import base64
import logging
from typing import Optional

import anthropic

from ollama_client import OllamaClient

logger = logging.getLogger(__name__)

PROMPT = (
    "Briefly describe what's happening in this security camera image in 1-2 sentences. "
    "Focus on the people, vehicles, or animals and their activity. Be concise."
)


def analyze_snapshot(client: anthropic.Anthropic, image_bytes: bytes) -> str | None:
    """Send a snapshot to Claude Haiku for description. Returns None on failure."""
    try:
        b64 = base64.standard_b64encode(image_bytes).decode("utf-8")
        response = client.messages.create(
            model="claude-haiku-4-5-20251001",
            max_tokens=150,
            messages=[
                {
                    "role": "user",
                    "content": [
                        {
                            "type": "image",
                            "source": {
                                "type": "base64",
                                "media_type": "image/jpeg",
                                "data": b64,
                            },
                        },
                        {"type": "text", "text": PROMPT},
                    ],
                }
            ],
        )
        description = response.content[0].text.strip()
        logger.info("Vision analysis complete: %d chars", len(description))
        return description
    except Exception:
        logger.exception("Claude Vision API failed")
        return None


async def analyze_snapshot_ollama(
    ollama_client: OllamaClient, image_bytes: bytes
) -> str | None:
    """Send a snapshot to Ollama vision model for description.

    Args:
        ollama_client: Configured OllamaClient instance.
        image_bytes: Raw image bytes (JPEG).

    Returns:
        Description string or None on failure.
    """
    return await ollama_client.analyze_image(image_bytes, PROMPT)


async def get_description(
    image_bytes: bytes,
    vision_backend: str,
    claude_client: Optional[anthropic.Anthropic] = None,
    ollama_client: Optional[OllamaClient] = None,
) -> str | None:
    """Get a scene description using the configured vision backend.

    Args:
        image_bytes: Raw image bytes (JPEG).
        vision_backend: One of "haiku", "ollama", or "both".
            "both" tries Ollama first, falls back to Haiku.
        claude_client: Anthropic client (required for "haiku" and "both").
        ollama_client: OllamaClient instance (required for "ollama" and "both").

    Returns:
        Description string or None if all backends fail.
    """
    if vision_backend == "ollama":
        if ollama_client is None:
            logger.error("Ollama backend selected but no client provided")
            return None
        return await analyze_snapshot_ollama(ollama_client, image_bytes)

    if vision_backend == "haiku":
        if claude_client is None:
            logger.error("Haiku backend selected but no client provided")
            return None
        return analyze_snapshot(claude_client, image_bytes)

    if vision_backend == "both":
        # Try Ollama first, fall back to Haiku
        if ollama_client is not None:
            result = await analyze_snapshot_ollama(ollama_client, image_bytes)
            if result is not None:
                return result
            logger.info("Ollama failed, falling back to Haiku")

        if claude_client is not None:
            return analyze_snapshot(claude_client, image_bytes)

        logger.error("Both backend selected but no clients provided")
        return None

    logger.error("Unknown vision backend: %s", vision_backend)
    return None