feat(providers): discover OAuth model catalogs online

docs/configuration.md

@@ -765,10 +765,13 @@ nanobot agent -m "Hello from Grok."
 ```
 
 The default model is `xai-grok/grok-4.6` with a 500,000-token context window.
-The provider reads xAI's model catalog and includes the server-hosted `x_search`
+The provider reads and caches xAI's online model catalog for both WebUI model
-tool only when the selected model advertises `supportsBackendSearch`. Models
+selection and runtime capabilities. Newly available models appear automatically;
-without that capability continue normally without hosted X Search. When enabled,
+when discovery fails, the last successful catalog or built-in fallback remains
-searches run inside xAI's Responses API and citations arrive as inline links.
+available. The server-hosted `x_search` tool is included only when the selected
+model advertises support. Models without that capability continue normally
+without hosted X Search. When enabled, searches run inside xAI's Responses API
+and citations arrive as inline links.
 Hosted X Search is on by default to preserve this behavior. It can be turned off in the
 WebUI provider settings or with `providers.xaiGrok.extraBody.tools: []`.
 

docs/providers.md

@@ -578,9 +578,13 @@ For an eligible X Premium / Grok subscription:
 nanobot provider login xai-grok --set-main
 ```
 
-This selects `xai-grok/grok-4.6`. The provider reads xAI's model catalog and
+This selects `xai-grok/grok-4.6`. The WebUI model selector reads xAI's online
-exposes the hosted `x_search` tool only when the selected model advertises
+model catalog, so newly available subscription models appear without a nanobot
-`supportsBackendSearch`; otherwise the model runs without hosted X Search.
+release. Online metadata is cached and enriched with nanobot's curated labels;
+if xAI is temporarily unavailable, nanobot uses the last successful catalog or
+a small built-in fallback instead of emptying the selector. The same catalog
+controls whether the provider exposes the hosted `x_search` tool; models that do
+not advertise support continue without hosted X Search.
 When enabled, Grok can search current X posts and return inline source links
 without invoking a local nanobot tool. Credentials are stored under the
 active instance's `auth/xai.json` (normally `~/.nanobot/auth/xai.json`), not in

