Registry / web-framework / streamlit-feedback

streamlit-feedback

library0.1.4pypypiunverified

Streamlit-feedback is a Streamlit component that allows developers to easily collect structured or free-form user feedback, such as thumbs up/down, emoji faces, or text comments, directly within their Streamlit applications. It is currently at version 0.1.4 and receives updates for compatibility with new Streamlit versions and feature enhancements, maintaining an active development status.

web-framework data

pip install streamlit-feedback

package ↗

INSTALL

IMPORT

SIG · STREAMLIT-FEEDBACK

streamlit-feedback

web-frameworkpythonv0.1.4

Install

15.9s avg

Import

—

Disk

455MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.1.4 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 466.7MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 15.9s · import 0.000s · 436MB

455MB installed

● package 455MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

st_feedback

✓ from streamlit_feedback import st_feedback

This quickstart demonstrates how to integrate `streamlit-feedback` into a basic Streamlit application. It shows both 'thumbs' and 'faces' feedback types, including how to handle the returned feedback and the essential use of the `key` parameter for multiple components. The app must be run using `streamlit run`.

import streamlit as st from streamlit_feedback import st_feedback st.set_page_config(layout="wide") st.header("User Feedback Example") # Basic thumbs up/down feedback feedback_thumbs = st_feedback( feedback_type="thumbs", optional_text_label="Tell us more (optional):" ) if feedback_thumbs: st.success(f"Thumbs Feedback received: {feedback_thumbs}") # In a real application, you would store this feedback (e.g., to a database). else: st.info("Please provide your thumbs feedback.") st.markdown("--- ") # Faces feedback with a custom key st.subheader("Rate your experience") feedback_faces = st_feedback( feedback_type="faces", feedback_options=["😀 Excellent", "🙂 Good", "😐 Neutral", "🙁 Poor", "😞 Very Poor"], key="experience_feedback" # Unique key is crucial for multiple widgets ) if feedback_faces: st.success(f"Faces Feedback received: {feedback_faces}") else: st.info("Please rate your experience.") st.caption("To run this app, save it as `app.py` and execute: `streamlit run app.py`")

Debug

Known issues

gotchaThe `st_feedback` component must be executed within a Streamlit application (`streamlit run your_app.py`). Running the script as a standalone Python file will not display the UI component and may result in errors related to missing Streamlit context.

fix

Always launch your application using the `streamlit run` command.

affects: All

gotchaWhen using `st_feedback` multiple times on the same Streamlit page, each instance *must* be assigned a unique `key` parameter. Failing to do so will cause a `StreamlitAPIException` due to key conflicts.

fix

Provide a unique string for the `key` parameter for every `st_feedback` call, e.g., `st_feedback(..., key='unique_id_1')`.

affects: All

gotchaThe structure of the dictionary returned by `st_feedback` when feedback is submitted varies based on the `feedback_type` (e.g., 'thumbs', 'faces', 'text'). Developers must inspect the `feedback_type` field and conditionally access fields like `score` or `text`.

fix

Always check `feedback_result['feedback_type']` before trying to access `feedback_result['score']` or `feedback_result['text']` to ensure correct data parsing, as not all fields are present for all types.

affects: All

Upgrade

Version history

0.1.4latest on PyPI · released Jan 13, 2025

Audit

Dependencies

streamlitrequiredThis library is a component designed to run exclusively within a Streamlit application and requires Streamlit as its core framework dependency. Version >=1.20.0 is typically required.

Agent activity

10 hits · last 30 days

node

OpenAI (training)

Resources

packagehttps://pypi.org/project/streamlit-feedback/ ↗