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/config_flow.py

@@ -104,7 +104,7 @@ from .const import (
     UNSUPPORTED_PRIORITY_SERVICE_TIERS_MODELS,
     UNSUPPORTED_WEB_SEARCH_MODELS,
 )
-from .model_list import async_fetch_model_ids, model_field
+from .model_list import async_fetch_model_ids, default_model, model_field
 from .url_util import (
     CredentialsInBaseURL,
     InvalidBaseURL,
@@ -325,36 +325,58 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
                 }
             )
 
+        # The model belongs on the first screen. Picking one is the entire
+        # point of adding an endpoint, and behind the "recommended" checkbox
+        # it was unreachable: ticked, this step creates the subentry and the
+        # model silently stays RECOMMENDED_CHAT_MODEL -- an OpenAI name a
+        # third-party provider will not serve. entity.py reads
+        # CONF_CHAT_MODEL regardless of the recommended flag, so a model
+        # chosen here takes effect on either path.
+        model_ids = await async_fetch_model_ids(self._get_entry().runtime_data)
+        step_schema[
+            vol.Optional(CONF_CHAT_MODEL, default=default_model(model_ids))
+        ] = model_field(model_ids)
+
         step_schema[
             vol.Required(CONF_RECOMMENDED, default=options.get(CONF_RECOMMENDED, False))
         ] = bool
 
+        errors: dict[str, str] = {}
+
         if user_input is not None:
             if user_input.get(CONF_LLM_HASS_API) is None:
                 user_input.pop(CONF_LLM_HASS_API, None)
 
-            if user_input[CONF_RECOMMENDED]:
-                if self._is_new:
-                    return self.async_create_entry(
-                        title=user_input.pop(CONF_NAME),
+            # Checked here rather than on the next step, because the
+            # recommended path creates the subentry from this one and would
+            # otherwise skip the check entirely.
+            if user_input.get(CONF_CHAT_MODEL) in UNSUPPORTED_MODELS:
+                errors[CONF_CHAT_MODEL] = "model_not_supported"
+
+            if not errors:
+                if user_input[CONF_RECOMMENDED]:
+                    if self._is_new:
+                        return self.async_create_entry(
+                            title=user_input.pop(CONF_NAME),
+                            data=user_input,
+                        )
+                    return self.async_update_and_abort(
+                        self._get_entry(),
+                        self._get_reconfigure_subentry(),
                         data=user_input,
                     )
-                return self.async_update_and_abort(
-                    self._get_entry(),
-                    self._get_reconfigure_subentry(),
-                    data=user_input,
-                )
 
-            options.update(user_input)
-            if CONF_LLM_HASS_API in options and CONF_LLM_HASS_API not in user_input:
-                options.pop(CONF_LLM_HASS_API)
-            return await self.async_step_additional()
+                options.update(user_input)
+                if CONF_LLM_HASS_API in options and CONF_LLM_HASS_API not in user_input:
+                    options.pop(CONF_LLM_HASS_API)
+                return await self.async_step_additional()
 
         return self.async_show_form(
             step_id="init",
             data_schema=self.add_suggested_values_to_schema(
                 vol.Schema(step_schema), options
             ),
+            errors=errors,
         )
 
     async def async_step_additional(
@@ -365,14 +387,8 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
         errors: dict[str, str] = {}
 
         step_schema: VolDictType = {
-            # Upstream makes this a free-text box defaulting to an OpenAI
-            # model name. Offer what the provider actually serves instead.
-            vol.Optional(
-                CONF_CHAT_MODEL,
-                default=RECOMMENDED_CHAT_MODEL,
-            ): model_field(
-                await async_fetch_model_ids(self._get_entry().runtime_data)
-            ),
+            # CONF_CHAT_MODEL is asked on the init step, so that it is
+            # reachable without unticking "recommended" first.
             vol.Optional(
                 CONF_MAX_TOKENS,
                 default=RECOMMENDED_MAX_TOKENS,
@@ -393,8 +409,6 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
 
         if user_input is not None:
             options.update(user_input)
-            if user_input.get(CONF_CHAT_MODEL) in UNSUPPORTED_MODELS:
-                errors[CONF_CHAT_MODEL] = "model_not_supported"
 
             if not errors:
                 return await self.async_step_model()

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]

custom_components/openai_compatible/strings.json

@@ -123,12 +123,12 @@
           "data": {
             "chat_model": "[%key:common::generic::model%]",
             "max_tokens": "Maximum tokens to return in response",
-            "store_responses": "Store requests and responses in OpenAI",
+            "store_responses": "Store requests and responses on the provider",
             "temperature": "Temperature",
             "top_p": "Top P"
           },
           "data_description": {
-            "store_responses": "If enabled, requests and responses are stored by OpenAI and visible in your OpenAI dashboard logs"
+            "store_responses": "Sets the Responses API store flag, asking the provider to keep requests and responses in its own logs. Support varies: OpenAI shows them in its dashboard, while many compatible servers ignore the flag entirely."
           },
           "title": "Additional settings"
         },

custom_components/openai_compatible/translations/en.json

@@ -59,12 +59,12 @@
           "data": {
             "chat_model": "Model",
             "max_tokens": "Maximum tokens to return in response",
-            "store_responses": "Store requests and responses in OpenAI",
+            "store_responses": "Store requests and responses on the provider",
             "temperature": "Temperature",
             "top_p": "Top P"
           },
           "data_description": {
-            "store_responses": "If enabled, requests and responses are stored by OpenAI and visible in your OpenAI dashboard logs"
+            "store_responses": "Sets the Responses API store flag, asking the provider to keep requests and responses in its own logs. Support varies: OpenAI shows them in its dashboard, while many compatible servers ignore the flag entirely."
           },
           "title": "Additional settings"
         },
@@ -123,12 +123,12 @@
           "data": {
             "chat_model": "Model",
             "max_tokens": "Maximum tokens to return in response",
-            "store_responses": "Store requests and responses in OpenAI",
+            "store_responses": "Store requests and responses on the provider",
             "temperature": "Temperature",
             "top_p": "Top P"
           },
           "data_description": {
-            "store_responses": "If enabled, requests and responses are stored by OpenAI and visible in your OpenAI dashboard logs"
+            "store_responses": "Sets the Responses API store flag, asking the provider to keep requests and responses in its own logs. Support varies: OpenAI shows them in its dashboard, while many compatible servers ignore the flag entirely."
           },
           "title": "Additional settings"
         },