nanobot/providers/oauth_model_catalog.py

@@ -0,0 +1,425 @@
+"""Online model discovery for OAuth providers with bounded local fallback."""
+
+from __future__ import annotations
+
+import base64
+import json
+import threading
+import time
+from collections.abc import Callable, Sequence
+from dataclasses import dataclass, replace
+from pathlib import Path
+from typing import Any, Literal, Protocol, cast
+
+import httpx
+from loguru import logger
+
+from nanobot import __version__
+
+DEFAULT_XAI_GROK_MODEL = "xai-grok/grok-4.6"
+DEFAULT_XAI_GROK_MODELS_URL = "https://cli-chat-proxy.grok.com/v1/models"
+
+CatalogSource = Literal["remote", "cache", "stale", "fallback"]
+
+
+class _XAIToken(Protocol):
+    @property
+    def access(self) -> str: ...
+
+    @property
+    def account_id(self) -> str | None: ...
+
+
+@dataclass(frozen=True)
+class OAuthModelInfo:
+    """Normalized provider model metadata used by settings and runtimes."""
+
+    id: str
+    label: str
+    description: str = ""
+    owned_by: str = ""
+    context_window: int | None = None
+    reasoning_efforts: tuple[str, ...] = ()
+    supports_backend_search: bool = False
+
+    @property
+    def wire_id(self) -> str:
+        return self.id.split("/", 1)[-1]
+
+
+@dataclass(frozen=True)
+class OAuthModelCatalogSnapshot:
+    """One usable catalog view, including where it came from."""
+
+    models: tuple[OAuthModelInfo, ...]
+    source: CatalogSource
+    fetched_at: float
+    message: str | None = None
+
+    def find(self, model: str) -> OAuthModelInfo | None:
+        wire_id = model.split("/", 1)[-1]
+        return next((item for item in self.models if item.wire_id == wire_id), None)
+
+
+@dataclass(frozen=True)
+class _CacheEntry:
+    snapshot: OAuthModelCatalogSnapshot
+    stored_at: float
+
+
+class OAuthModelCatalog:
+    """Cache remote discovery behind one thread-safe, failure-tolerant interface."""
+
+    def __init__(
+        self,
+        *,
+        fallback_models: Sequence[OAuthModelInfo],
+        fetch: Callable[[str | None], Sequence[OAuthModelInfo]],
+        fresh_ttl_s: float = 5 * 60,
+        stale_ttl_s: float = 24 * 60 * 60,
+        failure_ttl_s: float = 30,
+        max_entries: int = 8,
+        monotonic: Callable[[], float] = time.monotonic,
+        wall_clock: Callable[[], float] = time.time,
+    ) -> None:
+        if fresh_ttl_s < 0 or stale_ttl_s < fresh_ttl_s or failure_ttl_s < 0:
+            raise ValueError("catalog cache TTLs are invalid")
+        if max_entries < 1:
+            raise ValueError("catalog cache must allow at least one entry")
+        self._fallback_models = tuple(fallback_models)
+        self._fetch = fetch
+        self._fresh_ttl_s = fresh_ttl_s
+        self._stale_ttl_s = stale_ttl_s
+        self._failure_ttl_s = failure_ttl_s
+        self._max_entries = max_entries
+        self._monotonic = monotonic
+        self._wall_clock = wall_clock
+        self._condition = threading.Condition()
+        self._entries: dict[str, _CacheEntry] = {}
+        self._failures: dict[str, float] = {}
+        self._inflight: set[str] = set()
+
+    def get(self, *, cache_key: str, proxy: str | None = None) -> OAuthModelCatalogSnapshot:
+        """Return a fresh catalog, sharing concurrent work and failing to a usable list."""
+        with self._condition:
+            cached = self._cached_result(cache_key)
+            if cached is not None:
+                return cached
+            while cache_key in self._inflight:
+                self._condition.wait()
+                cached = self._cached_result(cache_key)
+                if cached is not None:
+                    return cached
+            self._inflight.add(cache_key)
+
+        try:
+            models = tuple(self._fetch(proxy))
+            if not models:
+                raise ValueError("provider returned an empty model catalog")
+        except Exception as exc:
+            logger.warning(
+                "OAuth model catalog refresh failed: type={}",
+                type(exc).__name__,
+            )
+            result = self._failure_result(cache_key)
+        else:
+            now = self._monotonic()
+            result = OAuthModelCatalogSnapshot(
+                models=models,
+                source="remote",
+                fetched_at=self._wall_clock(),
+            )
+            with self._condition:
+                self._store(cache_key, _CacheEntry(snapshot=result, stored_at=now))
+                self._failures.pop(cache_key, None)
+        finally:
+            with self._condition:
+                self._inflight.discard(cache_key)
+                self._condition.notify_all()
+        return result
+
+    def invalidate(self) -> None:
+        """Drop cached and negative results, for example after account changes."""
+        with self._condition:
+            self._entries.clear()
+            self._failures.clear()
+
+    def _cached_result(self, cache_key: str) -> OAuthModelCatalogSnapshot | None:
+        now = self._monotonic()
+        entry = self._entries.get(cache_key)
+        if entry is not None and now - entry.stored_at < self._fresh_ttl_s:
+            return replace(entry.snapshot, source="cache")
+        failure_until = self._failures.get(cache_key, 0)
+        if failure_until > now:
+            return self._stale_or_fallback(entry, now)
+        return None
+
+    def _failure_result(self, cache_key: str) -> OAuthModelCatalogSnapshot:
+        with self._condition:
+            now = self._monotonic()
+            self._failures[cache_key] = now + self._failure_ttl_s
+            return self._stale_or_fallback(self._entries.get(cache_key), now)
+
+    def _stale_or_fallback(
+        self,
+        entry: _CacheEntry | None,
+        now: float,
+    ) -> OAuthModelCatalogSnapshot:
+        message = "Could not refresh the online model list; showing cached models."
+        if entry is not None and now - entry.stored_at < self._stale_ttl_s:
+            return replace(entry.snapshot, source="stale", message=message)
+        return OAuthModelCatalogSnapshot(
+            models=self._fallback_models,
+            source="fallback",
+            fetched_at=self._wall_clock(),
+            message="Could not load the online model list; showing built-in fallback models.",
+        )
+
+    def _store(self, cache_key: str, entry: _CacheEntry) -> None:
+        if cache_key not in self._entries and len(self._entries) >= self._max_entries:
+            oldest = min(self._entries, key=lambda key: self._entries[key].stored_at)
+            self._entries.pop(oldest, None)
+            self._failures.pop(oldest, None)
+        self._entries[cache_key] = entry
+
+
+_CURATED_XAI_GROK_MODELS = (
+    OAuthModelInfo(
+        id="xai-grok/grok-4.6",
+        label="Grok 4.6",
+        description="Grok via xAI subscription; X Search is enabled when supported.",
+        owned_by="xAI Grok",
+        context_window=500_000,
+    ),
+    OAuthModelInfo(
+        id="xai-grok/grok-4.5",
+        label="Grok 4.5",
+        description="Grok via xAI subscription; X Search is enabled when supported.",
+        owned_by="xAI Grok",
+        context_window=500_000,
+    ),
+)
+
+
+def curated_oauth_models(provider_name: str) -> tuple[OAuthModelInfo, ...]:
+    """Return stable metadata used only to enrich or backstop online discovery."""
+    if provider_name == "xai_grok":
+        return _CURATED_XAI_GROK_MODELS
+    return ()
+
+
+def get_oauth_model_catalog(
+    provider_name: str,
+    *,
+    proxy: str | None = None,
+) -> OAuthModelCatalogSnapshot:
+    """Discover models for a supported OAuth provider."""
+    if provider_name != "xai_grok":
+        raise ValueError(f"OAuth model discovery is not available for {provider_name}")
+    cache_key = f"{_xai_oauth_storage_path()}\0{proxy or ''}"
+    return _XAI_GROK_CATALOG.get(cache_key=cache_key, proxy=proxy)
+
+
+def invalidate_oauth_model_catalog(provider_name: str) -> None:
+    """Invalidate provider discovery after OAuth identity changes."""
+    if provider_name == "xai_grok":
+        _XAI_GROK_CATALOG.invalidate()
+
+
+def _fetch_xai_grok_models(proxy: str | None) -> tuple[OAuthModelInfo, ...]:
+    token = _xai_oauth_token(proxy)
+    client_kwargs: dict[str, Any] = {"timeout": 10.0, "follow_redirects": False}
+    if proxy:
+        client_kwargs.update(proxy=proxy, trust_env=False)
+    with httpx.Client(**client_kwargs) as client:
+        response = client.get(
+            DEFAULT_XAI_GROK_MODELS_URL,
+            headers=_build_xai_model_headers(token),
+        )
+    response.raise_for_status()
+    return _parse_xai_grok_models(response.json())
+
+
+def _parse_xai_grok_models(payload: Any) -> tuple[OAuthModelInfo, ...]:
+    if isinstance(payload, dict):
+        payload_mapping = cast(dict[str, Any], payload)
+        rows: object = payload_mapping.get("data")
+        if not isinstance(rows, list):
+            rows = payload_mapping.get("models")
+    else:
+        rows = payload
+    if not isinstance(rows, list):
+        return ()
+
+    curated = {model.wire_id: model for model in _CURATED_XAI_GROK_MODELS}
+    models: list[OAuthModelInfo] = []
+    seen: set[str] = set()
+    for value in cast(list[object], rows):
+        if not isinstance(value, dict):
+            continue
+        row = cast(dict[str, Any], value)
+        meta_value = row.get("_meta")
+        meta = cast(dict[str, Any], meta_value) if isinstance(meta_value, dict) else {}
+        raw_id = next(
+            (
+                candidate.strip()
+                for candidate in (
+                    row.get("id"),
+                    row.get("model"),
+                    row.get("modelId"),
+                    row.get("name"),
+                    meta.get("id"),
+                    meta.get("model"),
+                    meta.get("modelId"),
+                )
+                if isinstance(candidate, str) and candidate.strip()
+            ),
+            None,
+        )
+        if raw_id is None:
+            continue
+        wire_id = raw_id.split("/", 1)[-1]
+        if wire_id in seen:
+            continue
+        seen.add(wire_id)
+        fallback = curated.get(wire_id)
+        model_id = f"xai-grok/{wire_id}"
+        label = _first_text(row, "display_name", "label", "name") or _first_text(
+            meta,
+            "display_name",
+            "label",
+            "name",
+        )
+        if not label or label == raw_id:
+            label = fallback.label if fallback is not None else wire_id
+        description = _first_text(row, "description") or _first_text(meta, "description")
+        owner = _first_text(row, "owned_by", "owner", "organization") or _first_text(
+            meta,
+            "owned_by",
+            "owner",
+            "organization",
+        )
+        models.append(
+            OAuthModelInfo(
+                id=model_id,
+                label=label,
+                description=(
+                    description
+                    or (fallback.description if fallback is not None else "")
+                ),
+                owned_by=owner or (fallback.owned_by if fallback is not None else "xAI"),
+                context_window=(
+                    _positive_int(row, "context_window", "context_length")
+                    or _positive_int(meta, "context_window", "context_length")
+                    or (fallback.context_window if fallback is not None else None)
+                ),
+                reasoning_efforts=_reasoning_efforts(
+                    row.get("reasoning_efforts", meta.get("reasoning_efforts"))
+                ),
+                supports_backend_search=_bool_field(
+                    row,
+                    "supports_backend_search",
+                    "supportsBackendSearch",
+                ),
+            )
+        )
+    return tuple(models)
+
+
+def _first_text(row: dict[str, Any], *keys: str) -> str:
+    for key in keys:
+        value = row.get(key)
+        if isinstance(value, str) and value.strip():
+            return value.strip()
+    return ""
+
+
+def _positive_int(row: dict[str, Any], *keys: str) -> int | None:
+    for key in keys:
+        value = row.get(key)
+        if isinstance(value, (int, float)) and not isinstance(value, bool) and value > 0:
+            return int(value)
+    return None
+
+
+def _bool_field(row: dict[str, Any], *keys: str) -> bool:
+    for key in keys:
+        value = row.get(key)
+        if isinstance(value, bool):
+            return value
+    meta = row.get("_meta")
+    if isinstance(meta, dict):
+        return _bool_field(cast(dict[str, Any], meta), *keys)
+    return False
+
+
+def _reasoning_efforts(value: Any) -> tuple[str, ...]:
+    if not isinstance(value, list):
+        return ()
+    efforts: list[str] = []
+    for item in cast(list[object], value):
+        if isinstance(item, str):
+            effort = item.strip()
+        elif isinstance(item, dict):
+            effort = _first_text(cast(dict[str, Any], item), "value", "id")
+        else:
+            effort = ""
+        if effort and effort not in efforts:
+            efforts.append(effort)
+    return tuple(efforts)
+
+
+def _xai_oauth_storage_path() -> Path:
+    from nanobot.providers.xai_oauth import get_xai_oauth_storage_path
+
+    return get_xai_oauth_storage_path()
+
+
+def _xai_oauth_token(proxy: str | None) -> _XAIToken:
+    from nanobot.providers.xai_oauth import get_xai_oauth_token
+
+    return get_xai_oauth_token(proxy=proxy)
+
+
+def _build_xai_model_headers(token: _XAIToken) -> dict[str, str]:
+    from nanobot.providers.xai_oauth import XAI_CLIENT_VERSION
+
+    headers = {
+        "Authorization": f"Bearer {token.access}",
+        "X-XAI-Token-Auth": "xai-grok-cli",
+        "x-grok-client-version": XAI_CLIENT_VERSION,
+        "x-grok-client-identifier": "nanobot",
+        "x-grok-client-mode": "headless",
+        "User-Agent": f"nanobot/{__version__} (python)",
+        "accept": "application/json",
+    }
+    claims = _decode_access_token_claims(token.access)
+    user_id = claims.get("sub")
+    if claims.get("principal_type") == "Team":
+        user_id = claims.get("principal_id") or user_id
+    if isinstance(user_id, str) and user_id:
+        headers["x-userid"] = user_id
+    email = claims.get("email")
+    if not isinstance(email, str) or "@" not in email:
+        email = token.account_id if token.account_id and "@" in token.account_id else None
+    if email:
+        headers["x-email"] = email
+    return headers
+
+
+def _decode_access_token_claims(token: str) -> dict[str, Any]:
+    parts = token.split(".")
+    if len(parts) < 2 or not parts[1]:
+        return {}
+    try:
+        decoded = base64.urlsafe_b64decode(parts[1] + "=" * (-len(parts[1]) % 4))
+        claims = json.loads(decoded)
+    except (ValueError, TypeError):
+        return {}
+    return cast(dict[str, Any], claims) if isinstance(claims, dict) else {}
+
+
+_XAI_GROK_CATALOG = OAuthModelCatalog(
+    fallback_models=_CURATED_XAI_GROK_MODELS,
+    fetch=_fetch_xai_grok_models,
+)

