322 lines
11 KiB
Python
322 lines
11 KiB
Python
"""Conversation support for OpenAI."""
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from collections.abc import AsyncGenerator, Callable
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import json
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from typing import Any, Literal, cast
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import openai
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from openai._streaming import AsyncStream
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from openai._types import NOT_GIVEN
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from openai.types.chat import (
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ChatCompletionAssistantMessageParam,
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ChatCompletionChunk,
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ChatCompletionMessageParam,
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ChatCompletionMessageToolCallParam,
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ChatCompletionToolMessageParam,
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ChatCompletionToolParam,
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)
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from openai.types.chat.chat_completion_message_tool_call_param import Function
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from openai.types.shared_params import FunctionDefinition
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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.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
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from homeassistant.helpers import chat_session, device_registry as dr, intent, llm
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from homeassistant.helpers.entity_platform import AddConfigEntryEntitiesCallback
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from . import OpenAIConfigEntry
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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_REASONING_EFFORT,
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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_REASONING_EFFORT,
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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: OpenAIConfigEntry,
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async_add_entities: AddConfigEntryEntitiesCallback,
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) -> None:
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"""Set up conversation entities."""
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agent = OpenAIConversationEntity(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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def _convert_content_to_param(
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content: conversation.Content,
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) -> ChatCompletionMessageParam:
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"""Convert any native chat message for this agent to the native format."""
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if content.role == "tool_result":
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assert type(content) is conversation.ToolResultContent
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return ChatCompletionToolMessageParam(
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role="tool",
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tool_call_id=content.tool_call_id,
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content=json.dumps(content.tool_result),
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)
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if content.role != "assistant" or not content.tool_calls: # type: ignore[union-attr]
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role = content.role
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if role == "system":
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role = "developer"
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return cast(
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ChatCompletionMessageParam,
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{"role": content.role, "content": content.content}, # type: ignore[union-attr]
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)
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# Handle the Assistant content including tool calls.
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assert type(content) is conversation.AssistantContent
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return ChatCompletionAssistantMessageParam(
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role="assistant",
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content=content.content,
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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=json.dumps(tool_call.tool_args),
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name=tool_call.tool_name,
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),
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type="function",
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)
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for tool_call in content.tool_calls
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],
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)
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async def _transform_stream(
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result: AsyncStream[ChatCompletionChunk],
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) -> AsyncGenerator[conversation.AssistantContentDeltaDict]:
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"""Transform an OpenAI delta stream into HA format."""
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current_tool_call: dict | None = None
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async for chunk in result:
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LOGGER.debug("Received chunk: %s", chunk)
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choice = chunk.choices[0]
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if choice.finish_reason:
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if current_tool_call:
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yield {
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"tool_calls": [
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llm.ToolInput(
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id=current_tool_call["id"],
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tool_name=current_tool_call["tool_name"],
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tool_args=json.loads(current_tool_call["tool_args"]),
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)
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]
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}
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break
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delta = chunk.choices[0].delta
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# We can yield delta messages not continuing or starting tool calls
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if current_tool_call is None and not delta.tool_calls:
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yield { # type: ignore[misc]
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key: value
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for key in ("role", "content")
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if (value := getattr(delta, key)) is not None
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}
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continue
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# When doing tool calls, we should always have a tool call
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# object or we have gotten stopped above with a finish_reason set.
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if (
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not delta.tool_calls
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or not (delta_tool_call := delta.tool_calls[0])
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or not delta_tool_call.function
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):
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raise ValueError("Expected delta with tool call")
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if current_tool_call and delta_tool_call.index == current_tool_call["index"]:
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current_tool_call["tool_args"] += delta_tool_call.function.arguments or ""
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continue
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# We got tool call with new index, so we need to yield the previous
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if current_tool_call:
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yield {
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"tool_calls": [
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llm.ToolInput(
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id=current_tool_call["id"],
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tool_name=current_tool_call["tool_name"],
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tool_args=json.loads(current_tool_call["tool_args"]),
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)
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]
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}
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current_tool_call = {
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"index": delta_tool_call.index,
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"id": delta_tool_call.id,
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"tool_name": delta_tool_call.function.name,
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"tool_args": delta_tool_call.function.arguments or "",
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}
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class OpenAIConversationEntity(
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conversation.ConversationEntity, conversation.AbstractConversationAgent
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):
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"""OpenAI 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: OpenAIConfigEntry) -> None:
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"""Initialize the agent."""
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self.entry = entry
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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="OpenAI",
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model="ChatGPT",
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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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with (
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chat_session.async_get_chat_session(
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self.hass, user_input.conversation_id
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) as session,
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conversation.async_get_chat_log(self.hass, session, user_input) as chat_log,
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):
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return await self._async_handle_message(user_input, chat_log)
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async def _async_handle_message(
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self,
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user_input: conversation.ConversationInput,
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chat_log: conversation.ChatLog,
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) -> conversation.ConversationResult:
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"""Call the API."""
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options = self.entry.options
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try:
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await chat_log.async_update_llm_data(
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DOMAIN,
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user_input,
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options.get(CONF_LLM_HASS_API),
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options.get(CONF_PROMPT),
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)
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except conversation.ConverseError as err:
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return err.as_conversation_result()
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tools: list[ChatCompletionToolParam] | None = None
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if chat_log.llm_api:
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tools = [
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_format_tool(tool, chat_log.llm_api.custom_serializer)
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for tool in chat_log.llm_api.tools
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]
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model = options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL)
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messages = [_convert_content_to_param(content) for content in chat_log.content]
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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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model_args = {
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"model": model,
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"messages": messages,
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"tools": tools or NOT_GIVEN,
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"max_completion_tokens": options.get(
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CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS
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),
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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": chat_log.conversation_id,
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"stream": True,
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}
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if model.startswith("o"):
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model_args["reasoning_effort"] = options.get(
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CONF_REASONING_EFFORT, RECOMMENDED_REASONING_EFFORT
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)
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try:
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result = await client.chat.completions.create(**model_args)
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except openai.RateLimitError as err:
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LOGGER.error("Rate limited by OpenAI: %s", err)
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raise HomeAssistantError("Rate limited or insufficient funds") from err
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except openai.OpenAIError as err:
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LOGGER.error("Error talking to OpenAI: %s", err)
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raise HomeAssistantError("Error talking to OpenAI") from err
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messages.extend(
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[
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_convert_content_to_param(content)
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async for content in chat_log.async_add_delta_content_stream(
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user_input.agent_id, _transform_stream(result)
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)
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]
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)
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if not chat_log.unresponded_tool_results:
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break
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intent_response = intent.IntentResponse(language=user_input.language)
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assert type(chat_log.content[-1]) is conversation.AssistantContent
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intent_response.async_set_speech(chat_log.content[-1].content or "")
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return conversation.ConversationResult(
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response=intent_response, conversation_id=chat_log.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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