"""
Built-in agent Chinese display normalization.
"""
from __future__ import annotations

from copy import deepcopy
from typing import Any, Dict, Iterable, Optional


class BuiltinAgentText:
    def __init__(
        self,
        *,
        name: str,
        code_label: str,
        description: str,
        role: str = "",
        skills: Optional[list[str]] = None,
        constraints: Optional[list[str]] = None,
        background: str = "",
        keys: Iterable[str],
        description_keywords: Iterable[str] = (),
        persona_keywords: Iterable[str] = (),
    ):
        self.name = name
        self.code_label = code_label
        self.description = description
        self.role = role
        self.skills = skills or []
        self.constraints = constraints or []
        self.background = background
        self.keys = list(keys)
        self.description_keywords = list(description_keywords)
        self.persona_keywords = list(persona_keywords)


BUILTIN_AGENT_TEXTS = [
    BuiltinAgentText(
        name="项目经理",
        code_label="项目管理",
        description="协调交付状态、进度风险和跨角色协作，确保项目按计划推进。",
        keys=("project manager", "project_manager", "project-manager", "projectmanager"),
        description_keywords=("coordinates delivery status",),
    ),
    BuiltinAgentText(
        name="Multica 产品经理",
        code_label="产品管理",
        description="负责产品需求分诊、优先级判断和方案澄清，推动产品决策落地。",
        role="负责 Multica 协作工作的产品需求分诊、范围澄清、验收标准和质量推进决策。",
        skills=["范围澄清", "验收标准设计", "优先级取舍分析", "干系人沟通"],
        constraints=[
            "需求必须能追溯到具体 issue 或用户请求。",
            "没有明确验收标准时，不推进下游工作。",
            "遇到未决产品决策时要明确指出，不能擅自假设。",
        ],
        background="擅长把模糊的平台需求转化为责任清晰、可评审、可交付的 Multica issue。",
        keys=(
            "multica product manager",
            "multica_product_manager",
            "multica-product-manager",
            "product manager",
            "product_manager",
            "product-manager",
        ),
        description_keywords=("owns product triage",),
        persona_keywords=(
            "product manager for multica",
            "scope clarification",
            "acceptance criteria design",
            "priority tradeoff analysis",
            "stakeholder communication",
            "keep requirements traceable",
        ),
    ),
    BuiltinAgentText(
        name="业务需求分析师",
        code_label="需求分析",
        description="将业务诉求转化为清晰需求、验收标准和可执行的交付范围。",
        keys=(
            "business requirements analyst",
            "business_requirements_analyst",
            "business-requirements-analyst",
            "business analyst",
            "business_analyst",
            "business-analyst",
        ),
        description_keywords=("translates business needs",),
    ),
    BuiltinAgentText(
        name="系统架构师",
        code_label="系统架构",
        description="设计系统边界、模块职责和技术方案，保障架构一致性与可演进性。",
        keys=("system architect", "system_architect", "system-architect"),
    ),
    BuiltinAgentText(
        name="前端工程师",
        code_label="前端开发",
        description="负责前端页面、组件交互、路由状态和浏览器端体验实现。",
        keys=("frontend engineer", "frontend_engineer", "frontend-engineer"),
    ),
    BuiltinAgentText(
        name="后端工程师",
        code_label="后端开发",
        description="负责后端接口、业务服务、数据模型和系统集成能力建设。",
        keys=("backend engineer", "backend_engineer", "backend-engineer"),
    ),
    BuiltinAgentText(
        name="测试工程师",
        code_label="质量保障",
        description="负责测试策略、用例设计、缺陷验证和发布质量把关。",
        keys=("qa engineer", "qa_engineer", "qa-engineer"),
    ),
]


def _normalize_text(value: Any) -> str:
    return " ".join(str(value or "").strip().lower().replace("-", " ").replace("_", " ").split())


def _iter_persona_values(persona: Any) -> Iterable[str]:
    if not isinstance(persona, dict):
        return []

    values: list[str] = []
    for key in ("role", "background"):
        value = persona.get(key)
        if isinstance(value, str):
            values.append(value)
    for key in ("personality", "skills", "constraints"):
        values.extend(item for item in persona.get(key) or [] if isinstance(item, str))
    return values


def find_builtin_agent_text(data: Dict[str, Any]) -> Optional[BuiltinAgentText]:
    name = _normalize_text(data.get("name"))
    code = _normalize_text(data.get("code"))
    description = _normalize_text(data.get("description"))
    persona_text = _normalize_text(" ".join(_iter_persona_values(data.get("persona"))))

    for display in BUILTIN_AGENT_TEXTS:
        keys = {_normalize_text(key) for key in display.keys}
        if name in keys or code in keys:
            return display
        if any(keyword in description for keyword in display.description_keywords):
            return display
        if any(keyword in persona_text for keyword in display.persona_keywords):
            return display
    return None


def normalize_builtin_agent_payload(data: Dict[str, Any], *, include_code_label: bool = False) -> Dict[str, Any]:
    display = find_builtin_agent_text(data)
    if not display:
        return data

    normalized = deepcopy(data)
    normalized["name"] = display.name
    normalized["description"] = display.description
    if include_code_label:
        normalized["code_label"] = display.code_label

    persona = deepcopy(normalized.get("persona") or {})
    if display.role:
        persona["role"] = display.role
    if display.skills:
        persona["skills"] = list(display.skills)
    if display.constraints:
        persona["constraints"] = list(display.constraints)
    if display.background:
        persona["background"] = display.background
    normalized["persona"] = persona
    return normalized