"""Conversation support for OpenAI."""

from collections.abc import Callable
import json
from typing import Any, Literal, cast

import openai
from openai._types import NOT_GIVEN
from openai.types.chat import (
    ChatCompletionAssistantMessageParam,
    ChatCompletionMessage,
    ChatCompletionMessageParam,
    ChatCompletionMessageToolCallParam,
    ChatCompletionToolMessageParam,
    ChatCompletionToolParam,
)
from openai.types.chat.chat_completion_message_tool_call_param import Function
from openai.types.shared_params import FunctionDefinition
from voluptuous_openapi import convert

from homeassistant.components import assist_pipeline, conversation
from homeassistant.config_entries import ConfigEntry
from homeassistant.const import CONF_LLM_HASS_API, MATCH_ALL
from homeassistant.core import HomeAssistant
from homeassistant.exceptions import HomeAssistantError
from homeassistant.helpers import device_registry as dr, intent, llm
from homeassistant.helpers.entity_platform import AddEntitiesCallback

from . import OpenAIConfigEntry
from .const import (
    CONF_CHAT_MODEL,
    CONF_MAX_TOKENS,
    CONF_PROMPT,
    CONF_TEMPERATURE,
    CONF_TOP_P,
    DOMAIN,
    LOGGER,
    RECOMMENDED_CHAT_MODEL,
    RECOMMENDED_MAX_TOKENS,
    RECOMMENDED_TEMPERATURE,
    RECOMMENDED_TOP_P,
)

# Max number of back and forth with the LLM to generate a response
MAX_TOOL_ITERATIONS = 10


async def async_setup_entry(
    hass: HomeAssistant,
    config_entry: OpenAIConfigEntry,
    async_add_entities: AddEntitiesCallback,
) -> None:
    """Set up conversation entities."""
    agent = OpenAIConversationEntity(config_entry)
    async_add_entities([agent])


def _format_tool(
    tool: llm.Tool, custom_serializer: Callable[[Any], Any] | None
) -> ChatCompletionToolParam:
    """Format tool specification."""
    tool_spec = FunctionDefinition(
        name=tool.name,
        parameters=convert(tool.parameters, custom_serializer=custom_serializer),
    )
    if tool.description:
        tool_spec["description"] = tool.description
    return ChatCompletionToolParam(type="function", function=tool_spec)


def _message_convert(message: ChatCompletionMessage) -> ChatCompletionMessageParam:
    """Convert from class to TypedDict."""
    tool_calls: list[ChatCompletionMessageToolCallParam] = []
    if message.tool_calls:
        tool_calls = [
            ChatCompletionMessageToolCallParam(
                id=tool_call.id,
                function=Function(
                    arguments=tool_call.function.arguments,
                    name=tool_call.function.name,
                ),
                type=tool_call.type,
            )
            for tool_call in message.tool_calls
        ]
    param = ChatCompletionAssistantMessageParam(
        role=message.role,
        content=message.content,
    )
    if tool_calls:
        param["tool_calls"] = tool_calls
    return param


def _chat_message_convert(
    message: conversation.ChatMessage[ChatCompletionMessageParam],
    agent_id: str | None,
) -> ChatCompletionMessageParam:
    """Convert any native chat message for this agent to the native format."""
    if message.native is not None and message.agent_id == agent_id:
        return message.native
    return cast(
        ChatCompletionMessageParam,
        {"role": message.role, "content": message.content},
    )


class OpenAIConversationEntity(
    conversation.ConversationEntity, conversation.AbstractConversationAgent
):
    """OpenAI conversation agent."""

    _attr_has_entity_name = True
    _attr_name = None

    def __init__(self, entry: OpenAIConfigEntry) -> None:
        """Initialize the agent."""
        self.entry = entry
        self._attr_unique_id = entry.entry_id
        self._attr_device_info = dr.DeviceInfo(
            identifiers={(DOMAIN, entry.entry_id)},
            name=entry.title,
            manufacturer="OpenAI",
            model="ChatGPT",
            entry_type=dr.DeviceEntryType.SERVICE,
        )
        if self.entry.options.get(CONF_LLM_HASS_API):
            self._attr_supported_features = (
                conversation.ConversationEntityFeature.CONTROL
            )

