Update app.py

app.py

@@ -1,16 +1,22 @@
 import gradio as gr
+import requests
+import time
+import re
+import csv
+import json
+import random
 import nltk
 import numpy as np
 import tflearn
-import random
-import json
-import pickle
-import torch
+import os
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from bs4 import BeautifulSoup
+import chromedriver_autoinstaller
+import pandas as pd
 from nltk.tokenize import word_tokenize
 from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
-import requests
-import pandas as pd
 
 # Ensure necessary NLTK resources are downloaded
 nltk.download('punkt')
@@ -61,7 +67,7 @@ def bag_of_words(s, words):
 def chat(message, history):
     history = history or []
     message = message.lower()
-    
+
     try:
         # Predict the tag
         results = model.predict([bag_of_words(message, words)])
@@ -78,7 +84,7 @@ def chat(message, history):
             response = "I'm sorry, I didn't understand that. Could you please rephrase?"
     except Exception as e:
         response = f"An error occurred: {str(e)}"
-    
+
     history.append((message, response))
     return history, history
 
@@ -146,13 +152,26 @@ def provide_suggestions(emotion):
             "Article URL": "https://www.health.harvard.edu/health-a-to-z",
             "Video URL": "https://youtu.be/m1vaUGtyo-A"
         }, ignore_index=True)
-        
+
     return suggestions
 
 # Google Places API to get nearby wellness professionals
-api_key = "GOOGLE_API_KEY"  # Replace with your actual API key
-
-def get_places_data(query, location, radius, api_key, next_page_token=None):
+api_key = "YOUR_GOOGLE_API_KEY"  # Replace with your actual API key
+
+def install_chrome_and_driver():
+    os.system("apt-get update")
+    os.system("apt-get install -y wget curl")
+    os.system("wget -q https://dl.google.com/linux/direct/google-chrome-stable_current_amd64.deb")
+    os.system("dpkg -i google-chrome-stable_current_amd64.deb")
+    os.system("apt-get install -y -f")
+    os.system("google-chrome-stable --version")
+    chromedriver_autoinstaller.install()
+
+# Install Chrome and Chromedriver
+install_chrome_and_driver()
+
+# Fetch places data using Google Places API
+def get_places_data(query, location, radius, api_key):
     url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
     params = {
         "query": query,
@@ -160,62 +179,48 @@ def get_places_data(query, location, radius, api_key, next_page_token=None):
         "radius": radius,
         "key": api_key
     }
-    if next_page_token:
-        params["pagetoken"] = next_page_token
     response = requests.get(url, params=params)
-    return response.json() if response.status_code == 200 else None
-
-def get_all_places(query, location, radius, api_key):
-    all_results = []
-    next_page_token = None
-    while True:
-        data = get_places_data(query, location, radius, api_key, next_page_token)
-        if data:
-            results = data.get('results', [])
-            for place in results:
-                place_id = place.get("place_id")
-                name = place.get("name")
-                address = place.get("formatted_address")
-                website = place.get("website", "Not available")
-                all_results.append([name, address, website])
-            next_page_token = data.get('next_page_token')
-            if not next_page_token:
-                break
-        else:
-            break
-    return all_results
-
-def search_wellness_professionals(location):
-    query = "therapist OR counselor OR mental health professional"
-    radius = 50000
-    google_places_data = get_all_places(query, location, radius, api_key)
-    if google_places_data:
-        df = pd.DataFrame(google_places_data, columns=["Name", "Address", "Website"])
-        return df
-    else:
-        return pd.DataFrame([["No data found.", "", ""]], columns=["Name", "Address", "Website"])
-
-# Gradio Interface
-def gradio_interface(message, location, state):
-    history = state or []  # If state is None, initialize it as an empty list
-    
-    # Stage 1: Mental Health Chatbot
-    history, _ = chat(message, history)
-    
-    # Stage 2: Sentiment Analysis
-    sentiment = analyze_sentiment(message)
-    
-    # Stage 3: Emotion Detection and Suggestions
-    emotion = detect_emotion(message)
-    suggestions = provide_suggestions(emotion)
-    
-    # Stage 4: Search for Wellness Professionals
-    wellness_results = search_wellness_professionals(location)
-    
-    # Return the results in a tabular form within the Gradio interface
-    return history, sentiment, emotion, suggestions, wellness_results, history  # Last 'history' is for state
-
-# Gradio interface setup
+    if response.status_code == 200:
+        return response.json()
+    return None
+
+# Scrape website URL from Google Maps results (using Selenium)
+def scrape_website_from_google_maps(place_name):
+    chrome_options = Options()
+    chrome_options.add_argument("--headless")
+    chrome_options.add_argument("--no-sandbox")
+    chrome_options.add_argument("--disable-dev-shm-usage")
+    driver = webdriver.Chrome(options=chrome_options)
+    search_url = f"https://www.google.com/maps/search/{place_name.replace(' ', '+')}"
+    driver.get(search_url)
+    time.sleep(5)
+    try:
+        website_element = driver.find_element_by_xpath('//a[contains(@aria-label, "Visit") and contains(@aria-label, "website")]')
+        website_url = website_element.get_attribute('href')
+    except:
+        website_url = "Not available"
+    driver.quit()
+    return website_url
+
+# Get all wellness professionals based on the location
+def get_wellness_professionals(location):
+    query = "therapist OR counselor OR mental health professional OR marriage and family therapist OR psychotherapist OR psychiatrist OR psychologist OR nutritionist OR wellness doctor OR holistic practitioner"
+    radius = 50000  # 50 km radius
+    data = get_places_data(query, location, radius, api_key)
+    if data:
+        results = data.get('results', [])
+        wellness_data = []
+        for place in results:
+            name = place.get('name')
+            address = place.get('formatted_address')
+            website = place.get('website', 'Not available')
+            if website == 'Not available':
+                website = scrape_website_from_google_maps(name)
+            wellness_data.append([name, address, website])
+        return pd.DataFrame(wellness_data, columns=["Name", "Address", "Website"])
+    return pd.DataFrame()
+
+# Gradio Interface Setup
 iface = gr.Interface(
     fn=gradio_interface,
     inputs=[
@@ -224,11 +229,11 @@ iface = gr.Interface(
         gr.State()  # One state input
     ],
     outputs=[
-        gr.Chatbot(label="Chat History", type="messages"),  # Set type="messages" as per the warning
+        gr.Chatbot(label="Chat History", type="messages"),  # Set type="messages"
         gr.Textbox(label="Sentiment Analysis"),
         gr.Textbox(label="Detected Emotion"),
         gr.Dataframe(label="Suggestions & Resources"),
-        gr.Dataframe(label="Nearby Wellness Professionals"),  # Display results as a table
+        gr.Dataframe(label="Nearby Wellness Professionals"),
         gr.State()  # One state output
     ],
     allow_flagging="never",
@@ -236,5 +241,4 @@ iface = gr.Interface(
     description="This app provides a mental health chatbot, sentiment analysis, emotion detection, and wellness professional search functionality.",
 )
 
-# Launch Gradio interface
-iface.launch(debug=True, share=True)  # Set share=True to create a public link
+iface.launch(debug=True, share=True)  # Launch with share=True to create a public link