n    return load_sdk_info_from_tarball(read_url_bytes(str(tarball_url)), f\"npm tarball {SDK_PACKAGE_NAME}@{target_version}\")\n\n\ndef cmd_sdk_info(args: argparse.Namespace) -> None:\n    info = load_sdk_info(args)\n    if args.json:\n        print(json.dumps(info, ensure_ascii=False, indent=2))\n        return\n\n    print(\"# AIHubMix SDK Provider Info\")\n    print()\n    print(f\"- Package: `{info['package']}`\")\n    print(f\"- Version: `{info['version']}`\")\n    print(f\"- Source: `{info['source']}`\")\n    print(\"- Data role: SDK/provider usage source; not model price, context, or availability source.\")\n    print()\n    print(\"## Provider Surface\")\n    print()\n    rows = []\n    for name in info[\"provider_methods\"]:\n        if name in {\"chat\", \"languageModel\"}:\n            purpose = \"text/chat generation\"\n        elif name == \"responses\":\n            purpose = \"OpenAI Responses API style model\"\n        elif \"embedding\" in name.lower():\n            purpose = \"text embeddings\"\n        elif name.startswith(\"image\"):\n            purpose = \"image generation\"\n        elif \"transcription\" in name.lower():\n            purpose = \"audio transcription\"\n        elif \"speech\" in name.lower():\n            purpose = \"speech synthesis\"\n        elif name == \"completion\":\n            purpose = \"legacy text completion\"\n        else:\n            purpose = \"provider method\"\n        rows.append([name, purpose])\n    print_table([\"method\", \"purpose\"], rows)\n    print()\n    print(\"## Tools\")\n    print()\n    print(\", \".join(info[\"tools\"]) if info[\"tools\"] else \"-\")\n    print()\n    print(\"## Auth And Routing\")\n    print()\n    print_table(\n        [\"field\", \"value\"],\n        [\n            [\"api_key_env\", info[\"environment_variable\"]],\n            [\"base_urls\", compact(info[\"base_urls\"])],\n            [\"headers\", compact(info[\"headers\"])],\n            [\"exports\", compact(info[\"exports\"])],\n        ],\n    )\n    if info[\"routing\"]:\n        print()\n        print(\"## Routing Notes\")\n        for index, item in enumerate(info[\"routing\"], start=1):\n            print(f\"{index}. {item}\")\n    print()\n    print(\"## Boundary\")\n    print(\"Use `/api/v1/models` for live model price/context/availability. Use this SDK info for JavaScript provider usage.\")\n\n\ndef version_tuple(version: str) -> tuple[int, ...]:\n    parts: list[int] = []\n    for part in version.split(\".\"):\n        digits = \"\"\n        for char in part:\n            if char.isdigit():\n                digits += char\n            else:\n                break\n        parts.append(int(digits or 0))\n    return tuple(parts)\n\n\ndef cmd_sdk_check(args: argparse.Namespace) -> None:\n    installed, installed_path = find_installed_sdk_package(args.project)\n    installed_version = str(installed.get(\"version\")) if installed else \"-\"\n    latest_version = \"-\"\n    registry_source = SDK_REGISTRY_URL\n    metadata = None\n    if not args.offline:\n        metadata = fetch_npm_package_metadata()\n        latest_version = str((metadata.get(\"dist-tags\") or {}).get(\"latest\") or \"-\")\n    target_version = args.version or SDK_RECOMMENDED_VERSION\n\n    print(\"# AIHubMix SDK Check\")\n    print()\n    print(f\"- Package: `{SDK_PACKAGE_NAME}`\")\n    print(f\"- Recommended version for this skill: `{SDK_RECOMMENDED_VERSION}`\")\n    print(f\"- Target version: `{target_version}`\")\n    print(f\"- Installed version: `{installed_version}`\")\n    print(f\"- Installed package.json: `{installed_path or '-'}`\")\n    print(f\"- Registry latest: `{latest_version}`\")\n    print(f\"- Registry source: `{registry_source if not args.offline else 'not checked (--offline)'}`\")\n    print(\"- Auto update: `not performed`\")\n\n    status = []\n    if installed_version == \"-\":\n        status.append(\"SDK is not installed in the selected project path.\")\n    elif installed_version == target_version:\n        status.append(\"Installed SDK matches the target version.\")\n    else:\n        status.append(\"Installed SDK differs from the target version.\")\n\n    if latest_version != \"-\":\n        if version_tuple(latest_version) > version_tuple(target_version):\n            status.append(\"A newer npm version is available; review changelog before updating.\")\n        elif latest_version == target_version:\n            status.append(\"Target version is the npm latest version.\")\n        else:\n            status.append(\"Target version is newer than registry latest; verify the package tag.\")\n    else:\n        status.append(\"Latest npm version was not checked.\")\n\n    print()\n    print(\"## Status\")\n    for item in status:\n        print(f\"- {item}\")\n\n    print()\n    print(\"## Manual Commands\")\n    print()\n    print(\"```bash\")\n    print(f\"npm view {SDK_PACKAGE_NAME} version\")\n    print(f\"npm install {SDK_PACKAGE_NAME}@{target_version} ai\")\n    print(\"```\")\n    print()\n    print(\"Only run install/update commands after the user confirms the target project and version.\")\n\n\ndef base_url() -> str:\n    return os.environ.get(\"AIHUBMIX_BASE_URL\", DEFAULT_SERVER_URL).rstrip(\"/\")\n\n\ndef normalize_protocol(protocol: str) -> str:\n    normalized = PROTOCOL_ALIASES.get(protocol, protocol)\n    if normalized not in PROTOCOL_SPECS:\n        raise ValueError(normalized)\n    return normalized\n\n\ndef endpoint_path(protocol: str, model: str) -> str:\n    protocol = normalize_protocol(protocol)\n    path = PROTOCOL_SPECS[protocol][\"path\"]\n    return path.replace(\"{model}\", model).replace(\"{video_id}\", \"video_123\")\n\n\ndef example_payload(protocol: str, model: str) -> dict[str, Any]:\n    protocol = normalize_protocol(protocol)\n    if protocol == \"chat\":\n        return {\n            \"model\": model,\n            \"messages\": [{\"role\": \"user\", \"content\": \"Say hello in one short sentence.\"}],\n        }\n    if protocol == \"responses\":\n        return {\"model\": model, \"input\": \"Say hello in one short sentence.\"}\n    if protocol == \"messages\":\n        return {\n            \"model\": model,\n            \"max_tokens\": 128,\n            \"messages\": [{\"role\": \"user\", \"content\": \"Say hello in one short sentence.\"}],\n        }\n    if protocol == \"gemini\":\n        return {\"contents\": [{\"role\": \"user\", \"parts\": [{\"text\": \"Say hello in one short sentence.\"}]}]}\n    if protocol == \"completions\":\n        return {\"model\": model, \"prompt\": \"Say hello in one short sentence.\", \"max_tokens\": 64}\n    if protocol == \"embeddings\":\n        return {\"model\": model, \"input\": \"Text to embed with AIHubMix.\"}\n    if protocol == \"images\":\n        return {\"model\": model, \"prompt\": \"A clean product mockup on a white background.\", \"size\": \"1024x1024\"}\n    if protocol == \"videos\":\n        return {\"model\": model, \"prompt\": \"A short cinematic shot of a city at sunrise.\"}\n    if protocol == \"video-remix\":\n        return {\"model\": model, \"prompt\": \"Make the video brighter and more cinematic.\"}\n    if protocol == \"audio-speech\":\n        return {\"model\": model, \"input\": \"Hello from AIHubMix.\", \"voice\": \"alloy\", \"response_format\": \"mp3\"}\n    if protocol in {\"audio-transcriptions\", \"audio-translations\"}:\n        return {\"model\": model, \"file\": \"@/path/to/audio.mp3\"}\n    if protocol == \"moderations\":\n        return {\"model\": model, \"input\": \"I want to check whether this text is safe.