fix: make the integration work against a Claude proxy
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- Treat an empty tool argument string as no parameters instead of raising
  JSONDecodeError; the proxy sends "" for tools like the timer status
  (upstream issue #3).
- Do not replay earlier web searches in the history. The chat log keeps only
  their status, and a search without results makes the model disown the
  answers it based on it and search again (upstream issue #4).
- Look up the home location for web search with the subentry's model instead
  of gpt-4o-mini, and save the options without city/region if the lookup
  fails (upstream issue #5).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
pc-heiniandClaude Opus 5.5 committed 2026-10-22 08:38:01 +02:00
1 parent 8737e5d4ec
commit 235c536cab
6 files changed
+193 -39

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+17
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@@ -4,6 +4,23 @@
[![validate](https://github.com/adamjs83/ha-openai-compatible/actions/workflows/validate.yaml/badge.svg)](https://github.com/adamjs83/ha-openai-compatible/actions/workflows/validate.yaml)
[![HACS: custom](https://img.shields.io/badge/HACS-custom-41BDF5.svg)](https://hacs.xyz)
> **Fork of [adamjs83/ha-openai-compatible](https://github.com/adamjs83/ha-openai-compatible) v0.2.1**
> with fixes for running it against a proxy that serves Claude models. Drop it once
> upstream has fixed these issues:
>
> - [#3](https://github.com/adamjs83/ha-openai-compatible/issues/3): a tool call with an
> empty argument string (tools without parameters) is treated as `{}` instead of
> raising `JSONDecodeError`.
> - [#4](https://github.com/adamjs83/ha-openai-compatible/issues/4): earlier web searches
> are not replayed in the history; they carry no results, and the model then disowns
> its own answers and searches again.
> - [#5](https://github.com/adamjs83/ha-openai-compatible/issues/5): the home location
> lookup for web search uses the subentry's model instead of `gpt-4o-mini`, and a
> failed lookup no longer blocks saving the options.
>
> HACS only installs from GitHub, so this fork is installed by copying
> `custom_components/openai_compatible` into the Home Assistant config.
Home Assistant's built-in **OpenAI** integration, with one change that matters: the
**API base URL is configurable**. Point Home Assistant's conversation agent, AI Task,
speech-to-text and text-to-speech at any OpenAI-compatible endpoint — LiteLLM, vLLM,
@@ -702,8 +702,12 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
): str,
}
)
# Ask the subentry's own model: the endpoint may not serve
# RECOMMENDED_CHAT_MODEL (an OpenAI name). A failed lookup only
# costs the city/region hint, so it must not block saving.
try:
response = await client.responses.create(
model=RECOMMENDED_CHAT_MODEL,
model=self.options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL),
input=[
{
"role": "system",
@@ -727,6 +731,10 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
),
)
location_data = location_schema(json.loads(response.output_text) or {})
except (openai.OpenAIError, ValueError, vol.Invalid) as err:
_LOGGER.warning(
"Could not look up the home location for web search: %s", err
)
if self.hass.config.country:
location_data[CONF_WEB_SEARCH_COUNTRY] = self.hass.config.country
+7 -25
View File
@@ -22,7 +22,6 @@ from openai.types.responses import (
ResponseFunctionToolCall,
ResponseFunctionToolCallParam,
ResponseFunctionWebSearch,
ResponseFunctionWebSearchParam,
ResponseIncompleteEvent,
ResponseInputFileParam,
ResponseInputImageParam,
@@ -181,20 +180,13 @@ def _convert_content_to_param(
"""Convert any native chat message for this agent to the native format."""
messages: ResponseInputParam = []
reasoning_summary: list[str] = []
web_search_calls: dict[str, ResponseFunctionWebSearchParam] = {}
for content in chat_content:
if isinstance(content, conversation.ToolResultContent):
if (
content.tool_name == "web_search_call"
and content.tool_call_id in web_search_calls
):
web_search_call = web_search_calls.pop(content.tool_call_id)
web_search_call["status"] = content.tool_result.get( # type: ignore[typeddict-item]
"status", "completed"
)
messages.append(web_search_call)
else:
# Earlier web searches are not replayed: the chat log only keeps
# their status, not their results, and a search without results
# makes the model disown the answer it based on that search.
if content.tool_name != "web_search_call":
messages.append(
FunctionCallOutput(
type="function_call_output",
@@ -217,18 +209,8 @@ def _convert_content_to_param(
if isinstance(content, conversation.AssistantContent):
if content.tool_calls:
for tool_call in content.tool_calls:
if (
tool_call.external
and tool_call.tool_name == "web_search_call"
and "action" in tool_call.tool_args
):
web_search_calls[tool_call.id] = ResponseFunctionWebSearchParam(
type="web_search_call",
id=tool_call.id,
action=tool_call.tool_args["action"],
status="completed",
)
else:
if tool_call.external and tool_call.tool_name == "web_search_call":
continue
messages.append(
ResponseFunctionToolCallParam(
type="function_call",
@@ -418,7 +400,7 @@ async def _transform_stream( # noqa: C901 - This is complex, but better to have
llm.ToolInput(
id=current_tool_call.call_id,
tool_name=current_tool_call.name,
tool_args=json.loads(current_tool_call.arguments),
tool_args=json.loads(current_tool_call.arguments or "{}"),
)
]
}
+68
View File
@@ -1274,6 +1274,74 @@ async def test_subentry_web_search_user_location(
}
async def test_subentry_web_search_user_location_lookup_fails(
hass: HomeAssistant,
mock_config_entry,
mock_init_component,
) -> None:
"""Test the location lookup uses the subentry's model and may fail.
