updated the code

src/streamlit_app.py

@@ -1,40 +1,92 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import sys
+from typing import Any
+from dotenv import load_dotenv
+
 import streamlit as st
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+load_dotenv()
+
+from langchain_core.prompts import ChatPromptTemplate
+#from langchain_ollama import ChatOllama
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+
+# -------------------------------
+# LLM Initialization
+# -------------------------------
+@st.cache_resource
+def initialize_llm() -> ChatGoogleGenerativeAI:
+    try:
+        return ChatGoogleGenerativeAI(model="gemini-3-flash-preview")
+    except Exception as e:
+        st.error(f"Failed to initialize LLM: {e}")
+        st.stop()
+
+
+# -------------------------------
+# Prompt (Memory-enabled)
+# -------------------------------
+def create_prompt() -> ChatPromptTemplate:
+    return ChatPromptTemplate.from_messages([
+        ("system", "You are a helpful assistant."),
+        ("placeholder", "{messages}")
+    ])
+
+
+# -------------------------------
+# Chain Builder
+# -------------------------------
+def build_chain(prompt: ChatPromptTemplate, llm: ChatGoogleGenerativeAI) -> Any:
+    return prompt | llm
+
+
+# -------------------------------
+# App UI
+# -------------------------------
+def run_streamlit_app():
+    st.set_page_config(page_title="Chatbot", layout="centered")
+
+    st.title("💬 AI Chatbot")
+
+    llm = initialize_llm()
+    prompt = create_prompt()
+    chain = build_chain(prompt, llm)
+
+    # ✅ Session-based memory (equivalent to messages = [])
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    # Display chat history
+    for role, content in st.session_state.messages:
+        with st.chat_message(role):
+            st.markdown(content)
+
+    # Input box
+    user_input = st.chat_input("Type your message...")
+
+    if user_input:
+        # Add user message
+        st.session_state.messages.append(("user", user_input))
+
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        # Generate response
+        try:
+            response = chain.invoke({"messages": st.session_state.messages})
+            response_text = response.content
+        except Exception as e:
+            response_text = f"Error: {e}"
+
+        # Add assistant response
+        st.session_state.messages.append(("assistant", response_text))
+
+        with st.chat_message("assistant"):
+            st.markdown(response_text)
+
+
+# -------------------------------
+# Entry Point
+# -------------------------------
+if __name__ == "__main__":
+    run_streamlit_app()