""" Sensor platform for HA Text AI. @license: CC BY-NC-SA 4.0 International @author: SMKRV @github: https://github.com/smkrv/ha-text-ai @source: https://github.com/smkrv/ha-text-ai """ import logging import math from typing import Any, Dict from homeassistant.components.sensor import ( SensorEntity, SensorEntityDescription, ) from homeassistant.config_entries import ConfigEntry from homeassistant.core import HomeAssistant from homeassistant.helpers.device_registry import DeviceInfo from homeassistant.helpers.entity_platform import AddEntitiesCallback from homeassistant.helpers.typing import StateType from homeassistant.helpers.update_coordinator import CoordinatorEntity from homeassistant.util import dt as dt_util from homeassistant.util import slugify from .const import ( DOMAIN, CONF_MODEL, CONF_API_PROVIDER, ATTR_TOTAL_RESPONSES, ATTR_TOTAL_ERRORS, ATTR_AVG_RESPONSE_TIME, ATTR_LAST_REQUEST_TIME, ATTR_LAST_ERROR, ATTR_IS_PROCESSING, ATTR_IS_RATE_LIMITED, ATTR_IS_MAINTENANCE, ATTR_API_VERSION, ATTR_ENDPOINT_STATUS, ATTR_PERFORMANCE_METRICS, ATTR_HISTORY_SIZE, ATTR_UPTIME, ATTR_API_PROVIDER, ATTR_MODEL, ATTR_SYSTEM_PROMPT, ATTR_API_STATUS, ATTR_RESPONSE, ATTR_QUESTION, ATTR_CONVERSATION_HISTORY, METRIC_TOTAL_TOKENS, METRIC_PROMPT_TOKENS, METRIC_COMPLETION_TOKENS, METRIC_SUCCESSFUL_REQUESTS, METRIC_FAILED_REQUESTS, METRIC_AVERAGE_LATENCY, METRIC_MAX_LATENCY, METRIC_MIN_LATENCY, STATE_READY, STATE_PROCESSING, STATE_ERROR, STATE_INITIALIZING, STATE_MAINTENANCE, STATE_RATE_LIMITED, STATE_DISCONNECTED, ENTITY_ICON, ENTITY_ICON_ERROR, ENTITY_ICON_PROCESSING, DEFAULT_NAME_PREFIX, CONF_MAX_HISTORY_SIZE, MAX_ATTRIBUTE_SIZE, VERSION, ) from .coordinator import HATextAICoordinator _LOGGER = logging.getLogger(__name__) async def async_setup_entry( hass: HomeAssistant, entry: ConfigEntry, async_add_entities: AddEntitiesCallback, ) -> None: """Set up the HA Text AI sensor.""" _LOGGER.debug(f"Starting sensor setup for entry: {entry.entry_id}") try: coordinator = hass.data[DOMAIN][entry.entry_id] _LOGGER.debug(f"Found coordinator for entry {entry.entry_id}") instance_name = coordinator.instance_name _LOGGER.debug(f"Setting up sensor with instance: {instance_name}") sensor = HATextAISensor(coordinator, entry) _LOGGER.debug(f"Created sensor instance: {sensor.entity_id}") async_add_entities([sensor], True) _LOGGER.debug(f"Added sensor entity: {sensor.entity_id}") except Exception as err: _LOGGER.exception(f"Error setting up sensor: {err}") raise class HATextAISensor(CoordinatorEntity, SensorEntity): """HA Text AI Sensor.""" coordinator: HATextAICoordinator def __init__( self, coordinator: HATextAICoordinator, config_entry: ConfigEntry, ) -> None: """Initialize the sensor.""" _LOGGER.debug(f"Initializing sensor with config entry: {config_entry.data}") super().__init__(coordinator) self._config_entry = config_entry self._instance_name = coordinator.instance_name self._normalized_name = coordinator.normalized_name _LOGGER.debug(f"Instance name: {self._instance_name}") _LOGGER.debug(f"Normalized name: {self._normalized_name}") self._conversation_history = [] self._system_prompt = None self._attr_name = f"HA Text AI {self._instance_name}" self.entity_id = f"sensor.ha_text_ai_{self._normalized_name}" self._attr_unique_id = f"{config_entry.entry_id}" _LOGGER.debug(f"Created sensor with entity_id: {self.entity_id}") _LOGGER.debug(f"Sensor name: {self._attr_name}") _LOGGER.debug(f"Unique ID: {self._attr_unique_id}") self.entity_description = SensorEntityDescription( key=f"ha_text_ai_{self._normalized_name.lower()}", entity_registry_enabled_default=True, ) self._current_state = STATE_INITIALIZING self._error_count = 0 self._last_error = None self._last_update = None self._is_processing = False self._last_response = {} self._metrics = {} model = config_entry.data.get(CONF_MODEL, "Unknown") api_provider = config_entry.data.get(CONF_API_PROVIDER, "Unknown") self._attr_device_info = DeviceInfo( identifiers={(DOMAIN, self._attr_unique_id)}, name=self._attr_name, manufacturer="Community", model=f"{model} ({api_provider} provider)", sw_version=VERSION, ) _LOGGER.debug( f"Initialized sensor: {self.entity_id} for instance: {self._instance_name}" ) @property def available(self) -> bool: """Return if entity is available.""" return ( self.coordinator.last_update_success and self.coordinator.data is not None and self._current_state != STATE_DISCONNECTED ) def _sanitize_value(self, value: Any) -> Any: """Sanitize values for JSON serialization.""" if isinstance(value, float): if math.isinf(value) or math.isnan(value): return None return value def _sanitize_attributes(self, attributes: Dict[str, Any]) -> Dict[str, Any]: """Sanitize all attributes for JSON serialization.""" sanitized = { key: self._sanitize_value(value) for key, value in attributes.items() if value is not None } # Log metrics for debugging metrics_keys = [ METRIC_TOTAL_TOKENS, METRIC_PROMPT_TOKENS, METRIC_COMPLETION_TOKENS, METRIC_SUCCESSFUL_REQUESTS, METRIC_FAILED_REQUESTS, METRIC_AVERAGE_LATENCY, METRIC_MAX_LATENCY, METRIC_MIN_LATENCY, ] metrics_values = {k: sanitized.get(k) for k in metrics_keys if k in sanitized} _LOGGER.debug(f"Metrics for {self.entity_id}: {metrics_values}") return sanitized @property def native_value(self) -> StateType: """Return the native value of the sensor.""" if not self.coordinator.last_update_success or not self.coordinator.data: self._current_state = STATE_DISCONNECTED return self._current_state status = self.coordinator.data.get("state", STATE_READY) self._current_state = status return status @property def icon(self) -> str: """Return the icon based on the current state.""" if self._current_state == STATE_ERROR: return ENTITY_ICON_ERROR elif self._current_state == STATE_PROCESSING: return ENTITY_ICON_PROCESSING return ENTITY_ICON @property def extra_state_attributes(self) -> Dict[str, Any]: """Return entity specific state attributes.""" if not self.coordinator.data: return {} try: data = self.coordinator.data metrics = data.get("metrics", {}) # Base attributes attributes = { ATTR_MODEL: self._config_entry.data.get(CONF_MODEL, "Unknown"), ATTR_API_PROVIDER: self._config_entry.data.get(CONF_API_PROVIDER, "Unknown"), ATTR_API_STATUS: self._current_state, ATTR_TOTAL_ERRORS: metrics.get("total_errors", 0), "instance_name": self._instance_name, "normalized_name": self._normalized_name, ATTR_SYSTEM_PROMPT: (data.get("system_prompt", "")[:MAX_ATTRIBUTE_SIZE] if data.get("system_prompt") else None), ATTR_IS_PROCESSING: data.get("is_processing", False), ATTR_IS_RATE_LIMITED: data.get("is_rate_limited", False), ATTR_IS_MAINTENANCE: data.get("is_maintenance", False), ATTR_ENDPOINT_STATUS: data.get("endpoint_status", "unknown"), ATTR_UPTIME: round(data.get("uptime", 0), 2), ATTR_HISTORY_SIZE: data.get("history_size", 