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
