# -*- coding: utf-8 -*-
"""
智能体模块
"""

# 列举导入模块
from pathlib import Path

from typing import List, Optional, Union, cast

from starlette.applications import Starlette
from pydantic_ai import Agent as BaseAgent, AgentRunResult
from pydantic_ai.models import Model
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.capabilities import AgentCapability
from pydantic_ai.output import OutputSpec
from pydantic_ai.providers.openai import OpenAIProvider
from pydantic_ai.ui._web.api import ConfigureFrontend, ModelInfo, BuiltinToolInfo
from pydantic_ai_skills import SkillsCapability

from starlette.routing import Route
from starlette.requests import Request
from starlette.responses import Response




class Agent:
    """
    智能体，支持：
    1）实例智能体
    2）异步运行
    """

    def __init__(
        self,
        instructions: str,
        output_type: OutputSpec = str,
        capabilities: Optional[List[AgentCapability]] = None,
    ):
        """
        初始化智能体
        :param instructions: 指令
        :param skills: 智能体技能列表，默认为不使用技能
        :param output_type: 输出类型
        :return: 智能体实例
        """
        # 引入相应模块
        from uuid import uuid4
        from .memory import Memory

        # 创建智能体
        self.agent = self._create_agent(
            instructions=instructions,
            capabilities=capabilities,
            output_type=output_type,
        )

        # 生成会话唯一标识
        self.session_id = uuid4().hex.lower()

        # 实例记忆体
        self.memory = Memory()

    def _create_agent(
        self,
        instructions: str,
        capabilities: Optional[List[AgentCapability]],
        output_type: OutputSpec,
    ) -> BaseAgent:
        """
        创建智能体
        :param instructions: 指令
        :param capabilities: 智能体能力列表
        :param output_type: 输出类型
        :return: 智能体实例
        """
        agent = BaseAgent(
            model=OpenAIChatModel(
                model_name="deepseek-v4-flash",
                provider=OpenAIProvider(
                    base_url="https://tokenhub.tencentmaas.com/v1",
                    api_key="sk-D9Y1mCe8VlvNqLuSC4mAjqEwxJ2nW4C0h8a7EPn8kg9RLsHq",
                ),
            ),
            instructions=instructions,
            capabilities=capabilities,
            output_type=output_type,
            retries=1,
        )
        return agent

    async def run(self, user_prompt: str | List[str]) -> AgentRunResult:
        """
        异步运行
        :param user_prompt: 用户提示词
        :return: 智能体回复
        """
        # 查询会话历史消息
        message_history = self.memory.read(session_id=self.session_id)
        result = await self.agent.run(
            user_prompt=user_prompt, message_history=message_history
        )
        # 记录会话历史消息
        self.memory.create(
            session_id=self.session_id,
            dialogue_message=result.new_messages(),
        )
        return result

    def start_starlette_app(self) -> None:
        """
        启动 Starlette 应用，为智能体提供网页交互式对话界面
        :return: None
        """
        self.agent.to_web()

        model = cast(Model, self.agent.model)

        model_infos = [ModelInfo(id=model.model_id, name=model.label, builtin_tools=[])]

        async def options_chat(request: Request) -> Response:
            """处理 OPTIONS 请求"""
            return Response()

        async def configure_frontend(request: Request) -> Response:
            """向前端提供模型和技能"""
            config = ConfigureFrontend(
                models=[
                    ModelInfo(
                        id=model.model_id,
                        name=model.label,
                        builtin_tools=model.profile.supported_builtin_tools,
                    )
                ],
                builtin_tools=[],
            )
            return JSONResponse(config.model_dump(by_alias=True))

        Starlette(
            routes=[
                Route("/chat", options_chat, methods=["OPTIONS"]),
                Route("/chat", post_chat, methods=["POST"]),
                Route("/configure", configure_frontend, methods=["GET"]),
                Route("/health", health, methods=["GET"]),
            ]
        )


a = Agent(instructions="你是一个专业的翻译")

print(a)