Tidied up the app

app.py

@@ -17,19 +17,12 @@ description = """
 
 diction_text = "How now brown cow"
 
-test_text = f"""
-    <div>
-        <p>{diction_text}</p>
-    </div>
-"""
-
-# diction = gr.HTML(test_text)
 
 diction_script = gr.Textbox(diction_text, interactive=False)
 
 
 device = "cpu"
-# device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
 torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
 
 model_id = "openai/whisper-large-v3"
@@ -56,23 +49,19 @@ pipe = pipeline(
 )
 
 
-def diff_texts(audio_input: str):
-    test_text = diction_text
+def diff_texts(diction_text: str, audio_input: str):
+
     d = Differ()
 
     return [
         (token[2:], token[0] if token[0] != "" else None)
-        for token in d.compare(test_text, audio_input)
+        for token in d.compare(diction_text, audio_input)
     ]
 
 
-def transcribe_audio(diction, audio):
-    print("Diction", diction)
+def transcribe_audio(diction_text, audio):
     result = pipe(audio)
-    print(f'TRANSCRIPTION {result["text"]}')
-    diff_text = diff_texts(result["text"])
-
-    print("diff", diff_text)
+    diff_text = diff_texts(diction_text, result["text"])
 
     return diff_text
 
@@ -105,16 +94,6 @@ demo = gr.Interface(
     theme="abidlabs/Lime",
 )
 
-# with gr.Blocks() as demo:
-#     gr.HTML(description)
-#     gr.HTML(test_text)
-
-#     with gr.Row():
-#         inp = input_audio
-#         out = highlighted_results
-#     btn = gr.Button("Run")
-#     btn.click(fn=transcribe_audio, inputs=[diction_script, inp], outputs=out)
-
 
 if __name__ == "__main__":
     demo.launch()