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"""Conversation support for Groq Cloud."""
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from collections.abc import Callable
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import json
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from typing import Any, Literal
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import groq
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from groq._types import NOT_GIVEN
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from groq.types.chat import (
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ChatCompletionAssistantMessageParam,
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ChatCompletionMessage,
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ChatCompletionMessageParam,
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ChatCompletionMessageToolCallParam,
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ChatCompletionSystemMessageParam,
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ChatCompletionToolMessageParam,
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ChatCompletionToolParam,
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ChatCompletionUserMessageParam,
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)
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from groq.types.chat.chat_completion_message_tool_call_param import Function
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from groq.types.shared_params import FunctionDefinition
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import voluptuous as vol
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from voluptuous_openapi import convert
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from homeassistant.components import assist_pipeline, conversation
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from homeassistant.components.conversation import trace
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from homeassistant.config_entries import ConfigEntry
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from homeassistant.const import CONF_LLM_HASS_API, MATCH_ALL
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from homeassistant.core import HomeAssistant
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from homeassistant.exceptions import HomeAssistantError, TemplateError
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from homeassistant.helpers import device_registry as dr, intent, llm, template
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from homeassistant.helpers.entity_platform import AddEntitiesCallback
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from homeassistant.util import ulid
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from . import GroqConfigEntry
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from .const import (
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CONF_CHAT_MODEL,
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CONF_MAX_TOKENS,
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CONF_PROMPT,
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CONF_TEMPERATURE,
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CONF_TOP_P,
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DOMAIN,
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LOGGER,
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RECOMMENDED_CHAT_MODEL,
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RECOMMENDED_MAX_TOKENS,
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RECOMMENDED_TEMPERATURE,
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RECOMMENDED_TOP_P,
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)
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# Max number of back and forth with the LLM to generate a response
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MAX_TOOL_ITERATIONS = 10
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async def async_setup_entry(
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hass: HomeAssistant,
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config_entry: GroqConfigEntry,
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async_add_entities: AddEntitiesCallback,
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) -> None:
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"""Set up conversation entities."""
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agent = GroqConversationEntity(config_entry)
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async_add_entities([agent])
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def _format_tool(
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tool: llm.Tool, custom_serializer: Callable[[Any], Any] | None
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) -> ChatCompletionToolParam:
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"""Format tool specification."""
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tool_spec = FunctionDefinition(
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name=tool.name,
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parameters=convert(tool.parameters, custom_serializer=custom_serializer),
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)
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if tool.description:
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tool_spec["description"] = tool.description
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return ChatCompletionToolParam(type="function", function=tool_spec)
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class GroqConversationEntity(
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conversation.ConversationEntity, conversation.AbstractConversationAgent
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):
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"""Groq conversation agent."""
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_attr_has_entity_name = True
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_attr_name = None
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def __init__(self, entry: GroqConfigEntry) -> None:
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"""Initialize the agent."""
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self.entry = entry
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self.history: dict[str, list[ChatCompletionMessageParam]] = {}
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self._attr_unique_id = entry.entry_id
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self._attr_device_info = dr.DeviceInfo(
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identifiers={(DOMAIN, entry.entry_id)},
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name=entry.title,
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manufacturer="Groq",
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model="Groq Cloud",
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entry_type=dr.DeviceEntryType.SERVICE,
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)
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if self.entry.options.get(CONF_LLM_HASS_API):
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self._attr_supported_features = (
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conversation.ConversationEntityFeature.CONTROL
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)
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@property
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def supported_languages(self) -> list[str] | Literal["*"]:
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"""Return a list of supported languages."""
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return MATCH_ALL
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async def async_added_to_hass(self) -> None:
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"""When entity is added to Home Assistant."""
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await super().async_added_to_hass()
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assist_pipeline.async_migrate_engine(
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self.hass, "conversation", self.entry.entry_id, self.entity_id
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)
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conversation.async_set_agent(self.hass, self.entry, self)
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self.entry.async_on_unload(
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self.entry.add_update_listener(self._async_entry_update_listener)
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)
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async def async_will_remove_from_hass(self) -> None:
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"""When entity will be removed from Home Assistant."""
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conversation.async_unset_agent(self.hass, self.entry)
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await super().async_will_remove_from_hass()
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async def async_process(
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self, user_input: conversation.ConversationInput
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) -> conversation.ConversationResult:
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"""Process a sentence."""
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options = self.entry.options
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intent_response = intent.IntentResponse(language=user_input.language)
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llm_api: llm.APIInstance | None = None
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tools: list[ChatCompletionToolParam] | None = None
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user_name: str | None = None
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llm_context = llm.LLMContext(
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platform=DOMAIN,
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context=user_input.context,
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user_prompt=user_input.text,
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language=user_input.language,
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assistant=conversation.DOMAIN,
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device_id=user_input.device_id,
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)
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if options.get(CONF_LLM_HASS_API):
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try:
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llm_api = await llm.async_get_api(
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self.hass,
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options[CONF_LLM_HASS_API],
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llm_context,
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)
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except HomeAssistantError as err:
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LOGGER.error("Error getting LLM API: %s", err)
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intent_response.async_set_error(
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intent.IntentResponseErrorCode.UNKNOWN,
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f"Error preparing LLM API: {err}",
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)
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return conversation.ConversationResult(
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response=intent_response, conversation_id=user_input.conversation_id
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)
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tools = [
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_format_tool(tool, llm_api.custom_serializer) for tool in llm_api.tools
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]
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if user_input.conversation_id is None:
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conversation_id = ulid.ulid_now()
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messages = []
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elif user_input.conversation_id in self.history:
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conversation_id = user_input.conversation_id
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messages = self.history[conversation_id]
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else:
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# Conversation IDs are ULIDs. We generate a new one if not provided.
