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