\"}\n    if protocol in {\"video-retrieve\", \"video-delete\", \"video-content\"}:\n        return {}\n    raise ValueError(protocol)\n\n\ndef auth_header(protocol: str) -> tuple[str, str]:\n    protocol = normalize_protocol(protocol)\n    family = PROTOCOL_SPECS[protocol][\"family\"]\n    if family == \"anthropic\":\n        return \"x-api-key\", \"$AIHUBMIX_API_KEY\"\n    if family == \"gemini\":\n        return \"x-goog-api-key\", \"$AIHUBMIX_API_KEY\"\n    return \"Authorization\", \"Bearer $AIHUBMIX_API_KEY\"\n\n\ndef detect_os(requested: str) -> str:\n    if requested != \"auto\":\n        return requested\n    system = platform.system().lower()\n    if system.startswith(\"win\"):\n        return \"windows\"\n    if system == \"darwin\":\n        return \"mac\"\n    return \"linux\"\n\n\ndef powershell_literal(value: str) -> str:\n    return \"'\" + value.replace(\"'\", \"''\") + \"'\"\n\n\ndef powershell_response_printer() -> str:\n    return (\n        \"if ($response.choices -and $response.choices.Count -gt 0) {\\n\"\n        \"  [Console]::WriteLine($response.choices[0].message.content)\\n\"\n        \"} elseif ($response.output_text) {\\n\"\n        \"  [Console]::WriteLine($response.output_text)\\n\"\n        \"} elseif ($response.content -and $response.content.Count -gt 0) {\\n\"\n        \"  [Console]::WriteLine($response.content[0].text)\\n\"\n        \"} elseif ($response.candidates -and $response.candidates.Count -gt 0) {\\n\"\n        \"  [Console]::WriteLine($response.candidates[0].content.parts[0].text)\\n\"\n        \"} else {\\n\"\n        \"  $response | ConvertTo-Json -Depth 20\\n\"\n        \"}\\n\"\n    )\n\n\ndef powershell_response_printer_for(protocol: str) -> str:\n    protocol = normalize_protocol(protocol)\n    if protocol == \"embeddings\":\n        return (\n            \"if ($response.data -and $response.data.Count -gt 0) {\\n\"\n            \"  [Console]::WriteLine(\\\"embedding dimensions: \\\" + $response.data[0].embedding.Count)\\n\"\n            \"} else {\\n\"\n            \"  $response | ConvertTo-Json -Depth 20\\n\"\n            \"}\\n\"\n        )\n    if protocol == \"images\":\n        return (\n            \"if ($response.data -and $response.data.Count -gt 0) {\\n\"\n            \"  $item = $response.data[0]\\n\"\n            \"  if ($item.url) { [Console]::WriteLine($item.url) } elseif ($item.b64_json) { [Console]::WriteLine($item.b64_json) } else { $item | ConvertTo-Json -Depth 20 }\\n\"\n            \"} else {\\n\"\n            \"  $response | ConvertTo-Json -Depth 20\\n\"\n            \"}\\n\"\n        )\n    if protocol in {\"videos\", \"video-remix\", \"video-retrieve\"}:\n        return (\n            \"if ($response.id) {\\n\"\n            \"  [Console]::WriteLine(\\\"video id: \\\" + $response.id)\\n\"\n            \"} else {\\n\"\n            \"  $response | ConvertTo-Json -Depth 20\\n\"\n            \"}\\n\"\n        )\n    if protocol in {\"audio-transcriptions\", \"audio-translations\"}:\n        return (\n            \"if ($response.text) {\\n\"\n            \"  [Console]::WriteLine($response.text)\\n\"\n            \"} else {\\n\"\n            \"  $response | ConvertTo-Json -Depth 20\\n\"\n            \"}\\n\"\n        )\n    if protocol == \"moderations\":\n        return (\n            \"if ($response.results -and $response.results.Count -gt 0) {\\n\"\n            \"  $response.results[0] | ConvertTo-Json -Depth 20\\n\"\n            \"} else {\\n\"\n            \"  $response | ConvertTo-Json -Depth 20\\n\"\n            \"}\\n\"\n        )\n    return powershell_response_printer()\n\n\ndef shell_response_parser() -> str:\n    return (\n        \"import json,sys; d=json.load(sys.stdin); \"\n        \"text=(d.get('output_text') or ((d.get('choices') or [{}])[0].get('message') or {}).get('content') \"\n        \"or ((d.get('content') or [{}])[0]).get('text') \"\n        \"or ((((d.get('candidates') or [{}])[0].get('content') or {}).get('parts') or [{}])[0]).get('text')); \"\n        \"print(text if text is not None else json.dumps(d, ensure_ascii=False))\"\n    )\n\n\ndef shell_response_parser_for(protocol: str) -> str:\n    protocol = normalize_protocol(protocol)\n    if protocol == \"embeddings\":\n        return (\n            \"import json,sys; d=json.load(sys.stdin); data=d.get('data') or []; \"\n            \"print('embedding dimensions: ' + str(len((data[0] if data else {}).get('embedding') or [])))\"\n        )\n    if protocol == \"images\":\n        return (\n            \"import json,sys; d=json.load(sys.stdin); item=(d.get('data') or [{}])[0]; \"\n            \"print(item.get('url') or item.get('b64_json') or json.dumps(d, ensure_ascii=False))\"\n        )\n    if protocol in {\"videos\", \"video-remix\", \"video-retrieve\"}:\n        return (\n            \"import json,sys; d=json.load(sys.stdin); \"\n            \"print(('video id: ' + str(d.get('id'))) if d.get('id') else json.dumps(d, ensure_ascii=False))\"\n        )\n    if protocol in {\"audio-transcriptions\", \"audio-translations\"}:\n        return \"import json,sys; d=json.load(sys.stdin); print(d.get('text') or json.dumps(d, ensure_ascii=False))\"\n    if protocol == \"moderations\":\n        return (\n            \"import json,sys; d=json.load(sys.stdin); \"\n            \"print(json.dumps((d.get('results') or [d])[0], ensure_ascii=False))\"\n        )\n    return shell_response_parser()\n\n\ndef render_cmd_example(protocol: str, model: str, os_name: str) -> str:\n    protocol = normalize_protocol(protocol)\n    url = base_url() + endpoint_path(protocol, model)\n    payload = example_payload(protocol, model)\n    spec = PROTOCOL_SPECS[protocol]\n    method = spec[\"method\"]\n    is_get_or_delete = method in {\"GET\", \"DELETE\"}\n    is_multipart = bool(spec.get(\"multipart\"))\n    is_binary = bool(spec.get(\"binary_response\") or protocol == \"video-content\")\n    needs_video_id = bool(spec.get(\"needs_video_id\"))\n    body = json.dumps(payload, ensure_ascii=False, indent=2)\n    header_name, _ = auth_header(protocol)\n\n    if os_name == \"windows\":\n        if spec[\"family\"] == \"anthropic\":\n            auth_line = '\"x-api-key\" = $AIHUBMIX_API_KEY'\n        elif spec[\"family\"] == \"gemini\":\n            auth_line = '\"x-goog-api-key\" = $AIHUBMIX_API_KEY'\n        else:\n            auth_line = '\"Authorization\" = \"Bearer $AIHUBMIX_API_KEY\"'\n        if is_get_or_delete:\n            if is_binary:\n                return (\n                    \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                    \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                    \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n                    \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\"\n                    \"$videoId = Read-Host \\\"Paste video id\\\"\\n\"\n                    f\"$url = {powershell_literal(url)}.Replace('video_123', $videoId)\\n\\n\"\n                    \"Invoke-WebRequest `\\n\"\n                    \"  -Uri $url `\\n\"\n                    \"  -Method Get `\\n\"\n                    f\"  -Headers @{{ {auth_line} }} `\\n\"\n                    \"  -OutFile 'aihubmix-video.mp4'\\n\\n\"\n                    \"[Console]::WriteLine('Saved to aihubmix-video.mp4')\"\n                )\n            return (\n                \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n                \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\"\n                \"$videoId = Read-Host \\\"Paste video id\\\"\\n\"\n                f\"$url = {powershell_literal(url)}.Replace('video_123', $videoId)\\n\\n\"\n                \"$response = Invoke-RestMethod `\\n\"\n                \"  -Uri $url `\\n\"\n                f\"  -Method {method.title()} `\\n\"\n                f\"  -Headers @{{ {auth_line}; \\\"Accept\\\" = \\\"application/json\\\" }}\\n\\n\"\n                f\"{powershell_response_printer_for(protocol)}\"\n            )\n        if is_multipart:\n            return (\n                \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n                \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\"\n                \"$audioPath = Read-Host \\\"Paste local audio file path\\\"\\n\\n\"\n                \"$form = @{\\n\"\n                f\"  model = {powershell_literal(model)}\\n\"\n                \"  file = Get-Item -LiteralPath $audioPath\\n\"\n                \"}\\n\\n\"\n                \"$response = Invoke-RestMethod `\\n\"\n                f\"  -Uri {powershell_literal(url)} `\\n\"\n                \"  -Method Post `\\n\"\n                f\"  -Headers @{{ {auth_line}; \\\"Accept\\\" = \\\"application/json\\\" }} `\\n\"\n                \"  -Form $form\\n\\n\"\n                f\"{powershell_response_printer_for(protocol)}\"\n            )\n        if needs_video_id:\n            return (\n                \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Console]::InputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n                \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\"\n                \"$videoId = Read-Host \\\"Paste video id\\\"\\n\"\n                f\"$url = {powershell_literal(url)}.Replace('video_123', $videoId)\\n\\n\"\n                \"$body = @'\\n\"\n                f\"{body}\\n\"\n                \"'@\\n\\n\"\n                \"$response = Invoke-RestMethod `\\n\"\n                \"  -Uri $url `\\n\"\n                f\"  -Method {method.title()} `\\n\"\n                f\"  -Headers @{{ {auth_line}; \\\"Accept\\\" = \\\"application/json\\\" }} `\\n\"\n                \"  -ContentType \\\"application/json\\\" `\\n\"\n                \"  -Body $body\\n\\n\"\n                f\"{powershell_response_printer_for(protocol)}\\n\"\n                \"# To inspect the full response, uncomment the next line:\\n\"\n                \"# $response | ConvertTo-Json -Depth 20\"\n            )\n        if is_binary:\n            return (\n                \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n                \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n                \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\\n\"\n                \"$body = @'\\n\"\n                f\"{body}\\n\"\n                \"'@\\n\\n\"\n                \"Invoke-WebRequest `\\n\"\n                f\"  -Uri {powershell_literal(url)} `\\n\"\n                \"  -Method Post `\\n\"\n                f\"  -Headers @{{ {auth_line} }} `\\n\"\n                \"  -ContentType \\\"application/json\\\" `\\n\"\n                \"  -Body $body `\\n\"\n                \"  -OutFile 'aihubmix-output.mp3'\\n\\n\"\n                \"[Console]::WriteLine('Saved to aihubmix-output.mp3')\"\n            )\n        return (\n            \"$OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n            \"[Console]::OutputEncoding = [System.Text.Encoding]::UTF8\\n\"\n            \"[Console]::InputEncoding = [System.Text.Encoding]::UTF8\\n\"\n            \"[Net.ServicePointManager]::SecurityProtocol = [Net.SecurityProtocolType]::Tls12\\n\"\n            \"$AIHUBMIX_API_KEY = Read-Host \\\"Paste AIHubMix API Key\\\"\\n\\n\"\n            \"$body = @'\\n\"\n            f\"{body}\\n\"\n            \"'@\\n\\n\"\n            \"$response = Invoke-RestMethod `\\n\"\n            f\"  -Uri {powershell_literal(url)} `\\n\"\n            \"  -Method Post `\\n\"\n            f\"  -Headers @{{ {auth_line}; \\\"Accept\\\" = \\\"application/json\\\" }} `\\n\"\n            \"  -ContentType \\\"application/json\\\" `\\n\"\n            \"  -Body $body\\n\\n\"\n            f\"{powershell_response_printer_for(protocol)}\\n\"\n            \"# To inspect the full response, uncomment the next line:\\n\"\n            \"# $response | ConvertTo-Json -Depth 20\"\n        )\n\n    if spec[\"family\"] == \"anthropic\":\n        auth_arg = '-H \"x-api-key: $AIHUBMIX_API_KEY\"'\n    elif spec[\"family\"] == \"gemini\":\n        auth_arg = '-H \"x-goog-api-key: $AIHUBMIX_API_KEY\"'\n    else:\n        auth_arg = '-H \"Authorization: Bearer $AIHUBMIX_API_KEY\"'\n    if is_get_or_delete:\n        if is_binary:\n            return textwrap.dedent(\n                f\"\"\"\\\n                read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n                read -rp \"Paste video id: \" video_id\n\n                curl -L -s {json.dumps(url)} \\\\\n                  {auth_arg} \\\\\n                  -o aihubmix-video.mp4\n\n                echo \"Saved to aihubmix-video.mp4\"\n                \"\"\"\n            ).strip().replace(\"video_123\", \"${video_id}\")\n        return textwrap.dedent(\n            f\"\"\"\\\n            read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n            read -rp \"Paste video id: \" video_id\n\n            curl -s -X {method} {json.dumps(url)} \\\\\n              {auth_arg} \\\\\n              -H \"Accept: application/json\" \\\\\n              | python3 -c {json.dumps(shell_response_parser_for(protocol))}\n            \"\"\"\n        ).strip().replace(\"video_123\", \"${video_id}\")\n    if is_multipart:\n        return textwrap.dedent(\n            f\"\"\"\\\n            read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n            read -rp \"Paste local audio file path: \" audio_path\n\n            curl -s {json.dumps(url)} \\\\\n              {auth_arg} \\\\\n              -H \"Accept: application/json\" \\\\\n              -F model={json.dumps(model)} \\\\\n              -F file=@\"$audio_path\" \\\\\n              | python3 -c {json.dumps(shell_response_parser_for(protocol))}\n            \"\"\"\n        ).strip()\n    if needs_video_id:\n        compact_payload_video = json.dumps(payload, ensure_ascii=False)\n        return textwrap.dedent(\n            f\"\"\"\\\n            read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n            read -rp \"Paste video id: \" video_id\n\n            curl -s -X {method} {json.dumps(url)} \\\\\n              {auth_arg} \\\\\n              -H \"Content-Type: application/json\" \\\\\n              -d {json.dumps(compact_payload_video)} \\\\\n              | python3 -c {json.dumps(shell_response_parser_for(protocol))}\n            \"\"\"\n        ).strip().replace(\"video_123\", \"${video_id}\")\n    if is_binary:\n        compact_payload_binary = json.dumps(payload, ensure_ascii=False)\n        return textwrap.dedent(\n            f\"\"\"\\\n            read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n\n            curl -L -s {json.dumps(url)} \\\\\n              {auth_arg} \\\\\n              -H \"Content-Type: application/json\" \\\\\n              -d {json.dumps(compact_payload_binary)} \\\\\n              -o aihubmix-output.mp3\n\n            echo \"Saved to aihubmix-output.mp3\"\n            \"\"\"\n        ).strip()\n    compact_payload = json.dumps(payload, ensure_ascii=False)\n    return textwrap.dedent(\n        f\"\"\"\\\n        read -rsp \"Paste AIHubMix API Key: \" AIHUBMIX_API_KEY; echo\n\n        curl -s {json.dumps(url)} \\\\\n          {auth_arg} \\\\\n          -H \"Content-Type: application/json\" \\\\\n          -d {json.dumps(compact_payload)} \\\\\n          | python3 -c {json.dumps(shell_response_parser_for(protocol))}\n        \"\"\"\n    ).strip()\n\n\ndef render_js_example(protocol: str, model: str) -> str:\n    protocol = normalize_protocol(protocol)\n    if protocol == \"chat\":\n        return textwrap.dedent(\n            f\"\"\"\\\n            import {{ aihubmix }} from \"@aihubmix/ai-sdk-provider\";\n            import {{ generateText }} from \"ai\";\n\n            const {{ text }} = await generateText({{\n              model: aihubmix({json.dumps(model)}),\n              prompt: \"Say hello in one short sentence.\",\n            }});\n\n            console.log(text);\n            \"\"\"\n        ).strip()\n\n    payload = example_payload(protocol, model)\n    path = endpoint_path(protocol, model)\n    spec = PROTOCOL_SPECS[protocol]\n    header_name, header_value = auth_header(protocol)\n    header_value_js = (\n        \"process.env.AIHUBMIX_API_KEY\"\n        if spec[\"family\"] in {\"anthropic\", \"gemini\"}\n        else '`Bearer ${process.env.AIHUBMIX_API_KEY}`'\n    )\n    payload_js = json.dumps(payload, ensure_ascii=False, indent=2)\n    payload_body_lines = [\"  body: JSON.stringify(\" + payload_js.splitlines()[0]]\n    payload_body_lines.extend(\"  \" + line for line in payload_js.splitlines()[1:])\n    payload_body_lines[-1] = payload_body_lines[-1] + \"),\"\n    if spec.get(\"multipart\"):\n        return textwrap.dedent(\n            f\"\"\"\\\n            import {{ createReadStream }} from \"node:fs\";\n\n            const form = new FormData();\n            form.set(\"model\", {json.dumps(model)});\n            form.set(\"file\", createReadStream(process.env.AUDIO_FILE ?? \"./audio.mp3\"));\n\n            const response = await fetch(\"{base_url()}{path}\", {{\n              method: \"POST\",\n              headers: {{\n                {json.dumps(header_name)}: {header_value_js},\n              }},\n              body: form,\n            }});\n\n            if (!response.ok) {{\n              throw new Error(`${{response.status}} ${{await response.text()}}`);\n            }}\n\n            const data = await response.json();\n            console.log(data.text ?? JSON.stringify(data, null, 2));\n            \"\"\"\n        ).strip()\n    if spec.get(\"binary_response\"):\n        return \"\\n\".join(\n            [\n                'import { writeFile } from \"node:fs/promises\";',\n                \"\",\n                f'const response = await fetch(\"{base_url()}{path}\", {{',\n                '  method: \"POST\",',\n                \"  headers: {\",\n                f\"    {json.dumps(header_name)}: {header_value_js},\",\n                '    \"Content-Type\": \"application/json\",',\n                \"  },\",\n                *payload_body_lines,\n                \"});\",\n                \"\",\n                \"if (!response.ok) {\",\n                \"  throw new Error(`${response.status} ${await response.text()}`);\",\n                \"}\",\n                \"\",\n                'await writeFile(\"aihubmix-output.mp3\", Buffer.from(await response.arrayBuffer()));',\n                'console.log(\"Saved to aihubmix-output.mp3\");',\n            ]\n        )\n    if protocol == \"video-content\":\n        return textwrap.dedent(\n            f\"\"\"\\\n            import {{ writeFile }} from \"node:fs/promises\";\n\n            const videoId = process.env.AIHUBMIX_VIDEO_ID ?? \"video_123\";\n            const response = await fetch(\"{base_url()}{path}\".replace(\"video_123\", videoId), {{\n              method: \"GET\",\n              