import numpy as np
import librosa
import json
import warnings

warnings.filterwarnings("ignore")

def analyze_audio(file_path):
    print(f"Analyzing {file_path}...")
    try:
        # Use pydub first (mimic app behavior)
        from pydub import AudioSegment
        import io
        
        print("   Loading with pydub...")
        audio = AudioSegment.from_file(file_path)
        wav_io = io.BytesIO()
        audio.export(wav_io, format="wav")
        wav_io.seek(0)
        
        y, sr = librosa.load(wav_io, sr=16000)
        
        # 1. Silence Check
        rms = librosa.feature.rms(y=y)[0]
        silence_percent = np.sum(rms < 0.01) / len(rms)
        
        # 2. Spectral Properties (AI often has lower variance)
        centroid = librosa.feature.spectral_centroid(y=y, sr=sr)[0]
        centroid_var = np.var(centroid)
        
        # 3. Zero Crossing Rate
        zcr = librosa.feature.zero_crossing_rate(y)[0]
        zcr_var = np.var(zcr)
        
        results = {
            "duration": len(y)/sr,
            "silence_percent": float(silence_percent),
            "rms_mean": float(np.mean(rms)),
            "centroid_var": float(centroid_var),
            "zcr_var": float(zcr_var),
            "sample_rate": sr
        }
        
        print(json.dumps(results, indent=2))
        
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    analyze_audio("SH 69 4.mp3")