Update app.py

app.py

@@ -2,14 +2,14 @@ import streamlit as st
 import pandas as pd
 import requests
 import os
+from google.cloud import language_v1
+from google.oauth2 import service_account
 
-from groq import Groq
+# Set the API key for Google AI API (if not set in the environment variable)
+api_key = "AIzaSyAlvoXLqzqcZgVjhQeCNUsQgk6_SGHQNr8"  # Ensure your credentials are set up
 
-# Set the API key directly or from environment variable
-api_key = "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"  # Replace with your actual demo API key
-
-# Initialize the Groq client with the API key
-client = Groq(api_key=api_key)
+# Initialize Google AI Client
+client = language_v1.LanguageServiceClient(credentials=service_account.Credentials.from_service_account_file("path_to_your_service_account_json"))
 
 # Function to load and preprocess data
 @st.cache_data
@@ -17,50 +17,50 @@ def load_data(file):
     df = pd.read_csv(file)
     return df
 
-# Function to provide detailed health advice based on user data
-def provide_observed_advice(data):
+# Function to fetch and analyze text using Google AI's Natural Language API
+def analyze_text_with_google_ai(text):
+    document = language_v1.Document(content=text, type_=language_v1.Document.Type.PLAIN_TEXT)
+    response = client.analyze_sentiment(document=document)
+    sentiment_score = response.document_sentiment.score
+    sentiment_magnitude = response.document_sentiment.magnitude
+    
+    # Example: Based on sentiment, provide advice
+    if sentiment_score < -0.5:
+        return "You may want to focus on activities that improve your mood, such as physical exercise, talking with a counselor, or engaging in mindfulness practices."
+    elif sentiment_score > 0.5:
+        return "It seems you're in a positive emotional state. Keep nurturing these positive habits, such as engaging in social activities and continuing to practice stress-relief strategies."
+    else:
+        return "You are in a neutral emotional state. Consider exploring activities that help enhance your mood, such as engaging in hobbies or relaxation exercises."
+
+# Function to provide health advice based on user data and Google AI analysis
+def provide_google_ai_advice(data):
     advice = []
 
-    # High depression and anxiety with low stress-relief activities
-    if data['depression'] > 7 and data['anxiety'] > 7:
-        advice.append("You seem to be experiencing high levels of both depression and anxiety. It's important to consider professional mental health support. You might also benefit from engaging in calming activities like deep breathing, mindfulness, or yoga.")
-
-    # Moderate depression or anxiety
-    elif data['depression'] > 5 or data['anxiety'] > 5:
-        advice.append("You are showing moderate levels of depression or anxiety. It would be helpful to develop healthy coping strategies like maintaining a regular sleep schedule, engaging in physical activity, and reaching out to friends or family for support.")
-
-    # High isolation and low stress-relief activities
-    if data['isolation'] > 7 and data['stress_relief_activities'] < 5:
-        advice.append("It seems you are feeling isolated, and your engagement in stress-relief activities is low. It's important to connect with friends or join community groups. Incorporate activities that help alleviate stress, such as walking, journaling, or meditation.")
-
-    # High future insecurity
-    if data['future_insecurity'] > 7:
-        advice.append("You are feeling a significant amount of insecurity about the future. It can be helpful to break down your larger goals into smaller, manageable tasks. Seeking career counseling or mentorship could provide valuable guidance and reduce anxiety about the future.")
-
-    # Overall low engagement in stress-relief activities
-    if data['stress_relief_activities'] < 5:
-        advice.append("Your engagement in stress-relief activities is quite low. It's essential to engage in activities that reduce stress and promote mental wellness, such as hobbies, physical exercise, and relaxation techniques like deep breathing or yoga.")
+    # Example of analysis based on Google AI's sentiment analysis
+    if data['depression'] > 7 or data['anxiety'] > 7:
+        advice.append("It seems you're experiencing high levels of depression or anxiety. It might be helpful to talk to a professional or consider engaging in activities that can reduce stress, like mindfulness or physical exercise.")
+    
+    # Call Google AI for sentiment-based advice
+    user_data_summary = f"User's depression: {data['depression']}, anxiety: {data['anxiety']}, isolation: {data['isolation']}, future insecurity: {data['future_insecurity']}, stress-relief activities: {data['stress_relief_activities']}"
+    google_ai_advice = analyze_text_with_google_ai(user_data_summary)
+    advice.append(google_ai_advice)
 
     return advice
 
-# Function to fetch health articles from the GROC API based on the query
+# Function to fetch related health articles from GROC API (optional, for RAG-style application)
 def get_health_articles(query):
     url = f"https://api.groc.com/search?q={query}"
-    headers = {"Authorization": f"Bearer {api_key}"}  # Use the demo API key in the header
+    headers = {"Authorization": f"Bearer {api_key}"}  # Replace with actual Google API key if required
 
     try:
         response = requests.get(url, headers=headers)
-        response.raise_for_status()  # This will raise an HTTPError for bad responses
-        data = response.json()  # Assuming the API returns JSON
+        response.raise_for_status()
+        data = response.json()
         if 'results' in data:
             articles = [{"title": item["title"], "url": item["url"]} for item in data['results']]
         else:
             articles = []
         return articles
-    except requests.exceptions.HTTPError as http_err:
-        st.error(f"HTTP error occurred: {http_err}. Please check your API key and the endpoint.")
-        st.error(f"Response content: {response.text}")
-        return []
     except requests.exceptions.RequestException as err:
         st.error(f"Error fetching articles: {err}. Please check your internet connection.")
         return []
@@ -125,7 +125,7 @@ def main():
         # Provide advice based on user inputs
         if st.button("🔍 Get Observed Advice", key="advice_btn"):
             st.subheader("🔔 **Health Advice Based on Observations** 🔔")
-            advice = provide_observed_advice(user_data)
+            advice = provide_google_ai_advice(user_data)
             if advice:
                 for i, tip in enumerate(advice, 1):
                     st.write(f"📌 {i}. {tip}")