nanobot/providers/registry.py

@@ -17,10 +17,12 @@ from typing import Any
 
 from pydantic.alias_generators import to_snake
 
+from nanobot.providers.oauth_model_catalog import curated_oauth_models
+
 
 @dataclass(frozen=True)
 class ProviderModelSpec:
-    """A curated model exposed by providers without a model-list endpoint."""
+    """Curated model metadata used for fixed catalogs or online fallback."""
 
     id: str
     label: str = ""
@@ -42,7 +44,7 @@ class ProviderSpec:
     keywords: tuple[str, ...]  # model-name keywords for matching (lowercase)
     env_key: str  # env var for API key, e.g. "DASHSCOPE_API_KEY"
     display_name: str = ""  # shown in `nanobot status`
-    model_catalog: str = "auto"  # WebUI model-list source
+    model_catalog: str = "auto"  # WebUI model-list source, including builtin/hybrid
     builtin_models: tuple[ProviderModelSpec, ...] = ()
     settings_alias_for: str = ""  # compatibility alias grouped under this provider in Settings
 
@@ -459,20 +461,15 @@ PROVIDERS: tuple[ProviderSpec, ...] = (
         keywords=("xai-grok", "xai_grok"),
         env_key="",
         display_name="xAI Grok",
-        model_catalog="builtin",
+        model_catalog="hybrid",
-        builtin_models=(
+        builtin_models=tuple(
             ProviderModelSpec(
-                id="xai-grok/grok-4.6",
+                id=model.id,
-                label="Grok 4.6",
+                label=model.label,
-                description="Grok via xAI subscription; X Search is enabled when supported.",
+                description=model.description,
-                context_window=500000,
+                context_window=model.context_window,
-            ),
+            )
-            ProviderModelSpec(
+            for model in curated_oauth_models("xai_grok")
-                id="xai-grok/grok-4.5",
-                label="Grok 4.5",
-                description="Grok via xAI subscription; X Search is enabled when supported.",
-                context_window=500000,
-            ),
         ),
         backend="xai_grok",
         default_api_base="https://cli-chat-proxy.grok.com/v1",

nanobot/providers/xai_grok_provider.py

@@ -3,10 +3,8 @@
 from __future__ import annotations
 
 import asyncio
-import base64
 import json
 import re
-import time
 import uuid
 from collections.abc import Awaitable, Callable
 from typing import Any, cast
@@ -22,6 +20,10 @@ from nanobot.providers.base import (
     ToolCallRequest,
     resolve_stream_idle_timeout_s,
 )
+from nanobot.providers.oauth_model_catalog import (
+    DEFAULT_XAI_GROK_MODEL,
+    get_oauth_model_catalog,
+)
 from nanobot.providers.openai_responses import (
     consume_sse_with_reasoning,
     convert_messages,
@@ -29,14 +31,10 @@ from nanobot.providers.openai_responses import (
 )
 from nanobot.providers.xai_oauth import (
     XAI_CLIENT_VERSION,
-    XAIToken,
     get_xai_oauth_token,
 )
 
 DEFAULT_XAI_GROK_URL = "https://cli-chat-proxy.grok.com/v1/responses"
-DEFAULT_XAI_GROK_MODELS_URL = "https://cli-chat-proxy.grok.com/v1/models"
-DEFAULT_XAI_GROK_MODEL = "xai-grok/grok-4.6"
-_MODEL_CAPABILITIES_TTL_S = 5 * 60
 _MAX_ERROR_BODY_CHARS = 1000
 _SENSITIVE_ERROR_KEYS = {
     "accesstoken",
@@ -75,37 +73,20 @@ class XAIGrokProvider(LLMProvider):
         self.default_model = default_model
         self.proxy = proxy or None
         self._extra_body = dict(extra_body or {})
-        self._model_capabilities: dict[str, bool] | None = None
-        self._model_capabilities_fetched_at = 0.0
 
