Update app.py

app.py

@@ -2,7 +2,6 @@ import os
 import gradio as gr
 import nltk
 import numpy as np
-import tensorflow as tf
 import tflearn
 import random
 import json
@@ -16,7 +15,7 @@ import torch
 
 # Disable GPU usage for TensorFlow
 os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
-os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
+os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'  # Suppress TensorFlow warnings
 
 # Ensure necessary NLTK resources are downloaded
 nltk.download("punkt")
@@ -24,14 +23,14 @@ nltk.download("punkt")
 # Initialize stemmer
 stemmer = LancasterStemmer()
 
-# Load intents.json and training data for chatbot
+# Load chatbot intents and training data
 with open("intents.json") as file:
     intents_data = json.load(file)
 
 with open("data.pickle", "rb") as f:
     words, labels, training, output = pickle.load(f)
 
-# Build Chatbot Model
+# Build the chatbot's neural network model
 net = tflearn.input_data(shape=[None, len(training[0])])
 net = tflearn.fully_connected(net, 8)
 net = tflearn.fully_connected(net, 8)
@@ -40,18 +39,16 @@ net = tflearn.regression(net)
 chatbot_model = tflearn.DNN(net)
 chatbot_model.load("MentalHealthChatBotmodel.tflearn")
 
-# Sentiment Analysis Model (Hugging Face)
+# Hugging Face models for sentiment and emotion detection
 tokenizer_sentiment = AutoTokenizer.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
 model_sentiment = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitter-roberta-base-sentiment")
-
-# Emotion Detection Model
 tokenizer_emotion = AutoTokenizer.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
 model_emotion = AutoModelForSequenceClassification.from_pretrained("j-hartmann/emotion-english-distilroberta-base")
 
-# Google Maps API Client
+# Google Maps API client
 gmaps = googlemaps.Client(key=os.getenv('GOOGLE_API_KEY'))
 
-# Process Text Input for Chatbot
+# Chatbot logic
 def bag_of_words(s, words):
     bag = [0] * len(words)
     s_words = word_tokenize(s)
@@ -62,7 +59,6 @@ def bag_of_words(s, words):
                 bag[i] = 1
     return np.array(bag)
 
-# Chatbot Functionality
 def chatbot(message, history):
     history = history or []
     try:
@@ -79,7 +75,7 @@ def chatbot(message, history):
     history.append({"role": "assistant", "content": response})
     return history, response
 
-# Detect Sentiment
+# Sentiment analysis
 def analyze_sentiment(user_input):
     inputs = tokenizer_sentiment(user_input, return_tensors="pt")
     with torch.no_grad():
@@ -88,98 +84,99 @@ def analyze_sentiment(user_input):
     sentiment_map = ["Negative 😔", "Neutral 😐", "Positive 😊"]
     return sentiment_map[sentiment_class]
 
-# Detect Emotion
+# Emotion detection
 def detect_emotion(user_input):
     pipe = pipeline("text-classification", model=model_emotion, tokenizer=tokenizer_emotion)
     result = pipe(user_input)
     emotion = result[0]["label"]
-    emotion_map = {
-        "joy": "😊 Joy",
-        "anger": "😠 Anger",
-        "sadness": "😢 Sadness",
-        "fear": "😨 Fear",
-        "surprise": "😲 Surprise",
-        "neutral": "😐 Neutral",
-    }
-    return emotion_map.get(emotion, "Unknown Emotion 🤔")
+    return emotion
 
-# Generate Suggestions for Detected Emotion
+# Generate suggestions based on detected emotion
 def generate_suggestions(emotion):
-    resources = {
-        "😊 Joy": [
-            ["Relaxation Techniques", "Relaxation", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Visit</a>'],
-            ["Dealing with Stress", "Stress Management", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Emotional Wellness Toolkit", "Wellness", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
-            ["Relaxation Videos", "Video", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>']
+    suggestions = {
+        "joy": [
+            ["Relaxation Techniques", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Read</a>'],
+            ["Dealing with Stress", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Read</a>'],
+            ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Read</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>'],
+        ],
+        "anger": [
+            ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Read</a>'],
+            ["Stress Management Tips", '<a href="https://www.health.harvard.edu/health-a-to-z" target="_blank">Read</a>'],
+            ["Dealing with Anger", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Read</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/MIc299Flibs" target="_blank">Watch</a>'],
+        ],
+        "fear": [
+            ["Mindfulness Practices", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Read</a>'],
+            ["Coping with Anxiety", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Read</a>'],
+            ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Read</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>'],
         ],
-        "😢 Sadness": [
-            ["Emotional Wellness Toolkit", "Wellness", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
-            ["Dealing with Anxiety", "Anxiety Management", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Relaxation Videos", "Video", '<a href="https://youtu.be/-e-4Kx5px_I" target="_blank">Watch</a>']
+        "sadness": [
+            ["Emotional Wellness Toolkit", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Read</a>'],
+            ["Dealing with Anxiety", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Read</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/-e-4Kx5px_I" target="_blank">Watch</a>'],
+        ],
+        "surprise": [
+            ["Managing Stress", '<a href="https://www.health.harvard.edu/health-a-to-z" target="_blank">Read</a>'],
+            ["Coping Strategies", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Read</a>'],
+            ["Relaxation Video", '<a href="https://youtu.be/m1vaUGtyo-A" target="_blank">Watch</a>'],
         ],
-        "😨 Fear": [
-            ["Mindfulness Practices", "Mindfulness", '<a href="https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation" target="_blank">Visit</a>'],
-            ["Coping with Anxiety", "Anxiety Management", '<a href="https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety" target="_blank">Visit</a>'],
-            ["Emotional Wellness Toolkit", "Wellness", '<a href="https://www.nih.gov/health-information/emotional-wellness-toolkit" target="_blank">Visit</a>'],
-            ["Relaxation Videos", "Video", '<a href="https://youtu.be/yGKKz185M5o" target="_blank">Watch</a>']
-        ]
     }
-    return resources.get(emotion.split(" ")[1], [["No specific suggestions available", "", ""]])
+    return suggestions.get(emotion)
 
