Update app.py

app.py

@@ -7,8 +7,6 @@ import time
 import re
 from bs4 import BeautifulSoup
 import pandas as pd
-from selenium import webdriver
-from selenium.webdriver.chrome.options import Options
 import chromedriver_autoinstaller
 import os
 import nltk
@@ -20,7 +18,6 @@ import json
 import pickle
 from nltk.tokenize import word_tokenize
 from nltk.stem.lancaster import LancasterStemmer
-import subprocess
 
 # Ensure necessary NLTK resources are downloaded
 nltk.download('punkt')
@@ -111,40 +108,6 @@ query = "therapist OR counselor OR mental health professional OR marriage and fa
 location = "21.3,-157.8"  # Center of Hawaii (Oahu)
 radius = 50000  # 50 km radius
 
-# Install Chrome and Chromedriver
-def install_chrome_and_driver():
-    # Install Chrome (if not already installed)
-    os.system("apt-get update && apt-get install -y wget curl sudo")
-    os.system("wget -q https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb")
-    os.system("sudo dpkg -i google-chrome-stable_current_amd64.deb")
-    os.system("sudo apt-get install -y -f")
-    os.system("google-chrome-stable --version")
-
-    # Fix ownership of /etc/sudo.conf
-    os.system("sudo chown root:root /etc/sudo.conf")
-
-    # Verify Chrome installation
-    os.system("which google-chrome-stable")
-    if not os.path.exists("/usr/bin/google-chrome-stable"):
-        raise RuntimeError("Google Chrome was not installed correctly")
-
-    # Check if CUDA libraries are available and install them if present
-    try:
-        os.system("apt-get install -y cuda")
-        os.system("apt-get install -y libcudart.so.11.0")
-    except subprocess.CalledProcessError:
-        print("CUDA libraries not found or installation failed. Proceeding without GPU support.")
-
-    # Install Chromedriver (if not already installed)
-    chromedriver_autoinstaller.install()
-
-    # Verify Chromedriver installation
-    os.system("which chromedriver")
-    if not os.path.exists("/usr/local/bin/chromedriver"):
-        raise RuntimeError("ChromeDriver was not installed correctly")
-
-install_chrome_and_driver()
-
 # Function to send a request to Google Places API and fetch places data
 def get_places_data(query, location, radius, api_key, next_page_token=None):
     params = {
@@ -184,8 +147,8 @@ def get_place_details(place_id, api_key):
     else:
         return {}
 
-# Scrape website URL from Google Maps results (using Selenium)
-def scrape_website_from_google_maps(place_name):
+# Scrape website URL from Google Maps results (using Selenium WebDriver)
+def scrape_div_from_google_maps(place_name):
     chrome_options = Options()
     chrome_options.add_argument("--headless")
     chrome_options.add_argument("--no-sandbox")
@@ -206,7 +169,7 @@ def scrape_website_from_google_maps(place_name):
     return website_url
 
 # Scraping the website to extract phone number or email
-def scrape_website_for_contact_info(website):
+def scrape_div_for_contact_info(website):
     phone_number = "Not available"
     email = "Not available"
 
@@ -244,7 +207,7 @@ def get_all_places(query, location, radius, api_key):
                 address = place.get("formatted_address")
                 rating = place.get("rating", "Not available")
                 business_status = place.get("business_status", "Not available")
-                user_ratings_total = place.get("user_ratings_total", "Not available")
+                user_ratings_total = place.get("user_reviews_total", "Not available")
                 website = place.get("website", "Not available")
                 types = ", ".join(place.get("types", []))
                 location = place.get("geometry", {}).get("location", {})
@@ -254,15 +217,15 @@ def get_all_places(query, location, radius, api_key):
                 details = get_place_details(place_id, api_key)
                 phone_number = details.get("phone_number", "Not available")
                 if phone_number == "Not available" and website != "Not available":
-                    phone_number, email = scrape_website_for_contact_info(website)
+                    phone_number, email = scrape_div_for_contact_info(website)
                 else:
                     email = "Not available"
 
                 if website == "Not available":
-                    website = scrape_website_from_google_maps(name)
+                    website = scrape_div_from_google_maps(name)
 
                 all_results.append([name, address, phone_number, rating, business_status,
-                                    user_ratings_total, website, types, latitude, longitude,
+                                    user_div_total, website, types, latitude, longitude,
                                     details.get("opening_hours", "Not available"),
                                     details.get("reviews", "Not available"), email])
 
@@ -282,7 +245,7 @@ def save_to_csv(data, filename):
         writer = csv.writer(file)
         writer.writerow([
             "Name", "Address", "Phone", "Rating", "Business Status",
-            "User Ratings Total", "Website", "Types", "Latitude", "Longitude",
+            "User Reviews Total", "Website", "Types", "Latitude", "Longitude",
             "Opening Hours", "Reviews", "Email"
         ])
         writer.writerows(data)
@@ -306,7 +269,7 @@ with gr.Blocks() as demo:
 
