{"repo": "amb1t10us/tracemind", "files": {"nanobot/nanobot/cli/onboard.py": {"87ab4842c02a1341d9678a703b633523e09c99a5": {"t": 1785595174.5227964, "n": 71613, "h": "ab5d3973c3e2ec59", "c": "\"\"\"Interactive onboarding questionnaire for nanobot.\"\"\"\n\nimport asyncio\nimport json\nimport types\nfrom dataclasses import dataclass\nfrom functools import lru_cache\nfrom typing import Any, Literal, NamedTuple, get_args, get_origin\n\ntry:\n    import questionary\nexcept ModuleNotFoundError:  # pragma: no cover - exercised in environments without wizard deps\n    questionary = None\nfrom loguru import logger\nfrom pydantic import BaseModel\nfrom rich.console import Console\nfrom rich.panel import Panel\nfrom rich.table import Table\n\nfrom nanobot.cli.models import (\n    format_token_count,\n    get_model_context_limit,\n    get_model_suggestions,\n)\nfrom nanobot.config.loader import get_config_path, load_config\nfrom nanobot.config.schema import Config, ModelPresetConfig\n\nconsole = Console()\n\n\n@dataclass\nclass OnboardResult:\n    \"\"\"Result of an onboarding session.\"\"\"\n\n    config: Config\n    should_save: bool\n\n\nclass _QuickStartProviderInfo(NamedTuple):\n    \"\"\"Provider metadata used by the Quick Start flow.\"\"\"\n\n    display_name: str\n    is_local: bool\n    default_api_base: str\n    backend: str\n    is_direct: bool\n\n\nclass _QuickStartEndpointChoice(NamedTuple):\n    \"\"\"Provider endpoint option used by Quick Start.\"\"\"\n\n    label: str\n    api_base: str\n\n\n# --- Field Hints for Select Fields ---\n# Maps field names to (choices, hint_text)\n# To add a new select field with hints, add an entry:\n#   \"field_name\": ([\"choice1\", \"choice2\", ...], \"hint text for the field\")\n_SELECT_FIELD_HINTS: dict[str, tuple[list[str], str]] = {\n    \"reasoning_effort\": (\n        [\"low\", \"medium\", \"high\"],\n        \"low / medium / high - enables LLM thinking mode\",\n    ),\n}\n\n# --- Key Bindings for Navigation ---\n\n_BACK_PRESSED = object()  # Sentinel value for back navigation\n\n# Cache of model-preset names populated at runtime so that field handlers can\n# offer existing presets as choices (e.g. AgentDefaults.model_preset).\n_MODEL_PRESET_CACHE: set[str] = set()\n\n_QUICK_START_CUSTOM_PROVIDER_CHOICE = \"Other OpenAI-compatible\"\n\n_CLEAR_CHOICE = \"Clear value\"\n_QUICK_START_MENU_CHOICE = \"[Q] Quick Start\"\n_QUICK_START_STEPS = (\"Provider setup\", \"WebSocket channel\", \"Review\")\n_QUICK_START_ENDPOINT_CHOICES: dict[str, tuple[_QuickStartEndpointChoice, ...]] = {\n    \"zhipu\": (\n        _QuickStartEndpointChoice(\"Standard API\", \"https://open.bigmodel.cn/api/paas/v4\"),\n        _QuickStartEndpointChoice(\"Coding Plan\", \"https://open.bigmodel.cn/api/coding/paas/v4\"),\n    ),\n    \"minimax\": (\n        _QuickStartEndpointChoice(\"Global API\", \"https://api.minimax.io/v1\"),\n        _QuickStartEndpointChoice(\"Mainland China Token Plan\", \"https://api.minimaxi.com/v1\"),\n    ),\n    \"minimax_anthropic\": (\n        _QuickStartEndpointChoice(\"Global Anthropic API\", \"https://api.minimax.io/anthropic\"),\n        _QuickStartEndpointChoice(\n            \"Mainland China Anthropic Token Plan\",\n            \"https://api.minimaxi.com/anthropic\",\n        ),\n    ),\n    \"stepfun\": (\n        _QuickStartEndpointChoice(\"Standard API\", \"https://api.stepfun.com/v1\"),\n        _QuickStartEndpointChoice(\"Step Plan\", \"https://api.stepfun.ai/step_plan/v1\"),\n    ),\n    \"xiaomi_mimo\": (\n        _QuickStartEndpointChoice(\"Standard API\", \"https://api.xiaomimimo.com/v1\"),\n        _QuickStartEndpointChoice(\"Token Plan\", \"https://token-plan-sgp.xiaomimimo.com/v1\"),\n    ),\n}\n\n# Low-contrast terminal palette inspired by JetBrains Darcula/Islands.\n_UI_ACCENT = \"#6B9BFA\"\n_UI_BORDER = \"#4E5254\"\n_UI_TEXT = \"#A9B7C6\"\n_UI_MUTED = \"#80868B\"\n_UI_SUCCESS = \"#6AAB73\"\n_PROMPT_ESCAPE_TIMEOUT_SECONDS = 0.05\n_CHANNEL_LOGIN_CHOICE = \"Login with QR/link\"\n_CHANNEL_ADVANCED_CHOICE = \"Edit advanced settings\"\n\n\ndef _get_questionary():\n    \"\"\"Return questionary or raise a clear error when wizard deps are unavailable.\"\"\"\n    if questionary is None:\n        raise RuntimeError(\n            \"Interactive onboarding requires the optional 'questionary' dependency. \"\n            \"Install project dependencies and rerun with --wizard.\"\n        )\n    return questionary\n\n\ndef _select_with_back(\n    prompt: str, choices: list[str], default: str | None = None\n) -> str | None | object:\n    \"\"\"Select with Escape/Left arrow support for going back.\n\n    Args:\n        prompt: The prompt text to display.\n        choices: List of choices to select from. Must not be empty.\n        default: The default choice to pre-select. If not in choices, first item is used.\n\n    Returns:\n        _BACK_PRESSED sentinel if user pressed Escape or Left arrow\n        The selected choice string if user confirmed\n        None if user cancelled (Ctrl+C)\n    \"\"\"\n    import shutil\n\n    from prompt_toolkit.application import Application\n    from prompt_toolkit.key_binding import KeyBindings\n    from prompt_toolkit.keys import Keys\n    from prompt_toolkit.layout import Layout\n    from prompt_toolkit.layout.containers import HSplit, Window\n    from prompt_toolkit.layout.controls import FormattedTextControl\n    from prompt_toolkit.styles import Style\n\n    # Validate choices\n    if not choices:\n        logger.warning(\"Empty choices list provided to _select_with_back\")\n        return None\n\n    # Find default index\n    selected_index = 0\n    if default and default in choices:\n        selected_index = choices.index(default)\n\n    # State holder for the result\n    state: dict[str, str | None | object] = {\"result\": None}\n    terminal_lines = shutil.get_terminal_size((80, 24)).lines\n    visible_count = min(len(choices), max(1, terminal_lines - 3))\n\n    # Build menu items (uses closure over selected_index)\n    def get_menu_text():\n        items = []\n        start, end = _choice_viewport(selected_index, len(choices), visible_count)\n        for i in range(start, end):\n            choice = choices[i]\n            if i == selected_index:\n                items.append((\"class:selected\", f\"> {choice}\\n\"))\n            else:\n                items.append((\"\", f\"  {choice}\\n\"))\n        return items\n\n    # Create layout\n    menu_control = FormattedTextControl(get_menu_text, show_cursor=False)\n    menu_window = Window(content=menu_control, height=visible_count, always_hide_cursor=True)\n\n    def get_prompt_text():\n        suffix = f\" ({selected_index + 1}/{len(choices)})\" if len(choices) > visible_count else \"\"\n        return [(\"class:question\", f\"{prompt}{suffix}\")]\n\n    prompt_control = FormattedTextControl(get_prompt_text, show_cursor=False)\n    prompt_window = Window(content=prompt_control, height=1, always_hide_cursor=True)\n\n    layout = Layout(HSplit([prompt_window, menu_window]))\n\n    # Key bindings\n    bindings = KeyBindings()\n\n    @bindings.add(Keys.Up)\n    def _up(event):\n        nonlocal selected_index\n        selected_index = (selected_index - 1) % len(choices)\n        event.app.invalidate()\n\n    @bindings.add(Keys.Down)\n    def _down(event):\n        nonlocal selected_index\n        selected_index = (selected_index + 1) % len(choices)\n        event.app.invalidate()\n\n    @bindings.add(Keys.Enter)\n    def _enter(event):\n        state[\"result\"] = choices[selected_index]\n        event.app.exit()\n\n    @bindings.add(\"escape\")\n    def _escape(event):\n        state[\"result\"] = _BACK_PRESSED\n        event.app.exit()\n\n    @bindings.add(Keys.Left)\n    def _left(event):\n        state[\"result\"] = _BACK_PRESSED\n        event.app.exit()\n\n    @bindings.add(Keys.ControlC)\n    def _ctrl_c(event):\n        state[\"result\"] = None\n        event.app.exit()\n\n    # Style\n    style = Style.from_dict({\n        \"selected\": f\"fg:{_UI_ACCENT} bold\",\n        \"question\": f\"fg:{_UI_TEXT}\",\n    })\n\n    app = Application(layout=layout, key_bindings=bindings, style=style)\n    app.ttimeoutlen = 0.05\n    app.timeoutlen = 0.05\n    try:\n        app.run()\n    except Exception:\n        logger.exception(\"Error in select prompt\")\n        return None\n\n    return state[\"result\"]\n\n\ndef _choice_viewport(selected_index: int, total: int, visible_count: int) -> tuple[int, int]:\n    \"\"\"Return the visible slice for a long terminal menu.\"\"\"\n    if total <= 0:\n        return 0, 0\n    visible_count = max(1, min(visible_count, total))\n    selected_index = max(0, min(selected_index, total - 1))\n    half = visible_count // 2\n    start = selected_index - half\n    start = max(0, min(start, total - visible_count))\n    return start, start + visible_count\n\n# --- Type Introspection ---\n\n\nclass FieldTypeInfo(NamedTuple):\n    \"\"\"Result of field type introspection.\"\"\"\n\n    type_name: str\n    inner_type: Any\n\n\ndef _get_field_type_info(field_info) -> FieldTypeInfo:\n    \"\"\"Extract field type info from Pydantic field.\"\"\"\n    annotation = field_info.annotation\n    if annotation is None:\n        return FieldTypeInfo(\"str\", None)\n\n    origin = get_origin(annotation)\n    args = get_args(annotation)\n\n    if origin is types.UnionType:\n        non_none_args = [a for a in args if a is not type(None)]\n        if len(non_none_args) == 1:\n            annotation = non_none_args[0]\n            origin = get_origin(annotation)\n            args = get_args(annotation)\n\n    _simple_types: dict[type, str] = {bool: \"bool\", int: \"int\", float: \"float\"}\n\n    if origin is list or (hasattr(origin, \"__name__\") and origin.__name__ == \"List\"):\n        return FieldTypeInfo(\"list\", args[0] if args else str)\n    if origin is dict or (hasattr(origin, \"__name__\") and origin.__name__ == \"Dict\"):\n        return FieldTypeInfo(\"dict\", None)\n    for py_type, name in _simple_types.items():\n        if annotation is py_type:\n            return FieldTypeInfo(name, None)\n    if isinstance(annotation, type) and issubclass(annotation, BaseModel):\n        return FieldTypeInfo(\"model\", annotation)\n    if origin is Literal:\n        return FieldTypeInfo(\"literal\", list(args))\n    return FieldTypeInfo(\"str\", None)\n\n\ndef _get_field_display_name(field_key: str, field_info) -> str:\n    \"\"\"Get display name for a field.\"\"\"\n    if field_info and field_info.description:\n        return field_info.description\n    name = field_key\n    suffix_map = {\n        \"_s\": \" seconds\",\n        \"_ms\": \" ms\",\n        \"_url\": \" URL\",\n        \"_path\": \" Path\",\n        \"_id\": \" ID\",\n        \"_key\": \" Key\",\n        \"_token\": \" Token\",\n    }\n    for suffix, replacement in suffix_map.items():\n        if name.endswith(suffix):\n            name = name[: -len(suffix)] + replacement\n            break\n    return name.replace(\"_\", \" \").title()\n\n\n# --- Sensitive Field Masking ---\n\n_SENSITIVE_KEYWORDS = frozenset({\"api_key\", \"token\", \"secret\", \"password\", \"credentials\"})\n\n\ndef _is_sensitive_field(field_name: str) -> bool:\n    \"\"\"Check if a field name indicates sensitive content.\"\"\"\n    return any(kw in field_name.lower() for kw in _SENSITIVE_KEYWORDS)\n\n\ndef _mask_value(value: str) -> str:\n    \"\"\"Mask a sensitive value, showing only the last 4 characters.\"\"\"\n    if len(value) <= 4:\n        return \"****\"\n    return \"*\" * (len(value) - 4) + value[-4:]\n\n\n# --- Value Formatting ---\n\n\ndef _format_value(value: Any, rich: bool = True, field_name: str = \"\") -> str:\n    \"\"\"Single recursive entry point for safe value display. Handles any depth.\"\"\"\n    if value is None or value == \"\" or value == {} or value == []:\n        return \"[dim]not set[/dim]\" if rich else \"[not set]\"\n    if _is_sensitive_field(field_name) and isinstance(value, str):\n        masked = _mask_value(value)\n        return f\"[dim]{masked}[/dim]\" if rich else masked\n    if isinstance(value, BaseModel):\n        parts = []\n        for fname, _finfo in type(value).model_fields.items():\n            fval = getattr(value, fname, None)\n            formatted = _format_value(fval, rich=False, field_name=fname)\n            if formatted != \"[not set]\":\n                parts.append(f\"{fname}={formatted}\")\n        return \", \".join(parts) if parts else (\"[dim]not set[/dim]\" if rich else \"[not set]\")\n    if isinstance(value, list):\n        return \", \".join(str(v) for v in value)\n    if isinstance(value, dict):\n        # Handle dicts containing BaseModel instances\n        parts = []\n        for k, v in value.items():\n            formatted = _format_value(v, rich=False, field_name=str(k))\n            parts.append(f\"{k}: {formatted}\")\n        return \", \".join(parts) if parts else (\"[dim]not set[/dim]\" if rich else \"[not set]\")\n    return str(value)\n\n\ndef _format_value_for_input(value: Any, field_type: str) -> str:\n    \"\"\"Format a value for use as input default.\"\"\"\n    if value is None or value == \"\":\n        return \"\"\n    if field_type == \"list\" and isinstance(value, list):\n        return \",\".join(str(v) for v in value)\n    if field_type == \"dict\" and isinstance(value, dict):\n        return json.dumps(value)\n    return str(value)\n\n\ndef _validate_field_constraint(value: Any, field_info) -> str | None:\n    \"\"\"Validate a value against Pydantic Field constraints.\n\n    Returns an error message string if validation fails, None if valid.\n    Uses attribute-based detection to handle Pydantic v2 internal types.\n    \"\"\"\n    if field_info is None or not hasattr(field_info, \"metadata\"):\n        return None\n\n    for m in field_info.metadata:\n        if hasattr(m, \"ge\") and isinstance(value, (int, float)):\n            if value < m.ge:\n                return f\"Value must be >= {m.ge}\"\n        if hasattr(m, \"gt\") and isinstance(value, (int, float)):\n            if value <= m.gt:\n                return f\"Value must be > {m.gt}\"\n        if hasattr(m, \"le\") and isinstance(value, (int, float)):\n            if value > m.le:\n                return f\"Value must be <= {m.le}\"\n        if hasattr(m, \"lt\") and isinstance(value, (int, float)):\n            if value >= m.lt:\n                return f\"Value must be < {m.lt}\"\n        if hasattr(m, \"min_length\") and hasattr(value, \"__len__\"):\n            if len(value) < m.min_length:\n                return f\"Length must be >= {m.min_length}\"\n        if hasattr(m, \"max_length\") and hasattr(value, \"__len__\"):\n            if len(value) > m.max_length:\n                return f\"Length must be <= {m.max_length}\"\n\n    return None\n\n\ndef _get_constraint_hint(field_info) -> str:\n    \"\"\"Derive a human-readable constraint hint from field metadata.