from typing import Dict, Any, Optional

from core.base_engine import BaseEngine
from main.search_bot import SearchBot
from utils.logger import logger


class SearchEngine(BaseEngine):
    """
    Search-focused API engine that provides web research capabilities.
    Uses the modular SearchBot for consistent architecture.
    """

    def __init__(self):
        """Initialize the Search Engine"""
        super().__init__("search")

    def _initialize_bot(self):
        """Initialize the SearchBot instance"""
        try:
            self.bot = SearchBot()
        except Exception as e:
            logger.error(f"Failed to initialize SearchBot: {e}")
            raise

    # process_query is inherited from BaseEngine

    def search_market_trends(
        self, topic: str = "soy products", region: str = "Central America", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Search for current market trends on a specific topic

        Args:
            topic: Market topic to research (default: "soy products")
            region: Geographic region of interest (default: "Central America")
            user_name: Username for tracking

        Returns:
            Dict containing market trends analysis
        """
        query = f"Analiza las tendencias actuales del mercado de {topic} en {region}, incluyendo cambios recientes, factores de crecimiento y perspectivas futuras."
        return self.process_query(query, user_name)

    def research_competitors(
        self, company: str = "Delisoy", industry: str = "productos de soya", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Research competitors and competitive landscape

        Args:
            company: Company name to research competitors for (default: "Delisoy")
            industry: Industry sector (default: "productos de soya")
            user_name: Username for tracking

        Returns:
            Dict containing competitive analysis
        """
        query = f"Investiga los principales competidores de {company} en la industria de {industry}, analizando sus estrategias, fortalezas, debilidades y posicionamiento en el mercado."
        return self.process_query(query, user_name)

    def analyze_industry_news(
        self, industry: str = "food and beverage", keywords: str = "soy products", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Analyze recent industry news and developments

        Args:
            industry: Industry to research (default: "food and beverage")
            keywords: Specific keywords to focus on (default: "soy products")
            user_name: Username for tracking

        Returns:
            Dict containing industry news analysis
        """
        query = f"Busca y analiza las noticias y desarrollos más recientes en la industria {industry} relacionados con {keywords}, identificando tendencias, oportunidades y desafíos."
        return self.process_query(query, user_name)

    def research_consumer_behavior(
        self, product_category: str = "plant-based foods", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Research current consumer behavior and preferences

        Args:
            product_category: Product category to research (default: "plant-based foods")
            user_name: Username for tracking

        Returns:
            Dict containing consumer behavior analysis
        """
        query = f"Investiga el comportamiento actual del consumidor en la categoría {product_category}, incluyendo preferencias, motivaciones de compra, factores de decisión y tendencias emergentes."
        return self.process_query(query, user_name)

    def analyze_pricing_strategies(
        self, company: str = "Delisoy", competitors: str = "NIDO, Dos Pinos, Anchor", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Analyze pricing strategies and market positioning

        Args:
            company: Main company to analyze (default: "Delisoy")
            competitors: Competitor companies (default: "NIDO, Dos Pinos, Anchor")
            user_name: Username for tracking

        Returns:
            Dict containing pricing strategy analysis
        """
        query = f"Analiza las estrategias de precios de {company} comparándolas con las de sus competidores principales: {competitors}. Incluye posicionamiento, tácticas de precios y impacto en el mercado."
        return self.process_query(query, user_name)

    def research_market_opportunities(
        self, product_type: str = "soy-based products", region: str = "Central America", user_name: str = "user"
    ) -> Dict[str, Any]:
        """
        Research market opportunities and growth potential

        Args:
            product_type: Type of products to research (default: "soy-based products")
            region: Geographic region (default: "Central America")
            user_name: Username for tracking

        Returns:
            Dict containing market opportunities analysis
        """
        query = f"Identifica y analiza las oportunidades de mercado para {product_type} en {region}, incluyendo segmentos emergentes, necesidades no satisfechas y potencial de crecimiento."
        return self.process_query(query, user_name)

    # health_check is inherited from BaseEngine


# Create a singleton instance
search_engine = SearchEngine()