headers: {{\n                {json.dumps(header_name)}: {header_value_js},\n              }},\n            }});\n\n            if (!response.ok) {{\n              throw new Error(`${{response.status}} ${{await response.text()}}`);\n            }}\n\n            await writeFile(\"aihubmix-video.mp4\", Buffer.from(await response.arrayBuffer()));\n            console.log(\"Saved to aihubmix-video.mp4\");\n            \"\"\"\n        ).strip()\n    if spec[\"method\"] in {\"GET\", \"DELETE\"}:\n        return textwrap.dedent(\n            f\"\"\"\\\n            const videoId = process.env.AIHUBMIX_VIDEO_ID ?? \"video_123\";\n            const response = await fetch(\"{base_url()}{path}\".replace(\"video_123\", videoId), {{\n              method: {json.dumps(spec[\"method\"])},\n              headers: {{\n                {json.dumps(header_name)}: {header_value_js},\n                \"Accept\": \"application/json\",\n              }},\n            }});\n\n            if (!response.ok) {{\n              throw new Error(`${{response.status}} ${{await response.text()}}`);\n            }}\n\n            const data = await response.json();\n            console.log(data.id ? `video id: ${{data.id}}` : JSON.stringify(data, null, 2));\n            \"\"\"\n        ).strip()\n    if spec.get(\"needs_video_id\"):\n        path_expr = f'\"{base_url()}{path}\".replace(\"video_123\", videoId)'\n        return \"\\n\".join(\n            [\n                'const videoId = process.env.AIHUBMIX_VIDEO_ID ?? \"video_123\";',\n                f\"const response = await fetch({path_expr}, {{\",\n                f'  method: {json.dumps(spec[\"method\"])},',\n                \"  headers: {\",\n                f\"    {json.dumps(header_name)}: {header_value_js},\",\n                '    \"Content-Type\": \"application/json\",',\n                \"  },\",\n                *payload_body_lines,\n                \"});\",\n                \"\",\n                \"if (!response.ok) {\",\n                \"  throw new Error(`${response.status} ${await response.text()}`);\",\n                \"}\",\n                \"\",\n                \"const data = await response.json();\",\n                \"console.log(data.id ? `video id: ${data.id}` : JSON.stringify(data, null, 2));\",\n            ]\n        )\n    payload_json = json.dumps(payload, ensure_ascii=False, indent=2)\n    payload_lines = [\"  body: JSON.stringify(\" + payload_json.splitlines()[0]]\n    payload_lines.extend(\"  \" + line for line in payload_json.splitlines()[1:])\n    payload_lines[-1] = payload_lines[-1] + \"),\"\n    return \"\\n\".join(\n        [\n            f'const response = await fetch(\"{base_url()}{path}\", {{',\n            f'  method: {json.dumps(spec[\"method\"])},',\n            \"  headers: {\",\n            f\"    {json.dumps(header_name)}: {header_value_js},\",\n            '    \"Content-Type\": \"application/json\",',\n            \"  },\",\n            *payload_lines,\n            \"});\",\n            \"\",\n            \"if (!response.ok) {\",\n            \"  throw new Error(`${response.status} ${await response.text()}`);\",\n            \"}\",\n            \"\",\n            \"const data = await response.json();\",\n            \"const text =\",\n            \"  data.output_text ??\",\n            \"  data.choices?.[0]?.message?.content ??\",\n            \"  data.content?.[0]?.text ??\",\n            \"  data.candidates?.[0]?.content?.parts?.[0]?.text ??\",\n            \"  data.data?.[0]?.url ??\",\n            \"  data.data?.[0]?.b64_json ??\",\n            \"  data.text ??\",\n            \"  (data.id ? `video id: ${data.id}` : undefined);\",\n            \"\",\n            \"console.log(text ?? JSON.stringify(data, null, 2));\",\n        ]\n    )\n\n\ndef cmd_example(args: argparse.Namespace) -> None:\n    protocol = args.protocol\n    model = args.model\n    os_name = detect_os(args.os)\n    if args.lang == \"both\":\n        print(f\"## Command Line ({'Windows PowerShell' if os_name == 'windows' else 'macOS/Linux shell'})\")\n        print()\n        print(example_intro(\"command\", os_name))\n        print()\n        print(\"```\" + (\"powershell\" if os_name == \"windows\" else \"bash\"))\n        print(render_cmd_example(protocol, model, os_name))\n        print(\"```\")\n        print()\n        print(\"## JavaScript\")\n        print()\n        print(example_intro(\"js\"))\n        print()\n        print_env_setup(\"js\", os_name)\n        print(\"```js\")\n        print(render_js_example(protocol, model))\n        print(\"```\")\n        return\n\n    url = base_url() + endpoint_path(protocol, model)\n    payload = example_payload(protocol, model)\n    header_name, header_value = auth_header(protocol)\n    body = json.dumps(payload, ensure_ascii=False, indent=2)\n\n    if args.lang == \"json\":\n        print(body)\n        return\n\n    if args.lang == \"curl\":\n        print(render_cmd_example(protocol, model, os_name))\n        return\n\n    if args.lang == \"python\":\n        if normalize_protocol(protocol) == \"chat\":\n            print(\n                textwrap.dedent(\n                    f\"\"\"\\\n                    import os\n                    from openai import OpenAI\n\n                    client = OpenAI(\n                        api_key=os.environ[\"AIHUBMIX_API_KEY\"],\n                        base_url=\"{base_url()}/v1\",\n                    )\n\n                    response = client.chat.completions.create(\n                        model={model!r},\n                        messages=[{{\"role\": \"user\", \"content\": \"Say hello in one short sentence.\"}}],\n                    )\n                    print(response.choices[0].message.content)\n                    \"\"\"\n                ).strip()\n            )\n        else:\n            print(\"# Use the command-line or JavaScript example for this endpoint shape.\")\n        return\n\n    if args.lang == \"js\":\n        print(render_js_example(protocol, model))\n        return\n\n    raise ValueError(args.lang)\n\n\ndef parse_error_body(body_text: str | None, body_file: str | None) -> dict[str, Any] | None:\n    if body_file:\n        body_text = Path(body_file).read_text(encoding=\"utf-8\")\n    if not body_text:\n        return None\n    try:\n        data = json.loads(body_text)\n        return data if isinstance(data, dict) else {\"raw\": data}\n    except json.JSONDecodeError:\n        return {\"raw\": body_text}\n\n\ndef cmd_troubleshoot(args: argparse.Namespace) -> None:\n    body = parse_error_body(args.body, args.body_file)\n    error = body.get(\"error\") if isinstance(body, dict) and isinstance(body.get(\"error\"), dict) else {}\n    message = error.get(\"message\") or (body or {}).get(\"message\") if isinstance(body, dict) else None\n    kind = error.get(\"type\")\n    param = error.get(\"param\")\n    code = error.get(\"code\")\n\n    print(\"Observed\")\n    print_table(\n        [\"field\", \"value\"],\n        [\n            [\"status\", str(args.status or \"-\")],\n            [\"endpoint\", args.endpoint or \"-\"],\n            [\"model\", args.model or \"-\"],\n            [\"error.type\", str(kind or \"-\")],\n            [\"error.param\", str(param or \"-\")],\n            [\"error.code\", str(code or \"-\")],\n            [\"error.message\", str(message or \"-\")],\n            [\"request_id\", args.request_id or \"check X-Request-Id response header\"],\n        ],\n    )\n\n    if args.contract:\n        contract = load_error_contract()\n        status_key = \"5XX\" if args.status and args.status >= 500 else str(args.status or \"\")\n        status_contract = contract[\"statuses\"].get(status_key, {})\n        is_gateway_shape = isinstance(error, dict) and bool(message)\n        print(\"\\nContract Match\")\n        print_table(\n            [\"field\", \"value\"],\n            [\n                [\"contract_source\", display_error_contract_source()],\n                [\"schema\", contract[\"schema_name\"]],\n                [\"status_contract\", status_contract.get(\"description\", \"not declared\")],\n                [\"body_shape\", \"GatewayError-like\" if is_gateway_shape else \"not enough evidence\"],\n                [\"request_id_rule\", contract[\"request_id\"]],\n                [\"error_type_rule\", contract[\"envelope\"][\"fields\"][\"error.type\"]],\n            ],\n        )\n\n    print(\"\\nSuggested checks\")\n    suggestions = []\n    status = args.status\n    if status in (401, 403):\n        suggestions.extend(\n            [\n                \"Confirm AIHUBMIX_API_KEY is present and sent with the right header for the endpoint.\",\n                \"Use Authorization: Bearer for OpenAI-shaped endpoints, x-api-key for /v1/messages, and x-goog-api-key or ?key= for Gemini-shaped endpoints.