"""Prompt templates for natural language outputs."""
from __future__ import annotations

from typing import Dict, TYPE_CHECKING

from .templates import TemplateRegistry

if TYPE_CHECKING:  # pragma: no cover
    from app.utils.config import DepartmentSettings
    from app.agents.departments import DepartmentContext


def plan_prompt(data: Dict) -> str:
    """Build a concise instruction prompt for the LLM."""

    _ = data
    return "你是一个投资助理，请根据提供的数据给出三条要点和两条风险提示。"


def department_prompt(
    settings: "DepartmentSettings",
    context: "DepartmentContext",
    supplements: str = "",
) -> str:
    """Compose a structured prompt for department-level LLM ensemble."""
    
    # Format data for template
    feature_lines = "\n".join(
        f"- {key}: {value}" for key, value in sorted(context.features.items())
    )
    market_lines = "\n".join(
        f"- {key}: {value}" for key, value in sorted(context.market_snapshot.items())
    )
    scope_lines = "\n".join(f"- {item}" for item in settings.data_scope)
    role_description = settings.description.strip()
    role_instruction = settings.prompt.strip()
    
    # Determine template ID based on department settings
    template_id = f"{settings.code.lower()}_dept"
    if not TemplateRegistry.get(template_id):
        template_id = "department_base"
        
    # Prepare template variables
    template_vars = {
        "title": settings.title,
        "ts_code": context.ts_code,
        "trade_date": context.trade_date,
        "description": role_description or "未配置，默认沿用部门名称所代表的研究职责。",
        "instruction": role_instruction or "在保持部门风格的前提下，结合可用数据做出审慎判断。",
        "data_scope": scope_lines or "- 使用系统提供的全部上下文，必要时指出仍需的额外数据。",
        "features": feature_lines or "- (无)",
        "market_snapshot": market_lines or "- (无)",
        "supplements": supplements.strip() or "- 当前无追加数据"
    }
    
    # Get template and format prompt
    template = TemplateRegistry.get(template_id)
    return template.format(template_vars)