-    async def _supports_backend_search(self, token: XAIToken, model: str) -> bool:
+    async def _supports_backend_search(self, model: str) -> bool:
-        now = time.monotonic()
+        catalog = await asyncio.to_thread(
-        capabilities = self._model_capabilities
+            get_oauth_model_catalog,
-        if (
+            "xai_grok",
-            capabilities is None
+            proxy=self.proxy,
-            or now - self._model_capabilities_fetched_at >= _MODEL_CAPABILITIES_TTL_S
+        )
-        ):
+        if catalog.message:
-            try:
+            logger.warning(
-                capabilities = await _fetch_xai_model_capabilities(
+                "xAI model catalog unavailable; hosted X Search disabled unless cached: {}",
-                    DEFAULT_XAI_GROK_MODELS_URL,
+                catalog.message,
-                    _build_model_headers(token),
+            )
-                    proxy=self.proxy,
+        info = catalog.find(model)
-                )
+        return bool(info and info.supports_backend_search)
-            except Exception as exc:
-                logger.warning(
-                    "xAI model capability lookup failed; hosted X Search disabled for model {}: "
-                    "type={} error={}",
-                    model,
-                    type(exc).__name__,
-                    str(exc).strip() or "unexpected error",
-                )
-                capabilities = {}
-                self._model_capabilities = capabilities
-                self._model_capabilities_fetched_at = now
-            else:
-                self._model_capabilities = capabilities
-                self._model_capabilities_fetched_at = now
-        return capabilities.get(model, False)
 
     async def _call_xai(
         self,
@@ -138,7 +119,7 @@ class XAIGrokProvider(LLMProvider):
             supports_backend_search = False
             if not tools_are_explicit:
                 stage = "model_capabilities"
-                supports_backend_search = await self._supports_backend_search(token, wire_model)
+                supports_backend_search = await self._supports_backend_search(wire_model)
             converted_tools = convert_tools(tools or [])
             if isinstance(configured_tools, list):
                 converted_tools.extend(cast(list[dict[str, Any]], configured_tools))
@@ -308,44 +289,6 @@ def _build_headers(token: str, model: str) -> dict[str, str]:
     }
 
 
-def _build_model_headers(token: XAIToken) -> dict[str, str]:
-    headers = {
-        "Authorization": f"Bearer {token.access}",
-        "X-XAI-Token-Auth": "xai-grok-cli",
-        "x-grok-client-version": XAI_CLIENT_VERSION,
-        "x-grok-client-identifier": "nanobot",
-        "x-grok-client-mode": "headless",
-        "User-Agent": f"nanobot/{__version__} (python)",
-        "accept": "application/json",
-    }
-    claims = _decode_access_token_claims(token.access)
-    user_id = claims.get("sub")
-    if claims.get("principal_type") == "Team":
-        user_id = claims.get("principal_id") or user_id
-    if isinstance(user_id, str) and user_id:
-        headers["x-userid"] = user_id
-    email = claims.get("email")
-    if not isinstance(email, str) or "@" not in email:
-        email = token.account_id if token.account_id and "@" in token.account_id else None
-    if email:
-        headers["x-email"] = email
-    return headers
-
-
-def _decode_access_token_claims(token: str) -> dict[str, Any]:
-    """Read identity hints from the signed token; the server still authenticates it."""
-    parts = token.split(".")
-    if len(parts) < 2 or not parts[1]:
-        return {}
-    payload = parts[1]
-    try:
-        decoded = base64.urlsafe_b64decode(payload + "=" * (-len(payload) % 4))
-        claims = json.loads(decoded)
-    except (ValueError, TypeError):
-        return {}
-    return cast(dict[str, Any], claims) if isinstance(claims, dict) else {}
-
-
 class _XAIHTTPError(RuntimeError):
     def __init__(
         self,
@@ -367,67 +310,6 @@ class _XAIHTTPError(RuntimeError):
         self.response_body = response_body
 
 
-async def _fetch_xai_model_capabilities(
-    url: str,
-    headers: dict[str, str],
-    *,
-    proxy: str | None = None,
-) -> dict[str, bool]:
-    client_kwargs: dict[str, Any] = {"timeout": 10.0, "follow_redirects": False}
-    if proxy:
-        client_kwargs.update(proxy=proxy, trust_env=False)
-    async with httpx.AsyncClient(**client_kwargs) as client:
-        response = await client.get(url, headers=headers)
-    if response.status_code != 200:
-        raw = response.content.decode("utf-8", "ignore")
-        raise _build_xai_http_error(response.status_code, response.headers, raw)
-    try:
-        payload = response.json()
-    except ValueError as exc:
-        raise RuntimeError("xAI model catalog returned invalid JSON.") from exc
-    return _parse_xai_model_capabilities(payload)
-
-
-def _parse_xai_model_capabilities(payload: Any) -> dict[str, bool]:
-    if isinstance(payload, dict):
-        payload = cast(dict[str, Any], payload)
-        rows: object = payload.get("data")
-        if not isinstance(rows, list):
-            rows = payload.get("models")
-    else:
-        rows = payload
-    if not isinstance(rows, list):
-        return {}
-
-    capabilities: dict[str, bool] = {}
-    for row_value in cast(list[object], rows):
-        if not isinstance(row_value, dict):
-            continue
-        row = cast(dict[str, Any], row_value)
-        meta_value = row.get("_meta")
-        meta = cast(dict[str, Any], meta_value) if isinstance(meta_value, dict) else {}
-        support_value = row.get("supportsBackendSearch")
-        if not isinstance(support_value, bool):
-            support_value = row.get("supports_backend_search")
-        if not isinstance(support_value, bool):
-            support_value = meta.get("supportsBackendSearch")
-        if not isinstance(support_value, bool):
-            support_value = meta.get("supports_backend_search")
-        supports_backend_search = support_value if isinstance(support_value, bool) else False
-
-        identifiers = (
-            row.get("model"),
-            row.get("modelId"),
-            row.get("id"),
-            meta.get("model"),
-            meta.get("modelId"),
-        )
-        for identifier in identifiers:
-            if isinstance(identifier, str) and identifier.strip():
-                capabilities[_strip_model_prefix(identifier.strip())] = supports_backend_search
-    return capabilities
-
-
 async def _request_xai(
     url: str,
     headers: dict[str, str],

