Update app.py

app.py

@@ -7,16 +7,28 @@ from langchain.chains import RetrievalQA
 from langchain.chains import ConversationalRetrievalChain
 
 from langchain_openai import ChatOpenAI
-import os
 from langchain_community.vectorstores import Chroma
 
-import tempfile
 
+st.sidebar.title("Introduction")
+st.sidebar.markdown("""
+ChatMate is an advanced conversational AI interface, expertly crafted to demonstrate the fusion of Streamlit's user-friendly design and OpenAI's powerful GPT-3.5 model. Here are its highlights:
+
+<ul style='text-align: left;'>
+<li><strong>Intuitive Interface</strong>: Built with Streamlit, ChatMate offers a clean, responsive user experience, allowing for natural dialogue with the AI.</li>
+<li><strong>Advanced NLP</strong>: Incorporating OpenAI's most advanced GPT model, the app provides nuanced understanding and generation of human-like text, showcasing the model's impressive capabilities.</li>
+<li><strong>State Management</strong>: Utilizes <code>ConversationChain</code> and <code>ConversationMemory</code> from <code>langchain</code> to preserve the context and flow, ensuring coherent and engaging interactions.</li>
+<li><strong>Python Proficiency</strong>: The app's robust backend, written in Python, reflects the data scientist’s adeptness in programming and system design.</li>
+<li><strong>Secure Interaction</strong>: Streamlit's session state management is used for secure API key handling and user input retention across sessions.</li>
+</ul>
+
+ChatMate is developed by Lorentz Yeung
+""", unsafe_allow_html=True)
+
+if 'API_Key' not in st.session_state:
+    st.session_state['API_Key'] =''
+st.session_state['API_Key']= st.text_input("First, to get it work, put your OpenAI API Key here please, the system will enter for you automatically.",type="password")
 
-user_api_key = st.sidebar.text_input(
-    label="#### Your OpenAI API key 👇",
-    placeholder="user_historye your openAI API key, sk-",
-    type="password")
 
 # uploaded_file = st.sidebar.file_uploader("upload", type="csv")
 
@@ -32,7 +44,7 @@ if KaggleX_courses_db :
     retriever = KaggleX_courses_db.as_retriever() # search_kwargs={"k": 4}
 
     chain = ConversationalRetrievalChain.from_llm(llm = ChatOpenAI(temperature=0.0,model_name='gpt-3.5-turbo',
-                                                                openai_api_key=user_api_key),
+                                                                openai_api_key=st.session_state['API_Key']),
                                                                 retriever = retriever)
 
     def conversational_chat(query):