Create app.py

app.py

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+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()