Creating Smart Text Input in Streamlit with Real-Time Suggestions

The Problem

Streamlit has rapidly become the go-to framework for building fast and interactive ML/AI apps. However, one thing that’s always been missing: a smart text input box that offers real-time suggestions.

Sure, Streamlit introduced st.chat_input() and other basic widgets, but none of them come close to offering:

🔮 Context-aware autocomplete

⚡ Real-time NLP suggestions

✨ A true UX upgrade for text entry

If you’ve tried building such a component manually, you know how painful it is. Until now.

The Solution: streamlit-smart-text-input

Introducing streamlit-smart-text-input — an open-source Python package that brings an autocomplete UI component to your Streamlit apps, similar to what you'd expect in modern IDEs or search engines.

Features

• 🔍 Real-time suggestions as you type
• 📚 Works with any string-based source (static or dynamic)
• 🌍 Fully customizable UI and behavior
• 🛠️ Built with minimal setup
• 📦 Pure Python + JS component under the hood

Streamlit Smart Text Input

This component implements a selectbox that allows free text input. It is based on React-Select's 'Select'
component.

Installation

pip install streamlit-smart-text-input

Usage (Example 1)

import streamlit as st
from streamlit_smart_text_input import st_smart_text_input

st.set_page_config(page_title="SmartText Input Demo", layout="centered")
st.title("Streamlit SmartText Input Test")

# Options to test with
options = ["Toyota", "BMW", "Tesla", "Ford", "Audi", "Mercedes", "Honda"]


# Call the custom component
value = st_smart_text_input(
    label="Choose or Type a Fruit or Greeting",
    options=options,
    index=None,
    placeholder="Start typing and press Enter...",
    delay=200,
    disabled=False,
    label_visibility="visible",
)

# Display what was selected or typed
if value:
    if value.lower() in [o.lower() for o in options]:
        st.info(f"'{value}' is a known car brand from the list.")
    elif value.lower() in ["hi", "hey", "hello"]:
        st.info("Hello, I am a Python package crafted by [Ankit Guria](https://github.com/ankitguria).")
    else:
        st.warning(f"'{value}' is a new input. You can add this to the list!")

# UI Divider
st.markdown("---")
st.caption("Press ⏎ Enter after typing to trigger input capture.")

Usage (Example 2)

import streamlit as st
from streamlit_smart_text_input import st_smart_text_input

st.set_page_config(page_title="SmartText Chat Thread", layout="centered")
st.title("Streamlit SmartText Chat")

# Initialize chat history
if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

# Options (can be dynamic)
options = ["hi", "hello", "help", "bye", "thanks", "how are you?"]

# Display existing chat
st.markdown("### Conversation")
for i, msg in enumerate(st.session_state.chat_history):
    is_user = msg["sender"] == "user"
    with st.chat_message("user" if is_user else "assistant"):
        st.markdown(msg["text"])

# User input (free-form or from options)
user_input = st_smart_text_input(
    label="Type your message",
    options=options,
    placeholder="Ask something or say hello...",
    delay=100,
    disabled=False,
    label_visibility="collapsed",
    key=f"chat_input_{len(st.session_state.chat_history)}"

)

# When user submits a message
if user_input:
    # Add user message to history
    st.session_state.chat_history.append({
        "sender": "user",
        "text": user_input,
    })

    # Simple bot logic (replace with your own model later)
    if user_input.lower() in ["hi", "hello", "hey"]:
        bot_reply = " Hello, I am a Python package crafted by [Ankit Guria](https://github.com/ankit142)! How can I help you today?"
    elif "help" in user_input.lower():
        bot_reply = "Sure! I'm here to assist. Ask me anything."
    elif user_input.lower() in ["bye", "goodbye"]:
        bot_reply = " Goodbye! Have a great day."
    else:
        bot_reply = f"I heard you say: '{user_input}'"

    # Add bot reply to history
    st.session_state.chat_history.append({
        "sender": "bot",
        "text": bot_reply,
    })

    # Force rerun to refresh chat display and clear input
    st.rerun()

Docs

Parameters

• label : str A short label explaining to the user what this input is for.
• options : list A list of predefined options to choose from.
• index : int An optional index to select an option by default, defaults to None.
• format_func : callable A callable function to format the options, defaults to None.
• placeholder : str A string to display when the input is empty, defaults to None.
• disabled : bool Whether the input is disabled, defaults to False.
• delay : int The time in milliseconds to wait before updating the component, defaults to 300.
• key : str An optional string to use as the unique key for the widget, defaults to None.
• label_visibility : str The visibility of the label, defaults to "visible". Options are "visible", "hidden", "collapsed".

Returns
str or None
The value of the free text select input.

📽 Watch the demo on YouTube

Contributors

Ankit Guria

GitHub Repo
Check out the full source code, examples, and issues here:
🔗 GitHub

💻 Use Cases

• 🤖 Chatbots that offer topic or intent suggestions
• 🧠 Prompt builders for LLMs
• 📝 Auto-tagging or smart search forms
• 🔍 Query builders with real-time assist

** How It Works (Under the Hood)**

This package wraps a React component using Streamlit’s custom components API. It uses basic fuzzy matching to filter suggestions and sends back the selected/typed value.

You can easily plug in your own logic, such as an OpenAI or spaCy-based suggestion engine.

👨‍💻 Developer Notes
You can customize the font, size, placeholder, and behavior.

The component gracefully falls back to a standard input if JS is disabled.

Works out-of-the-box on local or deployed Streamlit apps (Streamlit Cloud, HuggingFace, etc.)

** Connect With Me
**🔗 LinkedIn: Ankit Guria

Python Package on PyPI

💬 Drop feedback or PRs on GitHub