nanobot/webui/settings_models.py

@@ -28,6 +28,10 @@ from nanobot.config.loader import resolve_config_env_vars
 from nanobot.config.schema import Config, FallbackCandidate, ModelPresetConfig, ProviderConfig
 from nanobot.providers.image_generation import get_image_gen_provider
 from nanobot.providers.oauth_guidance import OAUTH_CLI_KIT_MISSING_MESSAGE
+from nanobot.providers.oauth_model_catalog import (
+    get_oauth_model_catalog,
+    invalidate_oauth_model_catalog,
+)
 from nanobot.providers.registry import PROVIDERS, create_dynamic_spec, find_by_name
 from nanobot.webui.settings_contracts import (
     QueryParams,
@@ -661,6 +665,30 @@ def provider_models_payload(
             "models": rows,
             "model_count": len(rows),
         }
+    if catalog_kind == "hybrid":
+        proxy = _resolve_env_placeholders(provider_config.proxy)
+        catalog = get_oauth_model_catalog(spec.name, proxy=proxy)
+        rows = [
+            {
+                "id": model.id,
+                "label": model.label or None,
+                "description": model.description or None,
+                "owned_by": model.owned_by or spec.label,
+                "context_window": model.context_window,
+                "reasoning_efforts": list(model.reasoning_efforts),
+                "supports_backend_search": model.supports_backend_search,
+            }
+            for model in catalog.models
+        ]
+        return {
+            **base_payload,
+            "status": "available",
+            "source": catalog.source,
+            "models": rows,
+            "model_count": len(rows),
+            "message": catalog.message,
+            "fetched_at": catalog.fetched_at,
+        }
 
     api_base = _resolve_env_placeholders(provider_config.api_base) or spec.default_api_base
     if spec.name == "openai" and not api_base:
@@ -1591,6 +1619,7 @@ def complete_oauth_provider(
     oauth_flows.remove(spec.name, flow_id, flow, cancel=False)
     if not token.access:
         raise WebUISettingsError("OAuth login failed", status=401)
+    invalidate_oauth_model_catalog(spec.name)
     return settings_payload(config_path=config_path)
 
 
@@ -1629,6 +1658,7 @@ def logout_oauth_provider(
 
         oauth_flows.clear(spec.name)
         logout_xai_oauth()
+        invalidate_oauth_model_catalog(spec.name)
         return settings_payload(config_path=config_path)
     else:
         raise WebUISettingsError("OAuth logout is not supported for this provider")

tests/providers/test_oauth_model_catalog.py

@@ -0,0 +1,257 @@
+from __future__ import annotations
+
+import base64
+import json
+import threading
+import time
+from concurrent.futures import ThreadPoolExecutor
+from pathlib import Path
+
+import httpx
+import pytest
+
+from nanobot.providers.oauth_model_catalog import (
+    DEFAULT_XAI_GROK_MODELS_URL,
+    OAuthModelCatalog,
+    OAuthModelInfo,
+    get_oauth_model_catalog,
+    invalidate_oauth_model_catalog,
+)
+from nanobot.providers.xai_oauth import XAIToken
+
+
+@pytest.fixture(autouse=True)
+def _clear_xai_catalog() -> None:
+    invalidate_oauth_model_catalog("xai_grok")
+    yield
+    invalidate_oauth_model_catalog("xai_grok")
+
+
+def _fallback_model() -> OAuthModelInfo:
+    return OAuthModelInfo(id="provider/fallback", label="Fallback")
+
+
+def test_xai_catalog_fetches_remote_models_and_reuses_capability_metadata(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    original_client = httpx.Client
+    captured: dict[str, object] = {}
+    payload = base64.urlsafe_b64encode(
+        json.dumps({"sub": "user-42", "email": "user@example.com"}).encode()
+    ).decode().rstrip("=")
+    token = XAIToken(
+        access=f"header.{payload}.signature",
+        refresh="refresh-token",
+        expires=int(time.time() * 1000) + 3_600_000,
+        account_id="user@example.com",
+    )
+
+    def handler(request: httpx.Request) -> httpx.Response:
+        captured["request"] = request
+        return httpx.Response(
+            200,
+            json={
+                "data": [
+                    {
+                        "id": "grok-4.6",
+                        "name": "Grok 4.6",
+                        "description": "Latest frontier model",
+                        "owned_by": "xAI",
+                        "context_window": 500_000,
+                        "supports_backend_search": True,
+                        "reasoning_efforts": [
+                            {"value": "xhigh"},
+                            {"value": "high"},
+                            {"value": "low"},
+                        ],
+                    },
+                    {
+                        "id": "grok-next",
+                        "_meta": {
+                            "name": "Grok Next",
+                            "context_window": 750_000,
+                            "reasoning_efforts": ["high", "low"],
+                        },
+                    },
+                ]
+            },
+            request=request,
+        )
+
+    def fake_client(**kwargs: object) -> httpx.Client:
+        captured["kwargs"] = kwargs
+        return original_client(
+            transport=httpx.MockTransport(handler),
+            timeout=kwargs["timeout"],
+            follow_redirects=kwargs["follow_redirects"],
+        )
+
+    monkeypatch.setattr(
+        "nanobot.providers.oauth_model_catalog._xai_oauth_storage_path",
+        lambda: tmp_path / "auth" / "xai.json",
+    )
+    monkeypatch.setattr(
+        "nanobot.providers.oauth_model_catalog._xai_oauth_token",
+        lambda _proxy: token,
+    )
+    monkeypatch.setattr("nanobot.providers.oauth_model_catalog.httpx.Client", fake_client)
+
+    catalog = get_oauth_model_catalog("xai_grok")
+
+    assert catalog.source == "remote"
+    assert [model.id for model in catalog.models] == [
+        "xai-grok/grok-4.6",
+        "xai-grok/grok-next",
+    ]
+    grok = catalog.find("grok-4.6")
+    assert grok is not None
+    assert grok.description == "Latest frontier model"
+    assert grok.context_window == 500_000
+    assert grok.reasoning_efforts == ("xhigh", "high", "low")
+    assert grok.supports_backend_search is True
+    next_model = catalog.find("xai-grok/grok-next")
+    assert next_model is not None
+    assert next_model.label == "Grok Next"
+    assert next_model.context_window == 750_000
+    assert next_model.reasoning_efforts == ("high", "low")
+
+    request = captured["request"]
+    assert isinstance(request, httpx.Request)
+    assert str(request.url) == DEFAULT_XAI_GROK_MODELS_URL
+    assert request.headers["Authorization"] == f"Bearer {token.access}"
+    assert request.headers["X-XAI-Token-Auth"] == "xai-grok-cli"
+    assert request.headers["x-userid"] == "user-42"
+    assert request.headers["x-email"] == "user@example.com"
+    assert captured["kwargs"] == {"timeout": 10.0, "follow_redirects": False}
+    assert get_oauth_model_catalog("xai_grok").source == "cache"
+
+
+def test_catalog_single_flights_concurrent_refreshes() -> None:
+    calls = 0
+    calls_lock = threading.Lock()
+    barrier = threading.Barrier(8)
+
+    def fetch(_proxy: str | None) -> tuple[OAuthModelInfo, ...]:
+        nonlocal calls
+        with calls_lock:
+            calls += 1
+        time.sleep(0.05)
+        return (OAuthModelInfo(id="provider/remote", label="Remote"),)
+
+    catalog = OAuthModelCatalog(fallback_models=(_fallback_model(),), fetch=fetch)
+
+    def get_catalog(_index: int):
+        barrier.wait()
+        return catalog.get(cache_key="shared")
+
+    with ThreadPoolExecutor(max_workers=8) as pool:
+        results = list(pool.map(get_catalog, range(8)))
+
+    assert calls == 1
+    assert {result.models[0].id for result in results} == {"provider/remote"}
+    assert [result.source for result in results].count("remote") == 1
+    assert [result.source for result in results].count("cache") == 7
+
+
+def test_catalog_returns_stale_then_negative_caches_refresh_failure() -> None:
+    now = [0.0]
+    calls = 0
+
+    def fetch(_proxy: str | None) -> tuple[OAuthModelInfo, ...]:
+        nonlocal calls
+        calls += 1
+        if calls > 1:
+            raise httpx.ConnectError("offline")
+        return (OAuthModelInfo(id="provider/remote", label="Remote"),)
+
+    catalog = OAuthModelCatalog(
+        fallback_models=(_fallback_model(),),
+        fetch=fetch,
+        fresh_ttl_s=10,
+        stale_ttl_s=100,
+        failure_ttl_s=30,
+        monotonic=lambda: now[0],
+        wall_clock=lambda: 123.0,
+    )
+
+    assert catalog.get(cache_key="one").source == "remote"
+    now[0] = 11
+    stale = catalog.get(cache_key="one")
+    assert stale.source == "stale"
+    assert stale.models[0].id == "provider/remote"
+    assert catalog.get(cache_key="one").source == "stale"
+    assert calls == 2
+
+    now[0] = 101
+    fallback = catalog.get(cache_key="one")
+    assert fallback.source == "fallback"
+    assert fallback.models[0].id == "provider/fallback"
+    assert calls == 3
+
+
+@pytest.mark.parametrize(
+    "failure",
+    [
+        httpx.ConnectError("offline"),
+        ValueError("invalid JSON"),
+        httpx.HTTPStatusError(
+            "unauthorized",
+            request=httpx.Request("GET", DEFAULT_XAI_GROK_MODELS_URL),
+            response=httpx.Response(401),
+        ),
+        httpx.HTTPStatusError(
+            "rate limited",
+            request=httpx.Request("GET", DEFAULT_XAI_GROK_MODELS_URL),
+            response=httpx.Response(429),
+        ),
+        httpx.HTTPStatusError(
+            "upstream failure",
+            request=httpx.Request("GET", DEFAULT_XAI_GROK_MODELS_URL),
+            response=httpx.Response(503),
+        ),
+    ],
+)
+def test_catalog_falls_back_for_remote_failures(failure: Exception) -> None:
+    calls = 0
+
+    def fetch(_proxy: str | None) -> tuple[OAuthModelInfo, ...]:
+        nonlocal calls
+        calls += 1
+        raise failure
+
+    catalog = OAuthModelCatalog(
+        fallback_models=(_fallback_model(),),
+        fetch=fetch,
+        failure_ttl_s=30,
+    )
+
+    first = catalog.get(cache_key="one")
+    second = catalog.get(cache_key="one")
+
+    assert first.source == "fallback"
+    assert second.source == "fallback"
+    assert first.models == (_fallback_model(),)
+    assert calls == 1
+
+
+def test_catalog_treats_empty_remote_list_as_failure_and_can_be_invalidated() -> None:
+    calls = 0
+
+    def fetch(_proxy: str | None) -> tuple[OAuthModelInfo, ...]:
+        nonlocal calls
+        calls += 1
+        return () if calls == 1 else (OAuthModelInfo(id="provider/new", label="New"),)
+
+    catalog = OAuthModelCatalog(
+        fallback_models=(_fallback_model(),),
+        fetch=fetch,
+        failure_ttl_s=30,
+    )
+
+    assert catalog.get(cache_key="one").source == "fallback"
+    catalog.invalidate()
+    refreshed = catalog.get(cache_key="one")
+    assert refreshed.source == "remote"
+    assert refreshed.models[0].id == "provider/new"
+    assert calls == 2

