app.py

from flask import Flask, request, jsonify
from birdnetlib import Recording
from birdnetlib.analyzer import Analyzer
from datetime import datetime
import tempfile, os, subprocess

app = Flask(__name__)
print("Loading BirdNET model...")
analyzer = Analyzer()
print("BirdNET model loaded.")

@app.route('/health', methods=['GET'])
def health():
    return jsonify({'status': 'ok', 'model': 'BirdNET-Analyzer'})

@app.route('/analyze', methods=['POST'])
def analyze():
    if 'audio' not in request.files:
        return jsonify({'error': 'No audio file provided'}), 400

    audio_file = request.files.get('audio')
    lat = float(request.args.get('lat', 0))
    lon = float(request.args.get('lon', 0))

    # Save incoming .m4a to temp file
    with tempfile.NamedTemporaryFile(suffix='.m4a', 
                                     delete=False) as tmp_m4a:
        tmp_m4a_path = tmp_m4a.name
        audio_file.save(tmp_m4a_path)

    # Convert .m4a to .wav using ffmpeg
    tmp_wav_path = tmp_m4a_path.replace('.m4a', '.wav')
    
    try:
        subprocess.run([
            'ffmpeg', '-y',
            '-i', tmp_m4a_path,
            '-ar', '48000',
            '-ac', '1',
            '-f', 'wav',
            tmp_wav_path
        ], check=True, capture_output=True)

        # Run BirdNET on the WAV file
        recording = Recording(
            analyzer,
            tmp_wav_path,
            lat=lat,
            lon=lon,
            date=datetime.now(),
            min_conf=0.25
        )
        recording.analyze()
        detections = recording.detections

    except subprocess.CalledProcessError as e:
        return jsonify({
            'error': 'Audio conversion failed',
            'detail': e.stderr.decode()
        }), 500
    except Exception as e:
        return jsonify({
            'error': 'Analysis failed',
            'detail': str(e)
        }), 500
    finally:
        # Always clean up temp files
        if os.path.exists(tmp_m4a_path):
            os.unlink(tmp_m4a_path)
        if os.path.exists(tmp_wav_path):
            os.unlink(tmp_wav_path)

    if not detections:
        return jsonify({'error': 'No species detected'}), 404

    top = sorted(detections,
                 key=lambda x: x['confidence'],
                 reverse=True)[0]

    return jsonify({
        'species': top['common_name'],
        'scientific_name': top['scientific_name'],
        'confidence': round(top['confidence'], 3),
        'all_detections': [
            {
                'species': d['common_name'],
                'confidence': round(d['confidence'], 3)
            }
            for d in detections[:5]
        ]
    })

if __name__ == '__main__':
    port = int(os.environ.get('PORT', 7860))
    app.run(host='0.0.0.0', port=port)