Streamlit : Making Your Enterprise Knowledge Assistant AI Accessible

Last time, I built a working enterprise knowledge assistant in Python using RAG + OpenAI + Chroma. It could read documents, answer questions, and even remember chat history.

Today, I’m taking it a step further: giving it a friendly web interface. Instead of typing commands in a terminal, employees can now interact with the assistant right in their browser using Streamlit.

What is Streamlit?

Streamlit is an open-source Python framework that lets you turn scripts into interactive web apps quickly and easily.

Install Streamlit

pip install streamlit

Adding a Streamlit Interface

Here’s a simple snippet to integrate a chat interface in enterprise_knowledge_assistant.py:

# -------------------------------------
# 4️ Build Streamlit chat interface
# -------------------------------------
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

user_input = st.chat_input(" Ask a question about enterprise knowledge...")

if user_input:
    wi
th st.spinner("Generating answer..."):
        answer = retrieval_chain.invoke({"question": user_input})
        st.session_state.chat_history.append((user_input, answer))

# Display conversation history
for q, a in st.session_state.chat_history:
    st.chat_message("user").write(q)
    st.chat_message("assistant").write(a)

Running App

 > streamlit run enterprise_knowledge_assistant_app.py

You can now access it in your browser:

• Local URL: http://localhost:8501

Your enterprise assistant is now just a webpage away!

Key Takeaways

Streamlit turns scripts into apps: A Python script becomes a usable tool without frontend work.

Session memory is crucial for multi-turn conversations in a web app.