\",\n            ]\n        )\n    elif status == 404:\n        suggestions.extend(\n            [\n                \"Confirm the endpoint path matches the protocol contract.\",\n                \"Confirm the model exists in /api/v1/models and the model ID is copied exactly.\",\n            ]\n        )\n    elif status == 400:\n        suggestions.extend(\n            [\n                \"Validate the request body against aihubmix-openapi openapi.json or contract.json.\",\n                \"Check whether the model supports the requested endpoint, modality, and feature fields.\",\n            ]\n        )\n    elif status == 429:\n        suggestions.append(\"Check rate limits, quota, and retry policy before re-sending the same request.\")\n    elif status and status >= 500:\n        suggestions.extend(\n            [\n                \"Treat this as gateway or upstream failure; preserve status, error body, and X-Request-Id.\",\n                \"Retry only when the operation is idempotent or the client can tolerate duplicate work.\",\n            ]\n        )\n    else:\n        suggestions.append(\"Start with status, error body, endpoint, model ID, and X-Request-Id.\")\n\n    if args.model:\n        suggestions.append(\"Run `models get <model_id>` to inspect context_length, max_output, endpoints, and features.\")\n    if args.endpoint:\n        suggestions.append(\"Run `protocols` to inspect the endpoint security scheme and requestBody contract.\")\n    for index, item in enumerate(suggestions, start=1):\n        print(f\"{index}. {item}\")\n\n\n# --- Preflight (doctor) + image-input candidates --------------------------\n\n\ndef _openai_base(explicit: str | None = None) -> str:\n    \"\"\"OpenAI-compatible base URL, tolerant of a trailing /v1 already present.\"\"\"\n    raw = (explicit or os.environ.get(\"AIHUBMIX_BASE_URL\") or DEFAULT_SERVER_URL).rstrip(\"/\")\n    return raw if raw.endswith(\"/v1\") else raw + \"/v1\"\n\n\ndef _http_request(\n    url: str,\n    method: str = \"GET\",\n    headers: dict[str, str] | None = None,\n    body: dict[str, Any] | None = None,\n    timeout: float = 30,\n) -> tuple[int | None, str]:\n    \"\"\"Minimal JSON HTTP call. Returns (status, text); status is None on network error.\"\"\"\n    data = json.dumps(body).encode(\"utf-8\") if body is not None else None\n    request = urllib.request.Request(url, data=data, method=method, headers=headers or {})\n    try:\n        with urllib.request.urlopen(request, timeout=timeout) as response:\n            status = getattr(response, \"status\", None) or response.getcode()\n            return status, response.read().decode(\"utf-8\", errors=\"replace\")\n    except urllib.error.HTTPError as exc:\n        return exc.code, exc.read().decode(\"utf-8\", errors=\"replace\")\n    except urllib.error.URLError as exc:\n        return None, f\"URLError: {exc.reason}\"\n    except (TimeoutError, OSError) as exc:\n        return None, f\"network error: {exc}\"\n\n\ndef _mask_secret(secret: str) -> str:\n    secret = (secret or \"\").strip()\n    if not secret:\n        return \"(none)\"\n    if len(secret) <= 12:\n        return secret[:2] + \"…\" + secret[-2:]\n    return secret[:5] + \"…\" + secret[-4:]\n\n\ndef _redact(text: str, *secrets: str) -> str:\n    \"\"\"Scrub keys from upstream text (AIHubMix echoes the key in invalid-key errors).\"\"\"\n    out = text or \"\"\n    for secret in secrets:\n        secret = (secret or \"\").strip()\n        if len(secret) >= 6:\n            out = out.replace(secret, \"[REDACTED]\")\n            if secret.lower().startswith(\"sk-\"):\n                out = out.replace(secret[3:], \"[REDACTED]\")\n    return re.sub(r\"sk-[A-Za-z0-9]{6,}\", \"[REDACTED]\", out)\n\n\ndef _extract_chat_reply(body: str) -> str | None:\n    try:\n        data = json.loads(body)\n        content = data[\"choices\"][0][\"message\"][\"content\"]\n    except (ValueError, KeyError, IndexError, TypeError):\n        return None\n    if isinstance(content, list):\n        return \" \".join(part.get(\"text\", \"\") for part in content if isinstance(part, dict)).strip()\n    return str(content).strip()\n\n\ndef _looks_like_auth_error(body: str) -> bool:\n    low = (body or \"\").lower()\n    return any(\n        token in low\n        for token in (\n            \"invalid key\", \"invalid api key\", \"incorrect api key\", \"unauthorized\",\n            \"authentication\", \"no permission\", \"无效\", \"鉴权\", \"未授权\", \"令牌\",\n        )\n    )\n\n\ndef _looks_like_balance_error(body: str) -> bool:\n    low = (body or \"\").lower()\n    return any(\n        token in low\n        for token in (\n            \"insufficient balance\", \"insufficient_quota\", \"insufficient funds\", \"no balance\",\n            \"balance is not enough\", \"arrearage\", \"余额不足\", \"余额已用\", \"欠费\", \"额度不足\",\n        )\n    )\n\n\ndef _solid_png_data_url(rgb: tuple[int, int, int] = (20, 90, 210), size: int = 64) -> str:\n    \"\"\"Build a tiny solid-color PNG data URL (stdlib only) for probing image input.\"\"\"\n    import base64\n    import struct\n    import zlib\n\n    def chunk(tag: bytes, payload: bytes) -> bytes:\n        return (\n            struct.pack(\">I\", len(payload))\n            + tag\n            + payload\n            + struct.pack(\">I\", zlib.crc32(tag + payload) & 0xFFFFFFFF)\n        )\n\n    signature = b\"\\x89PNG\\r\\n\\x1a\\n\"\n    ihdr = struct.pack(\">IIBBBBB\", size, size, 8, 2, 0, 0, 0)  # 8-bit RGB\n    raw = b\"\".join(b\"\\x00\" + bytes(rgb) * size for _ in range(size))\n    png = signature + chunk(b\"IHDR\", ihdr) + chunk(b\"IDAT\", zlib.compress(raw)) + chunk(b\"IEND\", b\"\")\n    return \"data:image/png;base64,\" + base64.b64encode(png).decode(\"ascii\")\n\n\ndef cmd_doctor(args: argparse.Namespace) -> int:\n    key = (args.key or os.environ.get(\"AIHUBMIX_API_KEY\") or \"\").strip()\n    base = _openai_base(args.base_url)\n    timeout = args.timeout\n\n    print(_t(\"AIHubMix preflight (doctor)\", \"AIHubMix 预检 (doctor)\"))\n    print(f\"base_url: {base}\")\n    print(f\"key: {_mask_secret(key)}\\n\")\n\n    if not key:\n        print(_t(\"[✗] KEY    missing — set AIHUBMIX_API_KEY or pass --key <key>\",\n                 \"[✗] KEY    未提供 — 设置环境变量 AIHUBMIX_API_KEY 或传 --key <key>\"))\n        print(_t(\"\\nResult: FAIL. No API key available.\", \"\\n结论: 失败。没有可用的 API key。\"))\n        return 1\n    print(_t(\"[✓] KEY    provided\", \"[✓] KEY    已提供\"))\n\n    headers = {\n        \"Authorization\": f\"Bearer {key}\",\n        \"Content-Type\": \"application/json\",\n        \"Accept\": \"application/json\",\n        \"User-Agent\": \"aihubmixApi-skill/0.1\",\n    }\n\n    # The public /v1/models list does NOT require auth, so it cannot validate a\n    # key. Only a real chat call can — use a tiny one as the auth + text probe.\n    probe_model = args.model or \"gpt-4o-mini\"\n    payload = {\"model\": probe_model, \"messages\": [{\"role\": \"user\", \"content\": \"ping\"}], \"max_tokens\": 8, \"temperature\": 0}\n    status, body = _http_request(f\"{base}/chat/completions\", method=\"POST\", headers=headers, body=payload, timeout=timeout)\n    reply = _extract_chat_reply(body) if status == 200 else None\n    if reply is not None:\n        note = \"\" if args.model else _t(\" (probe model gpt-4o-mini)\", \"（探测模型 gpt-4o-mini）\")\n        print(_t(f\"[✓] AUTH   key valid, {probe_model} call OK{note} → {reply[:60]!r}\",\n                 f\"[✓] AUTH   key 有效，{probe_model} 调用成功{note} → {reply[:60]!r}\"))\n    elif status == 402 or _looks_like_balance_error(body):\n        print(_t(f\"[✗] BILLING key valid but insufficient balance/quota — HTTP {status}: {_redact(body, key)[:300]}\",\n                 f\"[✗] 余额   key 有效但余额/额度不足 — HTTP {status}: {_redact(body, key)[:300]}\"))\n        print(_t(\"\\nResult: FAIL (billing). The key works; the account needs a top-up.\",\n                 \"\\n结论: 失败（计费）。key 本身可用，但账户需要充值。\"))\n        return 1\n    elif status in (401, 403) or _looks_like_auth_error(body):\n        print(_t(f\"[✗] AUTH   invalid key / no permission — HTTP {status}: {_redact(body, key)[:300]}\",\n                 f\"[✗] AUTH   key 无效/无权限 — HTTP {status}: {_redact(body, key)[:300]}\"))\n        print(_t(\"\\nResult: FAIL. Check the key is correct, enabled, and funded.\",\n                 \"\\n结论: 失败。请检查 key 是否正确、已启用、有余额。\"))\n        return 1\n    else:\n        info = f\"HTTP {status}\" if status else _t(\"network unreachable\", \"网络不可达\")\n        print(_t(f\"[⚠] AUTH   unconfirmed — probing with {probe_model} returned {info}: {_redact(body, key)[:200]}\",\n                 f\"[⚠] AUTH   未能确认 — 用 {probe_model} 探测返回 {info}: {_redact(body, key)[:200]}\"))\n        print(_t(\"           Usually the model is not available to your key (key likely fine); retry with --model <a model you can access>.