"""AI integration for BLOT SDK - Powered by OpenClaw."""

from dataclasses import dataclass
from typing import Optional, Literal
from enum import Enum

from blot.config import Config


class Sentiment(str, Enum):
    """Market sentiment."""
    BULLISH = "bullish"
    BEARISH = "bearish"
    NEUTRAL = "neutral"


class Recommendation(str, Enum):
    """Trading recommendation."""
    BUY = "buy"
    SELL = "sell"
    HOLD = "hold"


@dataclass
class TokenAnalysis:
    """Result of AI token analysis."""
    
    token: str
    sentiment: Sentiment
    risk_score: int  # 0-100
    recommendation: Recommendation
    confidence: float  # 0-1
    reasons: list[str]
    
    @property
    def is_promising(self) -> bool:
        """Check if token looks promising based on analysis."""
        return (
            self.sentiment == Sentiment.BULLISH
            and self.risk_score < 50
            and self.confidence > 0.7
        )


@dataclass
class MarketAnalysis:
    """Result of AI market analysis."""
    
    token: str
    signal: Literal["BUY", "SELL", "HOLD"]
    strength: float  # 0-1
    support_level: Optional[float]
    resistance_level: Optional[float]
    trend: Literal["up", "down", "sideways"]


class AI:
    """AI assistant for market analysis - Powered by OpenClaw.
    
    Example:
        ```python
        from blot import Bot
        
        bot = Bot(private_key="...")
        
        # Analyze a token
        analysis = await bot.ai.analyze_token("JUP")
        print(analysis.sentiment)      # bullish/bearish
        print(analysis.risk_score)     # 0-100
        print(analysis.recommendation) # buy/sell/hold
        
        # Check if token is promising
        if analysis.is_promising:
            print("Token looks good!")
        ```
    """
    
    def __init__(self, config: Optional[Config] = None):
        self.config = config or Config()
    
    async def analyze_token(self, token: str) -> TokenAnalysis:
        """Analyze a token using AI.
        
        Args:
            token: Token symbol or address.
            
        Returns:
            TokenAnalysis with AI insights.
        """
        # TODO: Implement actual AI analysis via OpenClaw API
        return TokenAnalysis(
            token=token,
            sentiment=Sentiment.NEUTRAL,
            risk_score=50,
            recommendation=Recommendation.HOLD,
            confidence=0.5,
            reasons=["Analysis pending - connect to BLOT infrastructure"],
        )
    
    async def analyze_market(self, token: str) -> MarketAnalysis:
        """Analyze market conditions for a token.
        
        Args:
            token: Token symbol or address.
            
        Returns:
            MarketAnalysis with trading signals.
        """
        # TODO: Implement actual market analysis
        return MarketAnalysis(
            token=token,
            signal="HOLD",
            strength=0.5,
            support_level=None,
            resistance_level=None,
            trend="sideways",
        )
    
    async def check_honeypot(self, token_address: str) -> bool:
        """Check if a token is a honeypot.
        
        Args:
            token_address: Token contract address.
            
        Returns:
            True if token appears to be a honeypot.
        """
        # TODO: Implement honeypot detection
        return False
    
    async def check_rug_risk(self, token_address: str) -> float:
        """Assess rug pull risk for a token.
        
        Args:
            token_address: Token contract address.
            
        Returns:
            Risk score from 0.0 (safe) to 1.0 (high risk).
        """
        # TODO: Implement rug pull detection
        return 0.5
    
    async def analyze_wallet(self, wallet_address: str) -> dict:
        """Analyze a wallet's trading performance.
        
        Args:
            wallet_address: Wallet address to analyze.
            
        Returns:
            Dict with wallet statistics and performance metrics.
        """
        # TODO: Implement wallet analysis
        return {
            "address": wallet_address,
            "win_rate": 0.0,
            "total_trades": 0,
            "profit_loss": 0.0,
            "avg_hold_time": "unknown",
            "top_tokens": [],
        }

