What problem does it solve?
This Skill streamlines the process of creating chat interfaces using Streamlit, reducing development time and simplifying the user experience for chatbots and AI assistants.
Core Features & Use Cases
- Streamlit Chat Elements: Provides an overview of how to use Streamlit's chat features, such as
st.chat_message and st.chat_input.
- Message History: Enables managing message history and streaming responses for more engaging interactions.
- Quick Start: Offers a straightforward way to get started with chat interfaces using Streamlit.
Quick Start
To build a chat interface, use the following Streamlit script to start a basic conversation.
import streamlit as st
if "messages" not in st.session_state:
st.session_state.messages = []
# Display chat history
for msg in st.session_state.messages:
with st.chat_message(msg["role"]):
st.write(msg["content"])
# Handle new input
if prompt := st.chat_input("Ask a question"):
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.write(prompt)
with st.chat_message("assistant"):
response = get_response(prompt) # Your LLM call
st.write(response)
st.session_state.messages.append({"role": "assistant", "content": response})