\",\n                 \"           多半是该模型对你的 key 不可用，而非 key 失效；用 --model <你有权限的模型> 重测。\"))\n        print(_t(\"\\nResult: NOT PASSED (could not confirm key). Retry with --model <available model>.\",\n                 \"\\n结论: 未通过（无法确认 key）。建议用 --model 指定可用模型重测。\"))\n        return 1\n\n    overall_ok = True\n\n    if args.image:\n        if not args.model:\n            print(_t(\"[–] IMAGE  skipped (image probe needs --model <id>; you/the LLM pick which vision model)\",\n                     \"[–] IMAGE  跳过（图片实测需要 --model <id>；该测哪个视觉模型由你/LLM 决定）\"))\n        else:\n            payload = {\n                \"model\": args.model,\n                \"max_tokens\": 16,\n                \"temperature\": 0,\n                \"messages\": [\n                    {\n                        \"role\": \"user\",\n                        \"content\": [\n                            {\"type\": \"text\", \"text\": \"What is the dominant color of this image? Answer with one word.\"},\n                            {\"type\": \"image_url\", \"image_url\": {\"url\": _solid_png_data_url()}},\n                        ],\n                    }\n                ],\n            }\n            status, body = _http_request(f\"{base}/chat/completions\", method=\"POST\", headers=headers, body=payload, timeout=timeout)\n            reply = _extract_chat_reply(body) if status == 200 else None\n            if reply is not None:\n                print(_t(f\"[✓] IMAGE  {args.model} accepts image input → {reply[:60]!r}\",\n                         f\"[✓] IMAGE  {args.model} 接受图片输入 → {reply[:60]!r}\"))\n            else:\n                overall_ok = False\n                print(_t(f\"[✗] IMAGE  {args.model} no image support or call failed — HTTP {status}: {_redact(body, key)[:300]}\",\n                         f\"[✗] IMAGE  {args.model} 不支持图片或调用失败 — HTTP {status}: {_redact(body, key)[:300]}\"))\n\n    print()\n    if overall_ok:\n        tail = (\n            _t(\"Tested capabilities all OK.\", \"已实测的能力均正常。\")\n            if args.model\n            else _t(\"Key valid; add --model <id> (and --image) to test a specific model.\",\n                    \"key 有效；加 --model <id>（可再加 --image）可实测具体模型。\")\n        )\n        print(_t(f\"Result: PASS. {tail}\", f\"结论: 通过。{tail}\"))\n        return 0\n    print(_t(\"Result: some checks did not pass — see the [✗] items above.\",\n             \"结论: 部分检查未通过，见上面的 [✗] 项。\"))\n    return 1\n\n\n# Categories that cannot accept chat input, dropped from input-modality\n# candidate ranges (e.g. vision) even when the noisy modality field tags them.\n_NON_CHAT_RE = re.compile(\n    r\"(embed|rerank|\\bbge\\b|\\bbce\\b|\\bgte\\b|\\bm3e\\b|jina|moderation|\"\n    r\"whisper|\\btts\\b|text-to-speech|speech|transcrib|\"\n    r\"flux|stable-diffusion|\\bsdxl\\b|dall-?e|midjourney|imagen|gpt-image|qwen-image|\"\n    r\"seedream|seededit|kolors|cogview|ideogram|recraft|hunyuan-image|\"\n    r\"\\bveo\\b|sora|kling|runway|video|hailuo|seedance|vidu)\",\n    re.IGNORECASE,\n)\n\n\ndef _is_non_chat(model: dict[str, Any]) -> bool:\n    \"\"\"Drop models that cannot accept chat input (embeddings, generation, audio, video).\"\"\"\n    if suggested_protocol(model) in {\n        \"embeddings\", \"images\", \"videos\", \"moderations\",\n        \"audio-speech\", \"audio-transcriptions\", \"audio-translations\",\n    }:\n        return True\n    return bool(_NON_CHAT_RE.search(f\"{model_id(model)} {model_label(model)}\"))\n\n\n# Capability discovery is deliberately broad + heuristic. Each spec scores a\n# model by up to three signals and the caller/LLM picks from the range:\n#   protocol: suggested_protocol(model) lands in the capability's endpoint set\n#   modality: the model's metadata text contains a capability keyword\n#   family:   the model id/name matches a known family regex\n# protocol/family are treated as reliable; modality-only is noisy. The tool\n# never picks a default and never asserts a hard capability fact.\nCAPABILITY_SPECS: dict[str, dict[str, Any]] = {\n    \"vision\": {\n        \"label\": \"图片输入 / 看图（chat 模型接受图片）\",\n        \"aliases\": [\"image-input\", \"multimodal\", \"mm\", \"vlm\", \"看图\", \"图片输入\", \"多模态\"],\n        \"protocols\": None,\n        \"modality_tokens\": [\"image\", \"vision\", \"multimodal\", \"visual\"],\n        \"require_chat\": True,\n        \"family\": (\n            r\"gpt-4o|gpt-4\\.1|gpt-4-vision|gpt-4-turbo|gpt-5|chatgpt-4o|o1|o3|o4-mini|\"\n            r\"gemini|claude-3|claude-4|claude-sonnet|claude-opus|claude-haiku|\"\n            r\"qwen[\\w.-]*vl|qwen-vl|glm-4v|glm-[\\d.]+v|cogvlm|cogagent|yi-vision|yi-vl|\"\n            r\"step-1v|step-1o|step-3|internvl|llava|pixtral|moondream|\"\n            r\"llama[\\w.-]*vision|grok[\\w.-]*vision|grok-2-vision|grok-4|\"\n            r\"doubao[\\w.-]*vision|ernie[\\w.-]*vl|minicpm-v|nova-lite|nova-pro|\"\n            r\"phi-3[\\w.-]*vision|phi-4[\\w.-]*multimodal|kimi[\\w.-]*vl|kimi-latest|moonshot[\\w.-]*vl|\"\n            r\"mistral-small-3|molmo|deepseek-vl\"\n        ),\n    },\n    \"image-gen\": {\n        \"label\": \"图像生成 / 文生图（text-to-image）\",\n        \"aliases\": [\"t2i\", \"image-generation\", \"imagegen\", \"生图\", \"文生图\", \"画图\"],\n        \"protocols\": {\"images\"},\n        \"modality_tokens\": [\"image_generation\", \"text-to-image\"],\n        \"require_chat\": False,\n        \"family\": (\n            r\"flux|kontext|stable-diffusion|\\bsd3\\b|\\bsdxl\\b|dall-?e|midjourney|\\bmj\\b|\"\n            r\"imagen|gpt-image|qwen-image|hunyuan-image|hidream|seedream|seededit|kolors|\"\n            r\"cogview|ideogram|recraft|wanx|gemini[\\w.-]*image|nano-banana|grok[\\w.-]*image|playground-v\"\n        ),\n    },\n    \"video\": {\n        \"label\": \"视频生成（text/image-to-video）\",\n        \"aliases\": [\"t2v\", \"video-generation\", \"生视频\", \"文生视频\", \"视频\"],\n        \"protocols\": {\"videos\"},\n        \"modality_tokens\": [\"video\"],\n        \"require_chat\": False,\n        \"family\": (\n            r\"veo|sora|kling|runway|gen-?3|hailuo|minimax[\\w.-]*video|seedance|vidu|\"\n            r\"wan[\\w.-]*|cogvideo|pika|luma|dream-machine|ray-?2|pixverse|mochi|\\bltx\\b\"\n        ),\n    },\n    \"audio-tts\": {\n        \"label\": \"语音合成（文字转语音 TTS）\",\n        \"aliases\": [\"tts\", \"text-to-speech\", \"speech\", \"语音合成\"],\n        \"protocols\": {\"audio-speech\"},\n        \"modality_tokens\": [\"speech\", \"text-to-speech\", \"tts\"],\n        \"require_chat\": False,\n        \"family\": (\n            r\"\\btts\\b|text-to-speech|speech-0|cosyvoice|fish[\\w.-]*audio|elevenlabs|\"\n            r\"gpt-4o[\\w.-]*tts|qwen[\\w.-]*tts|doubao[\\w.-]*tts|minimax[\\w.-]*speech|index-tts\"\n        ),\n    },\n    \"audio-stt\": {\n        \"label\": \"语音识别 / 转写（STT/ASR）\",\n        \"aliases\": [\"stt\", \"asr\", \"transcription\", \"whisper\", \"语音识别\", \"转写\"],\n        \"protocols\": {\"audio-transcriptions\", \"audio-translations\"},\n        \"modality_tokens\": [\"transcription\", \"translation\"],\n        \"require_chat\": False,\n        \"family\": (\n            r\"whisper|transcrib|gpt-4o[\\w.-]*transcribe|qwen[\\w.-]*audio|sensevoice|paraformer|fun-?asr\"\n        ),\n    },\n    \"embedding\": {\n        \"label\": \"向量嵌入（embedding）\",\n        \"aliases\": [\"embed\", \"embeddings\", \"向量\", \"嵌入\"],\n        \"protocols\": {\"embeddings\"},\n        \"modality_tokens\": [\"embedding\"],\n        \"require_chat\": False,\n        \"exclude\": r\"rerank\",\n        \"family\": (\n            r\"embed|text-embedding|\\bbge\\b|bge-[\\w.-]+|\\bbce\\b|\\bgte\\b|\\bm3e\\b|jina[\\w.-]*embed|\"\n            r\"nomic[\\w.-]*embed|qwen[\\w.-]*embedding|conan-embedding|doubao[\\w.-]*embedding|\\bgme\\b\"\n        ),\n    },\n    \"rerank\": {\n        \"label\": \"重排（rerank）\",\n        \"aliases\": [\"reranker\", \"重排\"],\n        \"protocols\": None,\n        \"modality_tokens\": [\"rerank\"],\n        \"require_chat\": False,\n        \"family\": r\"rerank|reranker|bge[\\w.-]*rerank|bce[\\w.-]*rerank|jina[\\w.-]*rerank|qwen3?-?rerank\",\n    },\n}\n\nfor _spec in CAPABILITY_SPECS.values():\n    _spec[\"_family_re\"] = re.compile(_spec[\"family\"], re.IGNORECASE)\n    _spec[\"_exclude_re\"] = re.compile(_spec[\"exclude\"], re.IGNORECASE) if _spec.get(\"exclude\") else None\n\n\ndef resolve_capability(name: str | None) -> str:\n    key = (name or \"vision\").strip().lower()\n    if key in CAPABILITY_SPECS:\n        return key\n    for cap, spec in CAPABILITY_SPECS.items():\n        if key in [alias.lower() for alias in spec[\"aliases\"]]:\n            return cap\n    raise SystemExit(f\"未知能力: {name}。