Update app.py

app.py

@@ -1,5 +1,7 @@
 import gradio as gr
 from sentence_transformers import SentenceTransformer, util
+import transformers
+from transformers import pipeline
 import openai
 import os
 
@@ -60,10 +62,16 @@ def find_relevant_segment(user_query, segments):
 
 def generate_response(user_query, relevant_segment):
     """
-    Generate a response emphasizing the bot's capability in providing information related to composting food.
+    Generate a response emphasizing the bot's capability to provide information related to composting food.
     """
+    generator = pipeline("text-davinci-003", device=0) 
+    response = generator(query=f"Here's the information on composting: {relevant_segment} {user_query}", max_length=150, temperature=0.2, top_p=1)
+    generated_text = response[0]['generated_text'].strip()
+    confidence_score = response[0]['score']
+
+    return generated_text, confidence_score
     try:
-        system_message = "You are a chess chatbot specialized in providing information about food composting tips, tricks, and basics."
+        system_message = "You are a chatbot specialized in providing information about food composting tips, tricks, and basics."
         user_message = f"Here's the information on composting: {relevant_segment}"
         messages = [
             {"role": "system", "content": system_message},
@@ -83,6 +91,8 @@ def generate_response(user_query, relevant_segment):
         print(f"Error in generating response: {e}")
         return f"Error in generating response: {e}"
 
+    
+
 def query_model(question):
     """
     Process a question, find relevant information, and generate a response.