Put basic transcription in app.py

app.py

@@ -1,7 +1,43 @@
+from flask import Flask, request, jsonify
+from whisper_online import *
+import librosa
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+@lru_cache
+def load_audio(fname):
+    a, _ = librosa.load(fname, sr=16000, dtype=np.float32)
+    return a
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+
+asr = FasterWhisperASR("en", "large-v2")  # loads and wraps Whisper model
+online = OnlineASRProcessor(asr)  # create processing object with default buffer trimming option
+
+def transcribe(audio_file)
+    try:
+        audio_data = load_audio(audio_file)
+        
+        # Insert audio chunk into the ASR processor
+        online.insert_audio_chunk(audio_data)
+        
+        # Process the audio chunk
+        o = online.process_iter()
+        
+        # Send current partial output
+        return o
+        
+    except Exception as e:
+        return str(e)
+
+def finish_stream():
+    try:
+        # Finish audio processing
+        o = online.finish()
+        
+        # Send last output
+        return o
+        
+    except Exception as e:
+        return str(e)
+
+iface = gr.Interface(fn=transcribe,inputs = "text", outputs = "text")
+iface.launch()