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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+b48c8274-61df-480f-9cd9-47d697ef03e9.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,91 @@
+import streamlit as st
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.output_parsers import StrOutputParser
+from langchain_community.chat_message_histories import SQLChatMessageHistory
+from langchain_core.runnables.history import RunnableWithMessageHistory
+import os
+
+# Use environment variable for security
+API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Define Chat Prompt Template
+template = ChatPromptTemplate(
+    messages=[
+        ("system", """You are a highly knowledgeable and helpful AI assistant specializing in Data Science.
+         Your primary objective is to assist users with topics related to Data Science, including but not limited to Machine Learning, 
+         Deep Learning, Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Statistics, 
+         Data Analysis, and related programming techniques in Python, SQL, and relevant tools.
+         You should provide accurate, well-explained, and relevant answers, ensuring clarity and conciseness. 
+         If a query is outside the scope of Data Science, politely inform the user that you can only answer Data Science-related questions."""),
+        MessagesPlaceholder(variable_name="chat_history"),
+        ("human", "{input}") 
+    ]
+)
+
+# Initialize AI Model
+model = ChatGoogleGenerativeAI(api_key=API_KEY, model='models/gemini-2.0-flash')
+output = StrOutputParser()
+chain = template | model | output
+
+# Chat History Management
+def messages_history(session_id):
+    return SQLChatMessageHistory(session_id=session_id, connection="sqlite:///sqlite.db")
+
+conversation_chain = RunnableWithMessageHistory(
+    chain, messages_history, input_message_key="input", history_messages_key="chat_history"
+)
+
+# Streamlit UI Enhancements
+st.set_page_config(page_title="AI Data Science Chatbot", layout="wide")
+st.markdown("""
+    <style>
+        body { background-color: #f5f5f5; }
+        .stChatMessage { border-radius: 12px; padding: 10px; }
+    </style>
+""", unsafe_allow_html=True)
+
+# Sidebar - User Login
+with st.sidebar:
+    st.image("b48c8274-61df-480f-9cd9-47d697ef03e9.jpg", width=150)  # Optional: Add chatbot logo
+    st.title("🤖 AI Data Science Chatbot")
+    st.markdown("💡 Ask me anything about Data Science!")
+    st.divider()
+    st.header("User Login")
+    user_id = st.text_input("Enter your User ID:", key="user_id_input")
+    if st.button("Logout"):
+        st.session_state.clear()
+        st.rerun()
+
+if not user_id:
+    st.warning("Please enter a User ID to start chatting.")
+    st.stop()
+
+if "last_user_id" not in st.session_state or st.session_state.last_user_id != user_id:
+    st.session_state.chat_history = []  
+    st.session_state.last_user_id = user_id  
+
+chat_history = messages_history(user_id).messages
+st.session_state.chat_history = [(msg.type, msg.content) for msg in chat_history]
+
+st.markdown("<h2 style='text-align: center;'>💬 Chat with the AI Assistant</h2>", unsafe_allow_html=True)
+
+for role, message in st.session_state.chat_history:
+    if role == "user":
+        st.chat_message("user").markdown(f"**🧑‍💻 You:** {message}")
+    else:
+        st.chat_message("assistant").markdown(f"**🤖 AI:** {message}")
+
+# User Input & AI Response
+user_input = st.chat_input("Type your message...")
+
+if user_input:
+    st.session_state.chat_history.append(("user", user_input))
+    st.chat_message("user").write(user_input)
+    
+    config = {"configurable": {"session_id": user_id}}
+    input_prompt = {"input": user_input} 
+    response = conversation_chain.invoke(input_prompt, config=config)
+    
+    st.session_state.chat_history.append(("assistant", response))
+    st.chat_message("assistant").write(response)

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+langchain_core
+langchain_community
+langchain_google_genai