Upload app.py

app.py

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+import os
+import time
+import streamlit as st
+from qa_loader import load_qa_and_create_vectorstore
+from rag_chain import generate_response
+from dotenv import load_dotenv
+
+# 🔹 Load environment variables
+load_dotenv()
+
+# 🔹 Streamlit Page Configuration
+st.set_page_config(page_title="Vistula University AI Assistant", layout="centered")
+
+# 🔹 Title and Description
+st.title("📚 University AI Assistant")
+st.write("🚀 Ask me anything about University!")
+
+# 🔹 Retrieve Data (Cached for Performance)
+@st.cache_resource
+def get_retriever():
+    return load_qa_and_create_vectorstore()
+
+retriever = get_retriever()
+
+if isinstance(retriever, tuple):  
+    retriever = retriever[0]
+
+# 🔹 Start or Load Chat History
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+# 🔹 Display Chat History
+st.write("### 🗂️ Chat History")
+
+for entry in st.session_state.chat_history:
+    with st.chat_message("user"):
+        st.write(entry["question"])
+    with st.chat_message("assistant"):
+        st.write(entry["answer"])
+
+# 🔹 User Input
+query = st.chat_input("Ask your question about Vistula University!")
+
+# 🔹 Process When User Submits a Question
+if query:
+    with st.spinner("🤖 Thinking..."):
+        response = generate_response(retriever, query)
+
+    # 🔹 Add to Chat History
+    st.session_state.chat_history.append({
+        "question": query,
+        "answer": response
+    })
+
+    # 🔹 Display User Question and AI Response
+    with st.chat_message("user"):
+        st.write(query)
+    with st.chat_message("assistant"):
+        placeholder = st.empty()
+        current_text = ""
+
+        # Typing Effect
+        for word in response.split():
+            current_text += word + " "
+            placeholder.write(current_text)
+            time.sleep(0.05)