app.py

from flask import Flask, render_template, jsonify

app = Flask(__name__)

# Replace with your AssemblyAI API key
ASSEMBLYAI_API_KEY = "67883cd71f0d4a58a27a34e058f0d924"

# URL of the file to transcribe
FILE_URL = "/content/call.mp3"

# You can also transcribe a local file by passing in a file path
# FILE_URL = './path/to/file.mp3'

@app.route('/analyze', methods=['GET'])
def analyze():
    # Transcribe audio to text
    transcriber = aai.Transcriber(api_key=ASSEMBLYAI_API_KEY)
    transcript = transcriber.transcribe(FILE_URL)
    text = transcript.text

    # Perform sentiment analysis
    sentiment_analyzer = pipeline("sentiment-analysis")
    sentiment = sentiment_analyzer(text)

    # Perform emotion analysis
    emotion_analyzer = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
    emotions = emotion_analyzer(text)

    # Format results
    result = {
        "transcript": text,
        "sentiment": {
            "score": sentiment[0]['score'],
            "label": sentiment[0]['label']
        },
        "emotion": [{
            "label": emotion['label'],
            "score": emotion['score']
        } for emotion in emotions[0]]
    }

    return render_template('analyze.html', result=result)

if __name__ == '__main__':
    app.run(debug=True)