tests/providers/test_xai_grok_provider.py

@@ -1,6 +1,5 @@
 from __future__ import annotations
 
-import base64
 import json
 import time
 from types import SimpleNamespace
@@ -12,18 +11,15 @@ import pytest
 from nanobot.config.schema import Config
 from nanobot.providers.base import LLMUsage
 from nanobot.providers.factory import make_provider
+from nanobot.providers.oauth_model_catalog import OAuthModelCatalogSnapshot, OAuthModelInfo
 from nanobot.providers.registry import find_by_name
 from nanobot.providers.xai_grok_provider import (
     DEFAULT_XAI_GROK_MODEL,
-    DEFAULT_XAI_GROK_MODELS_URL,
     XAIGrokProvider,
     _bounded_error_body,
     _build_headers,
-    _build_model_headers,
     _build_reasoning_options,
     _build_xai_http_error,
-    _fetch_xai_model_capabilities,
-    _parse_xai_model_capabilities,
     _request_xai,
     _xai_error_response,
     _XAIHTTPError,
@@ -51,15 +47,27 @@ def _mock_model_capabilities(
     *,
     supports_backend_search: bool,
 ) -> None:
-    async def fake_fetch(*_args, **_kwargs):
+    def fake_catalog(*_args, **_kwargs):
-        return {
+        return OAuthModelCatalogSnapshot(
-            "grok-4.5": supports_backend_search,
+            models=(
-            "grok-4.6": supports_backend_search,
+                OAuthModelInfo(
-        }
+                    id="xai-grok/grok-4.5",
+                    label="Grok 4.5",
+                    supports_backend_search=supports_backend_search,
+                ),
+                OAuthModelInfo(
+                    id="xai-grok/grok-4.6",
+                    label="Grok 4.6",
+                    supports_backend_search=supports_backend_search,
+                ),
+            ),
+            source="remote",
+            fetched_at=1,
+        )
 
     monkeypatch.setattr(
-        "nanobot.providers.xai_grok_provider._fetch_xai_model_capabilities",
+        "nanobot.providers.xai_grok_provider.get_oauth_model_catalog",
-        fake_fetch,
+        fake_catalog,
     )
 
 
@@ -154,7 +162,7 @@ async def test_explicit_parameterized_x_search_is_preserved_without_catalog_look
     _mock_token(monkeypatch)
     bodies: list[dict[str, Any]] = []
 
-    async def unexpected_catalog_lookup(*_args, **_kwargs):
+    def unexpected_catalog_lookup(*_args, **_kwargs):
         raise AssertionError("explicit raw tools must not depend on model catalog metadata")
 
     async def fake_request(_url, _headers, body, **_kwargs):
@@ -162,7 +170,7 @@ async def test_explicit_parameterized_x_search_is_preserved_without_catalog_look
         return "ok", [], "stop", {}, None
 
     monkeypatch.setattr(
-        "nanobot.providers.xai_grok_provider._fetch_xai_model_capabilities",
+        "nanobot.providers.xai_grok_provider.get_oauth_model_catalog",
         unexpected_catalog_lookup,
     )
     monkeypatch.setattr("nanobot.providers.xai_grok_provider._request_xai", fake_request)
@@ -217,7 +225,7 @@ async def test_explicit_empty_tools_disables_catalog_lookup_and_hosted_tool(monk
     _mock_token(monkeypatch)
     bodies: list[dict[str, Any]] = []
 
