from __future__ import annotations

from dataclasses import dataclass
from typing import List, Dict, Any


@dataclass
class NewsArticle:
    title: str
    content: str
    url: str
    source: str
    published_date: str
    scraped_date: str
    article_id: str
    language: str = "english"  # Default to english, matches the JavaScript implementation


def normalize_result(result: Dict[str, Any]) -> Dict[str, Any]:
    out = {
        "verdict": result.get("verdict", "UNVERIFIED"),
        "confidence": result.get("confidence", 0.0),
        "reasoning": result.get("reasoning", ""),
        "supporting_evidence": result.get("supporting_evidence", []) or [],
        "contradicting_evidence": result.get("contradicting_evidence", []) or [],
        "context_quality": result.get("context_quality", "unknown"),
    }
    c = out["confidence"]
    try:
        if isinstance(c, str):
            c = float(c.strip().replace("%", ""))
        c = float(c)
        if c > 1.0:
            c = c / 100.0
        if c < 0:
            c = 0.0
        if c > 1:
            c = 1.0
    except Exception:
        c = 0.0
    out["confidence"] = c
    if not isinstance(out["supporting_evidence"], list):
        out["supporting_evidence"] = [str(out["supporting_evidence"])]
    if not isinstance(out["contradicting_evidence"], list):
        out["contradicting_evidence"] = [str(out["contradicting_evidence"])]
    if isinstance(out["verdict"], str):
        out["verdict"] = out["verdict"].upper()
    return out