feat: ask for the model on the first screen of the endpoint flow

The model field was one screen too late. Reported directly: "this is where
I would have expected to see the model dropdown", on the AI Task init step
that showed only Name and the recommended checkbox.

- CONF_CHAT_MODEL moves from async_step_additional to async_step_init for
  conversation and ai_task_data, so all four endpoint types now ask on the
  first screen. stt and tts already did.
- UNSUPPORTED_MODELS is validated there too, since the recommended path
  creates the subentry from that step and would otherwise skip the check.
- model_list.default_model() picks what to preselect: RECOMMENDED_CHAT_MODEL
  only when the provider actually serves it (or discovery returned nothing),
  otherwise the first advertised model. Offering a stranger's gpt-4o-mini to
  a LiteLLM user preselects a model that fails on first use.

This is the trade I got wrong last commit. I kept the field on the second
step to avoid touching 71 ported tests, having judged them unfixable
mechanically. They were not: the 71 were ~13 functions under parametrize,
and test_subentry_switching's data is already a list of per-step dicts, so
moving a model between steps is moving a key between two dicts. Two scripted
passes moved 14 of them; 5 needed reasoning about (an error that now surfaces
on init rather than the next step, and four cases whose expected data gains
the now-always-recorded model).

async_fetch_model_ids now also catches non-OpenAIError exceptions. Found via
a ported test whose client is a MagicMock: the TypeError from awaiting it
escaped and broke the whole form. A real proxy returning a payload the SDK
cannot parse would do the same, and this runs inside a dialog with a working
free-text fallback, so nothing it raises justifies taking the form down.

Also fixes a string that was simply false on a third-party provider, again
reported from the UI: "Store requests and responses in OpenAI" / "stored by
OpenAI and visible in your OpenAI dashboard logs". It now describes the
Responses API store flag and says support varies. Swept the other 43
OpenAI-mentioning strings while there -- the rest are [%key:...%]
self-references or this fork's own action names, and no other option text
makes a claim about who stores the data.

Local: 170 passed.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01NxJYWgGJtCw13qUHZtG8ki

custom_components/openai_compatible/model_list.py

@@ -22,7 +22,7 @@ from homeassistant.helpers.selector import (
     SelectSelectorMode,
 )
 
-from .const import LOGGER
+from .const import LOGGER, RECOMMENDED_CHAT_MODEL
 
 DEFAULT_TIMEOUT = 10.0
 
@@ -48,6 +48,14 @@ async def async_fetch_model_ids(
     except openai.OpenAIError as err:
         LOGGER.debug("Could not list models: %s", err)
         return []
+    except Exception:  # noqa: BLE001 - see below
+        # Deliberately broad. This runs inside a config-flow form and has a
+        # working fallback (a free-text model field), so nothing it can raise
+        # justifies taking the dialog down: a proxy may return a payload the
+        # SDK cannot parse, and the failure modes of arbitrary
+        # OpenAI-compatible servers are not enumerable in advance.
+        LOGGER.debug("Unexpected error listing models", exc_info=True)
+        return []
 
     return sorted({model.id for model in page.data if getattr(model, "id", None)})
 
@@ -71,3 +79,17 @@ def model_field(model_ids: list[str]) -> Any:
             sort=True,
         )
     )
+
+
+def default_model(model_ids: list[str]) -> str:
+    """Return the model to preselect for a new endpoint.
+
+    Upstream's default is RECOMMENDED_CHAT_MODEL, an OpenAI name. Offering it
+    to someone configuring a third-party provider preselects a model that will
+    fail on first use, so prefer it only when the provider actually serves it
+    (or when discovery told us nothing) and otherwise start from what is
+    advertised.
+    """
+    if not model_ids or RECOMMENDED_CHAT_MODEL in model_ids:
+        return RECOMMENDED_CHAT_MODEL
+    return model_ids[0]