可选: {', '.join(CAPABILITY_SPECS)}\")\n\n\ndef _capability_signals(model: dict[str, Any], spec: dict[str, Any]) -> list[str]:\n    signals: list[str] = []\n    if spec[\"protocols\"] and suggested_protocol(model) in spec[\"protocols\"]:\n        signals.append(\"protocol\")\n    cap_text = \" \".join(\n        compact(model.get(key))\n        for key in (\"features\", \"capabilities\", \"input_modalities\", \"modality\", \"modalities\", \"types\", \"type\", \"endpoints\")\n        if model.get(key) is not None\n    ).lower()\n    if any(token in cap_text for token in spec[\"modality_tokens\"]):\n        signals.append(\"modality\")\n    if spec[\"_family_re\"].search(f\"{model_id(model)} {model_label(model)}\"):\n        signals.append(\"family\")\n    return signals\n\n\n# --- Companion aihubmix CLI helpers (account data; opt-in only) -------------\n\n\ndef _find_aihubmix() -> str | None:\n    \"\"\"Locate the companion aihubmix CLI on PATH or known install locations.\"\"\"\n    found = shutil.which(CLI_BIN)\n    if found:\n        return found\n    candidates: list[Path] = []\n    local = os.environ.get(\"LOCALAPPDATA\")\n    if local:\n        candidates.append(Path(local) / \"aihubmix\" / \"bin\" / \"aihubmix.exe\")\n    home = Path.home()\n    candidates += [home / \".local\" / \"bin\" / CLI_BIN, Path(\"/usr/local/bin\") / CLI_BIN]\n    for candidate in candidates:\n        try:\n            if candidate.is_file():\n                return str(candidate)\n        except OSError:\n            continue\n    return None\n\n\ndef _install_aihubmix() -> bool:\n    \"\"\"Run the official per-OS installer (explicit / opt-in only). Returns success.\"\"\"\n    if platform.system().lower().startswith(\"win\"):\n        cmd = [\"powershell\", \"-NoProfile\", \"-Command\", f\"irm {CLI_INSTALL_PS1} | iex\"]\n    else:\n        cmd = [\"sh\", \"-c\", f\"curl -fsSL {CLI_INSTALL_SH} | sh\"]\n    try:\n        return subprocess.run(cmd, timeout=300).returncode == 0\n    except (OSError, subprocess.SubprocessError):\n        return False\n\n\ndef cmd_install_cli(args: argparse.Namespace) -> int:\n    existing = _find_aihubmix()\n    if existing and not args.force:\n        print(_t(f\"aihubmix CLI already installed: {existing}\", f\"aihubmix CLI 已安装：{existing}\"))\n        print(_t(f\"Project: {CLI_REPO_URL}\", f\"项目主页：{CLI_REPO_URL}\"))\n        return 0\n    print(_t(f\"Installing the aihubmix CLI (project: {CLI_REPO_URL}) ...\",\n             f\"正在安装 aihubmix CLI（项目主页：{CLI_REPO_URL}）...\"))\n    if _install_aihubmix() and _find_aihubmix():\n        print(_t(\"Done. Next: run `aihubmix login` to authenticate.\",\n                 \"完成。下一步：运行 `aihubmix login` 登录。\"))\n        return 0\n    print(_t(f\"Install failed. Install manually — see {CLI_REPO_URL}\",\n             f\"安装失败。请手动安装，见 {CLI_REPO_URL}\"))\n    return 1\n\n\ndef _my_callable_models(auto_install: bool = False) -> set[str]:\n    \"\"\"Lowercased ids the user's token can actually call (`aihubmix models list -j`).\"\"\"\n    exe = _find_aihubmix()\n    if not exe and auto_install:\n        print(_t(\"aihubmix CLI not found; installing (--auto-install) ...\",\n                 \"未找到 aihubmix CLI，正在自动安装（--auto-install）...\"), file=sys.stderr)\n        if _install_aihubmix():\n            exe = _find_aihubmix()\n    if not exe:\n        raise SystemExit(_t(\n            f\"--mine needs the aihubmix CLI. Run `install-cli` (or add --auto-install). Project: {CLI_REPO_URL}\",\n            f\"--mine 需要 aihubmix CLI。先运行 `install-cli`（或加 --auto-install）。项目主页：{CLI_REPO_URL}\"))\n    try:\n        result = subprocess.run([exe, \"models\", \"list\", \"-j\"], capture_output=True, text=True, timeout=60)\n    except (OSError, subprocess.SubprocessError) as exc:\n        raise SystemExit(f\"`aihubmix models list` failed: {exc}\")\n    if result.returncode != 0:\n        detail = (result.stderr or result.stdout or \"\").strip()\n        if \"未登录\" in detail or \"login\" in detail.lower() or \"token\" in detail.lower():\n            raise SystemExit(_t(\n                f\"Not logged in. Run `aihubmix login` first, or drop --mine. Project: {CLI_REPO_URL}\",\n                f\"尚未登录。请先 `aihubmix login`，或去掉 --mine。项目主页：{CLI_REPO_URL}\"))\n        raise SystemExit(f\"`aihubmix models list` error: {detail[:200]}\")\n    try:\n        data = json.loads(result.stdout)\n    except ValueError:\n        raise SystemExit(\"could not parse `aihubmix models list -j` output\")\n    rows = data.get(\"data\") if isinstance(data, dict) else data\n    return {\n        str(row.get(\"model\")).strip().lower()\n        for row in (rows or [])\n        if isinstance(row, dict) and row.get(\"model\")\n    }\n\n\ndef cmd_candidates(args: argparse.Namespace) -> None:\n    cap = resolve_capability(getattr(args, \"capability\", None))\n    spec = CAPABILITY_SPECS[cap]\n    models = extract_models(load_json_source(args.source))\n\n    mine = None\n    if getattr(args, \"mine\", False):\n        mine = _my_callable_models(auto_install=getattr(args, \"auto_install\", False))\n\n    picked: list[tuple[dict[str, Any], bool, str]] = []\n    for item in models:\n        if spec[\"require_chat\"] and _is_non_chat(item):\n            continue\n        exclude_re = spec.get(\"_exclude_re\")\n        if exclude_re and exclude_re.search(f\"{model_id(item)} {model_label(item)}\"):\n            continue\n        if mine is not None and model_id(item).strip().lower() not in mine:\n            continue  # keep only models the user's token can actually call\n        signals = _capability_signals(item, spec)\n        if not signals:\n            continue\n        strong = (\"protocol\" in signals) or (\"family\" in signals)\n        picked.append((item, strong, \"+\".join(signals)))\n    # Reliable protocol/family matches first, then noisier modality-only ones.\n    picked.sort(key=lambda row: (0 if row[1] else 1, model_id(row[0]).lower()))\n    selected = [(item, signal) for item, _strong, signal in picked[: args.limit]]\n\n    if args.json:\n        print(json.dumps(\n            [\n                {\n                    \"capability\": cap,\n                    \"mine\": mine is not None,\n                    \"model_id\": model_id(item),\n                    \"name\": model_label(item),\n                    \"signal\": signal,\n                    \"features\": features(item),\n                    \"context\": context_display(item),\n                }\n                for item, signal in selected\n            ],\n            ensure_ascii=False,\n            indent=2,\n        ))\n        return\n\n    mine_en = \" callable by your token\" if mine is not None else \"\"\n    mine_zh = \"（已按你的 token 可调过滤）\" if mine is not None else \"\"\n    print(_t(\n        f\"AIHubMix candidate models for capability '{cap}'{mine_en} (broad heuristic: protocol / family / modality; no default picked)\",\n        f\"AIHubMix【{spec['label']}】候选模型{mine_zh}（宽口径启发式：协议 / 家族名 / modality 字段；不替你挑默认）\",\n    ))\n    if mine is not None and not selected:\n        print(_t(\n            f\"\\nNone of the '{cap}' candidates are callable by your token. Try without --mine, or check `aihubmix models list`.\",\n            f\"\\n你的 token 在【{cap}】下没有可调候选。可去掉 --mine，或查 `aihubmix models list`。\",\n        ))\n        return\n    print(_t(\n        \"Note: a candidate is not a guarantee; pick per task (you/the LLM), then confirm with `doctor`.\",\n        \"注意：候选不等于确定可用；请由调用方/LLM 按任务从中挑选，再用 `doctor` 实测确认。\",\n    ))\n    print()\n    rows = [\n        [model_id(item), model_label(item), signal, features(item) or \"-\", context_display(item)]\n        for item, signal in selected\n    ]\n    print_table([\"model_id\", \"name\", \"signal\", \"features/modalities\", \"context\"], rows)\n    mine_foot_en = \" | filtered to your token\" if mine is not None else \"\"\n    mine_foot_zh = \" | 已按你的 token 过滤\" if mine is not None else \"\"\n    print(_t(\n        f\"\\ncapability: {cap} | {len(selected)} candidates{mine_foot_en} | source: {display_models_source()}\",\n        f\"\\n能力: {cap} | 共 {len(selected)} 个候选{mine_foot_zh} | source: {display_models_source()}\",\n    ))\n    print(_t(\n        \"signal: protocol=endpoint type; family=known family name (both reliable); modality=metadata keyword only (noisy, verify).\",\n        \"signal: protocol=接口类型匹配；family=按已知家族名匹配（均较可靠）；modality=仅元数据出现关键词（噪声大，需实测）。\",\n    ))\n\n\ndef build_parser() -> argparse.ArgumentParser:\n    parser = argparse.ArgumentParser(description=\"Query AIHubMix models and API contract helpers.\")\n    parser.add_argument(\n        \"--lang\", choices=[\"en\", \"zh\"],\n        help=\"Output language for status lines/labels (default: env AIHUBMIX_LANG or en).\",\n    )\n    subparsers = parser.add_subparsers(dest=\"command\", required=True)\n\n    list_parser = subparsers.add_parser(\"list\", help=\"List models from the models API.