Update app.py

app.py

@@ -1,55 +1,55 @@
-import gradio as gr
-from dotenv import load_dotenv
-from gradio import ChatMessage
-from setup import  Speech_Text
-from temp import Script
-load_dotenv()
-
-transcriptor = Speech_Text()
-output_id = None
-database_con = Script()
-
-# Function to generate chatbot response
-def generate_response(chat_history: list[ChatMessage]):
-    return database_con.request(chat_history)
-
-def process(audio, input_text, chat_history: list[ChatMessage]):
-
-    if audio is not None:
-        transcript = transcriptor.get_transcript(audio)
-        chat_history.append({"role": "user", "content": transcript})
-
-    elif input_text:
-        chat_history.append({"role": "user", "content": input_text})
-
-    else:
-        response = 'Provide a query text or an audio to query.'
-        chat_history.append({"role": "assistant", "content": response})
-        audio_data = transcriptor.speech_synthesis(response)
-        return audio_data, chat_history
-
-    response = generate_response(chat_history)
-    chat_history.append({"role": "assistant", "content": response})
-    # audio_data = transcriptor.speech_synthesis(response)
-    return chat_history
-
-# Create Gradio Blocks interface
-with gr.Blocks() as demo:
-    
-    with gr.Row():
-        chatbot = gr.Chatbot(label="Chatbot Conversation", type="messages", bubble_full_width=True, show_copy_button=True, autoscroll=True)
-    
-    with gr.Row():
-        input_textbox = gr.Textbox(label="Input Text", placeholder="Type your message here...")
-        input_audio = gr.Audio(label="Input Audio", sources="microphone", type="numpy")
-    
-    process_button = gr.Button("Submit Query")
-
-    process_button.click(
-        fn=process,
-        inputs=[input_audio, input_textbox, chatbot],
-        outputs=[chatbot]
-    )
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0",server_port=80)
+import gradio as gr
+from dotenv import load_dotenv
+from gradio import ChatMessage
+from setup import  Speech_Text
+from temp import Script
+load_dotenv()
+
+transcriptor = Speech_Text()
+output_id = None
+database_con = Script()
+
+# Function to generate chatbot response
+def generate_response(chat_history: list[ChatMessage]):
+    return database_con.request(chat_history)
+
+def process(audio, input_text, chat_history: list[ChatMessage]):
+
+    if audio is not None:
+        transcript = transcriptor.get_transcript(audio)
+        chat_history.append({"role": "user", "content": transcript})
+
+    elif input_text:
+        chat_history.append({"role": "user", "content": input_text})
+
+    else:
+        response = 'Provide a query text or an audio to query.'
+        chat_history.append({"role": "assistant", "content": response})
+        audio_data = transcriptor.speech_synthesis(response)
+        return audio_data, chat_history
+
+    response = generate_response(chat_history)
+    chat_history.append({"role": "assistant", "content": response})
+    # audio_data = transcriptor.speech_synthesis(response)
+    return chat_history
+
+# Create Gradio Blocks interface
+with gr.Blocks() as demo:
+    
+    with gr.Row():
+        chatbot = gr.Chatbot(label="Chatbot Conversation", type="messages", bubble_full_width=True, show_copy_button=True, autoscroll=True)
+    
+    with gr.Row():
+        input_textbox = gr.Textbox(label="Input Text", placeholder="Type your message here...")
+        input_audio = gr.Audio(label="Input Audio", sources="microphone", type="numpy")
+    
+    process_button = gr.Button("Submit Query")
+
+    process_button.click(
+        fn=process,
+        inputs=[input_audio, input_textbox, chatbot],
+        outputs=[chatbot]
+    )
+
+if __name__ == "__main__":
+    demo.launch()