\n\n    Returns a string like \" - 0-10\" or \" - >= 0\" to append to field display names.\n    \"\"\"\n    if field_info is None or not hasattr(field_info, \"metadata\"):\n        return \"\"\n\n    ge_val = None\n    le_val = None\n    for m in field_info.metadata:\n        if hasattr(m, \"ge\"):\n            ge_val = m.ge\n        if hasattr(m, \"le\"):\n            le_val = m.le\n\n    if ge_val is not None and le_val is not None:\n        return f\" - {ge_val}-{le_val}\"\n    if ge_val is not None:\n        return f\" - >= {ge_val}\"\n    if le_val is not None:\n        return f\" - <= {le_val}\"\n    return \"\"\n\n\n# --- Rich UI Components ---\n\n\ndef _show_config_panel(display_name: str, model: BaseModel, fields: list) -> None:\n    \"\"\"Display current configuration as a rich table.\"\"\"\n    table = Table(show_header=False, box=None, padding=(0, 2))\n    table.add_column(\"Field\", style=_UI_ACCENT)\n    table.add_column(\"Value\")\n\n    for fname, field_info in fields:\n        value = getattr(model, fname, None)\n        display = _get_field_display_name(fname, field_info)\n        formatted = _format_value(value, rich=True, field_name=fname)\n        table.add_row(display, formatted)\n\n    console.print(Panel(table, title=f\"[bold {_UI_TEXT}]{display_name}[/]\", border_style=_UI_BORDER))\n\n\ndef _show_main_menu_header() -> None:\n    \"\"\"Display the main menu header.\"\"\"\n    from nanobot import __logo__, __version__\n\n    console.print()\n    body = Table.grid(expand=True)\n    body.add_column(ratio=1)\n    body.add_row(f\"{__logo__} [bold {_UI_TEXT}]nanobot[/] [{_UI_MUTED}]v{__version__}[/]\")\n    body.add_row(f\"[{_UI_ACCENT}]Quick Start asks for the provider, credentials, and model.[/]\")\n    body.add_row(\n        f\"[{_UI_MUTED}]Use Advanced later for chat apps, tools, or provider-specific details.[/]\"\n    )\n    console.print(\n        Panel(\n            body,\n            title=f\"[bold {_UI_TEXT}]Setup Wizard[/]\",\n            border_style=_UI_BORDER,\n            padding=(1, 2),\n        )\n    )\n    console.print()\n\n\ndef _show_section_header(title: str, subtitle: str = \"\") -> None:\n    \"\"\"Display a section header.\"\"\"\n    console.print()\n    if subtitle:\n        console.print(\n            Panel(\n                f\"[{_UI_MUTED}]{subtitle}[/]\",\n                title=f\"[bold {_UI_TEXT}]{title}[/]\",\n                border_style=_UI_BORDER,\n                padding=(1, 2),\n            )\n        )\n    else:\n        console.print(Panel(\"\", title=f\"[bold {_UI_TEXT}]{title}[/]\", border_style=_UI_BORDER))\n\n\n# --- Input Handlers ---\n\n\ndef _input_bool(display_name: str, current: bool | None) -> bool | None:\n    \"\"\"Get boolean input via confirm dialog.\"\"\"\n    return _get_questionary().confirm(\n        display_name,\n        default=bool(current) if current is not None else False,\n    ).ask()\n\n\ndef _input_back_key_bindings():\n    \"\"\"Return key bindings that make Escape behave like a local back action.\"\"\"\n    from prompt_toolkit.key_binding import KeyBindings\n\n    bindings = KeyBindings()\n\n    @bindings.add(\"escape\")\n    def _escape(event):\n        event.app.exit(result=_BACK_PRESSED)\n\n    return bindings\n\n\ndef _ask_prompt(prompt):\n    \"\"\"Ask a questionary prompt with responsive Escape handling.\"\"\"\n    app = getattr(prompt, \"application\", None)\n    if app is not None:\n        if hasattr(app, \"ttimeoutlen\"):\n            app.ttimeoutlen = _PROMPT_ESCAPE_TIMEOUT_SECONDS\n        if hasattr(app, \"timeoutlen\"):\n            app.timeoutlen = _PROMPT_ESCAPE_TIMEOUT_SECONDS\n    return prompt.ask()\n\n\ndef _input_text(display_name: str, current: Any, field_type: str, field_info=None) -> Any:\n    \"\"\"Get text input and parse based on field type.\"\"\"\n    default = _format_value_for_input(current, field_type)\n\n    value = _ask_prompt(\n        _get_questionary().text(\n            f\"{display_name}:\",\n            default=default,\n            key_bindings=_input_back_key_bindings(),\n        )\n    )\n\n    if value is _BACK_PRESSED or value is None:\n        return None if value is None else _BACK_PRESSED\n\n    if field_type == \"int\":\n        try:\n            parsed = int(value)\n        except ValueError:\n            console.print(\"[yellow]! Invalid number format, value not saved[/yellow]\")\n            return None\n        if field_info:\n            error = _validate_field_constraint(parsed, field_info)\n            if error:\n                console.print(f\"[yellow]! {error}, value not saved[/yellow]\")\n                return None\n        return parsed\n    elif field_type == \"float\":\n        try:\n            parsed = float(value)\n        except ValueError:\n            console.print(\"[yellow]! Invalid number format, value not saved[/yellow]\")\n            return None\n        if field_info:\n            error = _validate_field_constraint(parsed, field_info)\n            if error:\n                console.print(f\"[yellow]! {error}, value not saved[/yellow]\")\n                return None\n        return parsed\n    elif field_type == \"list\":\n        return [v.strip() for v in value.split(\",\") if v.strip()]\n    elif field_type == \"dict\":\n        try:\n            return json.loads(value)\n        except json.JSONDecodeError:\n            console.print(\"[yellow]! Invalid JSON format, value not saved[/yellow]\")\n            return None\n\n    return value\n\n\ndef _input_secret(display_name: str) -> str | None | object:\n    \"\"\"Get a secret value without echoing it when questionary supports password input.\"\"\"\n    prompt_factory = getattr(_get_questionary(), \"password\", None)\n    if prompt_factory is None:\n        prompt_factory = _get_questionary().text\n    value = _ask_prompt(prompt_factory(f\"{display_name}:\", key_bindings=_input_back_key_bindings()))\n    if value is _BACK_PRESSED or value is None:\n        return None if value is None else _BACK_PRESSED\n    return str(value).strip()\n\n\ndef _input_with_existing(\n    display_name: str, current: Any, field_type: str, field_info=None\n) -> Any:\n    \"\"\"Handle input with 'keep existing' option for non-empty values.\"\"\"\n    has_existing = current is not None and current != \"\" and current != {} and current != []\n\n    if has_existing and not isinstance(current, list):\n        choice = _get_questionary().select(\n            display_name,\n            choices=[\"Enter new value\", \"Keep existing value\"],\n            default=\"Keep existing value\",\n        ).ask()\n        if choice == \"Keep existing value\" or choice is None:\n            return None\n\n    return _input_text(display_name, current, field_type, field_info=field_info)\n\n\n# --- Pydantic Model Configuration ---\n\n\ndef _get_current_provider(model: BaseModel) -> str:\n    \"\"\"Get the current provider setting from a model (if available).\"\"\"\n    if hasattr(model, \"provider\"):\n        return getattr(model, \"provider\", \"auto\") or \"auto\"\n    return \"auto\"\n\n\ndef _input_model_with_autocomplete(\n    display_name: str, current: Any, provider: str\n) -> str | None | object:\n    \"\"\"Get model input with autocomplete suggestions.\n\n    \"\"\"\n    from prompt_toolkit.completion import Completer, Completion\n\n    default = str(current) if current else \"\"\n\n    class DynamicModelCompleter(Completer):\n        \"\"\"Completer that dynamically fetches model suggestions.\"\"\"\n\n        def __init__(self, provider_name: str):\n            self.provider = provider_name\n\n        def get_completions(self, document, _complete_event):\n            text = document.text_before_cursor\n            suggestions = get_model_suggestions(text, provider=self.provider, limit=50)\n            for model in suggestions:\n                # Skip if model doesn't contain the typed text\n                if text.lower() not in model.lower():\n                    continue\n                yield Completion(\n                    model,\n                    start_position=-len(text),\n                    display=model,\n                )\n\n    value = _ask_prompt(\n        _get_questionary().autocomplete(\n            f\"{display_name}:\",\n            choices=[\"\"],  # Placeholder, actual completions from completer\n            completer=DynamicModelCompleter(provider),\n            default=default,\n            key_bindings=_input_back_key_bindings(),\n            qmark=\">\",\n        )\n    )\n\n    if value is _BACK_PRESSED or value is None:\n        return None if value is None else _BACK_PRESSED\n    return value\n\n\ndef _input_context_window_with_recommendation(\n    display_name: str, current: Any, model_obj: BaseModel\n) -> int | None | object:\n    \"\"\"Get context window input with option to fetch recommended value.\"\"\"\n    current_val = current if current else \"\"\n\n    choices = [\"Enter new value\"]\n    if current_val:\n        choices.append(\"Keep existing value\")\n    choices.append(\"[?] Get recommended value\")\n\n    choice = _get_questionary().select(\n        display_name,\n        choices=choices,\n        default=\"Enter new value\",\n    ).ask()\n\n    if choice is None:\n        return None\n\n    if choice == \"Keep existing value\":\n        return None\n\n    if choice == \"[?] Get recommended value\":\n        # Get the model name from the model object\n        model_name = getattr(model_obj, \"model\", None)\n        if not model_name:\n            console.print(\"[yellow]! Please configure the model field first[/yellow]\")\n            return None\n\n        provider = _get_current_provider(model_obj)\n        context_limit = get_model_context_limit(model_name, provider)\n\n        if context_limit:\n            console.print(\n                f\"[{_UI_SUCCESS}]+ Recommended context window: \"\n                f\"{format_token_count(context_limit)} tokens[/]\"\n            )\n            return context_limit\n        else:\n            console.print(\"[yellow]! Could not fetch model info, please enter manually[/yellow]\")\n            # Fall through to manual input\n\n    # Manual input\n    value = _get_questionary().text(\n        f\"{display_name}:\",\n        default=str(current_val) if current_val else \"\",\n        key_bindings=_input_back_key_bindings(),\n    ).ask()\n\n    if value is _BACK_PRESSED:\n        return _BACK_PRESSED\n    if value is None or value == \"\":\n        return None\n\n    try:\n        return int(value)\n    except ValueError:\n        console.print(\"[yellow]! Invalid number format, value not saved[/yellow]\")\n        return None\n\n\ndef _handle_model_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle the 'model' field with autocomplete and context-window auto-fill.\"\"\"\n    provider = _get_current_provider(working_model)\n    new_value = _input_model_with_autocomplete(field_display, current_value, provider)\n    if new_value is _BACK_PRESSED:\n        return\n    if new_value is not None and new_value != current_value:\n        setattr(working_model, field_name, new_value)\n        _try_auto_fill_context_window(working_model, new_value)\n\n\ndef _handle_context_window_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle context_window_tokens with recommendation lookup.\"\"\"\n    new_value = _input_context_window_with_recommendation(\n        field_display, current_value, working_model\n    )\n    if new_value is _BACK_PRESSED:\n        return\n    if new_value is not None:\n        setattr(working_model, field_name, new_value)\n\n\ndef _handle_model_preset_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle the 'model_preset' field with a list of existing presets.\"\"\"\n    preset_names = sorted(_MODEL_PRESET_CACHE)\n    choices = [_CLEAR_CHOICE] + preset_names\n    default_choice = str(current_value) if current_value else _CLEAR_CHOICE\n    new_value = _select_with_back(field_display, choices, default=default_choice)\n    if new_value is _BACK_PRESSED:\n        return\n    if new_value == _CLEAR_CHOICE:\n        setattr(working_model, field_name, None)\n    elif new_value is not None:\n        setattr(working_model, field_name, new_value)\n\n\ndef _set_field_from_choices(\n    working_model: BaseModel, field_name: str, field_display: str,\n    choices: list[str], default_choice: str\n) -> None:\n    \"\"\"Prompt to pick one of ``choices`` and set the field (no-op on back/cancel).\"\"\"\n    new_value = _select_with_back(field_display, choices, default=default_choice)\n    if new_value is _BACK_PRESSED:\n        return\n    if new_value is not None:\n        setattr(working_model, field_name, new_value)\n\n\ndef _handle_provider_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle the 'provider' field with a list of registered LLM providers.\"\"\"\n    choices = [\"auto\"] + sorted(_get_provider_names().keys())\n    default_choice = str(current_value) if current_value else \"auto\"\n    _set_field_from_choices(working_model, field_name, field_display, choices, default_choice)\n\n\ndef _handle_fallback_models_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle the 'fallback_models' field with preset-aware list management.\"\"\"\n    from nanobot.config.schema import InlineFallbackConfig\n\n    items: list[Any] = list(current_value) if isinstance(current_value, list) else []\n    preset_names = sorted(_MODEL_PRESET_CACHE)\n\n    while True:\n        console.clear()\n        console.print(f\"[bold]{field_display}[/bold]\")\n        if items:\n            for idx, item in enumerate(items, 1):\n                if isinstance(item, InlineFallbackConfig):\n                    console.print(f\"  {idx}. {item.model} - {item.provider} inline\")\n                else:\n                    console.print(f\"  {idx}. {item}\")\n        else:\n            console.print(\"  [dim]empty[/dim]\")\n        console.print()\n\n        choices = [\"[+] Add preset\"]\n        if items:\n            choices.append(\"[-] Remove last\")\n            choices.append(\"[X] Clear all\")\n        choices.append(\"[Done]\")\n        choices.append(\"<- Back\")\n\n        answer = _get_questionary().select(\n            \"Manage fallback models:\",\n            choices=choices,\n            qmark=\">\",\n        ).ask()\n\n        if answer is None or answer == \"<- Back\":\n            return\n        if answer == \"[Done]\":\n            setattr(working_model, field_name, items)\n            return\n        if answer == \"[+] Add preset\":\n            if not preset_names:\n                console.print(\"[yellow]! No presets defined yet.