Update app.py

app.py

@@ -11,6 +11,7 @@ from nltk.stem.lancaster import LancasterStemmer
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
 import requests
 import pandas as pd
+import os
 
 # Ensure necessary NLTK resources are downloaded
 nltk.download('punkt')
@@ -149,11 +150,13 @@ def provide_suggestions(emotion):
         
     return suggestions
 
-# Google Places API to get nearby wellness professionals
-api_key = "YOUR_GOOGLE_API_KEY"  # Replace with your actual Google API key
+# Google Places API integration
+api_key = os.environ.get("GOOGLE_API_KEY") # Get API key from environment variable
+
+url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
+places_details_url = "https://maps.googleapis.com/maps/api/place/details/json"
 
 def get_places_data(query, location, radius, api_key, next_page_token=None):
-    url = "https://maps.googleapis.com/maps/api/place/textsearch/json"
     params = {
         "query": query,
         "location": location,
@@ -165,6 +168,23 @@ def get_places_data(query, location, radius, api_key, next_page_token=None):
     response = requests.get(url, params=params)
     return response.json() if response.status_code == 200 else None
 
+def get_place_details(place_id, api_key):
+    params = {
+        "place_id": place_id,
+        "key": api_key
+    }
+    response = requests.get(places_details_url, params=params)
+    if response.status_code == 200:
+        details_data = response.json().get("result", {})
+        return {
+            "opening_hours": details_data.get("opening_hours", {}).get("weekday_text", "Not available"),
+            "reviews": details_data.get("reviews", "Not available"),
+            "phone_number": details_data.get("formatted_phone_number", "Not available"),
+            "website": details_data.get("website", "Not available")
+        }
+    else:
+        return {}
+
 def get_all_places(query, location, radius, api_key):
     all_results = []
     next_page_token = None
@@ -173,11 +193,13 @@ def get_all_places(query, location, radius, api_key):
         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")
+                place_id = place.get("place_id", "N/A") # Handle missing place_id
+                name = place.get("name", "N/A") # Handle missing name
+                address = place.get("formatted_address", "N/A") # Handle missing address
                 website = place.get("website", "Not available")
-                all_results.append([name, address, website])
+                details = get_place_details(place_id, api_key) if place_id != "N/A" else {} #Avoid error if place_id is missing
+                phone_number = details.get("phone_number", "Not available")
+                all_results.append([name, address, phone_number, website])
             next_page_token = data.get('next_page_token')
             if not next_page_token:
                 break
@@ -188,12 +210,16 @@ def get_all_places(query, location, radius, api_key):
 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"])
+    try:
+        google_places_data = get_all_places(query, location, radius, api_key)
+        if google_places_data:
+            df = pd.DataFrame(google_places_data, columns=["Name", "Address", "Phone", "Website"])
+            return df
+        else:
+            return pd.DataFrame([["No data found.", "", "", ""]], columns=["Name", "Address", "Phone", "Website"])
+    except Exception as e:
+        return pd.DataFrame([["Error fetching data: " + str(e), "", "", ""]], columns=["Name", "Address", "Phone", "Website"])
+
 
 # Gradio Interface
 def gradio_interface(message, location, state):
@@ -210,7 +236,10 @@ def gradio_interface(message, location, state):
     suggestions = provide_suggestions(emotion)
     
     # Stage 4: Search for Wellness Professionals
-    wellness_results = search_wellness_professionals(location)
+    try:
+        wellness_results = search_wellness_professionals(location)
+    except Exception as e:
+        wellness_results = pd.DataFrame([["Error: " + str(e), "", "", ""]], columns=["Name", "Address", "Phone", "Website"])
     
     # Return the results in a tabular form within the Gradio interface
     return history, sentiment, emotion, suggestions, wellness_results, history  # Last 'history' is for state
@@ -236,5 +265,9 @@ iface = gr.Interface(
     description="This chatbot provides mental health support with sentiment analysis, emotion detection, suggestions, and a list of nearby wellness professionals."
 )
 
+# Check for API key; if not found, print an error message
+if api_key is None:
+    print("Error: GOOGLE_MAPS_API_KEY environment variable not set. Please set this environment variable with your Google Maps API key.")
+
 # Launch the interface
 iface.launch(debug=True, share=True)