"""
Test script for the deployed Hugging Face API
"""

import requests
import base64
import numpy as np
import cv2
from PIL import Image
import io

def create_test_image():
    """Create a test image for API testing"""
    # Create a simple test image
    img = np.random.randint(0, 255, (100, 100, 3), dtype=np.uint8)
    
    # Convert to PIL Image
    pil_img = Image.fromarray(img)
    
    # Convert to base64
    buffer = io.BytesIO()
    pil_img.save(buffer, format='JPEG')
    img_str = base64.b64encode(buffer.getvalue()).decode()
    
    return img_str

def test_api_similarity():
    """Test the similarity API endpoint"""
    url = "https://pavaniyerra-hackthon4.hf.space/predict_similarity/"
    
    print("Testing Hugging Face API...")
    print("=" * 40)
    
    try:
        # Create two test images
        img1_b64 = create_test_image()
        img2_b64 = create_test_image()
        
        # Prepare the request data - API expects file1 and file2
        data = {
            "file1": img1_b64,
            "file2": img2_b64
        }
        
        print("Sending request to API...")
        response = requests.post(url, json=data, timeout=30)
        
        if response.status_code == 200:
            result = response.json()
            print("SUCCESS: API Response received successfully!")
            print(f"Similarity Score: {result}")
            
            # Interpret the similarity score
            if isinstance(result, (int, float)):
                if result > 0.8:
                    print("Result: Very High Similarity (likely same person)")
                elif result > 0.6:
                    print("Result: High Similarity (possibly same person)")
                elif result > 0.4:
                    print("Result: Moderate Similarity (uncertain)")
                elif result > 0.2:
                    print("Result: Low Similarity (likely different persons)")
                else:
                    print("Result: Very Low Similarity (definitely different persons)")
            else:
                print(f"Unexpected response format: {result}")
                
        else:
            print(f"ERROR: API Error: {response.status_code}")
            print(f"Response: {response.text}")
            
    except requests.exceptions.RequestException as e:
        print(f"ERROR: Network Error: {e}")
    except Exception as e:
        print(f"ERROR: Error: {e}")

def test_api_classification():
    """Test the classification API endpoint (if available)"""
    # Try different possible endpoints
    possible_urls = [
        "https://pavaniyerra-hackthon4.hf.space/predict_class/",
        "https://pavaniyerra-hackthon4.hf.space/classify/",
        "https://pavaniyerra-hackthon4.hf.space/predict/"
    ]
    
    print("\nTesting Classification API...")
    print("=" * 40)
    
    for url in possible_urls:
        try:
            # Create a test image
            img_b64 = create_test_image()
            
            # Prepare the request data - try different parameter names
            data = {
                "file": img_b64
            }
            
            print(f"Trying endpoint: {url}")
            response = requests.post(url, json=data, timeout=30)
            
            if response.status_code == 200:
                result = response.json()
                print("SUCCESS: Classification API Response received successfully!")
                print(f"Predicted Class: {result}")
                return
            else:
                print(f"ERROR: {response.status_code} - {response.text[:100]}...")
                
        except requests.exceptions.RequestException as e:
            print(f"ERROR: Network Error for {url}: {e}")
        except Exception as e:
            print(f"ERROR: Error for {url}: {e}")
    
    print("No working classification endpoint found.")

if __name__ == "__main__":
    print("Hugging Face API Test")
    print("=" * 50)
    print(f"API URL: https://pavaniyerra-hackthon4.hf.space/predict_similarity/")
    print()
    
    # Test similarity API
    test_api_similarity()
    
    # Test classification API (if available)
    test_api_classification()
    
    print("\n" + "=" * 50)
    print("API Testing Complete!")
    print("\nNote: This test uses random images.")
    print("For real testing, use actual face images.")