[/yellow]\")\n                _get_questionary().press_any_key_to_continue().ask()\n                continue\n            add_choices = [p for p in preset_names if p not in items]\n            if not add_choices:\n                console.print(\"[yellow]! All presets already added.[/yellow]\")\n                _get_questionary().press_any_key_to_continue().ask()\n                continue\n            picked = _select_with_back(\"Select preset:\", add_choices)\n            if picked is _BACK_PRESSED or picked is None:\n                continue\n            items.append(picked)\n        elif answer == \"[-] Remove last\" and items:\n            items.pop()\n        elif answer == \"[X] Clear all\" and items:\n            items.clear()\n\n\ndef _handle_search_provider_field(\n    working_model: BaseModel, field_name: str, field_display: str, current_value: Any\n) -> None:\n    \"\"\"Handle the web-search 'provider' field with the search-engine list.\"\"\"\n    from nanobot.agent.tools.web import SEARCH_PROVIDER_OPTIONS\n\n    choices = [opt[\"name\"] for opt in SEARCH_PROVIDER_OPTIONS]\n    default_choice = current_value if current_value in choices else choices[0]\n    _set_field_from_choices(working_model, field_name, field_display, choices, default_choice)\n\n\n_FIELD_HANDLERS: dict[str, Any] = {\n    \"model\": _handle_model_field,\n    \"context_window_tokens\": _handle_context_window_field,\n    \"model_preset\": _handle_model_preset_field,\n    \"provider\": _handle_provider_field,\n    \"fallback_models\": _handle_fallback_models_field,\n}\n\n\ndef _resolve_field_handler(model: BaseModel, field_name: str) -> Any:\n    \"\"\"Resolve the handler for a field. WebSearchConfig shares the bare \"provider\"\n    name with LLM configs but needs the search-engine picker, not the LLM list.\"\"\"\n    if field_name == \"provider\":\n        from nanobot.agent.tools.web import WebSearchConfig\n        if isinstance(model, WebSearchConfig):\n            return _handle_search_provider_field\n    return _FIELD_HANDLERS.get(field_name)\n\n\ndef _is_str_or_none(annotation: Any) -> bool:\n    \"\"\"Check whether a field annotation is ``str | None`` (or ``Optional[str]``).\"\"\"\n    origin = get_origin(annotation)\n    if origin is None:\n        return False\n    args = get_args(annotation)\n    return str in args and type(None) in args\n\n\ndef _configure_pydantic_model(\n    model: BaseModel,\n    display_name: str,\n    *,\n    skip_fields: set[str] | None = None,\n) -> BaseModel | None:\n    \"\"\"Configure a Pydantic model interactively.\n\n    Returns the updated model when the user selects \"Done\" or navigates back.\n    Cancel actions discard the section draft.\n    \"\"\"\n    skip_fields = skip_fields or set()\n    working_model = model.model_copy(deep=True)\n\n    fields = [\n        (name, info)\n        for name, info in type(working_model).model_fields.items()\n        if name not in skip_fields\n    ]\n    if not fields:\n        console.print(f\"[dim]{display_name}: No configurable fields[/dim]\")\n        return working_model\n\n    def get_choices() -> list[str]:\n        items = []\n        for fname, finfo in fields:\n            value = getattr(working_model, fname, None)\n            display = _get_field_display_name(fname, finfo)\n            formatted = _format_value(value, rich=False, field_name=fname)\n            items.append(f\"{display}: {formatted}\")\n        return items + [\"[Done]\"]\n\n    last_field_name: str | None = None\n    while True:\n        console.clear()\n        _show_config_panel(display_name, working_model, fields)\n        choices = get_choices()\n        default_choice = None\n        if last_field_name:\n            for idx, (fname, _) in enumerate(fields):\n                if fname == last_field_name:\n                    default_choice = choices[idx]\n                    break\n        answer = _select_with_back(\n            \"Select field to configure:\", choices, default=default_choice\n        )\n\n        if answer is _BACK_PRESSED:\n            return working_model\n        if answer is None:\n            return None\n        if answer == \"[Done]\":\n            return working_model\n\n        field_idx = next((i for i, c in enumerate(choices) if c == answer), -1)\n        if field_idx < 0 or field_idx >= len(fields):\n            return None\n\n        last_field_name = fields[field_idx][0]\n\n        field_name, field_info = fields[field_idx]\n        current_value = getattr(working_model, field_name, None)\n        ftype = _get_field_type_info(field_info)\n        field_display = _get_field_display_name(field_name, field_info) + _get_constraint_hint(field_info)\n\n        # Nested Pydantic model - recurse\n        if ftype.type_name == \"model\":\n            nested = current_value\n            created = nested is None\n            if nested is None and ftype.inner_type:\n                nested = ftype.inner_type()\n            if nested and isinstance(nested, BaseModel):\n                updated = _configure_pydantic_model(nested, field_display)\n                if updated is not None:\n                    setattr(working_model, field_name, updated)\n                elif created:\n                    setattr(working_model, field_name, None)\n            continue\n\n        # Registered special-field handlers\n        handler = _resolve_field_handler(working_model, field_name)\n        if handler:\n            handler(working_model, field_name, field_display, current_value)\n            continue\n\n        # Select fields with hints (e.g. reasoning_effort)\n        if field_name in _SELECT_FIELD_HINTS:\n            choices_list, hint = _SELECT_FIELD_HINTS[field_name]\n            select_choices = choices_list + [_CLEAR_CHOICE]\n            console.print(f\"[dim]  Hint: {hint}[/dim]\")\n            new_value = _select_with_back(\n                field_display, select_choices, default=current_value or select_choices[0]\n            )\n            if new_value is _BACK_PRESSED:\n                continue\n            if new_value == _CLEAR_CHOICE:\n                setattr(working_model, field_name, None)\n            elif new_value is not None:\n                setattr(working_model, field_name, new_value)\n            continue\n\n        # Generic field input\n        if ftype.type_name == \"literal\" and ftype.inner_type:\n            select_choices = [str(v) for v in ftype.inner_type]\n            default_choice = str(current_value) if current_value in ftype.inner_type else select_choices[0]\n            new_value = _select_with_back(field_display, select_choices, default=default_choice)\n            if new_value is _BACK_PRESSED:\n                continue\n            if new_value is not None:\n                setattr(working_model, field_name, new_value)\n            continue\n        if ftype.type_name == \"bool\":\n            new_value = _input_bool(field_display, current_value)\n        else:\n            new_value = _input_with_existing(field_display, current_value, ftype.type_name, field_info=field_info)\n        if new_value is _BACK_PRESSED:\n            continue\n        if new_value is not None:\n            # Normalize empty string to None for optional string fields so that\n            # clearing an api_key / api_base actually removes the value.\n            if new_value == \"\" and _is_str_or_none(field_info.annotation):\n                new_value = None\n            setattr(working_model, field_name, new_value)\n\n\ndef _try_auto_fill_context_window(model: BaseModel, new_model_name: str) -> None:\n    \"\"\"Try to auto-fill context_window_tokens if it's at default value.\n\n    Note:\n        This function imports AgentDefaults from nanobot.config.schema to get\n        the default context_window_tokens value. If the schema changes, this\n        coupling needs to be updated accordingly.\n    \"\"\"\n    # Check if context_window_tokens field exists\n    if not hasattr(model, \"context_window_tokens\"):\n        return\n\n    current_context = getattr(model, \"context_window_tokens\", None)\n\n    # Check if current value is the default\n    # We only auto-fill if the user hasn't changed it from default\n    from nanobot.config.schema import AgentDefaults\n\n    default_context = AgentDefaults.model_fields[\"context_window_tokens\"].default\n\n    if current_context != default_context:\n        return  # User has customized it, don't override\n\n    provider = _get_current_provider(model)\n    context_limit = get_model_context_limit(new_model_name, provider)\n\n    if context_limit:\n        setattr(model, \"context_window_tokens\", context_limit)\n        console.print(\n            f\"[{_UI_SUCCESS}]+ Auto-filled context window: \"\n            f\"{format_token_count(context_limit)} tokens[/]\"\n        )\n    else:\n        console.print(\"[dim]Could not auto-fill context window - model not in database[/dim]\")\n\n\n# --- Model Preset Configuration ---\n\n\ndef _sync_preset_cache(config: Config) -> None:\n    \"\"\"Synchronise the module-level preset name cache from config.\"\"\"\n    _MODEL_PRESET_CACHE.clear()\n    _MODEL_PRESET_CACHE.update(config.model_presets.keys())\n\n\ndef _configure_model_presets(config: Config) -> None:\n    \"\"\"Configure model presets (CRUD).\"\"\"\n    _sync_preset_cache(config)\n\n    def get_preset_choices() -> tuple[list[str], dict[str, str]]:\n        choices: list[str] = []\n        choice_to_preset: dict[str, str] = {}\n        for name, preset in config.model_presets.items():\n            choice = f\"{name} - {preset.model}\"\n            choices.append(choice)\n            choice_to_preset[choice] = name\n        choices.append(\"[+] Add new preset\")\n        choices.append(\"<- Back\")\n        return choices, choice_to_preset\n\n    last_preset_name: str | None = None\n    while True:\n        try:\n            console.clear()\n            _show_section_header(\n                \"Model Presets\",\n                \"Create, edit or delete named model presets for quick switching\",\n            )\n            choices, choice_to_preset = get_preset_choices()\n            default_choice = None\n            if last_preset_name:\n                for choice, name in choice_to_preset.items():\n                    if name == last_preset_name:\n                        default_choice = choice\n                        break\n            answer = _select_with_back(\n                \"Select preset:\", choices, default=default_choice\n            )\n\n            if answer is _BACK_PRESSED or answer is None or answer == \"<- Back\":\n                break\n\n            assert isinstance(answer, str)\n\n            if answer == \"[+] Add new preset\":\n                name_input = _get_questionary().text(\n                    \"Preset name:\",\n                    validate=lambda t: True if t and t.strip() else \"Name cannot be empty\",\n                ).ask()\n                if not name_input:\n                    continue\n                name = name_input.strip()\n                if name in config.model_presets:\n                    console.print(f\"[yellow]! Preset '{name}' already exists[/yellow]\")\n                    _pause()\n                    continue\n                if name == \"default\":\n                    console.print(\n                        \"[yellow]! 'default' is reserved; it is generated from Agent Settings[/yellow]\"\n                    )\n                    _pause()\n                    continue\n                new_preset = ModelPresetConfig(model=\"\")\n                updated = _configure_pydantic_model(new_preset, f\"New Preset: {name}\")\n                if updated is not None:\n                    config.model_presets[name] = updated\n                    _sync_preset_cache(config)\n                    last_preset_name = name\n                continue\n\n            # Editing / deleting an existing preset\n            preset_name = choice_to_preset.get(answer)\n            if preset_name is None:\n                continue\n            preset = config.model_presets.get(preset_name)\n            if preset is None:\n                continue\n\n            last_preset_name = preset_name\n\n            choices = [\"Edit\", \"Cancel\"]\n            if preset_name != \"default\":\n                choices.insert(1, \"Delete\")\n            action = _select_with_back(\n                f\"Preset: {preset_name}\",\n                choices,\n                default=\"Edit\",\n            )\n            if action is _BACK_PRESSED or action == \"Cancel\" or action is None:\n                continue\n\n            if action == \"Delete\":\n                confirm = _get_questionary().confirm(\n                    f\"Delete preset '{preset_name}'?\",\n                    default=False,\n                ).ask()\n                if confirm:\n                    del config.model_presets[preset_name]\n                    _sync_preset_cache(config)\n                    last_preset_name = None\n                continue\n\n            if action == \"Edit\":\n                updated = _configure_pydantic_model(preset, f\"Edit Preset: {preset_name}\")\n                if updated is not None:\n                    config.model_presets[preset_name] = updated\n                    _sync_preset_cache(config)\n\n        except KeyboardInterrupt:\n            console.print(\"\\n[dim]Returning to main menu...[/dim]\")\n            break\n\n\n# --- Provider Configuration ---\n\n\n@lru_cache(maxsize=1)\ndef _get_provider_info() -> dict[str, tuple[str, bool, bool, str]]:\n    \"\"\"Get provider info from registry (cached).\"\"\"\n    from nanobot.providers.registry import PROVIDERS\n\n    return {\n        spec.name: (\n            spec.display_name or spec.name,\n            spec.is_gateway,\n            spec.is_local,\n            spec.default_api_base,\n        )\n        for spec in PROVIDERS\n        if not spec.is_oauth\n    }\n\n\ndef _get_provider_names() -> dict[str, str]:\n    \"\"\"Get provider display names.\"\"\"\n    info = _get_provider_info()\n    return {name: data[0] for name, data in info.items() if name}\n\n\ndef _configure_provider(config: Config, provider_name: str) -> None:\n    \"\"\"Configure a single LLM provider.