-# Search Professionals and Generate Map
+# Search nearby professionals and generate map
 def get_health_professionals_and_map(location, query):
     try:
         geo_location = gmaps.geocode(location)
         if geo_location:
             lat, lng = geo_location[0]["geometry"]["location"].values()
-            places_result = gmaps.places_nearby(
-                location=(lat, lng), radius=10000, type="doctor", keyword=query
-            )["results"]
+            places_result = gmaps.places_nearby(location=(lat, lng), radius=10000, keyword=query)["results"]
+
             map_ = folium.Map(location=(lat, lng), zoom_start=13)
             professionals = []
             for place in places_result:
                 professionals.append(f"{place['name']} - {place.get('vicinity', '')}")
-                lat, lng = place["geometry"]["location"]["lat"], place["geometry"]["location"]["lng"]
-                folium.Marker([lat, lng], popup=place["name"]).add_to(map_)
+                folium.Marker([place["geometry"]["location"]["lat"], place["geometry"]["location"]["lng"]],
+                              popup=place["name"]).add_to(map_)
             return professionals, map_._repr_html_()
-        return ["No professionals found"], ""
+        return [], ""
     except Exception as e:
         return [f"Error: {e}"], ""
 
-# Gradio App Function
+# Application logic integrated in one function
 def app_function(message, location, query, history):
     chatbot_history, _ = chatbot(message, history)
     sentiment = analyze_sentiment(message)
-    emotion = detect_emotion(message)
+    emotion = detect_emotion(message.lower())
     suggestions = generate_suggestions(emotion)
     professionals_info, map_html = get_health_professionals_and_map(location, query)
     return chatbot_history, sentiment, emotion, suggestions, professionals_info, map_html
 
-# Gradio Interface
-with gr.Blocks() as demo:
+# Gradio app interface
+with gr.Blocks() as app:
     gr.Markdown("# 🌟 Well-Being Companion")
-    gr.Markdown("Empowering your mental health journey 💚")
-    
+    gr.Markdown("Empowering Your Mental Health Journey 💚")
+
     with gr.Row():
-        user_input = gr.Textbox(label="Your Message")
-        location_input = gr.Textbox(label="Your Location")
-        query_input = gr.Textbox(label="Search Query")
-        submit_button = gr.Button("Submit")
-
-    chatbot_output = gr.Chatbot(label="Chat History", type="messages")
-    sentiment_output = gr.Textbox(label="Sentiment Detected")
-    emotion_output = gr.Textbox(label="Emotion Detected")
-    suggestions_output = gr.DataFrame(label="Suggestions", headers=["Title", "Subject", "Link"])
-    professionals_output = gr.Textbox(label="Nearby Professionals", lines=5)
-    map_output = gr.HTML(label="Map of Nearby Professionals")
-
-    submit_button.click(
+        user_message = gr.Textbox(label="Your Message", placeholder="Enter your message...")
+        user_location = gr.Textbox(label="Your Location", placeholder="Enter location...")
+        search_query = gr.Textbox(label="Query (e.g., therapist)", placeholder="Search for professionals...")
+        submit_btn = gr.Button(value="Submit")
+
+    chatbot_box = gr.Chatbot(label="Chat History", type="messages")
+    emotion_display = gr.Textbox(label="Detected Emotion")
+    sentiment_display = gr.Textbox(label="Detected Sentiment")
+    suggestions_table = gr.DataFrame(headers=["Title", "Links"], label="Suggestions", height=250)
+    map_output = gr.HTML(label="Nearby Professionals Map")
+    professional_display = gr.Textbox(label="Nearby Professionals", lines=5)
+
+    submit_btn.click(
         app_function,
-        inputs=[user_input, location_input, query_input, chatbot_output],
+        inputs=[user_message, user_location, search_query, chatbot_box],
         outputs=[
-            chatbot_output, sentiment_output, emotion_output,
-            suggestions_output, professionals_output, map_output
+            chatbot_box, sentiment_display, emotion_display, suggestions_table, professional_display, map_output,
         ],
     )
 
-demo.launch()
+app.launch()