Files
core/homeassistant/components/ai_task/task.py
2025-07-15 08:51:08 +02:00

170 lines
5.2 KiB
Python

"""AI tasks to be handled by agents."""
from __future__ import annotations
from dataclasses import dataclass
import mimetypes
from pathlib import Path
import tempfile
from typing import Any
import voluptuous as vol
from homeassistant.components import camera, conversation, media_source
from homeassistant.core import HomeAssistant, callback
from homeassistant.exceptions import HomeAssistantError
from homeassistant.helpers.chat_session import async_get_chat_session
from .const import DATA_COMPONENT, DATA_PREFERENCES, AITaskEntityFeature
def _save_camera_snapshot(image: camera.Image) -> Path:
"""Save camera snapshot to temp file."""
with tempfile.NamedTemporaryFile(
mode="wb",
suffix=mimetypes.guess_extension(image.content_type, False),
delete=False,
) as temp_file:
temp_file.write(image.content)
return Path(temp_file.name)
async def async_generate_data(
hass: HomeAssistant,
*,
task_name: str,
entity_id: str | None = None,
instructions: str,
structure: vol.Schema | None = None,
attachments: list[dict] | None = None,
) -> GenDataTaskResult:
"""Run a task in the AI Task integration."""
if entity_id is None:
entity_id = hass.data[DATA_PREFERENCES].gen_data_entity_id
if entity_id is None:
raise HomeAssistantError("No entity_id provided and no preferred entity set")
entity = hass.data[DATA_COMPONENT].get_entity(entity_id)
if entity is None:
raise HomeAssistantError(f"AI Task entity {entity_id} not found")
if AITaskEntityFeature.GENERATE_DATA not in entity.supported_features:
raise HomeAssistantError(
f"AI Task entity {entity_id} does not support generating data"
)
# Resolve attachments
resolved_attachments: list[conversation.Attachment] = []
created_files: list[Path] = []
if (
attachments
and AITaskEntityFeature.SUPPORT_ATTACHMENTS not in entity.supported_features
):
raise HomeAssistantError(
f"AI Task entity {entity_id} does not support attachments"
)
for attachment in attachments or []:
media_content_id = attachment["media_content_id"]
# Special case for camera media sources
if media_content_id.startswith("media-source://camera/"):
# Extract entity_id from the media content ID
entity_id = media_content_id.removeprefix("media-source://camera/")
# Get snapshot from camera
image = await camera.async_get_image(hass, entity_id)
temp_filename = await hass.async_add_executor_job(
_save_camera_snapshot, image
)
created_files.append(temp_filename)
resolved_attachments.append(
conversation.Attachment(
media_content_id=media_content_id,
mime_type=image.content_type,
path=temp_filename,
)
)
else:
# Handle regular media sources
media = await media_source.async_resolve_media(hass, media_content_id, None)
if media.path is None:
raise HomeAssistantError(
"Only local attachments are currently supported"
)
resolved_attachments.append(
conversation.Attachment(
media_content_id=media_content_id,
mime_type=media.mime_type,
path=media.path,
)
)
with async_get_chat_session(hass) as session:
if created_files:
def cleanup_files() -> None:
"""Cleanup temporary files."""
for file in created_files:
file.unlink(missing_ok=True)
@callback
def cleanup_files_callback() -> None:
"""Cleanup temporary files."""
hass.async_add_executor_job(cleanup_files)
session.async_on_cleanup(cleanup_files_callback)
return await entity.internal_async_generate_data(
session,
GenDataTask(
name=task_name,
instructions=instructions,
structure=structure,
attachments=resolved_attachments or None,
),
)
@dataclass(slots=True)
class GenDataTask:
"""Gen data task to be processed."""
name: str
"""Name of the task."""
instructions: str
"""Instructions on what needs to be done."""
structure: vol.Schema | None = None
"""Optional structure for the data to be generated."""
attachments: list[conversation.Attachment] | None = None
"""List of attachments to go along the instructions."""
def __str__(self) -> str:
"""Return task as a string."""
return f"<GenDataTask {self.name}: {id(self)}>"
@dataclass(slots=True)
class GenDataTaskResult:
"""Result of gen data task."""
conversation_id: str
"""Unique identifier for the conversation."""
data: Any
"""Data generated by the task."""
def as_dict(self) -> dict[str, Any]:
"""Return result as a dict."""
return {
"conversation_id": self.conversation_id,
"data": self.data,
}