Update app.py

app.py

@@ -10,14 +10,8 @@ from nltk.tokenize import word_tokenize
 from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 import requests
-import re
 from bs4 import BeautifulSoup
-import time
 import pandas as pd
-from selenium import webdriver
-from selenium.webdriver.chrome.options import Options
-import chromedriver_autoinstaller
-import os
 import geocoder  # Use geocoder to get latitude/longitude from city
 
 # Ensure necessary NLTK resources are downloaded
@@ -212,89 +206,38 @@ def find_wellness_professionals(location, state):
     
     google_places_data = get_all_places(query, location_coords, radius, api_key)
     if google_places_data:
-        df = pd.DataFrame(google_places_data, columns=[
-            "Name", "Address", "Phone", "Rating", "Business Status",
-            "User Ratings Total", "Website", "Types", "Latitude", "Longitude",
-            "Opening Hours", "Reviews", "Email"
-        ])
-        # Display results in Gradio interface
-        if not df.empty:
-            df_html = df.to_html(classes="table table-striped", index=False)
-            return f"Found wellness professionals in your area: \n{df_html}", state
-        else:
-            return "No wellness professionals found for your location. Try another search.", state
+        response = "Wellness professionals near you:\n"
+        for place in google_places_data:
+            response += f"- {place['name']} at {place['formatted_address']}\n"
     else:
-        return "Sorry, there was an issue fetching data. Please try again later.", state
+        response = "Sorry, no wellness professionals found in your area. Please try another location."
+
+    return response, state
 
-# Function to fetch places data using Google Places API
+# Call Google Places API
 def get_all_places(query, location, radius, api_key):
-    url = f"https://maps.googleapis.com/maps/api/place/textsearch/json?query={query}&location={location}&radius={radius}&key={api_key}"
-    response = requests.get(url)
-    if response.status_code == 200:
-        results = response.json().get("results", [])
-        places = []
-        for place in results:
-            name = place.get("name")
-            address = place.get("formatted_address")
-            phone = place.get("formatted_phone_number", "Not available")
-            rating = place.get("rating", "Not rated")
-            business_status = place.get("business_status", "N/A")
-            user_ratings_total = place.get("user_ratings_total", "N/A")
-            website = place.get("website", "Not available")
-            types = place.get("types", [])
-            lat, lng = place.get("geometry", {}).get("location", {}).values()
-            opening_hours = place.get("opening_hours", {}).get("weekday_text", [])
-            reviews = place.get("reviews", [])
-            email = "Not available"  # Assume email is not included in the API response
-            
-            # Adding the place data to the list
-            places.append([name, address, phone, rating, business_status, user_ratings_total,
-                           website, types, lat, lng, opening_hours, reviews, email])
-        return places
-    else:
-        return []
+    search_url = f"https://maps.googleapis.com/maps/api/place/textsearch/json?query={query}&location={location}&radius={radius}&key={api_key}"
+    response = requests.get(search_url).json()
+    
+    if 'results' in response:
+        return response['results']
+    return []
 
-# Gradio interface setup
-def gradio_interface():
+# Gradio UI components
+def create_ui():
     with gr.Blocks() as demo:
-        # Set title and description
-        gr.Markdown("<h1 style='text-align: center;'>Mental Health Support Chatbot 🤖</h1>")
-        gr.Markdown("<p style='text-align: center;'>Get emotional well-being suggestions and find wellness professionals nearby.</p>")
-        
-        # State to manage step transitions
-        state = gr.State({"step": 1})
-        
-        # Chat interface
-        with gr.Row():
-            chatbot = gr.Chatbot(label="Chatbot")
-            user_input = gr.Textbox(placeholder="Type your message here...", label="Your Message")
-            send_button = gr.Button("Send")
-        
-        # Output for emotion, sentiment, suggestions
-        with gr.Row():
-            sentiment_output = gr.Textbox(label="Sentiment Analysis")
-            emotion_output = gr.Textbox(label="Emotion Detection")
-            suggestions_output = gr.Textbox(label="Suggestions")
+        state = gr.State()
+        chatbot = gr.Chatbot(elem_id="chatbot", label="Mental Health Chatbot")
+        message_input = gr.Textbox(placeholder="Ask me something...", label="Enter your message")
+        sentiment_output = gr.Textbox(placeholder="Sentiment result", label="Sentiment")
+        emotion_output = gr.Textbox(placeholder="Detected emotion", label="Emotion")
+        wellness_output = gr.Textbox(placeholder="Wellness professional list", label="Wellness Professionals")
         
-        # Input for location for wellness professionals
-        with gr.Row():
-            location_input = gr.Textbox(label="Your Location (City/Region)", placeholder="Enter your city...")
-            search_button = gr.Button("Search Wellness Professionals")
-        
-        # Button actions
-        send_button.click(chat, inputs=[user_input, chatbot, state], outputs=[chatbot, chatbot, state])
-        user_input.submit(chat, inputs=[user_input, chatbot, state], outputs=[chatbot, chatbot, state])
-        
-        send_button.click(analyze_sentiment, inputs=[user_input, state], outputs=[sentiment_output, state])
-        user_input.submit(analyze_sentiment, inputs=[user_input, state], outputs=[sentiment_output, state])
-        
-        send_button.click(detect_emotion, inputs=[user_input, state], outputs=[emotion_output, suggestions_output, state])
-        user_input.submit(detect_emotion, inputs=[user_input, state], outputs=[emotion_output, suggestions_output, state])
-        
-        search_button.click(find_wellness_professionals, inputs=[location_input, state], outputs=[suggestions_output, state])
-    
-    demo.launch(debug=True)
-
-# Run the Gradio interface
-if __name__ == "__main__":
-    gradio_interface()
+        message_input.submit(chat, [message_input, chatbot, state], [chatbot, chatbot, state])
+        message_input.submit(analyze_sentiment, [message_input, state], [sentiment_output, state])
+        sentiment_output.submit(detect_emotion, [sentiment_output, state], [emotion_output, wellness_output, state])
+        return demo
+
+# Launch the Gradio interface
+demo = create_ui()
+demo.launch(debug=True)