Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the Hugging Face model
+emotion_classifier = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions", return_all_scores=True)
+
+# Define a function to process the transcribed text with the emotion model
+def transcribe_and_analyze(audio):
+    # Load Whisper for transcription
+    whisper = gr.load("models/openai/whisper-large-v3-turbo")
+    transcription = whisper(audio)  # Transcribe audio
+    # Analyze emotions in the transcribed text
+    emotions = emotion_classifier(transcription["text"])
+    return transcription["text"], emotions
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=transcribe_and_analyze,
+    inputs=gr.Audio(source="microphone", type="filepath"),  # Accept audio input
+    outputs=[
+        gr.Textbox(label="Transcription"),  # Show the transcription
+        gr.JSON(label="Emotion Analysis")  # Show the emotion analysis
+    ],
+    title="Audio to Emotion Analysis"
+)
+
+# Launch the Gradio app
+interface.launch()