     # Model prediction for emotion detection
     def predict_emotion(text):
-        pipe = pipeline("text-classification", model=model, tokenizer=tokenizer)
+        pipe = pipeline("text-classification", model=model, tokenizer=tokenizer_sentiment)
         result = pipe(text)
         emotion = result[0]['label']
         return emotion
@@ -318,13 +281,13 @@ with gr.Blocks() as demo:
         if emotion == 'joy':
             return "You're feeling happy! Keep up the great mood!\nUseful Resources:\n[Relaxation Techniques](https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation)\n[Dealing with Stress](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n[Emotional Wellness Toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/m1vaUGtyo-A)"
         elif emotion == 'anger':
-            return "You're feeling angry. It's okay to feel this way. Let's try to calm down.\nUseful Resources:\n[Emotional Wellness Toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n[Stress Management Tips](https://www.health.harvard.edu/health-a-to-z)\n[Dealing with Anger](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/MIc299Flibs)"
+            return "You're feeling angry. It's okay to feel this way. Let's try to calm down.\nUseful Resources:\n[Emotional Wellness toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n[Stress management tips](https://www.health.harvard.edu/health-a-to-z)\n[Dealing with anger](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/MIc299Flibs)"
         elif emotion == 'fear':
-            return "You're feeling fearful. Take a moment to breathe and relax.\nUseful Resources:\n[Mindfulness Practices](https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation)\n[Coping with Anxiety](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n[Emotional Wellness Toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/yGKKz185M5o)"
+            return "You're feeling fearful. Take a moment to breathe and relax.\nUseful Resources:\n[Mindfulness practices](https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation)\n[Coping with anxiety](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n[Emotional wellness toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/yGKKz185M5o)"
         elif emotion == 'sadness':
-            return "You're feeling sad. It's okay to take a break.\nUseful Resources:\n[Emotional Wellness Toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n[Dealing with Anxiety](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/-e-4Kx5px_I)"
+            return "You're feeling sad. It's okay to take a break.\nUseful Resources:\n[Emotional wellness toolkit](https://www.nih.gov/health-information/emotional-wellness-toolkit)\n[Dealing with anxiety](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/-e-4Kx5px_I)"
         elif emotion == 'surprise':
-            return "You're feeling surprised. It's okay to feel neutral!\nUseful Resources:\n[Managing Stress](https://www.health.harvard.edu/health-a-to-z)\n[Coping Strategies](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/m1vaUGtyo-A)"
+            return "You're feeling surprised. It's okay to feel neutral!\nUseful Resources:\n[Managing stress](https://www.health.harvard.edu/health-a-to-z)\n[Coping strategies](https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety)\n\nRelaxation Videos:\n[Watch on YouTube](https://youtu.be/m1vaUGtyo-A)"
 
     emotion_output = gr.Textbox(label="Emotion Detected")
     emotion_output.change(show_suggestions, inputs=emotion_output, outputs=gr.Textbox(label="Suggestions"))
@@ -347,10 +310,12 @@ with gr.Blocks() as demo:
         message = message.lower()
         
         try:
+            # Predict the tag
             results = model.predict([bag_of_words(message, words)])
             results_index = np.argmax(results)
             tag = labels[results_index]
 
+            # Match tag with intent and choose a random response
             for tg in data["intents"]:
                 if tg['tag'] == tag:
                     responses = tg['responses']
@@ -369,7 +334,7 @@ with gr.Blocks() as demo:
 
     # User input for text (sentiment analysis)
     user_input_sentiment = gr.Textbox(lines=1, label="Enter text to analyze sentiment:")
-
+    
     # Prediction button for sentiment analysis
     def predict_sentiment(text):
         inputs = tokenizer_sentiment(text, return_tensors="pt")
@@ -383,13 +348,13 @@ with gr.Blocks() as demo:
     user_input_sentiment.change(predict_sentiment, inputs=user_input_sentiment, outputs=sentiment_output)
 
     # Button to fetch wellness professionals data
-    fetch_button = gr.Button("Fetch Wellness Professionals Data")
-    data_output = gr.Dataframe(headers=["Name", "Address", "Phone", "Rating", "Business Status", "User Ratings Total", "Website", "Types", "Latitude", "Longitude", "Opening Hours", "Reviews", "Email"])
+    fetch_button = gr.Button("Fetch Wellness professionals data")
+    data_output = gr.Dataframe(headers=["Name", "Address", "Phone", "Rating", "Business Status", "User Reviews Total", "Website", "Types", "Latitude", "Longitude", "Opening Hours", "Reviews", "Email"])
 
     def fetch_data():
         all_results = get_all_places(query, location, radius, api_key)
         if all_results:
-            return pd.DataFrame(all_results, columns=["Name", "Address", "Phone", "Rating", "Business Status", "User Ratings Total", "Website", "Types", "Latitude", "Longitude", "Opening Hours", "Reviews", "Email"])
+            return pd.DataFrame(all_results, columns=["Name", "Address", "Phone", "Rating", "Business Status", "User Reviews Total", "Website", "Types", "Latitude", "Longitude", "Opening Hours", "Reviews", "Email"])
         else:
             return "No data found."