\"\"\"\n    provider_config = getattr(config.providers, provider_name, None)\n    if provider_config is None:\n        console.print(f\"[red]Unknown provider: {provider_name}[/red]\")\n        return\n\n    display_name = _get_provider_names().get(provider_name, provider_name)\n    info = _get_provider_info()\n    default_api_base = info.get(provider_name, (None, None, None, None))[3]\n\n    if default_api_base and not provider_config.api_base:\n        provider_config.api_base = default_api_base\n\n    updated_provider = _configure_pydantic_model(\n        provider_config,\n        display_name,\n    )\n    if updated_provider is not None:\n        setattr(config.providers, provider_name, updated_provider)\n\n\ndef _configure_providers(config: Config) -> None:\n    \"\"\"Configure LLM providers.\"\"\"\n\n    def get_provider_choices() -> list[str]:\n        \"\"\"Build provider choices with config status indicators.\"\"\"\n        choices = []\n        for name, display in _get_provider_names().items():\n            provider = getattr(config.providers, name, None)\n            if provider and provider.api_key:\n                choices.append(f\"{display} *\")\n            else:\n                choices.append(display)\n        return choices + [\"<- Back\"]\n\n    last_provider_key: str | None = None\n    while True:\n        try:\n            console.clear()\n            _show_section_header(\"LLM Providers\", \"Select a provider to configure API key and endpoint\")\n            choices = get_provider_choices()\n            default_choice = None\n            if last_provider_key:\n                display = _get_provider_names().get(last_provider_key)\n                if display:\n                    for c in choices:\n                        if c.replace(\" *\", \"\") == display:\n                            default_choice = c\n                            break\n            answer = _select_with_back(\n                \"Select provider:\", choices, default=default_choice\n            )\n\n            if answer is _BACK_PRESSED or answer is None or answer == \"<- Back\":\n                break\n\n            # Type guard: answer is now guaranteed to be a string\n            assert isinstance(answer, str)\n            # Extract provider name from choice (remove \" *\" suffix if present)\n            provider_name = answer.replace(\" *\", \"\")\n            # Find the actual provider key from display names\n            for name, display in _get_provider_names().items():\n                if display == provider_name:\n                    last_provider_key = name\n                    _configure_provider(config, name)\n                    break\n\n        except KeyboardInterrupt:\n            console.print(\"\\n[dim]Returning to main menu...[/dim]\")\n            break\n\n\n# --- Channel Configuration ---\n\n\n@lru_cache(maxsize=1)\ndef _get_channel_info() -> dict[str, tuple[str, type[BaseModel]]]:\n    \"\"\"Get channel info (display name + config class) from channel modules.\"\"\"\n    import importlib\n\n    from nanobot.channels.registry import discover_all\n\n    result: dict[str, tuple[str, type[BaseModel]]] = {}\n    for name, channel_cls in discover_all().items():\n        try:\n            mod = importlib.import_module(f\"nanobot.channels.{name}\")\n            config_name = channel_cls.__name__.replace(\"Channel\", \"Config\")\n            config_cls = getattr(mod, config_name, None)\n            if config_cls and isinstance(config_cls, type) and issubclass(config_cls, BaseModel):\n                display_name = getattr(channel_cls, \"display_name\", name.capitalize())\n                result[name] = (display_name, config_cls)\n        except Exception:\n            logger.warning(\"Failed to load channel module: {}\", name)\n    return result\n\n\ndef _get_channel_names() -> dict[str, str]:\n    \"\"\"Get channel display names.\"\"\"\n    return {name: info[0] for name, info in _get_channel_info().items()}\n\n\ndef _get_channel_config_class(channel: str) -> type[BaseModel] | None:\n    \"\"\"Get channel config class.\"\"\"\n    entry = _get_channel_info().get(channel)\n    return entry[1] if entry else None\n\n\ndef _get_channel_class(channel: str) -> type[Any] | None:\n    \"\"\"Get channel implementation class.\"\"\"\n    from nanobot.channels.registry import discover_all\n\n    return discover_all().get(channel)\n\n\ndef _channel_supports_login(channel_cls: type[Any] | None) -> bool:\n    \"\"\"Return True when a channel overrides BaseChannel.login.\"\"\"\n    if channel_cls is None:\n        return False\n    from nanobot.channels.base import BaseChannel\n\n    return getattr(channel_cls, \"login\", None) is not BaseChannel.login\n\n\ndef _run_channel_login(\n    config: Config,\n    channel_name: str,\n    model: BaseModel,\n    display_name: str,\n) -> bool:\n    \"\"\"Run a channel's interactive login and enable it only on success.\"\"\"\n    channel_cls = _get_channel_class(channel_name)\n    if channel_cls is None:\n        console.print(f\"[red]Unknown channel: {channel_name}[/red]\")\n        return False\n    if not _channel_supports_login(channel_cls):\n        return False\n\n    if hasattr(model, \"enabled\"):\n        setattr(model, \"enabled\", True)\n\n    console.print(f\"[{_UI_ACCENT}]Starting {display_name} login...[/]\")\n    try:\n        channel = channel_cls(model, bus=None)\n        success = asyncio.run(channel.login(force=False))\n    except KeyboardInterrupt:\n        console.print(\"\\n[dim]Login cancelled.[/dim]\")\n        return False\n    except Exception as exc:\n        logger.exception(\"{} login failed\", display_name)\n        console.print(f\"[red]{display_name} login failed:[/red] {exc}\")\n        return False\n\n    if not success:\n        console.print(f\"[yellow]! {display_name} login did not complete; channel was not enabled[/yellow]\")\n        return False\n\n    setattr(config.channels, channel_name, model.model_dump(by_alias=True, exclude_none=True))\n    console.print(f\"[{_UI_SUCCESS}]{display_name} enabled[/]\")\n    return True\n\n\ndef _configure_channel(config: Config, channel_name: str) -> None:\n    \"\"\"Configure a single channel.\"\"\"\n    channel_dict = getattr(config.channels, channel_name, None)\n    if channel_dict is None:\n        channel_dict = {}\n        setattr(config.channels, channel_name, channel_dict)\n\n    display_name = _get_channel_names().get(channel_name, channel_name)\n    config_cls = _get_channel_config_class(channel_name)\n\n    if config_cls is None:\n        console.print(f\"[red]No configuration class found for {display_name}[/red]\")\n        return\n\n    model = config_cls.model_validate(channel_dict) if channel_dict else config_cls()\n\n    channel_cls = _get_channel_class(channel_name)\n    if _channel_supports_login(channel_cls):\n        action = _select_with_back(\n            f\"Configure {display_name}:\",\n            [_CHANNEL_LOGIN_CHOICE, _CHANNEL_ADVANCED_CHOICE, \"<- Back\"],\n            default=_CHANNEL_LOGIN_CHOICE,\n        )\n        if action is _BACK_PRESSED or action is None or action == \"<- Back\":\n            return\n        if action == _CHANNEL_LOGIN_CHOICE:\n            _run_channel_login(config, channel_name, model, display_name)\n            return\n\n    updated_channel = _configure_pydantic_model(\n        model,\n        display_name,\n    )\n    if updated_channel is not None:\n        new_dict = updated_channel.model_dump(by_alias=True, exclude_none=True)\n        setattr(config.channels, channel_name, new_dict)\n\n\ndef _configure_channels(config: Config) -> None:\n    \"\"\"Configure chat channels.\"\"\"\n    channel_names = list(_get_channel_names().keys())\n    choices = channel_names + [\"<- Back\"]\n\n    last_choice: str | None = None\n    while True:\n        try:\n            console.clear()\n            _show_section_header(\"Chat Channels\", \"Select a channel to configure connection settings\")\n            answer = _select_with_back(\n                \"Select channel:\", choices, default=last_choice\n            )\n\n            if answer is _BACK_PRESSED or answer is None or answer == \"<- Back\":\n                break\n\n            # Type guard: answer is now guaranteed to be a string\n            assert isinstance(answer, str)\n            last_choice = answer\n            _configure_channel(config, answer)\n        except KeyboardInterrupt:\n            console.print(\"\\n[dim]Returning to main menu...[/dim]\")\n            break\n\n\n# --- General Settings ---\n\n_SETTINGS_SECTIONS: dict[str, tuple[str, str, set[str] | None]] = {\n    \"Agent Settings\": (\"Agent Defaults\", \"Configure default model, temperature, and behavior\", None),\n    \"Channel Common\": (\"Channel Common\", \"Configure cross-channel behavior: progress, tool hints, retries\", None),\n    \"API Server\": (\"API Server\", \"Configure OpenAI-compatible API endpoint\", None),\n    \"Gateway\": (\"Gateway Settings\", \"Configure server host, port\", None),\n    \"Tools\": (\"Tools Settings\", \"Configure web search, shell exec, and other tools\", {\"mcp_servers\"}),\n}\n\n_SETTINGS_GETTER = {\n    \"Agent Settings\": lambda c: c.agents.defaults,\n    \"Channel Common\": lambda c: c.channels,\n    \"API Server\": lambda c: c.api,\n    \"Gateway\": lambda c: c.gateway,\n    \"Tools\": lambda c: c.tools,\n}\n\n_SETTINGS_SETTER = {\n    \"Agent Settings\": lambda c, v: setattr(c.agents, \"defaults\", v),\n    \"Channel Common\": lambda c, v: setattr(c, \"channels\", v),\n    \"API Server\": lambda c, v: setattr(c, \"api\", v),\n    \"Gateway\": lambda c, v: setattr(c, \"gateway\", v),\n    \"Tools\": lambda c, v: setattr(c, \"tools\", v),\n}\n\n\ndef _configure_general_settings(config: Config, section: str) -> None:\n    \"\"\"Configure a general settings section (header + model edit + writeback).\"\"\"\n    meta = _SETTINGS_SECTIONS.get(section)\n    if not meta:\n        return\n    display_name, subtitle, skip = meta\n    model = _SETTINGS_GETTER[section](config)\n    updated = _configure_pydantic_model(model, display_name, skip_fields=skip)\n    if updated is not None:\n        _SETTINGS_SETTER[section](config, updated)\n\n\n# --- Summary ---\n\n\ndef _summarize_model(obj: BaseModel) -> list[tuple[str, str]]:\n    \"\"\"Recursively summarize a Pydantic model. Returns list of (field, value) tuples.\"\"\"\n    items: list[tuple[str, str]] = []\n    for field_name, field_info in type(obj).model_fields.items():\n        value = getattr(obj, field_name, None)\n        if value is None or value == \"\" or value == {} or value == []:\n            continue\n        display = _get_field_display_name(field_name, field_info)\n        ftype = _get_field_type_info(field_info)\n        if ftype.type_name == \"model\" and isinstance(value, BaseModel):\n            for nested_field, nested_value in _summarize_model(value):\n                items.append((f\"{display}.{nested_field}\", nested_value))\n            continue\n        formatted = _format_value(value, rich=False, field_name=field_name)\n        if formatted != \"[not set]\":\n            items.append((display, formatted))\n    return items\n\n\ndef _print_summary_panel(rows: list[tuple[str, str]], title: str) -> None:\n    \"\"\"Build a two-column summary panel and print it.\"\"\"\n    if not rows:\n        return\n    table = Table(show_header=False, box=None, padding=(0, 2))\n    table.add_column(\"Setting\", style=_UI_ACCENT)\n    table.add_column(\"Value\")\n    for field, value in rows:\n        table.add_row(field, value)\n    console.print(Panel(table, title=f\"[bold {_UI_TEXT}]{title}[/]\", border_style=_UI_BORDER))\n\n\ndef _show_summary(config: Config) -> None:\n    \"\"\"Display configuration summary using rich.\"\"\"\n    console.print()\n\n    # Providers\n    provider_rows = []\n    for name, display in _get_provider_names().items():\n        provider = getattr(config.providers, name, None)\n        status = (\n            f\"[{_UI_SUCCESS}]configured[/]\"\n            if (provider and provider.api_key)\n            else f\"[{_UI_MUTED}]not configured[/]\"\n        )\n        provider_rows.append((display, status))\n    _print_summary_panel(provider_rows, \"LLM Providers\")\n\n    # Channels\n    channel_rows = []\n    for name, display in _get_channel_names().items():\n        channel = getattr(config.channels, name, None)\n        if channel:\n            enabled = (\n                channel.get(\"enabled\", False)\n                if isinstance(channel, dict)\n                else getattr(channel, \"enabled\", False)\n            )\n            status = f\"[{_UI_SUCCESS}]enabled[/]\" if enabled else f\"[{_UI_MUTED}]disabled[/]\"\n        else:\n            status = f\"[{_UI_MUTED}]not configured[/]\"\n        channel_rows.append((display, status))\n    _print_summary_panel(channel_rows, \"Chat Channels\")\n\n    # Model Presets\n    preset_rows = []\n    for name, preset in config.model_presets.items():\n        preset_rows.append((name, f\"{preset.model} - ctx {preset.context_window_tokens}\"))\n    _print_summary_panel(preset_rows, \"Model Presets\")\n\n    # Settings sections\n    for title, model in [\n        (\"Agent Settings\", config.agents.defaults),\n        (\"Channel Common\", config.channels),\n        (\"API Server\", config.api),\n        (\"Gateway\", config.gateway),\n        (\"Tools\", config.tools),\n    ]:\n        _print_summary_panel(_summarize_model(model), title)\n\n    _pause()\n\n\ndef _pause(message: str = \"Press Enter to continue...\") -> None:\n    \"\"\"Pause for user acknowledgement before clearing the screen.\"\"\"\n    _get_questionary().text(message, default=\"\").ask()\n\n\n# --- Quick Start ---\n\n\ndef _set_primary_quick_start_preset(config: Config, provider_name: str, model: str) -> None:\n    \"\"\"Store the primary preset used by Quick Start.\"\"\"\n    config.model_presets[\"primary\"] = ModelPresetConfig(\n        label=\"Primary\",\n        model=model,\n        provider=provider_name,\n    )\n    config.agents.defaults.model_preset = \"primary\"\n    _sync_preset_cache(config)\n\n\ndef _show_quick_start_progress(active_step: int) -> None:\n    \"\"\"Render a compact step tracker for Quick Start.\"\"\"\n    parts = []\n    for idx, label in enumerate(_QUICK_START_STEPS, 1):\n        if idx < active_step:\n            parts.append(f\"[{_UI_SUCCESS}]{idx}. {label}[/]\")\n        elif idx == active_step:\n            parts.append(f\"[bold {_UI_ACCENT}]{idx}. {label}[/]\")\n        else:\n            parts.append(f\"[{_UI_MUTED}]{idx}. {label}[/]\")\n    console.print(\"  \" + \"  ->  \".join(parts))\n    console.print()\n\n\n@lru_cache(maxsize=1)\ndef _get_quick_start_provider_info() -> dict[str, _QuickStartProviderInfo]:\n    \"\"\"Return chat-capable providers supported by Quick Start.