Update app.py

app.py

@@ -1,6 +1,7 @@
 from transformers import pipeline
 from transformers.pipelines.audio_utils import ffmpeg_microphone_live
 import torch
+import gradio as gr
 
 asr_model = "openai/whisper-tiny.en"
 nlp_model = "MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli"
@@ -36,6 +37,14 @@ while True:
     top_label = output['labels'][0]
     top_score = output['scores'][0]
     print(f"Top Prediction: {top_label} with a score of {top_score:.2f}")
+    
+
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.inputs.Audio(source="microphone", type="filepath"),
+    outputs="text",
+    title="Real-Time ASR Transcription",
+    description="Speak into the microphone and get the real-time transcription."
+)
 
-
-
+iface.launch()