"""
Core implementation for LlamaVector
"""
import os
from typing import Dict, List, Any, Optional, Union


class Client:
    """Main client for LlamaVector"""
    
    def __init__(self, config: Optional[Dict[str, Any]] = None):
        """Initialize with optional configuration"""
        self.config = config or {}
        
    def process(self, data: Any) -> Dict[str, Any]:
        """Process data using the client"""
        # Implementation would go here
        return {"result": "Processed data", "input": data}
    
    def add_vector(self, vector: List[float], metadata: Optional[Dict[str, Any]] = None) -> str:
        """Add a vector to the store"""
        # Implementation would go here
        vector_id = f"vec-{len(vector)}-{hash(str(vector))}"
        return vector_id
        
    def search_similar(self, vector: List[float], k: int = 10) -> List[Dict[str, Any]]:
        """Search for similar vectors"""
        # Implementation would go here
        return [{"id": f"result-{i}", "score": 1.0 - (i * 0.1), "metadata": {}} for i in range(k)]
    
    def get_status(self) -> Dict[str, Any]:
        """Get current status"""
        return {"status": "operational"}