\")\n    list_parser.add_argument(\"--source\", help=\"Models JSON URL, local JSON file, or '-' for stdin.\")\n    list_parser.add_argument(\"--query\", help=\"Filter models by substring.\")\n    list_parser.add_argument(\"--limit\", type=int, default=50)\n    list_parser.add_argument(\"--json\", action=\"store_true\")\n    list_parser.set_defaults(func=cmd_list)\n\n    get_parser = subparsers.add_parser(\"get\", help=\"Show one model by ID or substring.\")\n    get_parser.add_argument(\"model\")\n    get_parser.add_argument(\"--source\")\n    get_parser.add_argument(\"--json\", action=\"store_true\")\n    get_parser.set_defaults(func=cmd_get)\n\n    compare_parser = subparsers.add_parser(\"compare\", help=\"Compare pricing and context for models.\")\n    compare_parser.add_argument(\"models\", nargs=\"+\")\n    compare_parser.add_argument(\"--source\")\n    compare_parser.add_argument(\"--json\", action=\"store_true\")\n    compare_parser.set_defaults(func=cmd_compare)\n\n    latest_parser = subparsers.add_parser(\"latest-report\", help=\"Report the first N models with pricing, context, and an example.\")\n    latest_parser.add_argument(\"--source\", help=\"Models JSON URL, local JSON file, or '-' for stdin.\")\n    latest_parser.add_argument(\"--limit\", type=int, default=5)\n    latest_parser.add_argument(\"--os\", choices=[\"auto\", \"windows\", \"mac\", \"linux\"], default=\"auto\")\n    latest_parser.set_defaults(func=cmd_latest_report)\n\n    report_parser = subparsers.add_parser(\"report\", help=\"Report models matching a query with pricing, context, endpoint, and examples.\")\n    report_parser.add_argument(\"query\")\n    report_parser.add_argument(\"--source\", help=\"Models JSON URL, local JSON file, or '-' for stdin.\")\n    report_parser.add_argument(\"--limit\", type=int, default=20)\n    report_parser.add_argument(\"--os\", choices=[\"auto\", \"windows\", \"mac\", \"linux\"], default=\"auto\")\n    report_parser.set_defaults(func=cmd_report)\n\n    protocols_parser = subparsers.add_parser(\"protocols\", help=\"Summarize live aihubmix OpenAPI operations (remote).\")\n    protocols_parser.add_argument(\"--json\", action=\"store_true\")\n    protocols_parser.set_defaults(func=cmd_protocols)\n\n    error_contract_parser = subparsers.add_parser(\"error-contract\", help=\"Summarize the GatewayError contract from the live OpenAPI spec (remote).\")\n    error_contract_parser.add_argument(\"--json\", action=\"store_true\")\n    error_contract_parser.set_defaults(func=cmd_error_contract)\n\n    sdk_parser = subparsers.add_parser(\"sdk-check\", help=\"Check @aihubmix/ai-sdk-provider version without installing or updating it.\")\n    sdk_parser.add_argument(\"--project\", help=\"Project directory to search for node_modules.\")\n    sdk_parser.add_argument(\"--version\", help=\"Target SDK version to compare against.\")\n    sdk_parser.add_argument(\"--offline\", action=\"store_true\", help=\"Skip npm registry latest-version check.\")\n    sdk_parser.set_defaults(func=cmd_sdk_check)\n\n    sdk_info_parser = subparsers.add_parser(\"sdk-info\", help=\"Summarize @aihubmix/ai-sdk-provider capabilities and auth/routing defaults.\")\n    sdk_info_parser.add_argument(\"--project\", help=\"Project directory to search for installed node_modules.\")\n    sdk_info_parser.add_argument(\"--package-dir\", help=\"Path to an unpacked @aihubmix/ai-sdk-provider package directory.\")\n    sdk_info_parser.add_argument(\"--version\", default=SDK_RECOMMENDED_VERSION, help=\"SDK version to inspect from npm when no package is installed.\")\n    sdk_info_parser.add_argument(\n        \"--source\",\n        choices=[\"auto\", \"installed\", \"npm\"],\n        default=\"auto\",\n        help=\"SDK metadata source. npm reads the package tarball from the npm registry.\",\n    )\n    sdk_info_parser.add_argument(\"--json\", action=\"store_true\")\n    sdk_info_parser.set_defaults(func=cmd_sdk_info)\n\n    example_parser = subparsers.add_parser(\"example\", help=\"Generate minimal API call examples.\")\n    example_parser.add_argument(\n        \"protocol\",\n        choices=sorted([*PROTOCOL_SPECS.keys(), *PROTOCOL_ALIASES.keys()]),\n        help=\"Protocol or endpoint shape to generate.\",\n    )\n    example_parser.add_argument(\"--model\", required=True)\n    example_parser.add_argument(\"--lang\", choices=[\"both\", \"curl\", \"python\", \"js\", \"json\"], default=\"both\")\n    example_parser.add_argument(\"--os\", choices=[\"auto\", \"windows\", \"mac\", \"linux\"], default=\"auto\")\n    example_parser.set_defaults(func=cmd_example)\n\n    troubleshoot_parser = subparsers.add_parser(\"troubleshoot\", help=\"Explain common API failure checks.\")\n    troubleshoot_parser.add_argument(\"--status\", type=int)\n    troubleshoot_parser.add_argument(\"--body\", help=\"JSON error body string.\")\n    troubleshoot_parser.add_argument(\"--body-file\", help=\"Path to a JSON error body.\")\n    troubleshoot_parser.add_argument(\"--endpoint\")\n    troubleshoot_parser.add_argument(\"--model\")\n    troubleshoot_parser.add_argument(\"--request-id\")\n    troubleshoot_parser.add_argument(\"--contract\", action=\"store_true\", help=\"Also fetch the live GatewayError contract (remote) and show a match.\")\n    troubleshoot_parser.set_defaults(func=cmd_troubleshoot)\n\n    doctor_parser = subparsers.add_parser(\n        \"doctor\",\n        help=\"Preflight an AIHubMix key: verify auth, then optionally smoke-test text and image input on a chosen model.\",\n    )\n    doctor_parser.add_argument(\"--key\", help=\"API key. Defaults to env AIHUBMIX_API_KEY. Never printed in full.\")\n    doctor_parser.add_argument(\"--base-url\", help=\"OpenAI-compatible base. Defaults to env AIHUBMIX_BASE_URL or https://aihubmix.com/v1.\")\n    doctor_parser.add_argument(\"--model\", help=\"Model id to smoke-test (text; also image with --image).\")\n    doctor_parser.add_argument(\"--image\", action=\"store_true\", help=\"Also probe image input on --model.\")\n    doctor_parser.add_argument(\"--timeout\", type=float, default=30)\n    doctor_parser.set_defaults(func=cmd_doctor)\n\n    candidates_parser = subparsers.add_parser(\n        \"candidates\",\n        help=\"List a BROAD candidate range for a capability (vision/image-gen/video/audio-tts/audio-stt/embedding/rerank); caller/LLM picks, tool chooses no default.\",\n    )\n    candidates_parser.add_argument(\n        \"--capability\", \"-c\", required=True,\n        help=\"Capability or alias. One of: \" + \", \".join(CAPABILITY_SPECS) + \".\",\n    )\n    candidates_parser.add_argument(\"--source\", help=\"Models JSON URL, local JSON file, or '-' for stdin.\")\n    candidates_parser.add_argument(\"--limit\", type=int, default=40)\n    candidates_parser.add_argument(\"--json\", action=\"store_true\")\n    candidates_parser.add_argument(\"--mine\", action=\"store_true\", help=\"Filter to models your token can actually call (needs the aihubmix CLI + login).\")\n    candidates_parser.add_argument(\"--auto-install\", action=\"store_true\", help=\"With --mine: install the aihubmix CLI automatically if missing.\")\n    candidates_parser.set_defaults(func=cmd_candidates)\n\n    vision_parser = subparsers.add_parser(\n        \"vision-candidates\",\n        help=\"Alias for `candidates --capability vision`.\",\n    )\n    vision_parser.add_argument(\"--source\", help=\"Models JSON URL, local JSON file, or '-' for stdin.\")\n    vision_parser.add_argument(\"--limit\", type=int, default=40)\n    vision_parser.add_argument(\"--json\", action=\"store_true\")\n    vision_parser.add_argument(\"--mine\", action=\"store_true\", help=\"Filter to models your token can actually call.\")\n    vision_parser.add_argument(\"--auto-install\", action=\"store_true\", help=\"With --mine: install the aihubmix CLI automatically if missing.\")\n    vision_parser.set_defaults(func=cmd_candidates, capability=\"vision\")\n\n    install_cli_parser = subparsers.add_parser(\n        \"install-cli\",\n        help=\"Install the companion aihubmix CLI via its official per-OS installer.\",\n    )\n    install_cli_parser.add_argument(\"--force\", action=\"store_true\", help=\"Reinstall even if already present.\")\n    install_cli_parser.set_defaults(func=cmd_install_cli)\n\n    return parser\n\n\ndef main() -> int:\n    parser = build_parser()\n    args = parser.parse_args()\n    global _LANG\n    _LANG = (args.lang or os.environ.get(\"AIHUBMIX_LANG\") or \"en\").strip().lower()\n    if _LANG not in (\"en\", \"zh\"):\n        _LANG = \"en\"\n    result = args.func(args)\n    return result if isinstance(result, int) else 0\n\n\nif __name__ == \"__main__\":\n    raise SystemExit(main())\n"}}}}