An endpoint that only serves other providers' models rejects the OpenAI
default; saving must still succeed with country and time zone only.
"""
subentry = next(
sub
for sub in mock_config_entry.subentries.values()
if sub.subentry_type == "conversation"
)
subentry_flow = await mock_config_entry.start_subentry_reconfigure_flow(
hass, subentry.subentry_id
)
subentry_flow = await hass.config_entries.subentries.async_configure(
subentry_flow["flow_id"],
{
CONF_RECOMMENDED: False,
CONF_PROMPT: "Speak like a pirate",
CONF_CHAT_MODEL: "claude-sonnet-5-5",
},
)
subentry_flow = await hass.config_entries.subentries.async_configure(
subentry_flow["flow_id"],
{
CONF_TEMPERATURE: 1.0,
CONF_TOP_P: RECOMMENDED_TOP_P,
CONF_MAX_TOKENS: RECOMMENDED_MAX_TOKENS,
CONF_STORE_RESPONSES: False,
},
)
await hass.async_block_till_done()
assert subentry_flow["step_id"] == "model"
hass.config.country = "DE"
hass.config.time_zone = "Europe/Berlin"
hass.states.async_set("zone.home", "0", {"latitude": 50.9, "longitude": 12.1})
with patch(
"openai.resources.responses.AsyncResponses.create",
new_callable=AsyncMock,
side_effect=BadRequestError(
response=httpx.Response(status_code=400, request=httpx.Request("POST", "")),
body=None,
message="unknown provider for model",
),
) as mock_create:
subentry_flow = await hass.config_entries.subentries.async_configure(
subentry_flow["flow_id"],
{
CONF_WEB_SEARCH: True,
CONF_WEB_SEARCH_CONTEXT_SIZE: "medium",
CONF_WEB_SEARCH_USER_LOCATION: True,
},
)
await hass.async_block_till_done()
assert mock_create.call_args.kwargs["model"] == "claude-sonnet-5-5"
assert subentry_flow["type"] is FlowResultType.ABORT
assert subentry_flow["reason"] == "reconfigure_successful"
assert CONF_WEB_SEARCH_CITY not in subentry.data
assert CONF_WEB_SEARCH_REGION not in subentry.data
assert subentry.data[CONF_WEB_SEARCH_COUNTRY] == "DE"
assert subentry.data[CONF_WEB_SEARCH_TIMEZONE] == "Europe/Berlin"
async def test_creating_ai_task_subentry(
hass: HomeAssistant,
mock_config_entry: MockConfigEntry,
-13
View File
@@ -231,19 +231,6 @@ async def test_conversation_agent(
@pytest.mark.parametrize(
("description", "messages"),
[
(
"Test function call started with missing arguments",
(
*create_function_tool_call_item(
id="fc_1",
arguments=[],
call_id="call_call_1",
name="test_tool",
output_index=0,
),
*create_message_item(id="msg_A", text="Cool", output_index=1),
),
),
(
"Test invalid JSON",
(
+92
View File
@@ -0,0 +1,92 @@
"""Tests for the fork's chat log conversion fixes in entity.py."""
from unittest.mock import MagicMock
from homeassistant.components import conversation
from homeassistant.helpers import llm
from custom_components.openai_compatible.entity import (
_convert_content_to_param,
_transform_stream,
)
from . import create_function_tool_call_item
async def _stream(events):
for event in events:
yield event
async def test_tool_call_without_arguments() -> None:
"""Test an empty argument string means a call without parameters.
Some OpenAI-compatible endpoints send "" instead of "{}" for tools that
take no parameters, e.g. the timer status intent.
"""
events = create_function_tool_call_item(
id="fc_1",
arguments=[],
call_id="call_1",
name="HassTimerStatus",
output_index=0,
)
deltas = [delta async for delta in _transform_stream(MagicMock(), _stream(events))]
tool_calls = [call for delta in deltas for call in delta.get("tool_calls", [])]
assert len(tool_calls) == 1
assert tool_calls[0].tool_name == "HassTimerStatus"
assert tool_calls[0].tool_args == {}
def test_web_search_not_replayed() -> None:
"""Test earlier web searches are left out of the history.
The chat log keeps only a search's status, not its results. Replaying the
bare search makes the model disown the answer it based on that search.
"""
content = [
conversation.UserContent(content="How did the match go?"),
conversation.AssistantContent(
agent_id="conversation.test",
tool_calls=[
llm.ToolInput(
id="ws_1",
tool_name="web_search_call",
tool_args={"action": {"type": "search", "query": "match"}},
external=True,
)
],
),
conversation.ToolResultContent(
agent_id="conversation.test",
tool_call_id="ws_1",
tool_name="web_search_call",
result=llm.ToolResult(data={"status": "completed"}),
),
conversation.AssistantContent(
agent_id="conversation.test",
content="It ended 2 to 2.",
tool_calls=[
llm.ToolInput(id="call_1", tool_name="GetLiveContext", tool_args={})
],
),
conversation.ToolResultContent(
agent_id="conversation.test",
tool_call_id="call_1",
tool_name="GetLiveContext",
result=llm.ToolResult(data={"success": True}),
),
]
messages = _convert_content_to_param(content)
assert [message["type"] for message in messages] == [
"message",
"message",
"function_call",
"function_call_output",
]
assert messages[1]["content"] == "It ended 2 to 2."
assert messages[2]["call_id"] == "call_1"