"""OpenAI API integration."""

import os
from typing import Any, Dict, List, Optional, Union

try:
    import openai
    from openai import OpenAI
    HAS_OPENAI = True
except ImportError:
    HAS_OPENAI = False

from .base import AIProvider


class OpenAIProvider(AIProvider):
    """OpenAI API integration for AI services."""

    def __init__(
        self,
        api_key: Optional[str] = None,
        org_id: Optional[str] = None,
        credentials_path: Optional[str] = None,
        base_url: Optional[str] = None,
    ):
        """Initialize the OpenAI provider.
        
        Args:
            api_key: OpenAI API key
            org_id: OpenAI organization ID
            credentials_path: Path to a JSON file containing credentials
            base_url: Base URL for the API (for Azure OpenAI or self-hosted)
        """
        if not HAS_OPENAI:
            raise ImportError(
                "The 'openai' package is required for OpenAI integration. "
                "Install it with 'pip install openai'."
            )
            
        # Read credentials from environment variables if not provided
        self.api_key = api_key or os.environ.get("OPENAI_API_KEY")
        self.org_id = org_id or os.environ.get("OPENAI_ORG_ID")
        
        if credentials_path:
            # TODO: Implement loading credentials from file
            pass
            
        if not self.api_key:
            raise ValueError(
                "Missing OpenAI API key. "
                "Provide api_key or set OPENAI_API_KEY environment variable."
            )
            
        # Initialize the OpenAI client
        client_params = {"api_key": self.api_key}
        
        if self.org_id:
            client_params["organization"] = self.org_id
            
        if base_url:
            client_params["base_url"] = base_url
            
        self.client = OpenAI(**client_params)
        
    def generate_text(
        self, 
        prompt: str, 
        **kwargs
    ) -> str:
        """Generate text using an OpenAI model.
        
        Args:
            prompt: Text prompt to generate from
            **kwargs: Additional parameters (model, max_tokens, temperature, etc.)
            
        Returns:
            Generated text
        """
        # Default to GPT-3.5-turbo model if not specified
        model = kwargs.pop("model", "gpt-3.5-turbo-instruct")
        
        # TODO: Implement text generation using OpenAI API
        raise NotImplementedError("Method not yet implemented")
    
    def generate_chat_response(
        self, 
        messages: List[Dict[str, str]], 
        **kwargs
    ) -> Dict[str, Any]:
        """Generate a chat response using an OpenAI model.
        
        Args:
            messages: List of message objects with role and content
            **kwargs: Additional parameters (model, max_tokens, temperature, etc.)
            
        Returns:
            Dict containing the response and metadata
        """
        # Default to GPT-3.5-turbo model if not specified
        model = kwargs.pop("model", "gpt-3.5-turbo")
        
        # TODO: Implement chat response generation using OpenAI API
        raise NotImplementedError("Method not yet implemented")
    
    def embed_text(
        self, 
        text: str, 
        **kwargs
    ) -> List[float]:
        """Generate embeddings for text using OpenAI.
        
        Args:
            text: Text to embed
            **kwargs: Additional parameters (model, etc.)
            
        Returns:
            Vector embedding as a list of floats
        """
        # Default to text-embedding-ada-002 model if not specified
        model = kwargs.pop("model", "text-embedding-ada-002")
        
        # TODO: Implement text embedding using OpenAI API
        raise NotImplementedError("Method not yet implemented")
        
    def list_models(
        self, 
        **kwargs
    ) -> List[Dict[str, Any]]:
        """List available OpenAI models.
        
        Args:
            **kwargs: Filtering parameters
            
        Returns:
            List of available models with metadata
        """
        # TODO: Implement model listing using OpenAI API
        raise NotImplementedError("Method not yet implemented")
        
    def generate_image(
        self,
        prompt: str,
        **kwargs
    ) -> Dict[str, Any]:
        """Generate an image using DALL-E.
        
        Args:
            prompt: Text description for the image
            **kwargs: Additional parameters (size, n, etc.)
            
        Returns:
            Dict containing image information (URLs, etc.)
        """
        # TODO: Implement image generation using OpenAI API
        raise NotImplementedError("Method not yet implemented") 