# -*- coding: utf-8 -*-
"""
预定航班工作流（范式）
"""
import asyncio
import datetime
from typing import AsyncGenerator, cast

from pydantic import BaseModel, Field, field_validator, TypeAdapter
from pydantic_ai import (
    Agent,
    ApprovalRequired,
    DeferredToolRequests,
    DeferredToolResults,
    ModelMessage,
    ModelRetry,
    ModelSettings,
    RunContext,
    RunUsage,
    UsageLimits,
)
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider
from pydantic_ai.run import AgentRunResultEvent, AgentRunResult
from enum import StrEnum
from pydantic_ai._uuid import uuid7
from pydantic_ai.messages import (
    AgentStreamEvent,
    FunctionToolCallEvent,
    FunctionToolResultEvent,
    LoadCapabilityCallPart,
    PartDeltaEvent,
    PartEndEvent,
    PartStartEvent,
    TextPart,
    TextPartDelta,
    ThinkingPart,
    ThinkingPartDelta,
    ToolCallPart,
    ToolSearchCallPart,
    ToolReturnPart,
)


class TaskStatus(StrEnum):
    """
    任务状态枚举
    """

    RUNNING = "running"
    DONE = "done"
    ERROR = "error"
    PENDING_APPROVAL = "pending_approval"


class Task(BaseModel):
    """
    任务类
    """

    tool_name: str = Field(..., description="工具名称")
    tool_call_id: str = Field(..., description="工具调用唯一标识")
    status: TaskStatus = Field(default=TaskStatus.RUNNING, description="任务状态")
    title: str = Field(default="", description="任务标题")
    content: str = Field(default="", description="任务内容")


class MessageType(StrEnum):
    """
    消息类型枚举
    """

    USER_PROMPT = "user_prompt"
    THINKING = "thinking"
    WORK_OUTPUT = "work_output"
    RESULT_OUTPUT = "result_output"
    TEXT = "text"


class AgentRunWarmUpEvent(BaseModel):
    """
    智能体运行预热事件类
    """

    content: str = Field(
        default="",
        description="预热内容",
    )


class Message(BaseModel):
    """
    消息类
    """

    id: str = Field(default_factory=lambda: str(uuid7()), description="消息唯一标识")
    type: MessageType = Field(..., description="消息类型")
    title: str = Field(default="", description="消息标题")
    content: str = Field(default="", description="消息内容")
    tasks: dict[str, Task] = Field(
        default_factory=dict, description="任务字典，键为工具调用唯一标识"
    )
    is_running: bool = Field(
        default=False, description="正在运行，True 表示正在运行，False 表示运行完成"
    )
    is_shown: bool = Field(
        default=False, description="展示组件，True 表示展示，False 表示隐藏"
    )


DEEPSEEK_V4_FLASH_MODEL = OpenAIChatModel(
    model_name="deepseek-v4-flash",
    provider=OpenAIProvider(
        base_url="https://tokenhub.tencentmaas.com/v1",
        api_key="sk-D9Y1mCe8VlvNqLuSC4mAjqEwxJ2nW4C0h8a7EPn8kg9RLsHq",
    ),
)

MODEL_SETTINGS = ModelSettings(
    temperature=0, extra_body={"thinking": {"type": "disabled"}}  # 温度控制
)  # 禁用思考模式


class Flight(BaseModel):
    """
    航班类
    """

    number: str = Field(..., description="航班号")
    date: datetime.date = Field(..., description="日期")
    origin_airport_code: str = Field(..., description="出发机场代码")
    destination_airport_code: str = Field(..., description="到达机场代码")
    airfare: int = Field(..., description="机票价格")

    @field_validator("origin_airport_code", "destination_airport_code")
    @classmethod
    def validate_airport_code(cls, airport_code: str) -> str:
        """校验机场代码"""
        if (
            not airport_code.isalpha()
            or not airport_code.isupper()
            or len(airport_code) != 3
        ):
            raise ValueError(f"机场代码须为英文、大写、3位字符串")
        return airport_code


class NoResult(BaseModel):
    """
    无结果类
    """

    ...


class Deps(BaseModel):
    """
    依赖类
    """

    date: datetime.date = Field(..., description="日期")
    origin_airport_code: str = Field(..., description="出发机场代码")
    destination_airport_code: str = Field(..., description="到达机场代码")
    searched_flights: list[Flight] | None = Field(
        default=None, description="查询到的航班"
    )
    extracted_flight_number: str | None = Field(
        default=None, description="提取到的航班号"
    )
    booked_flight: Flight | None = Field(default=None, description="预定到的航班")


# 主智能体
agent = Agent[Deps, Flight | NoResult | DeferredToolRequests](
    model=DEEPSEEK_V4_FLASH_MODEL,
    model_settings=MODEL_SETTINGS,
    deps_type=Deps,
    output_type=Flight | NoResult | DeferredToolRequests,
    system_prompt=(
        "你的任务是帮助用户查询并预定航班，**必须按照下述步骤执行**：",
        "1. 使用 search_flights 查询满足用户需求的航班；",
        "2. 使用 book_flight 预定航班。若未选择到航班则返回 NoSelectedFlight；",
    ),
)


