V1

app.py

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+import gradio as gr
+from transformers import pipeline
+# Load Whisper pipeline
+pipe = pipeline(task="automatic-speech-recognition", model="openai/whisper-small")
+# Function to transcribe audio file
+def transcribe(audio_file):
+    if audio_file is None:
+        return "Please upload an audio file."
+    return pipe(audio_file)["text"]
+# Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("## 🎙 Whisper Speech-to-Text (ASR)\nUpload or record audio and get transcription.")
+    
+    with gr.Row():
+        audio_input = gr.Audio(type="filepath", label="Upload or Record Audio")
+        output_text = gr.Textbox(label="Transcription")
+    
+    transcribe_btn = gr.Button("Transcribe")
+    transcribe_btn.click(fn=transcribe, inputs=audio_input, outputs=output_text)
+app.launch()