import json
import os
from typing import Any, Dict

from openai import AsyncOpenAI


_client: AsyncOpenAI | None = None


def get_ai_client() -> AsyncOpenAI:
    """
    Create (or reuse) a singleton AsyncOpenAI client.

    The client is configured via:
    - AI_API_KEY / OPENAI_API_KEY
    - AI_BASE_URL (optional, defaults to official OpenAI endpoint)
    - AI_MODEL (optional, defaults to gpt-4.1-mini or a similar capable model)
    """
    global _client
    if _client is not None:
        return _client

    api_key = os.getenv("AI_API_KEY") or os.getenv("OPENAI_API_KEY")
    if not api_key:
        raise RuntimeError("AI_API_KEY or OPENAI_API_KEY must be set in environment.")

    base_url = os.getenv("AI_BASE_URL")  # can point to OpenAI, DeepSeek, Qwen, etc.

    _client = AsyncOpenAI(
        api_key=api_key,
        base_url=base_url or None,
    )
    return _client


def _build_requirement_prompt(raw_text: str) -> str:
    """
    Build a clear system/user prompt for requirement analysis.
    The model must output valid JSON only.
    """
    return (
        "你是一名资深的系统架构师，请阅读以下来自客户的原始需求文本，"
        "提炼出清晰的交付方案，并严格按照指定 JSON 结构输出。\n\n"
        "【要求】\n"
        "1. 按功能模块拆分需求。\n"
        "2. 每个模块给出简要说明和技术实现思路。\n"
        "3. 估算建议工时（以人天或人小时为单位，使用数字）。\n"
        "4. 可以根据你的经验给出每个模块的单价与小计金额，并给出总金额，"
        "方便后续生成报价单。\n\n"
        "【返回格式】请只返回 JSON，不要包含任何额外说明文字：\n"
        "{\n"
        '  "modules": [\n'
        "    {\n"
        '      "name": "模块名称",\n'
        '      "description": "模块说明（可以为 Markdown 格式）",\n'
        '      "technical_approach": "技术实现思路（Markdown 格式）",\n'
        '      "estimated_hours": 16,\n'
        '      "unit_price": 800,\n'
        '      "subtotal": 12800\n'
        "    }\n"
        "  ],\n"
        '  "total_estimated_hours": 40,\n'
        '  "total_amount": 32000,\n'
        '  "notes": "整体方案备注（可选，Markdown 格式）"\n'
        "}\n\n"
        f"【客户原始需求】\n{raw_text}"
    )


async def analyze_requirement(raw_text: str) -> Dict[str, Any]:
    """
    Call the AI model to analyze customer requirements.

    Returns a Python dict matching the JSON structure described
    in `_build_requirement_prompt`.
    """
    client = get_ai_client()
    model = os.getenv("AI_MODEL", "gpt-4.1-mini")

    prompt = _build_requirement_prompt(raw_text)

    completion = await client.chat.completions.create(
        model=model,
        response_format={"type": "json_object"},
        messages=[
            {
                "role": "system",
                "content": (
                    "你是一名严谨的系统架构师，只能输出有效的 JSON，不要输出任何解释文字。"
                ),
            },
            {
                "role": "user",
                "content": prompt,
            },
        ],
        temperature=0.2,
    )

    content = completion.choices[0].message.content or "{}"
    try:
        data: Dict[str, Any] = json.loads(content)
    except json.JSONDecodeError as exc:
        raise RuntimeError(f"AI 返回的内容不是合法 JSON：{content}") from exc

    return data