Update app.py

app.py

@@ -1,55 +1,24 @@
-import streamlit as st
-import os
-from dotenv import load_dotenv
-from langchain_groq import ChatGroq
-from langchain_community.agent_toolkits.load_tools import load_tools
-from langgraph.prebuilt import create_react_agent
-import langchainhub as hub
-
-# 1. Setup Page & Secrets
-st.set_page_config(page_title="My First AI Math Agent", layout="centered")
-st.title("My First AI Math Agent 🧮")
-
-# Look for API Key in environment (Local .env or HF Secrets)
-load_dotenv()
-api_key = os.getenv("GROQ_API_KEY")
-
-if not api_key:
-    st.error("Missing GROQ_API_KEY! Please check your secrets.")
-    st.stop()
-
-# 2. Initialize the Agent (Cached so it doesn't reload every click)
-@st.cache_resource
-def get_agent():
-    llm = ChatGroq(model_name="llama-3.3-70b-versatile", temperature=0)
-    tools = load_tools(["llm-math"], llm=llm)
-    # TODO: Create the agent using the same function we used in your terminal script
-    return create_react_agent(llm, tools)
-
-agent_executor = get_agent()
-
-# 3. Chat History Setup
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-# 4. The Interaction Loop
-if prompt := st.chat_input("What math problem should I solve?"):
-    st.session_state.messages.append({"role": "user", "content": prompt})
-    with st.chat_message("user"):
-        st.markdown(prompt)
-
-    with st.chat_message("assistant"):
-        with st.spinner("Thinking..."):
-            # TODO: Call the agent_executor with the correct input format
-            # Hint: We used .invoke({"messages": [("human", prompt)]}) before!
-            result = agent_executor.invoke({"messages": [("human", prompt)]})
-            
-            # Extract the text from the last message in the response
-            final_answer = result["messages"][-1].content
-            st.markdown(final_answer)
-            
-    st.session_state.messages.append({"role": "assistant", "content": final_answer})
+import streamlit as st
+import os
+from langchain_groq import ChatGroq
+from langchain_community.agent_toolkits.load_tools import load_tools
+from langgraph.prebuilt import create_react_agent
+
+# 1. Page Config (Best practice to put this at the very top)
+st.set_page_config(page_title="AI Math Agent", page_icon="🧮")
+
+st.title("My First AI Math Agent 🧮")
+
+# 2. Secret Retrieval
+api_key = os.getenv("GROQ_API_KEY")
+
+# 3. Validation Logic
+if not api_key:
+    st.warning("⚠️ Waiting for GROQ_API_KEY... Please add it to your Space Secrets in Settings.")
+    st.info("After adding the secret, you may need to 'Restart' the Space.")
+    st.stop()
+else:
+    st.success("🚀 API Key connected! The agent is ready.")
+    
+    # Simple placeholder for your agent logic
+    st.write("Next step: Initialize your ChatGroq model here.")