"""
Video analysis toolkit for video understanding and processing.

Provides tools for video analysis, question answering, and content extraction
using Google's Gemini API for video understanding.
"""

from typing import Callable, Dict

from noesium.core.library_consts import TOOLKIT_VIDEO
from noesium.core.toolify.base import AsyncBaseToolkit
from noesium.core.toolify.config import ToolkitConfig
from noesium.core.toolify.registry import register_toolkit
from noesium.core.utils.logging import get_logger

logger = get_logger(__name__)

try:
    from google import genai
    from google.genai.types import HttpOptions, Part

    GOOGLE_GENAI_AVAILABLE = True
except ImportError:
    genai = None
    HttpOptions = None
    Part = None
    GOOGLE_GENAI_AVAILABLE = False


@register_toolkit(TOOLKIT_VIDEO)
class VideoToolkit(AsyncBaseToolkit):
    """
    Toolkit for video analysis and understanding.

    This toolkit provides capabilities for:
    - Video content analysis using Google's Gemini API
    - Video question answering
    - Scene description and object detection
    - Temporal analysis of video content

    Features:
    - Support for various video formats
    - URL and local file processing
    - Comprehensive video understanding
    - Integration with Google's advanced video models

    Required dependencies:
    - google-genai package
    - Google API key with Gemini access

    Note: This is a simplified implementation. Full video processing
    capabilities require additional development and API integration.
    """

    def __init__(self, config: ToolkitConfig = None):
        """
        Initialize the video toolkit.

        Args:
            config: Toolkit configuration containing API keys and settings
        """
        super().__init__(config)

        if not GOOGLE_GENAI_AVAILABLE:
            self.logger.warning(
                "google-genai package not available. Video analysis will be limited. "
                "Install with: pip install google-genai"
            )

        # Configuration
        self.google_api_key = self.config.config.get("GOOGLE_API_KEY")
        self.model_name = self.config.config.get("google_model", "gemini-1.5-pro")

        # Initialize client if available
        self.client = None
        if GOOGLE_GENAI_AVAILABLE and self.google_api_key:
            try:
                self.client = genai.Client(api_key=self.google_api_key, http_options=HttpOptions(api_version="v1alpha"))
                self.logger.info("Google Gemini client initialized for video analysis")
            except Exception as e:
                self.logger.error(f"Failed to initialize Google client: {e}")

    async def analyze_video(self, video_path: str, question: str = "Describe this video") -> str:
        """
        Analyze a video and answer questions about its content.

        This tool uses Google's Gemini API to analyze video content and answer
        questions about what's happening in the video, including objects, actions,
        scenes, and temporal sequences.

        Args:
            video_path: Path or URL to the video file
            question: Question to ask about the video content

        Returns:
            Analysis or answer based on the video content

        Note: This is a placeholder implementation. Full functionality requires
        proper Google Gemini API integration and video processing capabilities.
        """
        self.logger.info(f"Analyzing video: {video_path}")

        if not self.client:
            return (
                "Video analysis not available. Please ensure:\n"
                "1. google-genai package is installed\n"
                "2. GOOGLE_API_KEY is configured\n"
                "3. API key has access to Gemini video capabilities"
            )

        try:
            # This is a simplified placeholder implementation
            # Full implementation would require proper video upload and processing
            return (
                f"Video analysis for: {video_path}\n"
                f"Question: {question}\n\n"
                "Note: Full video analysis capabilities are under development. "
                "This toolkit provides the framework for video understanding "
                "but requires additional implementation for complete functionality."
            )

        except Exception as e:
            error_msg = f"Video analysis failed: {str(e)}"
            self.logger.error(error_msg)
            return error_msg

    async def get_video_info(self, video_path: str) -> Dict:
        """
        Get basic information about a video file.

        Args:
            video_path: Path to the video file

        Returns:
            Dictionary with video metadata
        """
        try:
            import os
            from pathlib import Path

            if os.path.exists(video_path):
                file_path = Path(video_path)
                file_size = file_path.stat().st_size

                return {
                    "path": video_path,
                    "exists": True,
                    "size_bytes": file_size,
                    "size_mb": round(file_size / (1024 * 1024), 2),
                    "extension": file_path.suffix,
                    "note": "Detailed video metadata requires additional video processing libraries",
                }
            else:
                return {"path": video_path, "exists": False, "error": "File not found"}

        except Exception as e:
            return {"error": f"Failed to get video info: {str(e)}"}

    async def get_tools_map(self) -> Dict[str, Callable]:
        """
        Get the mapping of tool names to their implementation functions.

        Returns:
            Dictionary mapping tool names to callable functions
        """
        return {
            "analyze_video": self.analyze_video,
            "get_video_info": self.get_video_info,
        }
