Delete app.py

app.py

@@ -1,66 +0,0 @@
-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)