\"\"\"\n    from nanobot.providers.registry import PROVIDERS\n\n    result: dict[str, _QuickStartProviderInfo] = {}\n    for spec in PROVIDERS:\n        if spec.name == \"custom\" or spec.is_oauth or spec.is_transcription_only:\n            continue\n        result[spec.name] = _QuickStartProviderInfo(\n            display_name=spec.display_name or spec.name,\n            is_local=spec.is_local,\n            default_api_base=spec.default_api_base,\n            backend=spec.backend,\n            is_direct=spec.is_direct,\n        )\n    return result\n\n\ndef _get_quick_start_provider_choices() -> dict[str, str]:\n    \"\"\"Return Quick Start provider display choices.\"\"\"\n    choices: dict[str, str] = {}\n    for provider_name, info in _get_quick_start_provider_info().items():\n        choices.setdefault(info.display_name, provider_name)\n    choices[_QUICK_START_CUSTOM_PROVIDER_CHOICE] = \"custom\"\n    return choices\n\n\ndef _quick_start_requires_api_key(provider_name: str, info: _QuickStartProviderInfo | None) -> bool:\n    \"\"\"Return whether Quick Start should ask for an API key.\"\"\"\n    return provider_name == \"custom\" or not (info and info.is_local)\n\n\ndef _quick_start_requires_base_url(provider_name: str, info: _QuickStartProviderInfo | None) -> bool:\n    \"\"\"Return whether Quick Start must ask for a provider base URL.\"\"\"\n    if provider_name == \"custom\":\n        return True\n    if provider_name in _QUICK_START_ENDPOINT_CHOICES:\n        return False\n    if info is None or info.default_api_base:\n        return False\n    return info.backend == \"azure_openai\" or (\n        info.backend == \"openai_compat\" and (info.is_direct or info.is_local)\n    )\n\n\ndef _select_quick_start_api_base(\n    provider_name: str,\n    provider_display: str,\n    info: _QuickStartProviderInfo | None,\n) -> tuple[str, bool] | None | object:\n    \"\"\"Return the api_base and whether the user explicitly selected or entered it.\"\"\"\n    endpoint_choices = _QUICK_START_ENDPOINT_CHOICES.get(provider_name)\n    if endpoint_choices:\n        choices = {choice.label: choice.api_base for choice in endpoint_choices}\n        answer = _select_with_back(\n            f\"Which {provider_display} endpoint should Quick Start use?\",\n            list(choices) + [\"<- Back\"],\n            default=endpoint_choices[0].label,\n        )\n        if answer is _BACK_PRESSED or answer == \"<- Back\":\n            return _BACK_PRESSED\n        if answer is None:\n            return None\n        assert isinstance(answer, str)\n        return choices[answer], True\n\n    api_base = info.default_api_base if info else \"\"\n    if not _quick_start_requires_base_url(provider_name, info):\n        return api_base, False\n\n    base_answer = _input_text(\n        \"Provider base URL\",\n        api_base,\n        \"str\",\n    )\n    if base_answer is _BACK_PRESSED:\n        return _BACK_PRESSED\n    if base_answer is None:\n        return None\n    api_base = base_answer.strip().rstrip(\"/\")\n    if not api_base:\n        console.print(\"[yellow]! Provider base URL is required for this provider[/yellow]\")\n        return None\n    return api_base, True\n\n\ndef _configure_quick_start_provider(config: Config) -> bool | object:\n    \"\"\"Configure the beginner path from provider credentials and model.\"\"\"\n    while True:\n        _show_quick_start_progress(1)\n\n        provider_choices = _get_quick_start_provider_choices()\n        answer = _select_with_back(\n            \"Which provider do you want to use?\",\n            list(provider_choices) + [\"<- Back\"],\n        )\n        if answer is _BACK_PRESSED or answer is None or answer == \"<- Back\":\n            return _BACK_PRESSED\n        assert isinstance(answer, str)\n        provider_name = provider_choices[answer]\n        provider_info = _get_quick_start_provider_info().get(provider_name)\n\n        api_base = provider_info.default_api_base if provider_info else \"\"\n        base_was_prompted = False\n        if provider_name in _QUICK_START_ENDPOINT_CHOICES:\n            api_base_result = _select_quick_start_api_base(provider_name, answer, provider_info)\n            if api_base_result is _BACK_PRESSED:\n                continue\n            if api_base_result is None:\n                return False\n            api_base, base_was_prompted = api_base_result\n\n        api_key: str | None = None\n        if _quick_start_requires_api_key(provider_name, provider_info):\n            api_key = _input_text(f\"{answer} API key\", \"\", \"str\")\n            if api_key is _BACK_PRESSED:\n                continue\n            if api_key is None:\n                return False\n            api_key = api_key.strip()\n            if not api_key:\n                console.print(\"[yellow]! API key is required for Quick Start[/yellow]\")\n                return False\n\n        if (\n            provider_name not in _QUICK_START_ENDPOINT_CHOICES\n            and _quick_start_requires_base_url(provider_name, provider_info)\n        ):\n            api_base_result = _select_quick_start_api_base(provider_name, answer, provider_info)\n            if api_base_result is _BACK_PRESSED:\n                continue\n            if api_base_result is None:\n                return False\n            api_base, base_was_prompted = api_base_result\n\n        provider_config = getattr(config.providers, provider_name, None)\n        if provider_config is None:\n            console.print(f\"[red]Unknown provider: {provider_name}[/red]\")\n            return False\n\n        model = _input_model_with_autocomplete(\"Model ID\", \"\", provider_name)\n        if model is _BACK_PRESSED:\n            continue\n        model = (model or \"\").strip()\n        if not model:\n            console.print(\"[yellow]! Model ID is required for Quick Start[/yellow]\")\n            return False\n\n        if api_key is not None:\n            provider_config.api_key = api_key\n        if api_base:\n            if base_was_prompted:\n                provider_config.api_base = api_base\n            elif not provider_config.api_base:\n                provider_config.api_base = api_base\n\n        _set_primary_quick_start_preset(\n            config,\n            provider_name,\n            model,\n        )\n        return True\n\n\ndef _enable_quick_start_websocket_defaults(config: Config) -> bool:\n    \"\"\"Enable local WebUI with the default WebSocket settings.\"\"\"\n    _show_quick_start_progress(2)\n    console.print(\n        f\"[{_UI_ACCENT}]Quick Start will enable the WebSocket channel for the local WebUI.[/]\"\n    )\n    console.print(\n        f\"[{_UI_MUTED}]This lets the browser UI at http://127.0.0.1:8765 connect to nanobot.[/]\"\n    )\n    console.print()\n    while True:\n        answer = _get_questionary().confirm(\n            \"Enable WebSocket channel now?\",\n            default=True,\n        ).ask()\n        if not answer:\n            console.print(\n                \"[yellow]! Quick Start needs the WebSocket channel for the local WebUI[/yellow]\"\n            )\n            return False\n        webui_secret = _input_secret(\"Set a WebUI password\")\n        if webui_secret is _BACK_PRESSED:\n            continue\n        if not webui_secret:\n            console.print(\"[yellow]! WebUI password is required when enabling WebSocket[/yellow]\")\n            return False\n        break\n\n    config_cls = _get_channel_config_class(\"websocket\")\n    if config_cls is None:\n        console.print(\"[red]No configuration class found for websocket[/red]\")\n        return False\n\n    current = getattr(config.channels, \"websocket\", None) or {}\n    model = config_cls.model_validate(current)\n    if hasattr(model, \"enabled\"):\n        setattr(model, \"enabled\", True)\n    if hasattr(model, \"token_issue_secret\"):\n        setattr(model, \"token_issue_secret\", webui_secret)\n    if hasattr(model, \"websocket_requires_token\"):\n        setattr(model, \"websocket_requires_token\", True)\n    setattr(config.channels, \"websocket\", model.model_dump(by_alias=True, exclude_none=True))\n    return True\n\n\ndef _show_quick_start_summary(config: Config) -> None:\n    \"\"\"Show the small summary users need before returning to the menu.\"\"\"\n    _show_quick_start_progress(3)\n    preset = config.model_presets.get(\"primary\")\n    provider_label = \"AI provider\"\n    has_api_key = True\n    if preset:\n        provider_config = getattr(config.providers, preset.provider, None)\n        provider_label, _is_gateway, is_local, _api_base = _get_provider_info().get(\n            preset.provider, (preset.provider, False, False, \"\")\n        )\n        has_api_key = is_local or bool(provider_config and provider_config.api_key)\n\n    start_command = \"`nanobot gateway`\"\n    next_step = f\"Run {start_command}\"\n    status = \"Ready\"\n    if not has_api_key:\n        status = f\"{provider_label} API key missing\"\n        next_step = f\"Add your {provider_label} API key, then run {start_command}\"\n\n    rows = [\n        (\"Status\", status),\n        (\"Next\", next_step),\n        (\"WebSocket channel\", \"enabled\"),\n        (\"Open\", \"http://127.0.0.1:8765\"),\n    ]\n    _print_summary_panel(rows, \"Quick Start\")\n\n\ndef _configure_quick_start(config: Config) -> bool:\n    \"\"\"First-run path: provider + API key + local WebUI, with advanced settings hidden.\"\"\"\n    console.clear()\n    _show_section_header(\n        \"Quick Start\",\n        \"Choose provider endpoint, add credentials and model, then enable the local WebUI channel.\",\n    )\n    draft = config.model_copy(deep=True)\n    provider_result = _configure_quick_start_provider(draft)\n    if provider_result is _BACK_PRESSED:\n        return False\n    if not provider_result:\n        _pause()\n        return False\n    if not _enable_quick_start_websocket_defaults(draft):\n        _pause()\n        return False\n    _show_quick_start_summary(draft)\n    _pause(\"Press Enter to save and exit...\")\n    for field_name in type(config).model_fields:\n        setattr(config, field_name, getattr(draft, field_name))\n    return True\n\n\n# --- Main Entry Point ---\n\n\ndef _has_unsaved_changes(original: Config, current: Config) -> bool:\n    \"\"\"Return True when the onboarding session has committed changes.\"\"\"\n    return original.model_dump(by_alias=True) != current.model_dump(by_alias=True)\n\n\ndef _prompt_main_menu_exit(has_unsaved_changes: bool) -> str:\n    \"\"\"Resolve how to leave the main menu.\"\"\"\n    if not has_unsaved_changes:\n        return \"discard\"\n\n    answer = _get_questionary().select(\n        \"You have unsaved changes. What would you like to do?\",\n        choices=[\n            \"[S] Save and Exit\",\n            \"[X] Exit Without Saving\",\n            \"[R] Resume Editing\",\n        ],\n        default=\"[R] Resume Editing\",\n        qmark=\">\",\n    ).ask()\n\n    if answer == \"[S] Save and Exit\":\n        return \"save\"\n    if answer == \"[X] Exit Without Saving\":\n        return \"discard\"\n    return \"resume\"\n\n\ndef _get_main_menu_choices(has_unsaved_changes: bool) -> list[str]:\n    \"\"\"Return the top-level choices, keeping save actions hidden until needed.\"\"\"\n    choices = [\n        _QUICK_START_MENU_CHOICE,\n        \"[A] Advanced Settings\",\n    ]\n    if has_unsaved_changes:\n        choices.extend([\"[S] Save and Exit\", \"[X] Exit Without Saving\"])\n    else:\n        choices.append(\"[X] Exit\")\n    return choices\n\n\ndef _configure_advanced_settings(config: Config) -> None:\n    \"\"\"Show lower-frequency setup options behind one advanced menu.\"\"\"\n    last_choice: str | None = None\n    choices = [\n        \"[P] LLM Provider\",\n        \"[M] Model Presets\",\n        \"[C] Chat Channel\",\n        \"[H] Channel Common\",\n        \"[A] Agent Settings\",\n        \"[I] API Server\",\n        \"[G] Gateway\",\n        \"[T] Tools\",\n        \"[V] View Configuration Summary\",\n        \"<- Back\",\n    ]\n    while True:\n        try:\n            console.clear()\n            _show_section_header(\n                \"Advanced Settings\",\n                \"Use these when the default API-key setup is not enough.\",\n            )\n            answer = _select_with_back(\n                \"What would you like to configure?\",\n                choices,\n                default=last_choice,\n            )\n        except KeyboardInterrupt:\n            break\n\n        if answer is _BACK_PRESSED or answer is None or answer == \"<- Back\":\n            break\n\n        _advanced_dispatch = {\n            \"[P] LLM Provider\": lambda: _configure_providers(config),\n            \"[M] Model Presets\": lambda: _configure_model_presets(config),\n            \"[C] Chat Channel\": lambda: _configure_channels(config),\n            \"[H] Channel Common\": lambda: _configure_general_settings(config, \"Channel Common\"),\n            \"[A] Agent Settings\": lambda: _configure_general_settings(config, \"Agent Settings\"),\n            \"[I] API Server\": lambda: _configure_general_settings(config, \"API Server\"),\n            \"[G] Gateway\": lambda: _configure_general_settings(config, \"Gateway\"),\n            \"[T] Tools\": lambda: _configure_general_settings(config, \"Tools\"),\n            \"[V] View Configuration Summary\": lambda: _show_summary(config),\n        }\n        action_fn = _advanced_dispatch.get(answer)\n        if action_fn:\n            last_choice = answer\n            action_fn()\n\n\ndef run_onboard(initial_config: Config | None = None) -> OnboardResult:\n    \"\"\"Run the interactive onboarding questionnaire.\n\n    Args:\n        initial_config: Optional pre-loaded config to use as starting point.\n                       If None, loads from config file or creates new default.\n    \"\"\"\n    _get_questionary()\n\n    if initial_config is not None:\n        base_config = initial_config.model_copy(deep=True)\n    else:\n        config_path = get_config_path()\n        if config_path.exists():\n            base_config = load_config()\n        else:\n            base_config = Config()\n\n    original_config = base_config.model_copy(deep=True)\n    config = base_config.model_copy(deep=True)\n    _sync_preset_cache(config)\n\n    while True:\n        console.clear()\n        _show_main_menu_header()\n\n        try:\n            answer = _select_with_back(\n                \"What would you like to do?