# 提取所有航班信息智能体
extraction_flights_agent = Agent[Deps, list[Flight]](
    model=DEEPSEEK_V4_FLASH_MODEL,
    model_settings=MODEL_SETTINGS,
    deps_type=Deps,
    output_type=list[Flight],
    system_prompt=(
        "你的任务是在来源资料中提取所有航班信息，包括航班号、日期、出发机场代码、到达机场代码和机票价格。",
        "其中，出发机场代码和到达机场代码须为英文、大写、3位字符串，例如 San Francisco International Airport (SFO) 的机场代码为 SFO。",
        "若某航班信息不全则跳过该航班，若没有任何航班信息则返回空列表。",
        "禁止编造。",
    ),
)

# 提取航班号智能体
extraction_flight_number_agent = Agent[Deps, str | None](
    model=DEEPSEEK_V4_FLASH_MODEL,
    model_settings=MODEL_SETTINGS,
    deps_type=Deps,
    output_type=str | None,
    system_prompt=(
        "你的任务是从用户提示词中提取航班号且须在查询到的航班中。",
        "其中，航班号须由英文、数字和短横线组成、大写，例如 SFO-AK123。",
        "若用户提示词中没有航班号则返回 None。",
        "禁止编造。",
    ),
)


source_material = """
1. Flight SFO-AK123
- Price: $350
- Origin: San Francisco International Airport (SFO)
- Destination: Ted Stevens Anchorage International Airport (ANC)
- Date: January 10, 2025
2. Flight SFO-AK456
- Price: $370
- Origin: San Francisco International Airport (SFO)
- Destination: Fairbanks International Airport (FAI)
- Date: January 10, 2025
3. Flight SFO-AK789
- Price: $400
- Origin: San Francisco International Airport (SFO)
- Destination: Juneau International Airport (JNU)
- Date: January 20, 2025
4. Flight NYC-LA101
- Price: $250
- Origin: San Francisco International Airport (SFO)
- Destination: Ted Stevens Anchorage International Airport (ANC)
- Date: January 10, 2025
5. Flight CHI-MIA202
- Price: $200
- Origin: Chicago O'Hare International Airport (ORD)
- Destination: Miami International Airport (MIA)
- Date: January 12, 2025
6. Flight BOS-SEA303
- Price: $120
- Origin: Boston Logan International Airport (BOS)
- Destination: Ted Stevens Anchorage International Airport (ANC)
- Date: January 12, 2025
7. Flight DFW-DEN404
- Price: $150
- Origin: Dallas/Fort Worth International Airport (DFW)
- Destination: Denver International Airport (DEN)
- Date: January 10, 2025
8. Flight ATL-HOU505
- Price: $180
- Origin: Hartsfield-Jackson Atlanta International Airport (ATL)
- Destination: George Bush Intercontinental Airport (IAH)
- Date: January 10, 2025
"""


@agent.tool(name="查询航班")
async def search_flights(ctx: RunContext[Deps]) -> list[Flight]:
    """
    查询航班
    **如何提高提取准确率**
    1. 系统提示词规则约束
    2. 降低模型温度
    3. 输出类型约定和输出模型校验
    4. 业务规则约束（例如，输出不可为空列表）

    **设计工具需先设计业务流程**
    本示例按照 查询航班 -> 推荐航班 -> 预定航班
    """
    # 提取到的所有航班信息
    extracted_flights = (
        await extraction_flights_agent.run(
            f"来源资料：\n{source_material}",
            deps=ctx.deps,
            usage=ctx.usage,
            usage_limits=UsageLimits(request_limit=10),
        )
    ).output
    if not extracted_flights:  # 模拟业务规则约束：提取到的所有航班信息不可能为空
        raise ModelRetry(f"提取到的所有航班信息不可能为空")

    # 查询到的航班
    ctx.deps.searched_flights = sorted(
        [
            flight
            for flight in extracted_flights
            if flight.date == ctx.deps.date
            and flight.origin_airport_code == ctx.deps.origin_airport_code
            and flight.destination_airport_code == ctx.deps.destination_airport_code
        ],
        key=lambda flight: flight.airfare,
    )
    return ctx.deps.searched_flights


@agent.tool(name="预定航班")
async def book_flight(ctx: RunContext[Deps]) -> Flight | NoResult:
    """
    预定航班
    """
    if (searched_flights := ctx.deps.searched_flights) is None:
        raise ModelRetry("必须先使用 search_flights 查询航班")

    if not ctx.tool_call_approved:
        raise ApprovalRequired()

