"""
Image Generation
Part of SOVEREIGN PYTHON LLM ENGINE

Generate images using various providers (DALL-E, Stable Diffusion, etc.).
"""

from typing import Any
from pathlib import Path
from dataclasses import dataclass
import base64
from io import BytesIO

from ...core.evidence import WORMLedger


@dataclass
class GeneratedImage:
    """Generated image result"""
    image_bytes: bytes
    format: str  # "png", "jpeg", etc.
    size: tuple[int, int]
    prompt: str
    model: str
    metadata: dict[str, Any]


class ImageGenerator:
    """
    Image generation using multiple providers.

    Supports:
    - OpenAI DALL-E 3
    - Stable Diffusion (via API or local)
    - Amazon Bedrock (Stable Diffusion)
    """

    def __init__(
        self,
        provider: str = "openai",
        model: str | None = None,
        worm_ledger: WORMLedger | None = None
    ):
        """
        Initialize image generator.

        Args:
            provider: Provider name ("openai", "bedrock", "stability")
            model: Optional model override
            worm_ledger: Optional WORM ledger
        """
        self.provider = provider
        self.model = model
        self.worm_ledger = worm_ledger

    async def generate(
        self,
        prompt: str,
        size: str = "1024x1024",
        quality: str = "standard",
        n: int = 1
    ) -> list[GeneratedImage]:
        """
        Generate images from prompt.

        Args:
            prompt: Text prompt
            size: Image size ("1024x1024", "1792x1024", etc.)
            quality: Quality level ("standard", "hd")
            n: Number of images

        Returns:
            List of GeneratedImage
        """
        if self.provider == "openai":
            return await self._generate_openai(prompt, size, quality, n)
        elif self.provider == "bedrock":
            return await self._generate_bedrock(prompt, size)
        elif self.provider == "stability":
            return await self._generate_stability(prompt, size)
        else:
            raise ValueError(f"Unknown provider: {self.provider}")

    async def _generate_openai(
        self,
        prompt: str,
        size: str,
        quality: str,
        n: int
    ) -> list[GeneratedImage]:
        """Generate using OpenAI DALL-E"""
        try:
            from openai import AsyncOpenAI
        except ImportError:
            raise ImportError("openai is required. Install: pip install openai")

        client = AsyncOpenAI()

        response = await client.images.generate(
            model=self.model or "dall-e-3",
            prompt=prompt,
            size=size,
            quality=quality,
            n=n,
            response_format="b64_json"
        )

        results = []

        for image_data in response.data:
            # Decode base64
            image_bytes = base64.b64decode(image_data.b64_json)

            # Parse size
            width, height = map(int, size.split("x"))

            results.append(GeneratedImage(
                image_bytes=image_bytes,
                format="png",
                size=(width, height),
                prompt=prompt,
                model=self.model or "dall-e-3",
                metadata={
                    "revised_prompt": image_data.revised_prompt
                }
            ))

        # Log to WORM
        if self.worm_ledger:
            await self.worm_ledger.append({
                "event": "image_generate",
                "provider": "openai",
                "prompt": prompt,
                "images_count": len(results)
            })

        return results

    async def _generate_bedrock(
        self,
        prompt: str,
        size: str
    ) -> list[GeneratedImage]:
        """Generate using AWS Bedrock (Stable Diffusion)"""
        try:
            import boto3
            import json
        except ImportError:
            raise ImportError("boto3 is required")

        client = boto3.client("bedrock-runtime", region_name="us-east-1")

        # Parse size
        width, height = map(int, size.split("x"))

        # Build request
        request_body = {
            "text_prompts": [{"text": prompt}],
            "cfg_scale": 7,
            "steps": 30,
            "width": width,
            "height": height
        }

        # Invoke model
        response = client.invoke_model(
            modelId=self.model or "stability.stable-diffusion-xl-v1",
            body=json.dumps(request_body)
        )

        # Parse response
        response_body = json.loads(response["body"].read())

        results = []

        for artifact in response_body.get("artifacts", []):
            image_bytes = base64.b64decode(artifact["base64"])

            results.append(GeneratedImage(
                image_bytes=image_bytes,
                format="png",
                size=(width, height),
                prompt=prompt,
                model=self.model or "stability.stable-diffusion-xl-v1",
                metadata={}
            ))

        # Log to WORM
        if self.worm_ledger:
            await self.worm_ledger.append({
                "event": "image_generate",
                "provider": "bedrock",
                "prompt": prompt,
                "images_count": len(results)
            })

        return results

    async def _generate_stability(
        self,
        prompt: str,
        size: str
    ) -> list[GeneratedImage]:
        """Generate using Stability AI API"""
        try:
            import httpx
        except ImportError:
            raise ImportError("httpx is required")

        # This is a stub - would need Stability API key
        raise NotImplementedError("Stability AI provider not fully implemented")


async def save_image(image: GeneratedImage, output_path: Path) -> None:
    """
    Save generated image to file.

    Args:
        image: Generated image
        output_path: Where to save
    """
    output_path.write_bytes(image.image_bytes)


# Tool registration helper
async def generate_image_tool(
    prompt: str,
    provider: str = "bedrock",
    size: str = "1024x1024",
    output_path: str | None = None
) -> dict:
    """
    Tool wrapper for image generation.

    Args:
        prompt: Image prompt
        provider: Provider ("openai", "bedrock")
        size: Image size
        output_path: Optional path to save

    Returns:
        Dictionary with result
    """
    generator = ImageGenerator(provider=provider)
    images = await generator.generate(prompt, size=size)

    result = {
        "images_count": len(images),
        "prompt": prompt,
        "size": size,
        "model": images[0].model if images else None
    }

    # Save if requested
    if output_path and images:
        await save_image(images[0], Path(output_path))
        result["saved_to"] = output_path

    return result