backend/forecasting/rules.py

from __future__ import annotations

import hashlib
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Dict


RULES_PATH = Path(__file__).with_name("AI_MODEL_RULES.md")


@dataclass(frozen=True)
class ForecastRuleDocument:
    path: str
    version: str
    content: str
    default_horizon: int
    recommended_context_length: int
    default_line_width: int

    def to_metadata(self) -> Dict[str, Any]:
        return {
            "path": self.path,
            "version": self.version,
            "default_horizon": self.default_horizon,
            "recommended_context_length": self.recommended_context_length,
            "default_line_width": self.default_line_width,
        }


def load_forecast_rule_document(path: Path | None = None) -> ForecastRuleDocument:
    rules_path = path or RULES_PATH
    content = rules_path.read_text(encoding="utf-8").strip()
    version = hashlib.sha256(content.encode("utf-8")).hexdigest()[:12]
    return ForecastRuleDocument(
        path=str(rules_path),
        version=version,
        content=content,
        default_horizon=10,
        recommended_context_length=384,
        default_line_width=1,
    )


FORECAST_RULE_DOCUMENT = load_forecast_rule_document()