feat: vendor openai_conversation from core 2026.9.2, rename domain

Verbatim copy from home-assistant/core at tag 2026.9.2, with only the
domain constant and manifest changed. Apache-2.0, attribution in NOTICE.

Also fixed self-references the domain rename left dangling: the
config_entry selector's `integration:` field in services.yaml, the
`[%key:component::openai_conversation::...%]` translation
cross-references in strings.json, the deprecated-action descriptions
naming the old domain, and config_flow.py's instructions_url (now
pointing at this repo instead of the core docs page).

Local pytest run skipped per owner decision (see prior commit); files
validated with py_compile / json.load / yaml.safe_load instead. CI
(added in the prior commit) is the real gate.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01739Seac5eMAfNwFeiwV5r4

custom_components/openai_compatible/ai_task.py

@@ -0,0 +1,158 @@
+"""AI Task integration for OpenAI."""
+
+import base64
+from json import JSONDecodeError
+import logging
+from typing import TYPE_CHECKING, override
+
+from openai.types.responses.response_output_item import ImageGenerationCall
+
+from homeassistant.components import ai_task, conversation
+from homeassistant.core import HomeAssistant
+from homeassistant.exceptions import HomeAssistantError
+from homeassistant.helpers.entity_platform import AddConfigEntryEntitiesCallback
+from homeassistant.util.json import json_loads
+
+from .const import (
+    CONF_CHAT_MODEL,
+    CONF_IMAGE_MODEL,
+    RECOMMENDED_CHAT_MODEL,
+    RECOMMENDED_IMAGE_MODEL,
+    UNSUPPORTED_IMAGE_MODELS,
+)
+from .entity import OpenAIBaseLLMEntity
+
+if TYPE_CHECKING:
+    from homeassistant.config_entries import ConfigSubentry
+
+    from . import OpenAIConfigEntry
+
+_LOGGER = logging.getLogger(__name__)
+
+PARALLEL_UPDATES = 0
+
+
+async def async_setup_entry(
+    hass: HomeAssistant,
+    config_entry: OpenAIConfigEntry,
+    async_add_entities: AddConfigEntryEntitiesCallback,
+) -> None:
+    """Set up AI Task entities."""
+    for subentry in config_entry.subentries.values():
+        if subentry.subentry_type != "ai_task_data":
+            continue
+
+        async_add_entities(
+            [OpenAITaskEntity(config_entry, subentry)],
+            config_subentry_id=subentry.subentry_id,
+        )
+
+
+class OpenAITaskEntity(
+    ai_task.AITaskEntity,
+    OpenAIBaseLLMEntity,
+):
+    """OpenAI AI Task entity."""
+
+    def __init__(self, entry: OpenAIConfigEntry, subentry: ConfigSubentry) -> None:
+        """Initialize the entity."""
+        super().__init__(entry, subentry)
+        self._attr_supported_features = (
+            ai_task.AITaskEntityFeature.GENERATE_DATA
+            | ai_task.AITaskEntityFeature.SUPPORT_ATTACHMENTS
+        )
+        model = self.subentry.data.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL)
+        if not model.startswith(tuple(UNSUPPORTED_IMAGE_MODELS)):
+            self._attr_supported_features |= ai_task.AITaskEntityFeature.GENERATE_IMAGE
+
+    @override
+    async def _async_generate_data(
+        self,
+        task: ai_task.GenDataTask,
+        chat_log: conversation.ChatLog,
+    ) -> ai_task.GenDataTaskResult:
+        """Handle a generate data task."""
+        await self._async_handle_chat_log(
+            chat_log, task.name, task.structure, max_iterations=1000
+        )
+
+        if not isinstance(chat_log.content[-1], conversation.AssistantContent):
+            raise HomeAssistantError(
+                "Last content in chat log is not an AssistantContent"
+            )
+
+        text = chat_log.content[-1].content or ""
+
+        if not task.structure:
+            return ai_task.GenDataTaskResult(
+                conversation_id=chat_log.conversation_id,
+                data=text,
+            )
+        try:
+            data = json_loads(text)
+        except JSONDecodeError as err:
+            _LOGGER.error(
+                "Failed to parse JSON response: %s. Response: %s",
+                err,
+                text,
+            )
+            raise HomeAssistantError("Error with OpenAI structured response") from err
+
+        return ai_task.GenDataTaskResult(
+            conversation_id=chat_log.conversation_id,
+            data=data,
+        )
+
+    @override
+    async def _async_generate_image(
+        self,
+        task: ai_task.GenImageTask,
+        chat_log: conversation.ChatLog,
+    ) -> ai_task.GenImageTaskResult:
+        """Handle a generate image task."""
+        await self._async_handle_chat_log(chat_log, task.name, force_image=True)
+
+        if not isinstance(chat_log.content[-1], conversation.AssistantContent):
+            raise HomeAssistantError(
+                "Last content in chat log is not an AssistantContent"
+            )
+
+        image_call: ImageGenerationCall | None = None
+        for content in reversed(chat_log.content):
+            if not isinstance(content, conversation.AssistantContent):
+                break
+            if isinstance(content.native, ImageGenerationCall):
+                if image_call is None or image_call.result is None:
+                    image_call = content.native
+                else:  # Remove image data from chat log to save memory
+                    content.native.result = None
+
+        if image_call is None or image_call.result is None:
+            raise HomeAssistantError("No image returned")
+
+        image_data = base64.b64decode(image_call.result)
+        image_call.result = None
+
+        if hasattr(image_call, "output_format") and (
+            output_format := image_call.output_format
+        ):
+            mime_type = f"image/{output_format}"
+        else:
+            mime_type = "image/png"
+
+        if hasattr(image_call, "size") and (size := image_call.size):
+            width, height = tuple(size.split("x"))
+        else:
+            width, height = None, None
+
+        return ai_task.GenImageTaskResult(
+            image_data=image_data,
+            conversation_id=chat_log.conversation_id,
+            mime_type=mime_type,
+            width=int(width) if width else None,
+            height=int(height) if height else None,
+            model=self.subentry.data.get(CONF_IMAGE_MODEL, RECOMMENDED_IMAGE_MODEL),
+            revised_prompt=image_call.revised_prompt
+            if hasattr(image_call, "revised_prompt")
+            else None,
+        )