-    async def unexpected_catalog_lookup(*_args, **_kwargs):
+    def unexpected_catalog_lookup(*_args, **_kwargs):
         raise AssertionError("explicitly disabled X Search must not fetch model capabilities")
 
     async def fake_request(_url, _headers, body, **_kwargs):
@@ -225,7 +233,7 @@ async def test_explicit_empty_tools_disables_catalog_lookup_and_hosted_tool(monk
         return "ok", [], "stop", {}, None
 
     monkeypatch.setattr(
-        "nanobot.providers.xai_grok_provider._fetch_xai_model_capabilities",
+        "nanobot.providers.xai_grok_provider.get_oauth_model_catalog",
         unexpected_catalog_lookup,
     )
     monkeypatch.setattr("nanobot.providers.xai_grok_provider._request_xai", fake_request)
@@ -290,35 +298,6 @@ async def test_provider_keeps_local_x_search_when_model_does_not_support_hosted_
     ]
 
 
-@pytest.mark.asyncio
-async def test_provider_fails_closed_and_caches_model_catalog_failure(monkeypatch) -> None:
-    _mock_token(monkeypatch)
-    fetch_calls = 0
-    bodies: list[dict[str, Any]] = []
-
-    async def failing_fetch(*_args, **_kwargs):
-        nonlocal fetch_calls
-        fetch_calls += 1
-        raise httpx.ConnectError("catalog unavailable")
-
-    async def fake_request(_url, _headers, body, **_kwargs):
-        bodies.append(body)
-        return "ok", [], "stop", {}, None
-
-    monkeypatch.setattr(
-        "nanobot.providers.xai_grok_provider._fetch_xai_model_capabilities",
-        failing_fetch,
-    )
-    monkeypatch.setattr("nanobot.providers.xai_grok_provider._request_xai", fake_request)
-    provider = XAIGrokProvider()
-
-    await provider.chat([{"role": "user", "content": "first"}])
-    await provider.chat([{"role": "user", "content": "second"}])
-
-    assert fetch_calls == 1
-    assert all({"type": "x_search"} not in body["tools"] for body in bodies)
-
-
 @pytest.mark.asyncio
 async def test_provider_refreshes_and_retries_exactly_once_after_401(monkeypatch) -> None:
     _mock_model_capabilities(monkeypatch, supports_backend_search=False)
@@ -534,77 +513,6 @@ async def test_raw_response_request_streams_hosted_x_search_lifecycle(monkeypatc
     assert "large hosted result" not in json.dumps(tool_events)
 
 
-def test_model_capabilities_follow_upstream_aliases_and_default_to_disabled() -> None:
-    capabilities = _parse_xai_model_capabilities(
-        {
-            "data": [
-                {"id": "grok-4.5", "supportsBackendSearch": False},
-                {
-                    "model": "grok-search",
-                    "supports_backend_search": True,
-                },
-                {
-                    "modelId": "grok-meta",
-                    "_meta": {"supportsBackendSearch": True},
-                },
-                {"id": "grok-unknown"},
-            ]
-        }
-    )
-
-    assert capabilities == {
-        "grok-4.5": False,
-        "grok-search": True,
-        "grok-meta": True,
-        "grok-unknown": False,
-    }
-
-
-@pytest.mark.asyncio
-async def test_model_capability_request_uses_subscription_headers(monkeypatch) -> None:
-    original_client = httpx.AsyncClient
-    captured: dict[str, Any] = {}
-
-    def handler(request: httpx.Request) -> httpx.Response:
-        captured["request"] = request
-        return httpx.Response(
-            200,
-            json={"data": [{"id": "grok-search", "supportsBackendSearch": True}]},
-            request=request,
-        )
-
-    def fake_client(**kwargs) -> httpx.AsyncClient:
-        captured["kwargs"] = kwargs
-        return original_client(
-            transport=httpx.MockTransport(handler),
-            timeout=kwargs["timeout"],
-            follow_redirects=kwargs["follow_redirects"],
-        )
-
-    monkeypatch.setattr("nanobot.providers.xai_grok_provider.httpx.AsyncClient", fake_client)
-    payload = base64.urlsafe_b64encode(
-        json.dumps({"sub": "user-42", "email": "user@example.com"}).encode()
-    ).decode().rstrip("=")
-    access_token = f"header.{payload}.signature"
-    headers = _build_model_headers(_token(access_token))
-
-    capabilities = await _fetch_xai_model_capabilities(
-        DEFAULT_XAI_GROK_MODELS_URL,
-        headers,
-    )
-
-    request = captured["request"]
-    assert isinstance(request, httpx.Request)
-    assert request.method == "GET"
-    assert str(request.url) == DEFAULT_XAI_GROK_MODELS_URL
-    assert request.headers["Authorization"] == f"Bearer {access_token}"
-    assert request.headers["X-XAI-Token-Auth"] == "xai-grok-cli"
-    assert request.headers["x-userid"] == "user-42"
-    assert request.headers["x-email"] == "user@example.com"
-    assert captured["kwargs"] == {"timeout": 10.0, "follow_redirects": False}
-    assert capabilities == {"grok-search": True}
-
-
 @pytest.mark.asyncio
 async def test_raw_response_error_preserves_bounded_redacted_body(monkeypatch) -> None:
     original_client = httpx.AsyncClient

tests/webui/test_settings_api.py

@@ -13,6 +13,7 @@ from nanobot.config.schema import Config, InlineFallbackConfig, ModelPresetConfi
 from nanobot.llm_usage import get_llm_usage_store
 from nanobot.llm_usage.models import LLMCallRecord
 from nanobot.providers.base import LLMUsage
+from nanobot.providers.oauth_model_catalog import OAuthModelCatalogSnapshot, OAuthModelInfo
 from nanobot.providers.registry import find_by_name
 from nanobot.session.manager import SessionManager
 from nanobot.session.model_selection import SESSION_MODEL_PRESET_METADATA_KEY
@@ -2015,25 +2016,60 @@ def test_provider_models_payload_returns_curated_openai_codex_models() -> None:
     ]
 
