feat: one entry per provider, endpoints per type and model from a live dropdown

Reshapes setup around how a multi-model proxy is actually used: one config
entry per server/provider, then one endpoint per model added by hand, with
the model chosen from what that provider advertises right now.

Setup (async_step_user):
- Adds a Name field. With one entry per provider the title matters, and it
  was hardcoded to "ChatGPT" regardless of where the entry pointed. Blank
  falls back to the endpoint host via url_util.title_from_base_url.
  Deliberately absent from the reauth schema (now split out as
  STEP_REAUTH_DATA_SCHEMA): that step writes its input back into entry.data
  via data_updates, so a name field there would persist the title as
  connection data on every key rotation.
- Stops auto-creating four subentries. conversation/ai_task_data/stt/tts were
  all created up front carrying RECOMMENDED_* options, which pin OpenAI model
  names (gpt-4o-mini-tts, gpt-4o-mini-transcribe). Against a third-party
  endpoint those entities are dead on arrival -- the reported symptom was an
  install that "loads bits, it's all janky".
- Drops _async_abort_entries_match, so several entries may point at one
  server (one per provider-side key, for instance). Upstream aborts with
  already_configured on matching url+key.

Model discovery (new model_list.py, kept out of the vendored files like
url_util.py):
- async_fetch_model_ids asks the endpoint's GET /v1/models. It calls
  with_options(max_retries=0), because this runs while the user waits on a
  dialog and the SDK otherwise retries with backoff -- visible in the test
  run as repeated "Retrying request to /models" and a suite that went from
  5s to minutes.
- Returns [] on any OpenAIError, and model_field() then yields a plain text
  field instead of a dropdown, so an endpoint that serves /v1/responses but
  not /v1/models is still configurable by hand. The dropdown sets
  custom_value=True for the same reason (LiteLLM wildcard routes).
- Wired into all four types: conversation and ai_task_data on the additional
  step, stt (which hardcoded OpenAI's three transcribe models) and tts on
  init. TTS had no model field at all -- it silently used gpt-4o-mini-tts.

A new endpoint now starts with "recommended" unticked. Ticked, the flow ends
on the first step and never shows a model field, which is why the model
looked unpickable; reconfigure still keeps whatever was saved.

The model field stays on the additional step rather than moving to init. The
init position reads better, but 71 ported tests drive the model through the
additional step, several from parametrized option dicts that no mechanical
edit could relocate. Rewriting the only regression net against upstream to
save one click was the wrong trade.

Also: the setup description no longer says "your OpenAI API key", and
instructions_url pointed at a README anchor (#generate-an-api-key) that does
not exist -- now #configuration. strings.json re-verified against core's
RE_URL: 0 violations.

Local: 167 passed.

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

tests/test_model_list.py

@@ -0,0 +1,87 @@
+"""Model discovery: turn an endpoint's GET /v1/models into a picker."""
+
+from unittest.mock import AsyncMock, MagicMock
+
+import openai
+import pytest
+
+from homeassistant.helpers.selector import SelectSelector
+
+from custom_components.openai_compatible.model_list import (
+    async_fetch_model_ids,
+    model_field,
+)
+
+
+def _client(model_ids: list[str] | None = None, *, error: Exception | None = None):
+    """Return a stub AsyncOpenAI whose models.list yields model_ids or raises."""
+    client = MagicMock()
+    # Production calls client.with_options(...).models.list(); returning the
+    # same stub keeps the per-request options visible to assertions.
+    client.with_options.return_value = client
+    if error is not None:
+        client.models.list = AsyncMock(side_effect=error)
+    else:
+        page = MagicMock()
+        page.data = [MagicMock(id=model_id) for model_id in (model_ids or [])]
+        client.models.list = AsyncMock(return_value=page)
+    return client
+
+
+async def test_fetch_returns_sorted_unique_ids() -> None:
+    """A proxy can list the same alias twice; the picker should show it once."""
+    client = _client(["gpt-4o-mini", "claude-sonnet", "gpt-4o-mini", "llama-3.3"])
+
+    assert await async_fetch_model_ids(client) == [
+        "claude-sonnet",
+        "gpt-4o-mini",
+        "llama-3.3",
+    ]
+
+
+async def test_fetch_ignores_entries_without_an_id() -> None:
+    """Don't put a blank option in the dropdown."""
+    page = MagicMock()
+    page.data = [MagicMock(id="real-model"), MagicMock(id=None), MagicMock(id="")]
+    client = MagicMock()
+    client.with_options.return_value = client
+    client.models.list = AsyncMock(return_value=page)
+
+    assert await async_fetch_model_ids(client) == ["real-model"]
+
+
+async def test_fetch_does_not_retry() -> None:
+    """This runs while the user waits on a dialog; retries would stall it."""
+    client = _client(["gpt-4o-mini"])
+
+    await async_fetch_model_ids(client, timeout=3.0)
+
+    client.with_options.assert_called_once_with(max_retries=0, timeout=3.0)
+
+
+@pytest.mark.parametrize(
+    "error",
+    [
+        openai.APIConnectionError(request=MagicMock()),
+        openai.AuthenticationError(
+            "nope", response=MagicMock(status_code=401), body=None
+        ),
+    ],
+)
+async def test_fetch_survives_an_endpoint_that_will_not_list(error: Exception) -> None:
+    """Model discovery is a convenience; it must never break the config flow."""
+    assert await async_fetch_model_ids(_client(error=error)) == []
+
+
+async def test_field_is_a_dropdown_that_still_accepts_a_typed_name() -> None:
+    """A proxy may serve a model it does not advertise, so allow free text."""
+    field = model_field(["claude-sonnet", "gpt-4o-mini"])
+
+    assert isinstance(field, SelectSelector)
+    assert field.config["options"] == ["claude-sonnet", "gpt-4o-mini"]
+    assert field.config["custom_value"] is True
+
+
+async def test_field_falls_back_to_free_text_when_no_models_are_known() -> None:
+    """An endpoint that won't list models must still be configurable by hand."""
+    assert model_field([]) is str