# MIT License
# Copyright (c) 2024
"""LLM 抽象与 Dummy 实现。"""

from abc import ABC, abstractmethod
from typing import Any, Dict, List

import yaml

from .schema import DSLSpec, EventRecord

PROMPT_TEMPLATE = """你是一名自动化工程师，请将以下事件序列归纳为可参数化的自动化 DSL。
事件序列使用 JSON 描述，每个事件包含 kind、control（AutomationId/Name/ClassName/ControlType/BoundingRect）等。
输出 YAML，字段包括：params、steps、assertions、retry_policy、waits，支持 steps 内的 if/else、for_each。
输出示例：
params:
  text: "示例参数"
steps:
  - action: click
    target: {{AutomationId: "15", ControlType: "Edit"}}
  - action: type
    target: {{AutomationId: "15"}}
    text: "{{text}}"
assertions:
  - "输入框非空"
retry_policy: {{max_attempts: 2, interval: 1.0}}
waits: {{appear: 5.0, disappear: 5.0}}
现在请基于输入事件生成 YAML："""


class LLMClient(ABC):
    """LLM 抽象接口。"""

    @abstractmethod
    def generate(self, events: List[EventRecord]) -> DSLSpec:
        """将事件序列转为 DSL 规格。"""


class DummyLLM(LLMClient):
    """离线 dummy，实现一个简单的规则映射。"""

    def generate(self, events: List[EventRecord]) -> DSLSpec:
        steps: List[Dict[str, Any]] = []
        for ev in events:
            ctrl = ev.control.dict(by_alias=True) if ev.control else {}
            if ev.kind == "mouse_click":
                steps.append({"action": "click", "target": ctrl})
            elif ev.kind == "key_down" and ev.data.get("name"):
                # 仅在按键时记录输入
                steps.append({"action": "type", "target": ctrl, "text": ev.data.get("name")})
        if not steps:
            steps.append({"action": "assert_exists", "target": {"Name": "dummy"}})
        spec = DSLSpec(
            params={},
            steps=steps,
            assertions=["dummy generated"],
        )
        return spec


def render_prompt(events: List[EventRecord]) -> str:
    """把事件序列渲染到 prompt。"""
    event_dicts = [ev.dict(by_alias=True) for ev in events]
    return f"{PROMPT_TEMPLATE}\n\n{yaml.safe_dump(event_dicts, allow_unicode=True)}"