    # 提取到的航班号
    ctx.deps.extracted_flight_number = (
        await extraction_flight_number_agent.run(
            f"用户提示词：\n{ctx.prompt}\n查询到的航班：\n{(flight_numbers:= [flight.number for flight in searched_flights])}",
            deps=ctx.deps,
            usage=ctx.usage,
            usage_limits=UsageLimits(request_limit=10),
        )
    ).output
    if not ctx.deps.extracted_flight_number:
        return NoResult()
    if ctx.deps.extracted_flight_number not in flight_numbers:
        raise ModelRetry(
            f"提取到的航班号 {ctx.deps.extracted_flight_number} 不在查询到的航班中"
        )
    # 预定到的航班
    ctx.deps.booked_flight = next(
        flight
        for flight in searched_flights
        if flight.number == ctx.deps.extracted_flight_number
    )
    return ctx.deps.booked_flight


@agent.output_validator
async def validate_output(
    ctx: RunContext[Deps],
    output: Flight | NoResult | DeferredToolRequests,
) -> Flight | NoResult | DeferredToolRequests:
    """
    输出校验
    """
    if isinstance(output, (NoResult, DeferredToolRequests)):
        return output

    errors = []
    if output.date != ctx.deps.date:
        errors.append(f"航班日期应为 {ctx.deps.date}, 不是 {output.date}")
    if output.origin_airport_code != ctx.deps.origin_airport_code:
        errors.append(
            f"航班出发机场应为 {ctx.deps.origin_airport_code}, 不是 {output.origin_airport_code}"
        )
    if output.destination_airport_code != ctx.deps.destination_airport_code:
        errors.append(
            f"航班到达机场应为 {ctx.deps.destination_airport_code}, 不是 {output.destination_airport_code}"
        )
    if errors:
        raise ModelRetry("\n".join(errors))
    return output


async def run_stream_events(
    deps: Deps,
    user_prompt: str,
    message_history: list[ModelMessage],
    usage: RunUsage,
    deferred_tool_results: DeferredToolResults | None = None,
) -> AsyncGenerator[
    AgentStreamEvent
    | AgentRunResultEvent
    | AgentRunWarmUpEvent
    | Flight
    | NoResult
    | DeferredToolRequests,
    None,
]:
    # 构建智能体运行预热事件
    yield AgentRunWarmUpEvent(
        content=f"正在预定 {deps.date.strftime('%Y-%m-%d')} 从 {deps.origin_airport_code} 到 {deps.destination_airport_code} 的航班"
    )
    tool_names = set()
    async with agent.run_stream_events(
        user_prompt=user_prompt,
        deps=deps,
        message_history=message_history,
        usage=usage,
        deferred_tool_results=deferred_tool_results,
    ) as events:
        async for event in events:
            print(event)
            match event:
                case PartStartEvent(
                    part=part,
                ):
                    match part:
                        case ToolCallPart(tool_name=tool_name):
                            match tool_name:
                                case "查询航班" | "预定航班":
                                    if tool_name not in tool_names:
                                        tool_names.add(tool_name)
                                        yield event

                case FunctionToolResultEvent(part):
                    match part:
                        case ToolReturnPart(
                            tool_name=tool_name,
                            content=content,
                        ):
                            match tool_name:
                                case "查询航班":
                                    # 查询到的航班
                                    searched_flights = cast(list[Flight], content)
                                    event.part.content = f"已查询到 **{len(searched_flights)} 班航班**：\n"
                                    for searched_flight in searched_flights:
                                        event.part.content += f"{searched_flight.number} {searched_flight.airfare} 于 {searched_flight.date.strftime('%Y-%m-%d')} 从 {searched_flight.origin_airport_code} 到 {searched_flight.destination_airport_code}\n"
                                    yield event

                                case "预定航班":
                                    if isinstance(content, NoResult):
                                        event.part.content = "未查询到符合条件的航班"

                                    if isinstance(content, Flight):
                                        event.part.content = f"已预定航班：\n{content.number} {content.airfare} 于 {content.date.strftime('%Y-%m-%d')} 从 {content.origin_airport_code} 到 {content.destination_airport_code}\n"
                                    yield event

                case AgentRunResultEvent(
                    result=result,
                ):
                    match result:
                        case AgentRunResult(output=output):
                            match output:
                                case DeferredToolRequests(approvals=approvals):
                                    for approval in approvals:
                                        output = approvals
                                        yield event


async def main():
    # 实例化依赖
    deps = Deps(
        date=datetime.date(2025, 1, 10),
        origin_airport_code="SFO",
        destination_airport_code="ANC",
    )
    user_prompt = f"帮我查询并预定在 {deps.date.strftime('%Y-%m-%d')} 从 {deps.origin_airport_code} 到 {deps.destination_airport_code} 的航班"
    message_history: list[ModelMessage] = []
    events = run_stream_events(
        deps=deps,
        user_prompt=user_prompt,
        message_history=message_history,
        usage=RunUsage(),
    )
    # 消费异步生成器
    async for event in events:
        print()
        if isinstance(event, AgentRunResultEvent):
            # 保存本次运行新增消息
            message_history.extend(event.result.new_messages())
        if isinstance(event, Message):
            print(event)


asyncio.run(main())