    @property
    def supported_languages(self) -> list[str] | Literal["*"]:
        """Return a list of supported languages."""
        return MATCH_ALL

    async def async_added_to_hass(self) -> None:
        """When entity is added to Home Assistant."""
        await super().async_added_to_hass()
        assist_pipeline.async_migrate_engine(
            self.hass, "conversation", self.entry.entry_id, self.entity_id
        )
        conversation.async_set_agent(self.hass, self.entry, self)
        self.entry.async_on_unload(
            self.entry.add_update_listener(self._async_entry_update_listener)
        )

    async def async_will_remove_from_hass(self) -> None:
        """When entity will be removed from Home Assistant."""
        conversation.async_unset_agent(self.hass, self.entry)
        await super().async_will_remove_from_hass()

    async def async_process(
        self, user_input: conversation.ConversationInput
    ) -> conversation.ConversationResult:
        """Process a sentence."""
        async with conversation.async_get_chat_session(
            self.hass, user_input
        ) as session:
            return await self._async_call_api(user_input, session)

    async def _async_call_api(
        self,
        user_input: conversation.ConversationInput,
        session: conversation.ChatSession[ChatCompletionMessageParam],
    ) -> conversation.ConversationResult:
        """Call the API."""
        options = self.entry.options

        try:
            await session.async_update_llm_data(
                DOMAIN,
                user_input,
                options.get(CONF_LLM_HASS_API),
                options.get(CONF_PROMPT),
            )
        except conversation.ConverseError as err:
            return err.as_conversation_result()

        tools: list[ChatCompletionToolParam] | None = None
        if session.llm_api:
            tools = [
                _format_tool(tool, session.llm_api.custom_serializer)
                for tool in session.llm_api.tools
            ]

        messages = [
            _chat_message_convert(message, user_input.agent_id)
            for message in session.async_get_messages()
        ]

        client = self.entry.runtime_data

        # To prevent infinite loops, we limit the number of iterations
        for _iteration in range(MAX_TOOL_ITERATIONS):
            try:
                result = await client.chat.completions.create(
                    model=options.get(CONF_CHAT_MODEL, RECOMMENDED_CHAT_MODEL),
                    messages=messages,
                    tools=tools or NOT_GIVEN,
                    max_tokens=options.get(CONF_MAX_TOKENS, RECOMMENDED_MAX_TOKENS),
                    top_p=options.get(CONF_TOP_P, RECOMMENDED_TOP_P),
                    temperature=options.get(CONF_TEMPERATURE, RECOMMENDED_TEMPERATURE),
                    user=session.conversation_id,
                )
            except openai.OpenAIError as err:
                LOGGER.error("Error talking to OpenAI: %s", err)
                raise HomeAssistantError("Error talking to OpenAI") from err

            LOGGER.debug("Response %s", result)
            response = result.choices[0].message
            messages.append(_message_convert(response))

            session.async_add_message(
                conversation.ChatMessage(
                    role=response.role,
                    agent_id=user_input.agent_id,
                    content=response.content or "",
                    native=messages[-1],
                ),
            )

            if not response.tool_calls or not session.llm_api:
                break

            for tool_call in response.tool_calls:
                tool_input = llm.ToolInput(
                    tool_name=tool_call.function.name,
                    tool_args=json.loads(tool_call.function.arguments),
                )
                tool_response = await session.async_call_tool(tool_input)
                messages.append(
                    ChatCompletionToolMessageParam(
                        role="tool",
                        tool_call_id=tool_call.id,
                        content=json.dumps(tool_response),
                    )
                )
                session.async_add_message(
                    conversation.ChatMessage(
                        role="native",
                        agent_id=user_input.agent_id,
                        content="",
                        native=messages[-1],
                    )
                )

        intent_response = intent.IntentResponse(language=user_input.language)
        intent_response.async_set_speech(response.content or "")
        return conversation.ConversationResult(
            response=intent_response, conversation_id=session.conversation_id
        )

    async def _async_entry_update_listener(
        self, hass: HomeAssistant, entry: ConfigEntry
    ) -> None:
        """Handle options update."""
        # Reload as we update device info + entity name + supported features
        await hass.config_entries.async_reload(entry.entry_id)