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| import requests | |
| import base64 | |
| import json | |
| import sys | |
| import glob | |
| import random | |
| print("=" * 60) | |
| print("PHASE 4: API FUNCTIONAL TEST") | |
| print("=" * 60) | |
| API_URL = "http://localhost:8001/api/voice-detection" | |
| API_KEY = "secret123" | |
| # Get test files | |
| human_files = glob.glob("dataset/human/tamil/*.wav")[:1] | |
| ai_files = glob.glob("dataset/ai_generated/tamil/*.mp3")[:1] | |
| if not human_files or not ai_files: | |
| print("❌ Could not find test files") | |
| sys.exit(1) | |
| human_file = human_files[0] | |
| ai_file = ai_files[0] | |
| print(f"Human test file: {human_file}") | |
| print(f"AI test file: {ai_file}") | |
| def encode_audio_file(file_path): | |
| with open(file_path, 'rb') as f: | |
| return base64.b64encode(f.read()).decode('utf-8') | |
| def test_api_request(file_path, expected_class, test_name): | |
| print(f"\n{'-' * 60}") | |
| print(f"TEST: {test_name}") | |
| print(f"{'-' * 60}") | |
| # Encode audio | |
| audio_base64 = encode_audio_file(file_path) | |
| # Determine format | |
| audio_format = 'wav' if file_path.endswith('.wav') else 'mp3' | |
| # Create request | |
| payload = { | |
| "language": "Tamil", | |
| "audioFormat": audio_format, | |
| "audioBase64": audio_base64 | |
| } | |
| headers = { | |
| "x-api-key": API_KEY, | |
| "Content-Type": "application/json" | |
| } | |
| try: | |
| response = requests.post(API_URL, json=payload, headers=headers) | |
| print(f"Status Code: {response.status_code}") | |
| if response.status_code != 200: | |
| print(f"❌ Expected 200, got {response.status_code}") | |
| print(f"Response: {response.text}") | |
| return False | |
| # Parse JSON | |
| try: | |
| data = response.json() | |
| except: | |
| print(f"❌ Invalid JSON response") | |
| return False | |
| print(f"Response: {json.dumps(data, indent=2)}") | |
| # Validate schema | |
| required_fields = ['status', 'language', 'classification', 'confidenceScore', 'explanation'] | |
| missing_fields = [f for f in required_fields if f not in data] | |
| if missing_fields: | |
| print(f"❌ Missing fields: {missing_fields}") | |
| return False | |
| # Validate values | |
| if data['status'] != 'success': | |
| print(f"❌ Status is not 'success': {data['status']}") | |
| return False | |
| if data['classification'] not in ['HUMAN', 'AI_GENERATED']: | |
| print(f"❌ Invalid classification: {data['classification']}") | |
| return False | |
| confidence = data['confidenceScore'] | |
| if not (0.05 <= confidence <= 0.95): | |
| print(f"❌ Confidence score out of range [0.05, 0.95]: {confidence}") | |
| return False | |
| if not data['explanation'] or len(data['explanation']) < 10: | |
| print(f"❌ Explanation is empty or too short") | |
| return False | |
| # Check if classification matches expectation | |
| if expected_class and data['classification'] != expected_class: | |
| print(f"⚠️ Classification mismatch: expected {expected_class}, got {data['classification']}") | |
| print(f" (Not a failure, but worth noting)") | |
| print("✅ All schema validations passed") | |
| return True | |
| except requests.exceptions.ConnectionError: | |
| print("❌ Could not connect to API. Is it running on port 8000?") | |
| return False | |
| except Exception as e: | |
| print(f"❌ Error: {e}") | |
| return False | |
| # Run tests | |
| results = [] | |
| results.append(test_api_request(human_file, 'HUMAN', 'Valid HUMAN audio')) | |
| results.append(test_api_request(ai_file, 'AI_GENERATED', 'Valid AI audio')) | |
| # Summary | |
| print("\n" + "=" * 60) | |
| print("SUMMARY") | |
| print("=" * 60) | |
| passed = sum(results) | |
| total = len(results) | |
| print(f"Tests passed: {passed}/{total}") | |
| if passed == total: | |
| print("\n✅ PHASE 4 PASSED: API functional tests successful") | |
| else: | |
| print(f"\n❌ PHASE 4 FAILED: {total - passed} test(s) failed") | |
| sys.exit(1) | |