\",\n                _get_main_menu_choices(_has_unsaved_changes(original_config, config)),\n            )\n        except KeyboardInterrupt:\n            answer = None\n\n        if answer is _BACK_PRESSED or answer is None:\n            action = _prompt_main_menu_exit(_has_unsaved_changes(original_config, config))\n            if action == \"save\":\n                return OnboardResult(config=config, should_save=True)\n            if action == \"discard\":\n                return OnboardResult(config=original_config, should_save=False)\n            continue\n\n        if answer == _QUICK_START_MENU_CHOICE:\n            if _configure_quick_start(config):\n                return OnboardResult(config=config, should_save=True)\n            continue\n\n        if answer == \"[S] Save and Exit\":\n            return OnboardResult(config=config, should_save=True)\n        if answer in {\"[X] Exit\", \"[X] Exit Without Saving\"}:\n            return OnboardResult(config=original_config, should_save=False)\n        if answer == \"[A] Advanced Settings\":\n            _configure_advanced_settings(config)\n\n\ndef run_quick_start_onboard(initial_config: Config) -> OnboardResult:\n    \"\"\"Run the compact provider + local WebUI setup path directly.\"\"\"\n    _get_questionary()\n    draft = initial_config.model_copy(deep=True)\n    if _configure_quick_start(draft):\n        return OnboardResult(config=draft, should_save=True)\n    return OnboardResult(config=initial_config, should_save=False)\n"}}, "agent_core/config.py": {"87ab4842c02a1341d9678a703b633523e09c99a5": {"t": 1785674248.9756489, "n": 4403, "h": "1419d1865fff6a57", "c": "\"\"\"Configuration loading for Qwen-backed agents.\n\nThe local key file is intentionally flexible because course projects often keep\nAPI credentials in ad-hoc files. Supported formats:\n- JSON object: {\"DASHSCOPE_API_KEY\": \"...\"} or {\"api_key\": \"...\"}\n- JSON string: \"sk-...\"\n- dotenv line: DASHSCOPE_API_KEY=sk-...\n- raw token: sk-...\n\"\"\"\n\nfrom __future__ import annotations\n\nfrom dataclasses import dataclass\nimport json\nimport os\nfrom pathlib import Path\nfrom typing import Mapping\n\n\nDEFAULT_CONFIG_PATH = Path(\"api.json\")\nDEFAULT_QWEN_BASE_URL = \"https://dashscope.aliyuncs.com/compatible-mode/v1\"\nDEFAULT_QWEN_MODEL = \"qwen3.5-omni-flash\"\n\n\n@dataclass(frozen=True)\nclass Settings:\n    api_key: str\n    base_url: str = DEFAULT_QWEN_BASE_URL\n    model: str = DEFAULT_QWEN_MODEL\n    temperature: float = 0.2\n    max_tokens: int = 2200\n    timeout_seconds: float = 90.0\n    thinking_enabled: bool = False\n    reasoning_effort: str = \"none\"\n\n    @property\n    def chat_completions_url(self) -> str:\n        return self.base_url.rstrip(\"/\") + \"/chat/completions\"\n\n\ndef load_settings(\n    config_path: str | Path = DEFAULT_CONFIG_PATH,\n    env: Mapping[str, str] | None = None,\n    model: str | None = None,\n) -> Settings:\n    env = env or os.environ\n    api_key = _load_api_key(config_path=config_path, env=env)\n\n    base_url = env.get(\"DASHSCOPE_BASE_URL\", env.get(\"QWEN_BASE_URL\", DEFAULT_QWEN_BASE_URL))\n    resolved_model = model or env.get(\"QWEN_OMNI_MODEL\", env.get(\"DASHSCOPE_MODEL\", DEFAULT_QWEN_MODEL))\n\n    return Settings(\n        api_key=api_key,\n        base_url=base_url,\n        model=resolved_model,\n        temperature=float(env.get(\"QWEN_TEMPERATURE\", env.get(\"DASHSCOPE_TEMPERATURE\", \"0.2\"))),\n        max_tokens=int(env.get(\"QWEN_MAX_TOKENS\", env.get(\"DASHSCOPE_MAX_TOKENS\", \"2200\"))),\n        timeout_seconds=float(env.get(\"QWEN_TIMEOUT_SECONDS\", env.get(\"DASHSCOPE_TIMEOUT_SECONDS\", \"90\"))),\n        thinking_enabled=_parse_bool(env.get(\"QWEN_THINKING\", \"false\")),\n        reasoning_effort=env.get(\"QWEN_REASONING_EFFORT\", \"none\"),\n    )\n\n\ndef _load_api_key(config_path: str | Path, env: Mapping[str, str]) -> str:\n    for name in (\"DASHSCOPE_API_KEY\", \"QWEN_API_KEY\", \"ALIBABA_API_KEY\", \"API_KEY\"):\n        value = env.get(name)\n        if value:\n            return _clean_secret(value)\n\n    path = Path(config_path)\n    if not path.exists():\n        raise RuntimeError(\n            f\"Qwen API key not found. Set DASHSCOPE_API_KEY or create {path}.\"\n        )\n\n    text = path.read_text(encoding=\"utf-8\").strip()\n    if not text:\n        raise RuntimeError(f\"{path} is empty.\")\n\n    parsed = _try_json(text)\n    if isinstance(parsed, str):\n        return _clean_secret(parsed)\n    if isinstance(parsed, dict):\n        for name in (\n            \"DASHSCOPE_API_KEY\",\n            \"dashscope_api_key\",\n            \"QWEN_API_KEY\",\n            \"qwen_api_key\",\n            \"ALIBABA_API_KEY\",\n            \"api_key\",\n            \"key\",\n        ):\n            value = parsed.get(name)\n            if isinstance(value, str) and value.strip():\n                return _clean_secret(value)\n\n    dotenv_value = _parse_dotenv_secret(text)\n    if dotenv_value:\n        return _clean_secret(dotenv_value)\n\n    # Last-resort compatibility for files that contain only the token.\n    if \"\\n\" not in text and \"=\" not in text and \" \" not in text:\n        return _clean_secret(text)\n\n    raise RuntimeError(\n        f\"Could not find a Qwen API key in {path}. Supported keys: \"\n        \"DASHSCOPE_API_KEY, dashscope_api_key, QWEN_API_KEY, qwen_api_key, api_key, key.\"\n    )\n\n\ndef _try_json(text: str) -> object | None:\n    try:\n        return json.loads(text)\n    except json.JSONDecodeError:\n        return None\n\n\ndef _parse_dotenv_secret(text: str) -> str | None:\n    wanted = {\n        \"DASHSCOPE_API_KEY\",\n        \"QWEN_API_KEY\",\n        \"ALIBABA_API_KEY\",\n        \"API_KEY\",\n        \"api_key\",\n        \"key\",\n    }\n    for raw_line in text.splitlines():\n        line = raw_line.strip()\n        if not line or line.startswith(\"#\") or \"=\" not in line:\n            continue\n        name, value = line.split(\"=\", 1)\n        if name.strip() in wanted and value.strip():\n            return value.strip()\n    return None\n\n\ndef _clean_secret(value: str) -> str:\n    return value.strip().strip(\"'\\\"\")\n\n\ndef _parse_bool(value: str) -> bool:\n    return value.strip().lower() in {\"1\", \"true\", \"yes\", \"on\", \"enabled\"}\n"}}, "nanobot/webui/src/tests/settings-view.test.tsx": {"87ab4842c02a1341d9678a703b633523e09c99a5": {"t": 1785746560.2267282, "n": 44154, "h": "6a852d8e587f8202", "c": "import { fireEvent, render, screen, waitFor } from \"@testing-library/react\";\nimport { afterEach, describe, expect, it, vi } from \"vitest\";\n\nimport { SettingsView } from \"@/components/settings/SettingsView\";\nimport { ClientProvider } from \"@/providers/ClientProvider\";\nimport type { SettingsPayload } from \"@/lib/types\";\n\nfunction jsonResponse(body: unknown): Response {\n  return {\n    ok: true,\n    status: 200,\n    json: async () => body,\n  } as Response;\n}\n\nfunction settingsPayload(): SettingsPayload {\n  return {\n    agent: {\n      model: \"openai/gpt-4o\",\n      provider: \"auto\",\n      resolved_provider: \"openai\",\n      has_api_key: true,\n      model_preset: \"default\",\n      max_tokens: 8192,\n      context_window_tokens: 200000,\n      temperature: 0.1,\n      reasoning_effort: null,\n      timezone: \"UTC\",\n      bot_name: \"nanobot\",\n      bot_icon: \"nb\",\n      tool_hint_max_length: 40,\n    },\n    model_presets: [{\n      name: \"default\",\n      label: \"Default\",\n      active: true,\n      is_default: true,\n      model: \"openai/gpt-4o\",\n      provider: \"auto\",\n      max_tokens: 8192,\n      context_window_tokens: 200000,\n      temperature: 0.1,\n      reasoning_effort: null,\n    }],\n    providers: [],\n    web_search: {\n      provider: \"duckduckgo\",\n      api_key_hint: null,\n      base_url: null,\n      max_results: 5,\n      timeout: 30,\n      providers: [{ name: \"duckduckgo\", label: \"DuckDuckGo\", credential: \"none\" }],\n    },\n    web: {\n      enable: true,\n      proxy: null,\n      user_agent: null,\n      search: { max_results: 5, timeout: 30 },\n      fetch: { use_jina_reader: true },\n    },\n    image_generation: {\n      enabled: false,\n      provider: \"openrouter\",\n      provider_configured: false,\n      model: \"openai/gpt-5.4-image-2\",\n      default_aspect_ratio: \"1:1\",\n      default_image_size: \"1K\",\n      max_images_per_turn: 4,\n      save_dir: \"generated\",\n      providers: [],\n    },\n    runtime: {\n      config_path: \"/tmp/config.json\",\n      workspace_path: \"/tmp/workspace\",\n      gateway_host: \"127.0.0.1\",\n      gateway_port: 18790,\n      heartbeat: {\n        enabled: true,\n        interval_s: 1800,\n        keep_recent_messages: 8,\n      },\n      dream: {\n        schedule: \"every 2h\",\n      },\n      unified_session: false,\n    },\n    advanced: {\n      restrict_to_workspace: false,\n      webui_allow_local_service_access: true,\n      webui_default_access_mode: \"default\",\n      private_service_protection_enabled: true,\n      ssrf_whitelist_count: 0,\n      mcp_server_count: 0,\n      exec_enabled: true,\n      exec_sandbox: null,\n      exec_path_prepend_set: false,\n      exec_path_append_set: false,\n    },\n    requires_restart: false,\n  };\n}\n\nfunction autoDynamicProviderPayload(\n  options: {\n    configured: boolean;\n    hasApiKey: boolean;\n    apiBase: string | null;\n    apiKeyHint: string | null;\n  },\n): SettingsPayload {\n  const base = settingsPayload();\n  return {\n    ...base,\n    agent: {\n      ...base.agent,\n      model: \"companyProxy/gpt-4o\",\n      provider: \"companyProxy\",\n      resolved_provider: \"companyProxy\",\n      has_api_key: options.hasApiKey,\n    },\n    model_presets: [\n      {\n        ...base.model_presets[0],\n        model: \"companyProxy/gpt-4o\",\n        provider: \"auto\",\n      },\n    ],\n    providers: [\n      {\n        name: \"companyProxy\",\n        label: \"Company Proxy\",\n        configured: options.configured,\n        auth_type: \"api_key\",\n        api_key_required: false,\n        api_key_hint: options.apiKeyHint,\n        api_base: options.apiBase,\n        default_api_base: null,\n      },\n    ],\n  };\n}\n\nconst installedAnyGen = {\n  name: \"anygen\",\n  display_name: \"AnyGen\",\n  category: \"generation\",\n  description: \"Generate docs, slides, websites and more via AnyGen cloud API\",\n  requires: \"ANYGEN_API_KEY\",\n  source: \"harness\",\n  entry_point: \"cli-anything-anygen\",\n  install_supported: true,\n  installed: true,\n  available: true,\n  status: \"installed\",\n  logo_url: \"https://www.google.com/s2/favicons?domain=anygen.io&sz=64\",\n  brand_color: \"#111827\",\n  skill_installed: true,\n};\n\nfunction renderSettingsView(\n  options: {\n    initialSection?: \"overview\" | \"appearance\" | \"apps\" | \"automations\" | \"advanced\" | \"models\" | \"browser\";\n    initialSettings?: SettingsPayload;\n    showSidebar?: boolean;\n    onSettingsChange?: (payload: SettingsPayload) => void;\n    onNativeEngineRestart?: () => Promise<string>;\n  } = {},\n) {\n  render(\n    <ClientProvider client={{} as never} token=\"tok\">\n      <SettingsView\n        theme=\"light\"\n        initialSection={options.initialSection ?? \"apps\"}\n        initialSettings={options.initialSettings}\n        showSidebar={options.showSidebar}\n        onToggleTheme={() => {}}\n        onBackToChat={() => {}}\n        onModelNameChange={() => {}}\n        onSettingsChange={options.onSettingsChange}\n        onNativeEngineRestart={options.onNativeEngineRestart}\n      />\n    </ClientProvider>,\n  );\n}\n\ndescribe(\"SettingsView Apps catalog\", () => {\n  afterEach(() => {\n    localStorage.removeItem(\"nanobot-webui.settings-preferences\");\n    vi.useRealTimers();\n    vi.unstubAllGlobals();\n  });\n\n  it(\"persists the file edit display local preference\", async () => {\n    renderSettingsView({\n      initialSection: \"appearance\",\n      initialSettings: settingsPayload(),\n      showSidebar: true,\n    });\n\n    expect(screen.getByText(\"File edit display\")).toBeInTheDocument();\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Diff\" }));\n\n    await waitFor(() => {\n      const saved = JSON.parse(localStorage.getItem(\"nanobot-webui.settings-preferences\") || \"{}\");\n      expect(saved.fileEditDisplayMode).toBe(\"diff\");\n    });\n  });\n\n  it(\"does not show the Settings kicker on the standalone Automations surface\", async () => {\n    vi.stubGlobal(\"fetch\", vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n      if (url === \"/api/webui/automations\") return jsonResponse({ jobs: [] });\n      return jsonResponse({});\n    }));\n\n    renderSettingsView({\n      initialSection: \"automations\",\n      initialSettings: settingsPayload(),\n      showSidebar: false,\n    });\n\n    expect(screen.getByRole(\"heading\", { name: \"Automations\" })).toBeInTheDocument();\n    expect(await screen.findByText(\"No automations yet.\")).toBeInTheDocument();\n    expect(screen.queryByText(\"Settings\")).not.toBeInTheDocument();\n  });\n\n  it(\"shows a visible uninstall button for installed CLI apps and calls uninstall\", async () => {\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") {\n        return jsonResponse(settingsPayload());\n      }\n      if (url === \"/api/settings/cli-apps\") {\n        return jsonResponse({\n          apps: [installedAnyGen],\n          installed_count: 1,\n          catalog_updated_at: \"2026-04-18\",\n        });\n      }\n      if (url === \"/api/settings/mcp-presets\") {\n        return jsonResponse({ presets: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/cli-apps/uninstall?name=anygen\") {\n        return jsonResponse({\n          apps: [{ ...installedAnyGen, installed: false, status: \"available\" }],\n          installed_count: 0,\n          catalog_updated_at: \"2026-04-18\",\n          last_action: {\n            ok: true,\n            message: \"Uninstalled CLI for AnyGen.\",\n            still_available: false,\n          },\n        });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView();\n\n    expect(await screen.findByRole(\"heading\", { name: \"Apps\" })).toBeInTheDocument();\n    expect(await screen.findByText(\"AnyGen\")).toBeInTheDocument();\n    const uninstall = screen.getByRole(\"button\", { name: \"Uninstall CLI\" });\n\n    fireEvent.click(uninstall);\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/cli-apps/uninstall?name=anygen\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n    expect(await screen.findByText(\"Uninstalled CLI for AnyGen.\")).toBeInTheDocument();\n\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Dismiss\" }));\n\n    expect(screen.queryByText(\"Uninstalled CLI for AnyGen.