Create app.py

app.py

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+import whisper
+import gradio as gr
+import time
+
+# Load the Whisper model
+model = whisper.load_model("base")
+
+# Function to transcribe audio and return sentences with a delay
+def transcribe_audio(audio):
+    # Transcribe the audio file
+    result = model.transcribe(audio.name)
+
+    # Split the transcription into sentences
+    sentences = result["text"].split(". ")
+
+    # Print each sentence on a new line with a short delay
+    output = []
+    for sentence in sentences:
+        if sentence.strip():  # Check if the sentence is not empty
+            output.append(sentence.strip() + ".")
+            time.sleep(2)  # Add a short delay before printing the next sentence
+    return "\n".join(output)
+
+# Gradio interface
+interface = gr.Interface(
+    fn=transcribe_audio, 
+    inputs=gr.Audio(source="upload", type="file"), 
+    outputs="text",
+    title="Whisper Transcription with Delay",
+    description="Upload an audio file to transcribe and display each sentence with a short delay."
+)
+
+# Launch the Gradio app
+interface.launch()