Update app.py

app.py

@@ -1,3 +1,4 @@
+import os
 import streamlit as st
 from langchain.agents import create_react_agent, AgentExecutor
 from langchain_community.tools import DuckDuckGoSearchRun
@@ -6,10 +7,11 @@ from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
 from langchain_google_genai import ChatGoogleGenerativeAI
 
+# Get API Key from Hugging Face secrets
 key = os.environ.get("GOOGLE_API_KEY")
 if not key:
     st.error("❌ GOOGLE_API_KEY not found. Please set it in your Hugging Face Secrets.")
-    st.stop()
+    st.stop()
 
 # Set page config
 st.set_page_config(page_title="Company Info Agent", layout="wide")
@@ -19,8 +21,7 @@ st.markdown(
     "Ask anything about companies: *stock, revenue, growth, acquisitions, news*, etc."
 )
 
-
-# --- Your custom prompt ---
+# Custom Prompt
 prompt = PromptTemplate(
     input_variables=["input", "agent_scratchpad", "tool_names", "tools"],
     template="""You are a smart and reliable business assistant.
@@ -65,31 +66,29 @@ Thought:{agent_scratchpad}
 """
 )
 
+# Tool and LLM
 search_tool = DuckDuckGoSearchRun()
-
 tools = [search_tool]
 
-# --- Initializing the LLM
 llm = ChatGoogleGenerativeAI(
-    api_key = key,
-    model = "gemini-2.0-flash"
+    api_key=key,
+    model="gemini-2.0-flash"
 )
 
-# User input
+# User Input
 user_input = st.text_input("Enter your question:")
 
+# Create Agent and Executor
 agent = create_react_agent(llm=llm, tools=tools, prompt=prompt)
-
-# Create executor
 agent_executor = AgentExecutor(
     agent=agent,
     tools=tools,
     handle_parsing_errors=True,
 )
-    
-# Run on user input
+
+# Handle User Input
 if user_input:
     with st.spinner("🔎 Thinking..."):
         response = agent_executor.invoke({"input": user_input})
     st.markdown("### 🧠 Answer:")
-    st.write(response["output"])
+    st.write(response["output"])