Update app.py

app.py

@@ -1,7 +1,7 @@
 import os
 import streamlit as st
 from dotenv import load_dotenv
-from groq import Agent
+from phi.agent import Agent
 from phi.model.groq import Groq
 from phi.tools.duckduckgo import DuckDuckGo
 from phi.tools.yfinance import YFinanceTools
@@ -13,12 +13,16 @@ load_dotenv()
 deepseek_api_key = os.getenv("GROQ_DEEPSEEK_API_KEY")
 qwen_api_key = os.getenv("GROQ_QWEN_API_KEY")
 
+# Streamlit UI setup
+st.set_page_config(page_title="AI Agent Hub", layout="wide")
+st.title("🤖 AI Agent Hub")
+
 # Debugging API key loading
 if not deepseek_api_key or not qwen_api_key:
-    st.error("Missing API keys. Please set them in Hugging Face Secrets.")
+    st.error("Missing API keys. Ensure they are set in the Hugging Face Secrets.")
     st.stop()
 
-# Define Web Agent
+# Define the Web Agent using Groq's QWEN model
 web_agent = Agent(
     name="Web Agent",
     model=Groq(id="qwen-2.5-coder-32b", api_key=qwen_api_key),
@@ -28,7 +32,7 @@ web_agent = Agent(
     markdown=True,
 )
 
-# Define Finance Agent
+# Define the Finance Agent using Groq's DeepSeek model
 finance_agent = Agent(
     name="Finance Agent",
     role="Get financial data",
@@ -39,7 +43,7 @@ finance_agent = Agent(
     markdown=True,
 )
 
-# Create agent team
+# Combine agents into a team
 agent_team = Agent(
     model=Groq(id="deepseek-r1-distill-llama-70b", api_key=deepseek_api_key),
     team=[web_agent, finance_agent],
@@ -48,29 +52,13 @@ agent_team = Agent(
     markdown=True,
 )
 
-# Streamlit UI
-st.set_page_config(page_title="AI Chat Assistant", layout="wide")
-st.title("🤖 AI Chat Assistant")
-
 # User input
-if prompt := st.chat_input("Ask me anything..."):
-    with st.chat_message("user"):
-        st.markdown(prompt)
-
-    with st.chat_message("assistant"):
-        response_container = st.empty()
-        response_text = ""
+query = st.text_input("Enter your query:")
 
-        # Check available response method
-        if hasattr(agent_team, "respond") and callable(agent_team.respond):
-            try:
-                response_text = agent_team.respond(prompt) or "No response received."
-                response_container.markdown(response_text)
-            except Exception as e:
-                error_message = f"Error: {str(e)}"
-                st.error(error_message)
-                response_text = error_message
-        else:
-            error_message = "Error: Agent does not support responses."
-            st.error(error_message)
-            response_text = error_message
+if query:
+    with st.spinner("Fetching results..."):
+        try:
+            response = agent_team.respond(query)
+            st.write(response)
+        except Exception as e:
+            st.error(f"Error: {str(e)}")