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# If an old OLID is passed in, we will generate a new one to indicate
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# a new conversation was started. If the user picks their own, they
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# want to track a conversation and we respect it.
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try:
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ulid.ulid_to_bytes(user_input.conversation_id)
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conversation_id = ulid.ulid_now()
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except ValueError:
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conversation_id = user_input.conversation_id
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messages = []
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if (
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user_input.context
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and user_input.context.user_id
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and (
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user := await self.hass.auth.async_get_user(user_input.context.user_id)
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)
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):
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user_name = user.name
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try:
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prompt_parts = [
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template.Template(
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llm.BASE_PROMPT
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+ options.get(CONF_PROMPT, llm.DEFAULT_INSTRUCTIONS_PROMPT),
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self.hass,
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).async_render(
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{
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"ha_name": self.hass.config.location_name,
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"user_name": user_name,
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"llm_context": llm_context,
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},
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parse_result=False,
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)
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]
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except TemplateError as err:
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LOGGER.error("Error rendering prompt: %s", err)
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intent_response = intent.IntentResponse(language=user_input.language)
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intent_response.async_set_error(
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intent.IntentResponseErrorCode.UNKNOWN,
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f"Sorry, I had a problem with my template: {err}",
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)
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return conversation.ConversationResult(
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response=intent_response, conversation_id=conversation_id
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)
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if llm_api:
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prompt_parts.append(llm_api.api_prompt)
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prompt = "\n".join(prompt_parts)
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# Create a copy of the variable because we attach it to the trace
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messages = [
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ChatCompletionSystemMessageParam(role="system", content=prompt),
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*messages[1:],
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ChatCompletionUserMessageParam(role="user", content=user_input.text),
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]
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LOGGER.debug("Prompt: %s", messages)
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LOGGER.debug("Tools: %s", tools)
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trace.async_conversation_trace_append(
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trace.ConversationTraceEventType.AGENT_DETAIL,
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{"messages": messages, "tools": llm_api.tools if llm_api else None},
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)
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client = self.entry.runtime_data
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# To prevent infinite loops, we limit the number of iterations
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for _iteration in range(MAX_TOOL_ITERATIONS):
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try:
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result = await client.chat.completions.create(
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model=options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL),
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messages=messages,
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tools=tools or NOT_GIVEN,
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max_tokens=options.get(CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS),
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top_p=options.get(CONF_TOP_P, RECOMMENDED_TOP_P),
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temperature=options.get(CONF_TEMPERATURE, RECOMMENDED_TEMPERATURE),
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user=conversation_id,
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)
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except groq.GroqError as err:
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intent_response = intent.IntentResponse(language=user_input.language)
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intent_response.async_set_error(
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intent.IntentResponseErrorCode.UNKNOWN,
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f"Sorry, I had a problem talking to Groq: {err}",
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)
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return conversation.ConversationResult(
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response=intent_response, conversation_id=conversation_id
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)
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LOGGER.debug("Response %s", result)
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response = result.choices[0].message
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def message_convert(
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message: ChatCompletionMessage,
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) -> ChatCompletionMessageParam:
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"""Convert from class to TypedDict."""
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tool_calls: list[ChatCompletionMessageToolCallParam] = []
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if message.tool_calls:
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tool_calls = [
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ChatCompletionMessageToolCallParam(
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id=tool_call.id,
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function=Function(
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arguments=tool_call.function.arguments,
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name=tool_call.function.name,
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),
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type=tool_call.type,
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)
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for tool_call in message.tool_calls
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]
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param = ChatCompletionAssistantMessageParam(
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role=message.role,
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content=message.content,
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)
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if tool_calls:
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param["tool_calls"] = tool_calls
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return param
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messages.append(message_convert(response))
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tool_calls = response.tool_calls
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if not tool_calls or not llm_api:
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break
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for tool_call in tool_calls:
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tool_input = llm.ToolInput(
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tool_name=tool_call.function.name,
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tool_args=json.loads(tool_call.function.arguments),
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)
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LOGGER.debug(
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"Tool call: %s(%s)", tool_input.tool_name, tool_input.tool_args
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)
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try:
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tool_response = await llm_api.async_call_tool(tool_input)
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except (HomeAssistantError, vol.Invalid) as e:
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tool_response = {"error": type(e).__name__}
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if str(e):
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tool_response["error_text"] = str(e)
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LOGGER.debug("Tool response: %s", tool_response)
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messages.append(
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ChatCompletionToolMessageParam(
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role="tool",
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tool_call_id=tool_call.id,
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content=json.dumps(tool_response),
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)
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)
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self.history[conversation_id] = messages
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intent_response = intent.IntentResponse(language=user_input.language)
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intent_response.async_set_speech(response.content or "")
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return conversation.ConversationResult(
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response=intent_response, conversation_id=conversation_id
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)
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async def _async_entry_update_listener(
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self, hass: HomeAssistant, entry: ConfigEntry
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) -> None:
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"""Handle options update."""
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# Reload as we update device info + entity name + supported features
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await hass.config_entries.async_reload(entry.entry_id)
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