Update app.py

app.py

@@ -10,8 +10,6 @@ def translate_or_transcribe(audio, task):
     text_result = whisper(audio, None, task, fn_index=0)
     return text_result
     
-
-
 #Streaming endpoint
 API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
 
@@ -67,7 +65,7 @@ def predict(inputs, top_p, temperature, openai_api_key, history=[]):
 def reset_textbox():
     return gr.update(value='')
 
-title = """<h1 align="center">🔥ChatGPT API 🚀Streaming🚀</h1>"""
+title = """<h1 align="center">🔥ChatGPT API 🚀Streaming🚀 with Whisper</h1>"""
 description = """Language models can be conditioned to act like dialogue agents through a conversational prompt that typically takes the form:
 ```
 User: <utterance>
@@ -88,6 +86,12 @@ with gr.Blocks(css = """#col_container {width: 700px; margin-left: auto; margin-
     with gr.Column(elem_id = "col_container"):
         openai_api_key = gr.Textbox(type='password', label="Enter your OpenAI API key here")
         chatbot = gr.Chatbot(elem_id='chatbot') #c
+
+        prompt_input_audio = gr.Audio(source="microphone",type="filepath",label="Record Audio Input"
+                                    )
+        translate_btn = gr.Button("Check Whisper first ? 👍")
+            
+        whisper_task = gr.Radio(["translate", "transcribe"], value="translate", show_label=False)
         inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter") #t
         state = gr.State([]) #s
         b1 = gr.Button()
@@ -99,7 +103,11 @@ with gr.Blocks(css = """#col_container {width: 700px; margin-left: auto; margin-
             #top_k = gr.Slider( minimum=1, maximum=50, value=4, step=1, interactive=True, label="Top-k",)
             #repetition_penalty = gr.Slider( minimum=0.1, maximum=3.0, value=1.03, step=0.01, interactive=True, label="Repetition Penalty", )
     
-
+    translate_btn.click(fn=translate_or_transcribe, 
+                         inputs=[prompt_input_audio,whisper_task], 
+                         outputs=inputs
+                        )
+                    
     inputs.submit( predict, [inputs, top_p, temperature, openai_api_key, state], [chatbot, state],)
     b1.click( predict, [inputs, top_p, temperature, openai_api_key, state], [chatbot, state],)
     b1.click(reset_textbox, [], [inputs])