Update app.py

app.py

@@ -1,14 +1,13 @@
-import streamlit as st
-#from google.cloud import aiplatform
-from transformers import pipeline
-from google.cloud import aiplatform
+# Import necessary libraries
 import os
 import logging
-import whisper
-from gtts import gTTS
-import tempfile
-from pydub import AudioSegment
-from groq import Groq, GroqError
+from transformers import pipeline
+from google.cloud import aiplatform
+from google.oauth2 import service_account
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 # Set up Google Cloud credentials
 def setup_google_cloud_credentials():
@@ -19,31 +18,49 @@ def setup_google_cloud_credentials():
     else:
         raise FileNotFoundError(f"Google Cloud credentials file not found at {google_credentials_path}")
 
-# Initialize the client
-def init_palm(api_key):
+# Initialize the client for Google Cloud AI Platform
+def init_google_ai_platform(api_key):
     aiplatform.init(api_key=api_key)
 
-# Function to generate responses
-def generate_palm_response(prompt):
+# Function to generate a response using Hugging Face
+def generate_hugging_face_response(prompt):
+    # Load a Hugging Face model for text generation
+    generator = pipeline('text-generation', model='gpt2')
+    # Generate text based on the prompt
+    response = generator(prompt, max_length=50, num_return_sequences=1)
+    return response[0]['generated_text']
+
+# Function to generate a response using Google Cloud AI Platform
+def generate_google_ai_response(prompt):
     response = aiplatform.Model.predict(
         model_name="gemini-1.5-flash",
         instances=[{"prompt": prompt}]
     )
     return response.predictions[0]['content']
 
-# Main code to run the application
-if __name__ == "__main__":
+# Main function to run the application
+def main():
     try:
         # Set up Google Cloud credentials
         setup_google_cloud_credentials()
 
-        # Call the model
+        # Initialize Google Cloud AI Platform
         api_key = "AIzaSyD-49IyRzS6Ok_zymcEdv1QADw0rWQJFI4"
-        init_palm(api_key)
-        response = generate_palm_response("Heart health query...")
-        print(response)
+        init_google_ai_platform(api_key)
+
+        # Example prompt
+        prompt = "Tell me about heart health."
+
+        # Generate response from Hugging Face
+        hf_response = generate_hugging_face_response(prompt)
+        logger.info(f"Hugging Face Response: {hf_response}")
 
-        # Streamlit app or other logic goes here...
+        # Generate response from Google Cloud AI Platform
+        google_response = generate_google_ai_response(prompt)
+        logger.info(f"Google AI Response: {google_response}")
 
     except Exception as e:
-        logging.error(f"Error occurred: {e}")
+        logger.error(f"Error occurred: {e}")
+
+if __name__ == "__main__":
+    main()