Update app.py

app.py

@@ -11,6 +11,7 @@ import zepto
 from llama_index.core.tools import FunctionTool
 from llama_index.agent.openai import OpenAIAgent
 from typing import List, Tuple
+from llama_index.llms.openai import OpenAI
 
 load_dotenv()
 # Prompt user to enter their OpenAI API key
@@ -43,7 +44,7 @@ Identify the Best Prices: For each product, compare the prices across all websit
 
 Output Format: Present the results in the following structured format for each product:
 
-Product Name: The most accurate or common name for the product.
+Product Name: The most accurate or common name for the product (this is not the search term but the actual product name returned via search)
 
 Store: The name of the store.
 
@@ -51,7 +52,7 @@ Product URL: A clickable link to the product page.
 
 Price: The price of the product at that store.
 
-Ensure the store-wise product details are ordered by ascending price (cheapest first).
+Ensure the store-wise product details are ordered by ascending price (cheapest first) and the products themselves are sorted by ascending order of price.
 
 Handle Ambiguities: If product names or details are unclear, use context to determine if they refer to the same product. If uncertain, list them separately.
 
@@ -62,8 +63,11 @@ Product Name: Wireless Noise-Cancelling Headphones
 - Store: ElectroShop, Product URL: [ElectroShop Link], Price: ₹130
 
 '''
+
+llm = OpenAI(model="gpt-4o-mini")
 agent = OpenAIAgent.from_tools(
     tools=[zepto_tool],
+    llm=llm,
     api_key=os.environ['OPENAI_API_KEY'],
     system_message=system_instructions,
     verbose=True,
@@ -109,7 +113,7 @@ if prompt := st.chat_input(f"Hi I'm here to help you find the best price for a p
     with st.chat_message("assistant"):
 
         try:
-            full_prompt = f"{system_instructions}\n\nUser Query: {prompt}"
+            full_prompt =  prompt #f"{system_instructions}\n\nUser Query: {prompt}"
 
             response = agent.chat(full_prompt)
             processing_message.empty()