Adam SmithandClaude Opus 5
6a599e092a
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
140 lines
4.9 KiB
Python
140 lines
4.9 KiB
Python
"""Each endpoint type picks its model from what the provider advertises.
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Upstream defaults every model field to an OpenAI name and offers no way to see
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what the endpoint actually serves, so configuring a proxy meant typing exact
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model ids from memory -- and for conversation/AI Task the field was skipped
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entirely unless you knew to untick "recommended" first.
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"""
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from unittest.mock import patch
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import pytest
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from homeassistant import config_entries
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from homeassistant.const import CONF_NAME
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from homeassistant.core import HomeAssistant
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from homeassistant.data_entry_flow import FlowResultType
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from homeassistant.helpers.selector import SelectSelector
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from pytest_homeassistant_custom_component.common import MockConfigEntry
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from custom_components.openai_compatible.const import (
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CONF_CHAT_MODEL,
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CONF_RECOMMENDED,
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)
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PROVIDER_MODELS = ["claude-sonnet-4-6", "gpt-4o-mini", "whisper-1"]
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DISCOVERY = "custom_components.openai_compatible.config_flow.async_fetch_model_ids"
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def _field(result: dict, key: str):
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"""Return the schema field for key in a shown form."""
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schema = result["data_schema"].schema
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return next(value for marker, value in schema.items() if marker == key)
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def _marker(result: dict, key: str):
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"""Return the schema marker (which carries the default) for key."""
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schema = result["data_schema"].schema
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return next(marker for marker in schema if marker == key)
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async def _model_step(
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hass: HomeAssistant,
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entry: MockConfigEntry,
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subentry_type: str,
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models: list[str],
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) -> dict:
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"""Return the form that asks for the model, for any endpoint type.
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All four types ask on the first screen, so that picking a model never
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depends on noticing the "recommended" checkbox first.
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"""
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with patch(DISCOVERY, return_value=models):
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result = await hass.config_entries.subentries.async_init(
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(entry.entry_id, subentry_type),
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context={"source": config_entries.SOURCE_USER},
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)
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assert result["type"] is FlowResultType.FORM
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assert result["step_id"] == "init"
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return result
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@pytest.mark.parametrize(
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"subentry_type", ["conversation", "ai_task_data", "stt", "tts"]
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)
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async def test_every_type_offers_the_providers_models(
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hass: HomeAssistant,
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mock_init_component: None,
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mock_config_entry: MockConfigEntry,
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subentry_type: str,
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) -> None:
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"""All four endpoint types get a dropdown, not a free-text box."""
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result = await _model_step(
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hass, mock_config_entry, subentry_type, PROVIDER_MODELS
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)
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field = _field(result, CONF_CHAT_MODEL)
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assert isinstance(field, SelectSelector)
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assert field.config["options"] == PROVIDER_MODELS
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# A provider may route a model it does not advertise.
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assert field.config["custom_value"] is True
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@pytest.mark.parametrize(
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"subentry_type", ["conversation", "ai_task_data", "stt", "tts"]
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)
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async def test_falls_back_to_free_text_when_provider_lists_nothing(
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hass: HomeAssistant,
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mock_init_component: None,
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mock_config_entry: MockConfigEntry,
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subentry_type: str,
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) -> None:
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"""An endpoint without /v1/models must still be configurable by hand."""
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result = await _model_step(hass, mock_config_entry, subentry_type, [])
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assert _field(result, CONF_CHAT_MODEL) is str
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async def test_new_endpoint_starts_with_recommended_unticked(
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hass: HomeAssistant,
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mock_init_component: None,
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mock_config_entry: MockConfigEntry,
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) -> None:
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"""Ticked, the flow ends on the first step and never asks for a model."""
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with patch(DISCOVERY, return_value=PROVIDER_MODELS):
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result = await hass.config_entries.subentries.async_init(
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(mock_config_entry.entry_id, "conversation"),
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context={"source": config_entries.SOURCE_USER},
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)
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assert _marker(result, CONF_RECOMMENDED).default() is False
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async def test_a_non_openai_model_name_survives_the_flow(
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hass: HomeAssistant,
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mock_init_component: None,
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mock_config_entry: MockConfigEntry,
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) -> None:
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"""The point of the fork: the stored model is the provider's, and none of
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upstream's OpenAI-specific model gates reject it."""
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with patch(DISCOVERY, return_value=PROVIDER_MODELS):
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result = await hass.config_entries.subentries.async_init(
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(mock_config_entry.entry_id, "conversation"),
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context={"source": config_entries.SOURCE_USER},
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)
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# The model is chosen on the very first screen, alongside the name.
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result = await hass.config_entries.subentries.async_configure(
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result["flow_id"],
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{
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CONF_NAME: "Sonnet via LiteLLM",
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CONF_CHAT_MODEL: "claude-sonnet-4-6",
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CONF_RECOMMENDED: True,
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},
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)
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await hass.async_block_till_done()
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assert result["type"] is FlowResultType.CREATE_ENTRY
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assert result["title"] == "Sonnet via LiteLLM"
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assert result["data"][CONF_CHAT_MODEL] == "claude-sonnet-4-6"
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