import time
import threading
import logging
import requests
import json
from sqlalchemy.orm import Session
from database import SessionLocal, News, Stock
from config import get_kis_config, load_config

logger = logging.getLogger("NEWS_AI")

class NewsBot:
    def __init__(self):
        self.is_running = False
        self.thread = None
        self.config = load_config()
        self.naver_id = self.config.get('naver', {}).get('client_id', '')
        self.naver_secret = self.config.get('naver', {}).get('client_secret', '')
        self.google_key = self.config.get('google', {}).get('api_key', '')
        
    def start(self):
        if self.is_running:
            return
        self.is_running = True
        self.thread = threading.Thread(target=self._run_loop, daemon=True)
        self.thread.start()
        logger.info("News Bot Started")

    def stop(self):
        self.is_running = False
        if self.thread:
            self.thread.join()
        logger.info("News Bot Stopped")

    def _run_loop(self):
        while self.is_running:
            try:
                # Reload config to check current settings
                self.config = load_config()
                if self.config.get('preferences', {}).get('enable_news', False):
                    self._fetch_and_analyze()
                else:
                    logger.info("News collection is disabled.")
            except Exception as e:
                logger.error(f"Error in news loop: {e}")
            
            # Sleep 10 minutes (600 seconds)
            for _ in range(600):
                if not self.is_running: break
                time.sleep(1)

    def _fetch_and_analyze(self):
        logger.info("Fetching News...")
        if not self.naver_id or not self.naver_secret:
            logger.warning("Naver API Credentials missing.")
            return

        # 1. Fetch News (Naver)
        # Search for generic economy terms or specific watchlist
        query = "주식 시장" # General Stock Market
        url = "https://openapi.naver.com/v1/search/news.json"
        headers = {
            "X-Naver-Client-Id": self.naver_id,
            "X-Naver-Client-Secret": self.naver_secret
        }
        params = {"query": query, "display": 10, "sort": "date"}
        
        res = requests.get(url, headers=headers, params=params)
        if res.status_code != 200:
            logger.error(f"Naver News Failed: {res.text}")
            return
            
        items = res.json().get('items', [])
        
        db = SessionLocal()
        try:
            for item in items:
                title = item['title']
                link = item['originallink'] or item['link']
                pub_date = item['pubDate']
                
                # Check duplication
                if db.query(News).filter(News.link == link).first():
                    continue
                
                # 2. AI Analysis (Google Gemini)
                analysis = self._analyze_with_ai(title, item['description'])
                
                # Save to DB
                news = News(
                    title=title,
                    link=link,
                    pub_date=pub_date,
                    analysis_result=analysis.get('summary', ''),
                    impact_score=analysis.get('score', 0),
                    related_sector=analysis.get('sector', '')
                )
                db.add(news)
            db.commit()
            logger.info(f"Processed {len(items)} news items.")
        finally:
            db.close()

    def _analyze_with_ai(self, title, description):
        if not self.google_key:
            return {"summary": "No API Key", "score": 0, "sector": ""}

        logger.info(f"Analyzing: {title[:30]}...")
        
        # Prompt
        prompt = f"""
        Analyze the following news for stock market impact.
        Title: {title}
        Description: {description}
        
        Return JSON format:
        {{
            "summary": "One line summary of impact",
            "score": Integer between -10 (Negative) to 10 (Positive),
            "sector": "Related Industry/Sector or 'None'"
        }}
        """
        
        url = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key={self.google_key}"
        headers = {"Content-Type": "application/json"}
        body = {
            "contents": [{
                "parts": [{"text": prompt}]
            }]
        }
        
        try:
            res = requests.post(url, headers=headers, data=json.dumps(body))
            if res.status_code == 200:
                result = res.json()
                text = result['candidates'][0]['content']['parts'][0]['text']
                # Clean markdown json if any
                text = text.replace("```json", "").replace("```", "").strip()
                return json.loads(text)
            else:
                logger.error(f"Gemini API Error: {res.text}")
        except Exception as e:
            logger.error(f"AI Analysis Exception: {e}")
            
        return {"summary": "Error", "score": 0, "sector": ""}

news_bot = NewsBot()