import os
import sys
import requests
import json
import tkinter as tk
from tkinter import filedialog
from rich.console import Console
from rich.progress import Progress, SpinnerColumn, TextColumn
from rich.panel import Panel
from rich.table import Table
from rich import print

# --- CONFIGURATION ---
# TODO: Replace with your actual Sightengine API credentials
API_USER = "1020608869"
API_SECRET = "M7WF4mAXwSs2gs869LC9PecvYCBQyBSz"

API_ENDPOINT = "https://api.sightengine.com/1.0/video/check-sync.json"

console = Console()

def select_video_file():
    """Opens a file dialog to select a video file using Tkinter."""
    root = tk.Tk()
    root.withdraw() # Hide the main window
    
    file_path = filedialog.askopenfilename(
        title="Select a video file to analyze",
        filetypes=[
            ("Video Files", "*.mp4 *.mov *.avi *.mkv *.webm *.flv *.wmv"), 
            ("All Files", "*.*")
        ]
    )
    return file_path

def check_video(file_path):
    """Checks the video using Sightengine API."""
    if not os.path.exists(file_path):
        console.print(f"[bold red]Error:[/bold red] File not found: {file_path}")
        return

    params = {
        'models': 'genai',
        'api_user': API_USER,
        'api_secret': API_SECRET
    }

    files = {
        'media': open(file_path, 'rb')
    }

    try:
        with Progress(
            SpinnerColumn(),
            TextColumn("[progress.description]{task.description}"),
            transient=True
        ) as progress:
            progress.add_task(description="Uploading and analyzing video...", total=None)
            response = requests.post(API_ENDPOINT, files=files, data=params)
        
        response_data = json.loads(response.text)
        
        if response_data['status'] == 'success':
            display_results(file_path, response_data)
        else:
            error_msg = response_data.get('error', {}).get('message', 'Unknown error')
            console.print(f"[bold red]API Error:[/bold red] {error_msg}")

    except Exception as e:
        console.print(f"[bold red]System Error:[/bold red] {e}")
    finally:
        files['media'].close()

def display_results(file_path, data):
    """Displays the analysis results using Rich."""
    
    # Calculate aggregate score (average of all frames for simplicity in this demo)
    frames = data.get('data', {}).get('frames', [])
    if not frames:
        console.print("[yellow]No frames analyzed.[/yellow]")
        return

    total_ai_score = 0
    count = 0
    
    # Create detailed table for frames (showing first few or high scores)
    table = Table(title="Frame Analysis (Sample)")
    table.add_column("Time (s)", justify="right", style="cyan", no_wrap=True)
    table.add_column("AI Probability", justify="right", style="magenta")
    table.add_column("Verdict", justify="center")

    max_ai_score = 0

    for frame in frames:
        ai_score = frame.get('type', {}).get('ai_generated', 0)
        total_ai_score += ai_score
        count += 1
        if ai_score > max_ai_score:
            max_ai_score = ai_score
        
        # Add to table if it's a significant score or just to show some data
        # Showing only frames with > 0.1 score or every 10th frame to keep it clean if many frames
        if ai_score > 0.5 or count % 10 == 1:
             verdict = "[red]FAKE[/red]" if ai_score > 0.8 else ("[yellow]SUSPICIOUS[/yellow]" if ai_score > 0.4 else "[green]REAL[/green]")
             # Assuming 1 frame per second roughly? API documentation says 'position' is likely offset
             position = frame.get('info', {}).get('position', 0)
             # Provide string formatting for score
             table.add_row(str(position), f"{ai_score:.2%}", verdict)

    avg_ai_score = total_ai_score / count if count else 0
    
    # Final Verdict Panel
    final_verdict = "UNCERTAIN"
    color = "yellow"
    if max_ai_score > 0.85:
        final_verdict = "AI GENERATED"
        color = "red"
    elif max_ai_score < 0.2:
        final_verdict = "AUTHENTIC"
        color = "green"
    
    request_info = data.get('request', {})
    req_id = request_info.get('id', 'N/A')
    ops = request_info.get('operations', 0)
    
    panel_content = f"""
    [bold]File:[/bold] {os.path.basename(file_path)}
    [bold]Request ID:[/bold] {req_id}
    [bold]Operations Cost:[/bold] {ops}
    
    [bold]Max AI Score:[/bold] {max_ai_score:.2%}
    [bold]Average AI Score:[/bold] {avg_ai_score:.2%}
    
    [bold size=20 style={color}]VERDICT: {final_verdict}[/bold size=20 style={color}]
    """
    
    console.print(Panel(panel_content, title="Analysis Result", expand=False))
    console.print(table)

def main():
    if API_USER == "CHANGE_ME" or API_SECRET == "CHANGE_ME":
        console.print("[bold red]Configuration Error:[/bold red] Please set API_USER and API_SECRET in the script.")
        return

    if len(sys.argv) > 1:
        video_path = sys.argv[1]
    else:
        console.print(Panel(
            "[bold green]AI Video Authenticity Check[/bold green]\n\n"
            "This script analyzes a video to detect AI-generated content using Sightengine.\n"
            "Please select a video file in the window that opens...",
            title="Welcome",
            border_style="green"
        ))
        video_path = select_video_file()
        if not video_path:
            console.print("[yellow]No file selected. Exiting.[/yellow]")
            return

    console.print(f"[blue]Analyzing:[/blue] {video_path}")
    check_video(video_path)

if __name__ == "__main__":
    try:
        main()
    finally:
        input("Press Enter to continue...")