Create app.py

app.py

@@ -0,0 +1,50 @@
+import os
+os.system("pip install git+https://github.com/openai/whisper.git")
+import gradio as gr
+import whisper
+
+model = whisper.load_model("small")
+
+def inference(audio):
+    audio = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audio)
+    
+    mel = whisper.log_mel_spectrogram(audio).to(model.device)
+    
+    _, probs = model.detect_language(mel)
+    
+    options = whisper.DecodingOptions(fp16 = False)
+    result = whisper.decode(model, mel, options)
+    
+    print(result.text)
+    return result.text, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+
+
+with block:
+    with gr.Group():
+        with gr.Box():
+            with gr.Row().style(mobile_collapse=False, equal_height=True):
+                audio = gr.Audio(
+                    label="Input Audio",
+                    show_label=False,
+                    source="microphone",
+                    type="filepath"
+                )
+
+                btn = gr.Button("Transcribe")
+        text = gr.Textbox(show_label=False, elem_id="result-textarea")
+        with gr.Group(elem_id="share-btn-container"):
+            community_icon = gr.HTML(community_icon_html, visible=False)
+            loading_icon = gr.HTML(loading_icon_html, visible=False)
+            share_button = gr.Button("Share to community", elem_id="share-btn", visible=False)
+        
+
+
+        
+        btn.click(inference, inputs=[audio], outputs=[text, community_icon, loading_icon, share_button])
+        share_button.click(None, [], [], _js=share_js)
+
+
+block.launch()
+
+