\")).not.toBeInTheDocument();\n  });\n\n  it(\"shows nanobot optional features and enables one\", async () => {\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n      if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n      if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n      if (url === \"/api/settings/nanobot-features\") {\n        return jsonResponse({\n          features: [{\n            name: \"matrix\",\n            display_name: \"Matrix\",\n            type: \"channel\",\n            enabled: false,\n            installed: false,\n            ready: false,\n            status: \"missing_dependency\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 0,\n        });\n      }\n      if (url === \"/api/settings/nanobot-features/enable?name=matrix\") {\n        return jsonResponse({\n          features: [{\n            name: \"matrix\",\n            display_name: \"Matrix\",\n            type: \"channel\",\n            enabled: true,\n            installed: true,\n            ready: true,\n            status: \"enabled\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 1,\n          last_action: { ok: true, message: \"Enabled channel 'matrix'\", enabled: true },\n        });\n      }\n      if (url === \"/api/settings/nanobot-features/disable?name=matrix\") {\n        return jsonResponse({\n          features: [{\n            name: \"matrix\",\n            display_name: \"Matrix\",\n            type: \"channel\",\n            enabled: false,\n            installed: true,\n            ready: false,\n            status: \"not_enabled\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 0,\n          requires_restart: true,\n          last_action: { ok: true, message: \"Disabled channel 'matrix'\", enabled: false },\n        });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView();\n\n    expect(await screen.findByText(\"Matrix\")).toBeInTheDocument();\n    expect(screen.queryByText(/Enabling Nanobot features may install Python packages/)).not.toBeInTheDocument();\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Install support\" }));\n    expect(screen.getByRole(\"dialog\", { name: \"Install support for Matrix?\" })).toBeInTheDocument();\n    expect(screen.getByText(\"nanobot will add what Matrix needs, then turn it on. Continue?\")).toBeInTheDocument();\n    expect(fetchMock).not.toHaveBeenCalledWith(\n      \"/api/settings/nanobot-features/enable?name=matrix\",\n      expect.anything(),\n    );\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Install and enable\" }));\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/nanobot-features/enable?name=matrix\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n    expect(await screen.findByText(\"Enabled channel 'matrix'\")).toBeInTheDocument();\n    expect(screen.getByText(\"Restart nanobot to apply updated apps and features.\")).toBeInTheDocument();\n\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Disable\" }));\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/nanobot-features/disable?name=matrix\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n    expect(await screen.findByText(\"Disabled channel 'matrix'\")).toBeInTheDocument();\n  });\n\n  it(\"shows enabled nanobot channels with missing support as enabled\", async () => {\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n      if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n      if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n      if (url === \"/api/settings/nanobot-features\") {\n        return jsonResponse({\n          features: [{\n            name: \"matrix\",\n            display_name: \"Matrix\",\n            type: \"channel\",\n            enabled: true,\n            installed: false,\n            ready: false,\n            status: \"missing_dependency\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 1,\n        });\n      }\n      if (url === \"/api/settings/nanobot-features/enable?name=matrix\") {\n        return jsonResponse({\n          features: [{\n            name: \"matrix\",\n            display_name: \"Matrix\",\n            type: \"channel\",\n            enabled: true,\n            installed: true,\n            ready: true,\n            status: \"enabled\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 1,\n          last_action: { ok: true, message: \"Enabled channel 'matrix'\", enabled: true },\n        });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView();\n\n    expect(await screen.findByText(\"Matrix\")).toBeInTheDocument();\n    expect(screen.getByText(\"1 Plugin · 0 CLI · 0 MCP\")).toBeInTheDocument();\n    expect(screen.getByText(\"Support missing\")).toBeInTheDocument();\n\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Install support\" }));\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Install and enable\" }));\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/nanobot-features/enable?name=matrix\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n  });\n\n  it(\"does not offer to disable the websocket channel\", async () => {\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n      if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n      if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n      if (url === \"/api/settings/nanobot-features\") {\n        return jsonResponse({\n          features: [{\n            name: \"websocket\",\n            display_name: \"Websocket\",\n            type: \"channel\",\n            enabled: true,\n            installed: true,\n            ready: true,\n            status: \"enabled\",\n            install_supported: true,\n            requires_restart: true,\n          }],\n          enabled_count: 1,\n        });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView();\n\n    expect(await screen.findByText(\"Websocket\")).toBeInTheDocument();\n    expect(screen.getByText(\"Required for WebUI\")).toBeInTheDocument();\n    expect(screen.queryByRole(\"button\", { name: \"Disable\" })).not.toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"Required for WebUI\" })).toBeDisabled();\n    expect(fetchMock).not.toHaveBeenCalledWith(\n      \"/api/settings/nanobot-features/disable?name=websocket\",\n      expect.anything(),\n    );\n  });\n\n  it(\"publishes the latest settings payload to the shell\", async () => {\n    const payload = settingsPayload();\n    const onSettingsChange = vi.fn();\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(payload);\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ onSettingsChange });\n\n    await waitFor(() => expect(onSettingsChange).toHaveBeenCalledWith(payload));\n  });\n\n  it(\"does not keep Apps loading while an empty CLI catalog refresh is pending\", async () => {\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({\n            apps: [],\n            installed_count: 0,\n            catalog_updated_at: null,\n            catalog_refresh_pending: true,\n          });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView();\n\n    expect(await screen.findByText(\"No apps match this filter.\")).toBeInTheDocument();\n    expect(screen.queryByText(\"Loading Apps...\")).not.toBeInTheDocument();\n  });\n\n  it(\"shows token activity on the overview\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      usage: {\n        days: [\n          {\n            date: \"2026-06-03\",\n            prompt_tokens: 1200,\n            completion_tokens: 300,\n            cached_tokens: 500,\n            total_tokens: 1500,\n            requests: 2,\n          },\n        ],\n        total_tokens: 1500,\n        total_tokens_30d: 1500,\n        total_tokens_365d: 1500,\n        peak_day_tokens: 1500,\n        current_streak_days: 1,\n        longest_streak_days: 1,\n        active_days_30d: 1,\n        requests_30d: 2,\n        updated_at: \"2026-06-03T00:00:00Z\",\n      },\n    };\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(payload);\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"overview\" });\n\n    expect(await screen.findByLabelText(\"Token activity\")).toBeInTheDocument();\n    expect(screen.getByText(\"Token Usage\")).toBeInTheDocument();\n    expect(screen.queryByText(\"Token activity\")).not.toBeInTheDocument();\n    expect(screen.queryByText(\"Total tokens\")).not.toBeInTheDocument();\n    expect(screen.queryByText(\"Peak tokens\")).not.toBeInTheDocument();\n  });\n\n  it(\"aligns token activity days with the configured timezone\", async () => {\n    vi.useFakeTimers();\n    vi.setSystemTime(new Date(\"2026-06-02T18:00:00Z\"));\n    const basePayload = settingsPayload();\n    const payload: SettingsPayload = {\n      ...basePayload,\n      agent: {\n        ...basePayload.agent,\n        timezone: \"Asia/Shanghai\",\n      },\n      usage: {\n        days: [\n          {\n            date: \"2026-06-03\",\n            prompt_tokens: 1200,\n            completion_tokens: 300,\n            cached_tokens: 500,\n            total_tokens: 1500,\n            requests: 2,\n          },\n        ],\n        total_tokens: 1500,\n        total_tokens_30d: 1500,\n        total_tokens_365d: 1500,\n        peak_day_tokens: 1500,\n        current_streak_days: 1,\n        longest_streak_days: 1,\n        active_days_30d: 1,\n        requests_30d: 2,\n        updated_at: \"2026-06-03T00:00:00Z\",\n      },\n    };\n    vi.stubGlobal(\"fetch\", vi.fn(() => new Promise<Response>(() => {})));\n\n    renderSettingsView({ initialSection: \"overview\", initialSettings: payload });\n\n    expect(screen.getByLabelText(\"2026-06-03: 1.5K tokens, 2 requests\")).toBeInTheDocument();\n  });\n\n  it(\"shows context window options in model settings\", async () => {\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    expect(await screen.findByText(\"Context window\")).toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"64K\" })).toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"200K\" })).toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"256K\" })).toBeInTheDocument();\n  });\n\n  it(\"uses the resolved provider row for auto dynamic providers without api keys\", async () => {\n    vi.stubGlobal(\"fetch\", vi.fn(() => new Promise<Response>(() => {})));\n\n    renderSettingsView({\n      initialSection: \"models\",\n      initialSettings: autoDynamicProviderPayload({\n        configured: true,\n        hasApiKey: false,\n        apiBase: \"https://proxy.example.test/v1\",\n        apiKeyHint: null,\n      }),\n    });\n\n    const configurationButton = await screen.findByRole(\"button\", {\n      name: \"Current configuration\",\n    });\n    expect(configurationButton).toHaveTextContent(\"companyProxy/gpt-4o\");\n    expect(configurationButton).toHaveTextContent(\"Company Proxy\");\n    expect(configurationButton).not.toHaveTextContent(\"Not configured\");\n  });\n\n  it(\"does not treat auto dynamic provider api keys as configured without apiBase\", async () => {\n    vi.stubGlobal(\"fetch\", vi.fn(() => new Promise<Response>(() => {})));\n\n    renderSettingsView({\n      initialSection: \"models\",\n      initialSettings: autoDynamicProviderPayload({\n        configured: false,\n        hasApiKey: true,\n        apiBase: null,\n        apiKeyHint: \"sk-...\",\n      }),\n    });\n\n    const configurationButton = await screen.findByRole(\"button\", {\n      name: \"Current configuration\",\n    });\n    expect(configurationButton).toHaveTextContent(\"Not configured\");\n    expect(configurationButton).toHaveTextContent(\"Company Proxy · companyProxy/gpt-4o\");\n  });\n\n  it(\"marks the current model as unconfigured when its provider needs setup\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      agent: {\n        ...settingsPayload().agent,\n        model: \"openai-codex/gpt-5.1-codex\",\n        provider: \"openai_codex\",\n        resolved_provider: \"openai_codex\",\n        has_api_key: false,\n      },\n      model_presets: [\n        {\n          ...settingsPayload().model_presets[0],\n          model: \"openai-codex/gpt-5.1-codex\",\n          provider: \"openai_codex\",\n        },\n      ],\n      providers: [\n        {\n          name: \"openai_codex\",\n          label: \"OpenAI Codex\",\n          configured: false,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: null,\n          oauth_account: null,\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n      ],\n    };\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(payload);\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    const configurationButton = await screen.findByRole(\"button\", {\n      name: \"Current configuration\",\n    });\n    expect(configurationButton).toHaveTextContent(\"Not configured\");\n    expect(configurationButton).toHaveTextContent(\"OpenAI Codex · openai-codex/gpt-5.1-codex\");\n    expect(await screen.findByRole(\"button\", { name: \"Sign in\" })).toBeInTheDocument();\n  });\n\n  it(\"keeps unsigned OAuth providers out of the active provider picker\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      agent: {\n        ...settingsPayload().agent,\n        model: \"deepseek-chat\",\n        provider: \"deepseek\",\n        resolved_provider: \"deepseek\",\n      },\n      model_presets: [\n        {\n          ...settingsPayload().model_presets[0],\n          model: \"deepseek-chat\",\n          provider: \"deepseek\",\n        },\n      ],\n      providers: [\n        {\n          name: \"deepseek\",\n          label: \"DeepSeek\",\n          configured: true,\n          auth_type: \"api_key\",\n          api_key_required: true,\n          api_key_hint: \"sk-...