mirror of
https://github.com/home-assistant/core.git
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302 lines
9.1 KiB
Python
302 lines
9.1 KiB
Python
"""Conversation history."""
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from __future__ import annotations
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from collections.abc import AsyncGenerator, Generator
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from contextlib import contextmanager
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from dataclasses import dataclass, field, replace
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import logging
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import voluptuous as vol
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from homeassistant.core import HomeAssistant, callback
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from homeassistant.exceptions import HomeAssistantError, TemplateError
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from homeassistant.helpers import chat_session, intent, llm, template
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from homeassistant.util.hass_dict import HassKey
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from homeassistant.util.json import JsonObjectType
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from . import trace
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from .const import DOMAIN
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from .models import ConversationInput, ConversationResult
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DATA_CHAT_HISTORY: HassKey[dict[str, ChatLog]] = HassKey("conversation_chat_log")
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LOGGER = logging.getLogger(__name__)
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@contextmanager
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def async_get_chat_log(
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hass: HomeAssistant,
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session: chat_session.ChatSession,
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user_input: ConversationInput | None = None,
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) -> Generator[ChatLog]:
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"""Return chat log for a specific chat session."""
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all_history = hass.data.get(DATA_CHAT_HISTORY)
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if all_history is None:
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all_history = {}
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hass.data[DATA_CHAT_HISTORY] = all_history
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history = all_history.get(session.conversation_id)
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if history:
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history = replace(history, content=history.content.copy())
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else:
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history = ChatLog(hass, session.conversation_id)
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if user_input is not None:
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history.async_add_user_content(UserContent(content=user_input.text))
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last_message = history.content[-1]
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yield history
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if history.content[-1] is last_message:
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LOGGER.debug(
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"History opened but no assistant message was added, ignoring update"
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)
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return
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if session.conversation_id not in all_history:
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@callback
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def do_cleanup() -> None:
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"""Handle cleanup."""
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all_history.pop(session.conversation_id)
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session.async_on_cleanup(do_cleanup)
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all_history[session.conversation_id] = history
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class ConverseError(HomeAssistantError):
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"""Error during initialization of conversation.
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Will not be stored in the history.
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"""
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def __init__(
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self, message: str, conversation_id: str, response: intent.IntentResponse
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) -> None:
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"""Initialize the error."""
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super().__init__(message)
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self.conversation_id = conversation_id
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self.response = response
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def as_conversation_result(self) -> ConversationResult:
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"""Return the error as a conversation result."""
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return ConversationResult(
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response=self.response,
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conversation_id=self.conversation_id,
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)
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@dataclass(frozen=True)
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class SystemContent:
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"""Base class for chat messages."""
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role: str = field(init=False, default="system")
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content: str
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@dataclass(frozen=True)
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class UserContent:
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"""Assistant content."""
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role: str = field(init=False, default="user")
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content: str
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@dataclass(frozen=True)
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class AssistantContent:
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"""Assistant content."""
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role: str = field(init=False, default="assistant")
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agent_id: str
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content: str
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tool_calls: list[llm.ToolInput] | None = None
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@dataclass(frozen=True)
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class ToolResultContent:
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"""Tool result content."""
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role: str = field(init=False, default="tool_result")
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agent_id: str
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tool_call_id: str
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tool_name: str
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tool_result: JsonObjectType
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Content = SystemContent | UserContent | AssistantContent | ToolResultContent
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@dataclass
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class ChatLog:
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"""Class holding the chat history of a specific conversation."""
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hass: HomeAssistant
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conversation_id: str
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content: list[Content] = field(default_factory=lambda: [SystemContent(content="")])
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extra_system_prompt: str | None = None
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llm_api: llm.APIInstance | None = None
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@callback
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def async_add_user_content(self, content: UserContent) -> None:
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"""Add user content to the log."""
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self.content.append(content)
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@callback
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def async_add_assistant_content_without_tools(
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self, content: AssistantContent
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) -> None:
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"""Add assistant content to the log."""
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if content.tool_calls is not None:
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raise ValueError("Tool calls not allowed")
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self.content.append(content)
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async def async_add_assistant_content(
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self, content: AssistantContent
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) -> AsyncGenerator[ToolResultContent]:
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"""Add assistant content."""
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self.content.append(content)
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if content.tool_calls is None:
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return
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if self.llm_api is None:
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raise ValueError("No LLM API configured")
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for tool_input in content.tool_calls:
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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_result = await self.llm_api.async_call_tool(tool_input)
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except (HomeAssistantError, vol.Invalid) as e:
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tool_result = {"error": type(e).__name__}
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if str(e):
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tool_result["error_text"] = str(e)
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LOGGER.debug("Tool response: %s", tool_result)
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response_content = ToolResultContent(
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agent_id=content.agent_id,
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tool_call_id=tool_input.id,
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tool_name=tool_input.tool_name,
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tool_result=tool_result,
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)
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self.content.append(response_content)
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yield response_content
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async def async_update_llm_data(
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self,
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conversing_domain: str,
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user_input: ConversationInput,
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user_llm_hass_api: str | None = None,
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user_llm_prompt: str | None = None,
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) -> None:
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"""Set the LLM system prompt."""
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llm_context = llm.LLMContext(
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platform=conversing_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=DOMAIN,
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device_id=user_input.device_id,
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)
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llm_api: llm.APIInstance | None = None
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if user_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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user_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(
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"Error getting LLM API %s for %s: %s",
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user_llm_hass_api,
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conversing_domain,
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err,
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)
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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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"Error preparing LLM API",
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)
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raise ConverseError(
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f"Error getting LLM API {user_llm_hass_api}",
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conversation_id=self.conversation_id,
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response=intent_response,
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) from err
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user_name: str | None = None
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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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+ (user_llm_prompt or 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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"Sorry, I had a problem with my template",
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)
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raise ConverseError(
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"Error rendering prompt",
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conversation_id=self.conversation_id,
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response=intent_response,
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) from err
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if llm_api:
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prompt_parts.append(llm_api.api_prompt)
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extra_system_prompt = (
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# Take new system prompt if one was given
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user_input.extra_system_prompt or self.extra_system_prompt
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)
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if extra_system_prompt:
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prompt_parts.append(extra_system_prompt)
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prompt = "\n".join(prompt_parts)
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self.llm_api = llm_api
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self.extra_system_prompt = extra_system_prompt
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self.content[0] = SystemContent(content=prompt)
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LOGGER.debug("Prompt: %s", self.content)
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LOGGER.debug("Tools: %s", self.llm_api.tools if self.llm_api else None)
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trace.async_conversation_trace_append(
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trace.ConversationTraceEventType.AGENT_DETAIL,
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{
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"messages": self.content,
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"tools": self.llm_api.tools if self.llm_api else None,
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},
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)
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