Update app.py

app.py

@@ -6,17 +6,16 @@ import pickle
 import gradio as gr
 import requests
 import folium
+import pandas as pd
 from nltk.tokenize import word_tokenize
 from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+import torch
 import tensorflow as tf
 import tflearn
-import torch
-import pandas as pd
 import time
 from bs4 import BeautifulSoup
 import re  # Added for regex operations
-import os
 
 # Google Places API endpoint
 url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
@@ -53,9 +52,10 @@ tokenizer, emotion_model = load_model()
 
 # Google Places API query function
 def get_places_data(query, location, radius=5000, api_key="GOOGLE_API_KEY"):
+    latitude, longitude = map(float, location.split(","))
     params = {
         "query": query,
-        "location": location,
+        "location": f"{latitude},{longitude}",
         "radius": radius,
         "key": api_key
     }
@@ -150,14 +150,51 @@ def emotion_and_chatbot(user_input, history, query, location):
     sentiment = analyze_sentiment(user_input)
     emotion_response = f"Emotion Detected: {emotion}. Sentiment: {sentiment}"
     
+    # Provide suggestions based on emotion
+    suggestions = {
+        "joy": ["Relaxation Techniques", "Dealing with Stress", "Emotional Wellness Toolkit"],
+        "anger": ["Stress Management Tips", "Dealing with Anger", "Emotional Wellness Toolkit"],
+        "fear": ["Mindfulness Practices", "Coping with Anxiety", "Emotional Wellness Toolkit"],
+        "sadness": ["Dealing with Anxiety", "Emotional Wellness Toolkit"],
+        "surprise": ["Managing Stress", "Coping Strategies"]
+    }
+    
+    # Suggested articles and video links
+    if emotion in suggestions:
+        resources = suggestions[emotion]
+        links = {
+            "Relaxation Techniques": "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation",
+            "Dealing with Stress": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety",
+            "Emotional Wellness Toolkit": "https://www.nih.gov/health-information/emotional-wellness-toolkit",
+            "Stress Management Tips": "https://www.health.harvard.edu/health-a-to-z",
+            "Dealing with Anger": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety",
+            "Mindfulness Practices": "https://www.helpguide.org/mental-health/meditation/mindful-breathing-meditation",
+            "Coping with Anxiety": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety",
+            "Managing Stress": "https://www.health.harvard.edu/health-a-to-z",
+            "Coping Strategies": "https://www.helpguide.org/mental-health/anxiety/tips-for-dealing-with-anxiety"
+        }
+        
+        st.write("Useful Resources:")
+        for resource in resources:
+            st.markdown(f"[{resource}]({links[resource]})")
+
+        st.write("Relaxation Videos:")
+        st.markdown("[Watch on YouTube](https://youtu.be/m1vaUGtyo-A)")
+    
     # Search Places (for wellness or other queries)
     places_data = get_places_data(query, location)
+    places_df = pd.DataFrame(places_data)
+    
+    # Tabular output for places
+    places_table = places_df[['name', 'vicinity', 'geometry']].head(10).to_html(classes='table table-bordered') if not places_df.empty else "No places found."
+    
+    # Generate Map
     places_map = create_map(places_data) if places_data else "No places found."
     
     # Chatbot response
     history, _ = chatbot(user_input, history)
     
-    return emotion_response, places_map, history, history
+    return emotion_response, places_map, places_table, history, history
 
 # Gradio interface setup
 iface = gr.Interface(
@@ -171,6 +208,7 @@ iface = gr.Interface(
     outputs=[
         gr.Textbox(label="Emotion and Sentiment"),
         gr.HTML(label="Places Map"),
+        gr.HTML(label="Places Table"),
         gr.Chatbot(label="Chatbot History"),
         "state"
     ],
@@ -180,4 +218,4 @@ iface = gr.Interface(
 
 # Launch Gradio app
 if __name__ == "__main__":
-    iface.launch(debug=True)
+    iface.launch(debug=True)