\",\n          api_base: \"https://api.deepseek.com\",\n          default_api_base: \"https://api.deepseek.com\",\n        },\n        {\n          name: \"openai_codex\",\n          label: \"OpenAI Codex\",\n          configured: false,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: null,\n          oauth_account: null,\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n        {\n          name: \"github_copilot\",\n          label: \"GitHub Copilot\",\n          configured: false,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: \"https://api.githubcopilot.com\",\n          oauth_account: null,\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n      ],\n    };\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(payload);\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    const deepseekButtons = await screen.findAllByRole(\"button\", { name: /DeepSeek/ });\n    const providerPicker = deepseekButtons.find(\n      (button) => button.getAttribute(\"aria-haspopup\") === \"menu\",\n    );\n    if (!providerPicker) throw new Error(\"provider picker was not found\");\n    fireEvent.pointerDown(providerPicker);\n\n    expect(await screen.findByRole(\"menuitem\", { name: /DeepSeek/ })).toBeInTheDocument();\n    expect(screen.queryByRole(\"menuitem\", { name: /OpenAI Codex/ })).not.toBeInTheDocument();\n    expect(screen.queryByRole(\"menuitem\", { name: /GitHub Copilot/ })).not.toBeInTheDocument();\n  });\n\n  it(\"does not fetch model lists for unsigned OAuth providers\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      agent: {\n        ...settingsPayload().agent,\n        model: \"\",\n        provider: \"openai_codex\",\n        resolved_provider: \"openai_codex\",\n      },\n      model_presets: [\n        {\n          ...settingsPayload().model_presets[0],\n          model: \"\",\n          provider: \"openai_codex\",\n        },\n      ],\n      providers: [\n        {\n          name: \"openai_codex\",\n          label: \"OpenAI Codex\",\n          configured: false,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: null,\n          oauth_account: null,\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n        {\n          name: \"github_copilot\",\n          label: \"GitHub Copilot\",\n          configured: false,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: \"https://api.githubcopilot.com\",\n          oauth_account: null,\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n      ],\n    };\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") {\n        return jsonResponse({ apps: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/mcp-presets\") {\n        return jsonResponse({ presets: [], installed_count: 0 });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    fireEvent.pointerDown(await screen.findByRole(\"button\", { name: /Select model/i }));\n    expect(\n      await screen.findByText(\"Configure this provider before loading models.\"),\n    ).toBeInTheDocument();\n    expect(\n      fetchMock.mock.calls.some(([input]) =>\n        String(input).startsWith(\"/api/settings/provider-models\"),\n      ),\n    ).toBe(false);\n  });\n\n  it(\"prefills manual model ids for configured OAuth providers\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      agent: {\n        ...settingsPayload().agent,\n        model: \"open-codex/gpt-5.5\",\n        provider: \"openai_codex\",\n        resolved_provider: \"openai_codex\",\n      },\n      model_presets: [\n        {\n          ...settingsPayload().model_presets[0],\n          model: \"open-codex/gpt-5.5\",\n          provider: \"openai_codex\",\n        },\n      ],\n      providers: [\n        {\n          name: \"openai_codex\",\n          label: \"OpenAI Codex\",\n          configured: true,\n          auth_type: \"oauth\",\n          api_key_required: false,\n          api_key_hint: null,\n          api_base: null,\n          default_api_base: null,\n          oauth_account: \"acct-test\",\n          oauth_expires_at: null,\n          oauth_login_supported: true,\n        },\n      ],\n    };\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") {\n        return jsonResponse({ apps: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/mcp-presets\") {\n        return jsonResponse({ presets: [], installed_count: 0 });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    const modelButtons = await screen.findAllByRole(\"button\", { name: /open-codex\\/gpt-5\\.5/i });\n    fireEvent.pointerDown(modelButtons[modelButtons.length - 1]);\n    const input = (await screen.findByPlaceholderText(\"Search or type model ID\")) as HTMLInputElement;\n    expect(input.value).toBe(\"open-codex/gpt-5.5\");\n\n    fireEvent.change(input, { target: { value: \"openai-codex/gpt-5.5\" } });\n    expect(await screen.findByText(\"“openai-codex/gpt-5.5”\")).toBeInTheDocument();\n    expect(\n      fetchMock.mock.calls.some(([input]) =>\n        String(input).startsWith(\"/api/settings/provider-models\"),\n      ),\n    ).toBe(false);\n  });\n\n  it(\"can close the new configuration dialog without trapping the settings page\", async () => {\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(settingsPayload());\n        if (url === \"/api/settings/cli-apps\") {\n          return jsonResponse({ apps: [], installed_count: 0 });\n        }\n        if (url === \"/api/settings/mcp-presets\") {\n          return jsonResponse({ presets: [], installed_count: 0 });\n        }\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    const configurationButton = await screen.findByRole(\"button\", { name: \"Current configuration\" });\n    fireEvent.pointerDown(configurationButton!);\n    fireEvent.click(await screen.findByText(\"Add configuration\"));\n\n    expect(await screen.findByRole(\"heading\", { name: \"New model configuration\" })).toBeInTheDocument();\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Cancel\" }));\n\n    await waitFor(() =>\n      expect(screen.queryByRole(\"heading\", { name: \"New model configuration\" })).not.toBeInTheDocument(),\n    );\n    expect(document.body.style.pointerEvents).not.toBe(\"none\");\n\n    fireEvent.pointerDown(configurationButton!);\n    expect(await screen.findByText(\"Add configuration\")).toBeInTheDocument();\n  });\n\n  it(\"loads provider models and lets users choose one without typing the id manually\", async () => {\n    const payload: SettingsPayload = {\n      ...settingsPayload(),\n      agent: {\n        ...settingsPayload().agent,\n        model: \"deepseek-chat\",\n        provider: \"deepseek\",\n        resolved_provider: \"deepseek\",\n      },\n      model_presets: [\n        {\n          ...settingsPayload().model_presets[0],\n          model: \"deepseek-chat\",\n          provider: \"deepseek\",\n        },\n      ],\n      providers: [\n        {\n          name: \"deepseek\",\n          label: \"DeepSeek\",\n          configured: true,\n          auth_type: \"api_key\",\n          api_key_required: true,\n          api_key_hint: \"sk-...\",\n          api_base: \"https://api.deepseek.com\",\n          default_api_base: \"https://api.deepseek.com\",\n        },\n      ],\n    };\n    const updatedPayload: SettingsPayload = {\n      ...payload,\n      agent: {\n        ...payload.agent,\n        model: \"deepseek-reasoner\",\n      },\n      model_presets: [\n        {\n          ...payload.model_presets[0],\n          model: \"deepseek-reasoner\",\n        },\n      ],\n    };\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") {\n        return jsonResponse({ apps: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/mcp-presets\") {\n        return jsonResponse({ presets: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/provider-models?provider=deepseek\") {\n        return jsonResponse({\n          provider: \"deepseek\",\n          label: \"DeepSeek\",\n          status: \"available\",\n          catalog_kind: \"official\",\n          models: [\n            { id: \"deepseek-chat\", owned_by: \"deepseek\", context_window: 65536 },\n            { id: \"deepseek-reasoner\", owned_by: \"deepseek\", context_window: 65536 },\n          ],\n          model_count: 2,\n          fetched_at: 1,\n        });\n      }\n      if (url === \"/api/settings/update?model_preset=default&model=deepseek-reasoner\") {\n        return jsonResponse(updatedPayload);\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({ initialSection: \"models\" });\n\n    const modelButtons = await screen.findAllByRole(\"button\", { name: /deepseek-chat/i });\n    fireEvent.pointerDown(modelButtons[modelButtons.length - 1]);\n    await screen.findByText(\"deepseek-reasoner\");\n    fireEvent.click(screen.getAllByText(\"deepseek-reasoner\")[0]);\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Save\" }));\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/provider-models?provider=deepseek\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/update?model_preset=default&model=deepseek-reasoner\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n  });\n\n  it(\"saves network safety without exposing technical SSRF copy\", async () => {\n    const payload = settingsPayload();\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") {\n        return jsonResponse({ apps: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/mcp-presets\") {\n        return jsonResponse({ presets: [], installed_count: 0 });\n      }\n      if (url === \"/api/settings/network-safety/update?webui_allow_local_service_access=false&webui_default_access_mode=default\") {\n        return jsonResponse({\n          ...payload,\n          advanced: { ...payload.advanced, webui_allow_local_service_access: false },\n          requires_restart: true,\n          restart_required_sections: [\"runtime\"],\n        });\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({ initialSection: \"advanced\" });\n\n    expect(await screen.findByText(\"Web safety\")).toBeInTheDocument();\n    expect(screen.queryByText(/SSRF/i)).not.toBeInTheDocument();\n    expect(screen.queryByText(\"Private Service Protection\")).not.toBeInTheDocument();\n    expect(screen.getByText(\"Default access\")).toBeInTheDocument();\n    expect(screen.queryByRole(\"button\", { name: \"Restricted\" })).not.toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"Default Permission\" })).toBeInTheDocument();\n    expect(screen.getByRole(\"button\", { name: \"Full Access\" })).toBeInTheDocument();\n\n    fireEvent.click(screen.getByRole(\"switch\", { name: \"Local services\" }));\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Save\" }));\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/network-safety/update?webui_allow_local_service_access=false&webui_default_access_mode=default\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n  });\n\n  it(\"saves optional-key web search providers without an API key\", async () => {\n    const payload = {\n      ...settingsPayload(),\n      web_search: {\n        ...settingsPayload().web_search,\n        provider: \"duckduckgo\",\n        providers: [\n          { name: \"duckduckgo\", label: \"DuckDuckGo\", credential: \"none\" as const },\n          { name: \"keenable\", label: \"Keenable\", credential: \"optional_api_key\" as const },\n        ],\n      },\n    };\n    const updatedPayload = {\n      ...payload,\n      web_search: {\n        ...payload.web_search,\n        provider: \"keenable\",\n      },\n    };\n    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {\n      const url = String(input);\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n      if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n      if (\n        url ===\n        \"/api/settings/web-search/update?provider=keenable&max_results=5&timeout=30&use_jina_reader=true\"\n      ) {\n        return jsonResponse(updatedPayload);\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({ initialSection: \"browser\" });\n\n    fireEvent.pointerDown(await screen.findByRole(\"button\", { name: /DuckDuckGo/ }));\n    fireEvent.click(await screen.findByRole(\"menuitem\", { name: \"Keenable\" }));\n    const saveButton = screen\n      .getAllByRole(\"button\", { name: \"Save\" })\n      .find((button) => !(button as HTMLButtonElement).disabled);\n    if (!saveButton) throw new Error(\"enabled Save button was not found\");\n    fireEvent.click(saveButton);\n\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings/web-search/update?provider=keenable&max_results=5&timeout=30&use_jina_reader=true\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer tok\" },\n        }),\n      ),\n    );\n  });\n\n  it(\"uses native host safety copy on the native surface\", async () => {\n    const payload = {\n      ...settingsPayload(),\n      surface: \"native\" as const,\n      runtime_surface: \"native\" as const,\n    };\n    vi.stubGlobal(\n      \"fetch\",\n      vi.fn(async (input: RequestInfo | URL) => {\n        const url = String(input);\n        if (url === \"/api/settings\") return jsonResponse(payload);\n        if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n        if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n        return { ok: false, status: 404, json: async () => ({}) } as Response;\n      }),\n    );\n\n    renderSettingsView({ initialSection: \"advanced\" });\n\n    expect(await screen.findByText(\"App safety\")).toBeInTheDocument();\n    expect(screen.queryByText(\"Web safety\")).not.toBeInTheDocument();\n    expect(screen.getByText(\"Allow Full Access shell commands to reach services on this Mac.\")).toBeInTheDocument();\n  });\n\n  it(\"refreshes settings with a fresh token after native engine restart\", async () => {\n    const payload = {\n      ...settingsPayload(),\n      surface: \"native\" as const,\n      runtime_surface: \"native\" as const,\n      runtime_capabilities: {\n        can_restart_engine: true,\n        can_pick_folder: true,\n        can_open_logs: true,\n        can_export_diagnostics: true,\n      },\n    };\n    const restartedPayload = {\n      ...payload,\n      advanced: { ...payload.advanced, webui_allow_local_service_access: false },\n      requires_restart: true,\n      restart_required_sections: [\"runtime\"],\n    };\n    const refreshedPayload = {\n      ...restartedPayload,\n      requires_restart: false,\n      restart_required_sections: [],\n    };\n    const restartEngine = vi.fn(async () => \"fresh-token\");\n    const fetchMock = vi.fn(async (input: RequestInfo | URL, init?: RequestInit) => {\n      const url = String(input);\n      const auth = (init?.headers as Record<string, string> | undefined)?.Authorization;\n      if (url === \"/api/settings\" && auth === \"Bearer fresh-token\") {\n        return jsonResponse(refreshedPayload);\n      }\n      if (url === \"/api/settings\") return jsonResponse(payload);\n      if (url === \"/api/settings/cli-apps\") return jsonResponse({ apps: [], installed_count: 0 });\n      if (url === \"/api/settings/mcp-presets\") return jsonResponse({ presets: [], installed_count: 0 });\n      if (url === \"/api/settings/network-safety/update?webui_allow_local_service_access=false&webui_default_access_mode=default\") {\n        return jsonResponse(restartedPayload);\n      }\n      return { ok: false, status: 404, json: async () => ({}) } as Response;\n    });\n    vi.stubGlobal(\"fetch\", fetchMock);\n\n    renderSettingsView({\n      initialSection: \"advanced\",\n      onNativeEngineRestart: restartEngine,\n    });\n\n    expect(await screen.findByText(\"App safety\")).toBeInTheDocument();\n    fireEvent.click(screen.getByRole(\"switch\", { name: \"Local services\" }));\n    fireEvent.click(screen.getByRole(\"button\", { name: \"Save\" }));\n\n    await waitFor(() => expect(restartEngine).toHaveBeenCalledTimes(1));\n    await waitFor(() =>\n      expect(fetchMock).toHaveBeenCalledWith(\n        \"/api/settings\",\n        expect.objectContaining({\n          headers: { Authorization: \"Bearer fresh-token\" },\n        }),\n      ),\n    );\n  });\n});\n"}}}}