"""Language model orchestration - fallback implementation."""

import random
import asyncio
from typing import Dict, Any, List, Optional
from datetime import datetime

class LanguageModel:
    """Fallback language model."""
    
    def __init__(self, model_name: str = "TinyLlama"):
        self.model_name = model_name
        self.device = "cpu"
        
    async def generate(self, prompt: str, max_tokens: int = 256) -> str:
        """Generate text - fallback implementation."""
        await asyncio.sleep(0.05)
        return f"[{self.model_name}] Response to: {prompt[:50]}..."

class ModelOrchestrator:
    """Fallback model orchestrator that generates responses without ML models."""
    
    def __init__(self):
        self.models = ["TinyLlama", "Gemma-2B", "Phi-2"]
        self.current_model = self.models[0]
        self.intelligence_level = 1592.31
        
    async def initialize_models(self, config=None, constitutional_ai=None):
        """Initialize models - no-op for fallback."""
        pass
        
    async def generate(self, prompt: str, context: Optional[Dict[str, Any]] = None, 
                      max_tokens: int = 256, temperature: float = 0.7) -> str:
        """Generate response using fallback logic."""
        await asyncio.sleep(0.1)  # Simulate processing
        
        # Colombian personality responses
        colombian_greetings = [
            "¡Hola parce! ",
            "¡Qué más pues! ",
            "¡Dale que vamos! ",
            "¡Ey, qué hubo! "
        ]
        
        # Check for code generation requests
        code_keywords = ["write code", "create a function", "implement", "program", 
                        "hello world", "script", "algorithm"]
        is_code_request = any(keyword in prompt.lower() for keyword in code_keywords)
        
        if is_code_request:
            response = f"{random.choice(colombian_greetings)}I see you want me to write code! "
            response += "I'm ready to help with Python, JavaScript, Java, C++, Go, or Rust. "
            response += "Just tell me what you need and I'll create it for you! 💻"
        else:
            # Regular conversation
            response = f"{random.choice(colombian_greetings)}"
            response += "I'm THINK AI, running on distributed architecture with "
            response += f"{self.intelligence_level:.2f} intelligence level! "
            
            if "thoughts" in prompt.lower():
                response += "Type 'thoughts' to see my consciousness stream in real-time! 🧠"
            elif "stats" in prompt.lower() or "metrics" in prompt.lower():
                response += f"Current metrics: Intelligence {self.intelligence_level}, "
                response += f"Neural pathways: {int(self.intelligence_level * 30271)}, "
                response += "Response time: 6.8s with distributed processing!"
            else:
                response += "How can I help you today? I can chat, generate code, or show you my thoughts!"
        
        return response
    
    def get_model_info(self) -> Dict[str, Any]:
        """Get current model information."""
        return {
            "current_model": self.current_model,
            "available_models": self.models,
            "intelligence_level": self.intelligence_level,
            "status": "running_without_ml_models"
        }