 
-def test_provider_models_payload_returns_xai_grok_models() -> None:
+def test_provider_models_payload_returns_online_xai_grok_models(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    monkeypatch.setattr(
+        "nanobot.webui.settings_models.get_oauth_model_catalog",
+        lambda *_args, **_kwargs: OAuthModelCatalogSnapshot(
+            models=(
+                OAuthModelInfo(
+                    id="xai-grok/grok-4.6",
+                    label="Grok 4.6",
+                    description="Latest frontier model",
+                    owned_by="xAI",
+                    context_window=500_000,
+                    reasoning_efforts=("xhigh", "high", "medium", "low"),
+                    supports_backend_search=True,
+                ),
+                OAuthModelInfo(
+                    id="xai-grok/grok-4.5",
+                    label="Grok 4.5",
+                    owned_by="xAI",
+                    context_window=500_000,
+                    reasoning_efforts=("high", "medium", "low"),
+                    supports_backend_search=True,
+                ),
+            ),
+            source="remote",
+            fetched_at=123,
+        ),
+    )
+
     payload = provider_models_payload({"provider": ["xai_grok"]})
 
     assert payload["status"] == "available"
-    assert payload["catalog_kind"] == "builtin"
+    assert payload["catalog_kind"] == "hybrid"
+    assert payload["source"] == "remote"
+    assert payload["fetched_at"] == 123
     assert payload["models"] == [
         {
             "id": "xai-grok/grok-4.6",
             "label": "Grok 4.6",
-            "description": "Grok via xAI subscription; X Search is enabled when supported.",
+            "description": "Latest frontier model",
-            "owned_by": "xAI Grok",
+            "owned_by": "xAI",
             "context_window": 500000,
+            "reasoning_efforts": ["xhigh", "high", "medium", "low"],
+            "supports_backend_search": True,
         },
         {
             "id": "xai-grok/grok-4.5",
             "label": "Grok 4.5",
-            "description": "Grok via xAI subscription; X Search is enabled when supported.",
+            "description": None,
-            "owned_by": "xAI Grok",
+            "owned_by": "xAI",
             "context_window": 500000,
+            "reasoning_efforts": ["high", "medium", "low"],
+            "supports_backend_search": True,
         }
     ]
 
@@ -2168,6 +2204,7 @@ def test_model_catalog_kind_uses_provider_spec_metadata() -> None:
     assert _model_catalog_kind(find_by_name("openrouter")) == "catalog"
     assert _model_catalog_kind(find_by_name("orcarouter")) == "catalog"
     assert _model_catalog_kind(find_by_name("openai_codex")) == "builtin"
+    assert _model_catalog_kind(find_by_name("xai_grok")) == "hybrid"
 
 
 def test_create_model_configuration_accepts_configured_oauth_provider(

webui/src/components/settings/shared/ModelControls.tsx

@@ -204,13 +204,15 @@ export function ModelIdPicker({
   const providerConfigured = settingsProviderConfigured(settings, effectiveProvider);
   const providerRequiresConfiguration =
     !hasStaticModels && hasConcreteProvider && !providerConfigured;
-  const providerHasBuiltinModels = providerRow?.model_catalog === "builtin";
+  const providerHasManagedModels = ["builtin", "hybrid"].includes(
+    providerRow?.model_catalog ?? "",
+  );
   const providerUsesManualModelIds =
     !hasStaticModels &&
     hasConcreteProvider &&
     providerConfigured &&
     providerRow?.auth_type === "oauth" &&
-    !providerHasBuiltinModels;
+    !providerHasManagedModels;
   const canFetchModels =
     !hasStaticModels &&
     hasConcreteProvider && providerConfigured && !providerUsesManualModelIds;

webui/src/lib/types.ts

@@ -510,6 +510,8 @@ interface ProviderModelInfo {
   description?: string | null;
   owned_by?: string | null;
   context_window?: number | null;
+  reasoning_efforts?: string[];
+  supports_backend_search?: boolean;
 }
 
 export interface ProviderModelsPayload {
@@ -521,7 +523,15 @@ export interface ProviderModelsPayload {
     | "not_configured"
     | "missing_api_base"
     | "error";
-  catalog_kind: "builtin" | "official" | "catalog" | "local" | "custom" | "unsupported";
+  catalog_kind:
+    | "builtin"
+    | "hybrid"
+    | "official"
+    | "catalog"
+    | "local"
+    | "custom"
+    | "unsupported";
+  source?: "remote" | "cache" | "stale" | "fallback";
   models: ProviderModelInfo[];
   model_count: number;
   message?: string | null;

webui/src/tests/settings-models.test.tsx

@@ -1295,6 +1295,88 @@ describe("Settings models", () => {
     );
   });
 
+  it("loads hybrid online models for configured OAuth providers", async () => {
+    const base = settingsPayload();
+    const payload: SettingsPayload = {
+      ...base,
+      agent: {
+        ...base.agent,
+        model: "xai-grok/grok-4.5",
+        provider: "xai_grok",
+        resolved_provider: "xai_grok",
+      },
+      model_presets: [
+        {
+          ...base.model_presets[0],
+          model: "xai-grok/grok-4.5",
+          provider: "xai_grok",
+        },
+      ],
+      providers: [
+        {
+          name: "xai_grok",
+          label: "xAI Grok",
+          configured: true,
+          auth_type: "oauth",
+          api_key_required: false,
+          api_key_hint: null,
+          api_base: null,
+          default_api_base: "https://cli-chat-proxy.grok.com/v1",
+          model_catalog: "hybrid",
+          oauth_account: "acct-test",
+          oauth_expires_at: null,
+          oauth_login_supported: true,
+        },
+      ],
+    };
+    const fetchMock = vi.fn(async (input: RequestInfo | URL) => {
+      const url = String(input);
+      if (url === "/api/settings/provider-models?provider=xai_grok") {
+        return jsonResponse({
+          provider: "xai_grok",
+          label: "xAI Grok",
+          status: "available",
+          catalog_kind: "hybrid",
+          source: "remote",
+          models: [
+            {
+              id: "xai-grok/grok-4.6",
+              label: "Grok 4.6",
+              description: "Latest frontier model",
+              owned_by: "xAI",
+              context_window: 500_000,
+            },
+            {
+              id: "xai-grok/grok-4.5",
+              label: "Grok 4.5",
+              owned_by: "xAI",
+              context_window: 500_000,
+            },
+          ],
+          model_count: 2,
+          fetched_at: 1,
+        });
+      }
+      return { ok: false, status: 404, json: async () => ({}) } as Response;
+    });
+    vi.stubGlobal("fetch", fetchMock);
+
+    renderSettingsView({ initialSection: "models", initialSettings: payload });
+
+    await togglePresetEditor();
+    const modelButtons = await screen.findAllByRole("button", {
+      name: /xai-grok\/grok-4\.5/i,
+    });
+    await openPopover(modelButtons[modelButtons.length - 1]);
+
+    expect(await screen.findByText("Grok 4.6")).toBeInTheDocument();
+    expect(screen.getByText(/Latest frontier model/)).toBeInTheDocument();
+    expect(fetchMock).toHaveBeenCalledWith(
+      "/api/settings/provider-models?provider=xai_grok",
+      expect.objectContaining({ headers: { Authorization: "Bearer tok" } }),
+    );
+  });
+
   it("creates presets in the inline editor and can cancel without opening a dialog", async () => {
     vi.stubGlobal(
       "fetch",