Update app.py

app.py

@@ -1,3 +1,4 @@
+import os
 import gradio as gr
 import nltk
 import numpy as np
@@ -11,10 +12,12 @@ from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 import googlemaps
 import folium
-import os
 import pandas as pd
 import torch
 
+# Disable GPU usage for TensorFlow
+os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
 # Ensure necessary NLTK resources are downloaded
 nltk.download('punkt')
 
@@ -206,22 +209,24 @@ def gradio_app(message, location, health_query, submit_button, history, state):
 message_input = gr.Textbox(lines=1, label="Message")
 location_input = gr.Textbox(value="Honolulu, HI", label="Current Location")
 health_query_input = gr.Textbox(value="doctor", label="Health Professional Query (e.g., doctor, psychiatrist, psychologist)")
-submit_button = gr.Button("Submit")  # Submit button for triggering the app function
+submit_button = gr.Button("Submit")  # Submit button
 
-chat_history = gr.Chatbot(label="Well-Being Chat History")  # Renamed chatbot label
+# Updated chat history component with 'messages' type
+chat_history = gr.Chatbot(label="Well-Being Chat History", type='messages')
 
 # Outputs
 sentiment_output = gr.Textbox(label="Sentiment Analysis Result")
 emotion_output = gr.Textbox(label="Emotion Detection Result")
 route_info_output = gr.Textbox(label="Health Professionals Information")
 map_output = gr.HTML(label="Map with Health Professionals")
-suggestions_output = gr.DataFrame(label="Well-Being Suggestions", headers=["Title", "Subject", "Link"])  # Renamed suggestions output
+suggestions_output = gr.DataFrame(label="Well-Being Suggestions", headers=["Title", "Subject", "Link"])
 
 # Create Gradio interface
+# Ensure there is exactly one state input and one state output
 iface = gr.Interface(
     fn=gradio_app, 
-    inputs=[message_input, location_input, health_query_input, submit_button, gr.State(), gr.State()],  # Updated inputs to include submit button
-    outputs=[chat_history, sentiment_output, emotion_output, route_info_output, map_output, suggestions_output, gr.State()],  # Outputs remain unchanged
+    inputs=[message_input, location_input, health_query_input, submit_button, gr.State()],  # Updated to include only one state input
+    outputs=[chat_history, sentiment_output, emotion_output, route_info_output, map_output, suggestions_output, gr.State()],  # Updated to include only one state output
     allow_flagging="never",
     live=True,
     title="Well-Being App: Support, Sentiment, Emotion Detection & Health Professional Search"