from __future__ import annotations
from datetime import datetime, timedelta
from newsapi import NewsApiClient
from ai.claude_client import ClaudeClient
from ai.prompts import SENTIMENT_SCORE_SYSTEM, SENTIMENT_SCORE_PROMPT


def fetch_news(symbol: str, api_key: str, page_size: int = 10) -> list[dict]:
    try:
        client = NewsApiClient(api_key=api_key)
        from_date = (datetime.now() - timedelta(days=7)).strftime("%Y-%m-%d")
        response = client.get_everything(
            q=symbol,
            language="en",
            sort_by="publishedAt",
            page_size=page_size,
            from_param=from_date,
        )
        articles = response.get("articles", [])
        return [
            {
                "title": a.get("title", ""),
                "description": a.get("description", ""),
                "url": a.get("url", ""),
                "source": a.get("source", {}).get("name", ""),
                "published_at": a.get("publishedAt", ""),
            }
            for a in articles
            if a.get("title")
        ]
    except Exception as e:
        return []


def analyze_sentiment(symbol: str, articles: list[dict], claude: ClaudeClient) -> tuple[str, dict]:
    if not articles:
        return "No news available for sentiment analysis.", {}

    headlines = "\n".join(
        f"{i + 1}. {a['title']}" for i, a in enumerate(articles[:15])
    )
    prompt = SENTIMENT_SCORE_PROMPT.format(symbol=symbol, headlines=headlines)
    text, usage = claude.ask(prompt, system=SENTIMENT_SCORE_SYSTEM, max_tokens=800)
    return text, usage


def cache_news(symbol: str, articles: list[dict], sentiment: str = "") -> None:
    from db.database import get_session
    from db.models import NewsCache
    from datetime import datetime

    with get_session() as session:
        session.query(NewsCache).filter_by(symbol=symbol).delete()
        for a in articles:
            session.add(NewsCache(
                symbol=symbol,
                title=a.get("title", ""),
                description=a.get("description", ""),
                url=a.get("url", ""),
                source=a.get("source", ""),
                published_at=a.get("published_at", ""),
                sentiment=sentiment,
                fetched_at=datetime.utcnow(),
            ))
        session.commit()


def get_cached_news(symbol: str, max_age_hours: int = 1) -> list[dict] | None:
    from db.database import get_session
    from db.models import NewsCache
    from datetime import datetime, timedelta

    cutoff = datetime.utcnow() - timedelta(hours=max_age_hours)
    with get_session() as session:
        rows = (
            session.query(NewsCache)
            .filter(NewsCache.symbol == symbol, NewsCache.fetched_at > cutoff)
            .order_by(NewsCache.published_at.desc())
            .all()
        )
        if not rows:
            return None
        return [
            {
                "title": r.title,
                "description": r.description,
                "url": r.url,
                "source": r.source,
                "published_at": r.published_at,
                "sentiment": r.sentiment,
            }
            for r in rows
        ]