app.py

import gradio as gr
from transformers import pipeline

# Load Whisper for speech-to-text
whisper = pipeline("automatic-speech-recognition", model="openai/whisper-medium")

# Load DistilBERT for sentiment analysis
sentiment_analyzer = pipeline("sentiment-analysis", model="distilbert-base-uncased-finetuned-sst-2-english")

# Function to process audio and analyze tone
def analyze_call(audio_file):
    # Step 1: Transcribe audio to text
    transcription = whisper(audio_file)["text"]
    
    # Step 2: Analyze sentiment of the transcription
    sentiment_result = sentiment_analyzer(transcription)[0]
    
    return {
        "transcription": transcription,
        "sentiment": sentiment_result["label"],
        "confidence": sentiment_result["score"]
    }

# Gradio Interface
interface = gr.Interface(
    fn=analyze_call,
    inputs=gr.Audio(source="microphone", type="filepath"),
    outputs=[
        gr.Textbox(label="Transcription"),
        gr.Textbox(label="Sentiment"),
        gr.Textbox(label="Confidence")
    ],
    live=True,  # Enable real-time processing
    title="Real-Time Call Analysis",
    description="Upload or record audio to analyze tone and sentiment."
)

# Launch the app
interface.launch()