fix: make the integration work against a Claude proxy

- 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>

README.md

@@ -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,

custom_components/openai_compatible/config_flow.py

@@ -702,31 +702,39 @@ class OpenAISubentryFlowHandler(ConfigSubentryFlow):
                     ): str,
                 }
             )
-            response = await client.responses.create(
-                model=RECOMMENDED_CHAT_MODEL,
-                input=[
-                    {
-                        "role": "system",
-                        "content": "Where are the following coordinates located: "
-                        f"({zone_home.attributes[EntityStateAttribute.LATITUDE]},"
-                        f" {zone_home.attributes[EntityStateAttribute.LONGITUDE]})?",
-                    }
-                ],
-                text={
-                    "format": {
-                        "type": "json_schema",
-                        "name": "approximate_location",
-                        "description": "Approximate location data of the user "
-                        "for refined web search results",
-                        "schema": to_openapi(location_schema),
-                        "strict": False,
-                    }
-                },
-                store=self.options.get(
-                    CONF_STORE_RESPONSES, RECOMMENDED_STORE_RESPONSES
-                ),
-            )
-            location_data = location_schema(json.loads(response.output_text) or {})
+            # 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=self.options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL),
+                    input=[
+                        {
+                            "role": "system",
+                            "content": "Where are the following coordinates located: "
+                            f"({zone_home.attributes[EntityStateAttribute.LATITUDE]},"
+                            f" {zone_home.attributes[EntityStateAttribute.LONGITUDE]})?",
+                        }
+                    ],
+                    text={
+                        "format": {
+                            "type": "json_schema",
+                            "name": "approximate_location",
+                            "description": "Approximate location data of the user "
+                            "for refined web search results",
+                            "schema": to_openapi(location_schema),
+                            "strict": False,
+                        }
+                    },
+                    store=self.options.get(
+                        CONF_STORE_RESPONSES, RECOMMENDED_STORE_RESPONSES
+                    ),
+                )
+                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

custom_components/openai_compatible/entity.py

@@ -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",
@@ -217,26 +209,16 @@ 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:
-                        messages.append(
-                            ResponseFunctionToolCallParam(
-                                type="function_call",
-                                name=tool_call.tool_name,
-                                arguments=json_dumps(tool_call.tool_args),
-                                call_id=tool_call.id,
-                            )
+                    if tool_call.external and tool_call.tool_name == "web_search_call":
+                        continue
+                    messages.append(
+                        ResponseFunctionToolCallParam(
+                            type="function_call",
+                            name=tool_call.tool_name,
+                            arguments=json_dumps(tool_call.tool_args),
+                            call_id=tool_call.id,
                         )
+                    )
 
             if content.thinking_content:
                 reasoning_summary.append(content.thinking_content)
@@ -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 "{}"),
                     )
                 ]
             }

tests/test_config_flow.py

@@ -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,

tests/test_conversation.py

@@ -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",
             (

tests/test_entity.py

@@ -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"