0), } # History limit conversation_history = data.get("conversation_history", []) if conversation_history: limited_history = [] for entry in conversation_history: limited_entry = { "timestamp": entry["timestamp"], "question": entry["question"][:MAX_ATTRIBUTE_SIZE], "response": entry["response"][:MAX_ATTRIBUTE_SIZE] } limited_history.append(limited_entry) attributes[ATTR_CONVERSATION_HISTORY] = limited_history # Metrics if isinstance(metrics, dict): attributes.update({ METRIC_TOTAL_TOKENS: metrics.get("total_tokens", 0), METRIC_PROMPT_TOKENS: metrics.get("prompt_tokens", 0), METRIC_COMPLETION_TOKENS: metrics.get("completion_tokens", 0), METRIC_SUCCESSFUL_REQUESTS: metrics.get("successful_requests", 0), METRIC_FAILED_REQUESTS: metrics.get("failed_requests", 0), METRIC_AVERAGE_LATENCY: round(metrics.get("average_latency", 0), 2), METRIC_MAX_LATENCY: round(metrics.get("max_latency", 0), 2), METRIC_MIN_LATENCY: (metrics.get("min_latency") if metrics.get("min_latency") != float("inf") else None), }) # Last response handling last_response = data.get("last_response", {}) if isinstance(last_response, dict): attributes.update({ ATTR_RESPONSE: last_response.get("response", "")[:MAX_ATTRIBUTE_SIZE], ATTR_QUESTION: last_response.get("question", "")[:MAX_ATTRIBUTE_SIZE], "last_model": last_response.get("model", ""), "last_timestamp": last_response.get("timestamp", ""), "last_error": (last_response.get("error", "")[:MAX_ATTRIBUTE_SIZE] if last_response.get("error") else None), }) return self._sanitize_attributes(attributes) except Exception as err: _LOGGER.error("Error preparing attributes: %s", err, exc_info=True) return {} async def async_added_to_hass(self) -> None: """When entity is added to hass.""" await super().async_added_to_hass() self._handle_coordinator_update() _LOGGER.debug(f"Entity {self.entity_id} added to Home Assistant") def _handle_coordinator_update(self) -> None: """Handle updated data from the coordinator.""" try: data = self.coordinator.data if not self.coordinator.last_update_success or not data: self._current_state = STATE_DISCONNECTED _LOGGER.warning(f"No data available for {self.entity_id}") self.async_write_ha_state() return self._is_processing = data.get("is_processing", False) # Update metrics metrics = data.get("metrics", {}) if isinstance(metrics, dict): self._metrics.update(metrics) _LOGGER.debug(f"Updated metrics for {self.entity_id}: {self._metrics}") # Update conversation history and system prompt self._conversation_history = data.get("conversation_history", []) self._system_prompt = data.get("system_prompt") # Update state based on conditions if self._is_processing: self._current_state = STATE_PROCESSING elif data.get("is_rate_limited"): self._current_state = STATE_RATE_LIMITED elif data.get("is_maintenance"): self._current_state = STATE_MAINTENANCE elif data.get("error"): self._current_state = STATE_ERROR self._last_error = data["error"] self._error_count += 1 else: self._current_state = data.get("state", STATE_READY) # Update last update timestamp self._last_update = dt_util.utcnow() _LOGGER.debug( f"Updated {self.entity_id} state to: {self._current_state} " f"(available: {self.available})" ) except Exception as err: self._current_state = STATE_ERROR self._last_error = str(err) self._error_count += 1 _LOGGER.error( "Error handling update for %s: %s", self.entity_id, err, exc_info=True, ) self.async_write_ha_state()