Temporarily comment out OpenAI Whisper (STT) functionality

app.py

@@ -9,8 +9,8 @@ import gradio as gr
 import requests
 
 # UNCOMMENT TO USE WHISPER
-import warnings
-import whisper
+# import warnings
+# import whisper
 
 from langchain import ConversationChain, LLMChain
 
@@ -59,29 +59,27 @@ POLLY_VOICE_DATA = PollyVoiceData()
 
 
 # UNCOMMENT TO USE WHISPER
-warnings.filterwarnings("ignore")
-WHISPER_MODEL = whisper.load_model("tiny")
-print("WHISPER_MODEL", WHISPER_MODEL)
+# warnings.filterwarnings("ignore")
+# WHISPER_MODEL = whisper.load_model("tiny")
+# print("WHISPER_MODEL", WHISPER_MODEL)
 
 
 # UNCOMMENT TO USE WHISPER
-def transcribe(aud_inp):
-    if aud_inp is None:
-        return ""
-    aud = whisper.load_audio(aud_inp)
-    aud = whisper.pad_or_trim(aud)
-    mel = whisper.log_mel_spectrogram(aud).to(WHISPER_MODEL.device)
-    _, probs = WHISPER_MODEL.detect_language(mel)
-
-    options = whisper.DecodingOptions()
-    # options = whisper.DecodingOptions(language="ja")
-
-    result = whisper.decode(WHISPER_MODEL, mel, options)
-    print("result.text", result.text)
-    result_text = ""
-    if result and result.text:
-        result_text = result.text
-    return result_text
+# def transcribe(aud_inp):
+#     if aud_inp is None:
+#         return ""
+#     aud = whisper.load_audio(aud_inp)
+#     aud = whisper.pad_or_trim(aud)
+#     mel = whisper.log_mel_spectrogram(aud).to(WHISPER_MODEL.device)
+#     _, probs = WHISPER_MODEL.detect_language(mel)
+#     options = whisper.DecodingOptions()
+#     # options = whisper.DecodingOptions(language="ja")
+#     result = whisper.decode(WHISPER_MODEL, mel, options)
+#     print("result.text", result.text)
+#     result_text = ""
+#     if result and result.text:
+#         result_text = result.text
+#     return result_text
 
 
 # Pertains to Express-inator functionality
@@ -470,10 +468,10 @@ with gr.Blocks(css=".gradio-container {background-color: lightgray}") as block:
             submit = gr.Button(value="Send", variant="secondary").style(full_width=False)
 
         # UNCOMMENT TO USE WHISPER
-        with gr.Row():
-            audio_comp = gr.Microphone(source="microphone", type="filepath", label="Just say it!",
-                                       interactive=True, streaming=False)
-            audio_comp.change(transcribe, inputs=[audio_comp], outputs=[message])
+        # with gr.Row():
+        #     audio_comp = gr.Microphone(source="microphone", type="filepath", label="Just say it!",
+        #                                interactive=True, streaming=False)
+        #     audio_comp.change(transcribe, inputs=[audio_comp], outputs=[message])
 
         gr.Examples(
             examples=["How many people live in Canada?",