Spotify Song Reccomender

Spotify Song Reccomender

A small Streamlit app that suggests songs, shipped with a genres picture. The page gives no details on its data or method, so it suits people who want to read a simple recommender demo.

Made by ibrhmyi on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: This is a small Streamlit app that, going by its name, recommends songs. The repository holds the app file, a requirements file and a picture named Genres. The README is empty, so the page does not say where the song data comes from or how the recommendations are chosen. It runs on the basic CPU tier at Hugging Face.

Who it suits: Music fans who want to try a simple recommender, and learners who want a short Streamlit app to read.

Industry | Who uses it | How they use it | Example
Music | Listeners | Try a recommender to find new songs | Look at what the app suggests
Education | Students | Study how a small recommender app is built | Read app.py and change a setting
Software | Developers | Use it as a Streamlit starting point | Reuse the page layout

Skip it if you need a documented service, since the page gives no data source or method.

Where to use it:

• A web browser, on the Space's page at Hugging Face
• Windows, macOS or Linux with Python, as a local copy

Use case | Who | What they get back
Get song suggestions | Listeners | A list of recommended songs from the app
Study the app | Learners | A short Streamlit codebase

How to set it up:

• Nothing at all if you only use the online Space
• Python and pip, for a local copy
• The Python packages listed in requirements.txt

1. Open the Space's page at Hugging Face to use it online.
2. For a local copy, install the Hugging Face hub package and download the Space.
3. Move into the new folder and install Streamlit at the pinned version.
4. Install the packages from requirements.txt.
5. Start the app with the Streamlit command.

pip install -U huggingface_hub
hf download ibrhmyi/Spotify_Song_Recommender --repo-type space --local-dir Spotify_Song_Recommender
cd Spotify_Song_Recommender
pip install streamlit==1.33.0
pip install -r requirements.txt
streamlit run app.py

The page does not say what a local run needs beyond the packages.

How to use it: Online, open the Space and use the controls on its page. On your own machine, run the Streamlit command and open the page it serves in your browser. The page lists no other commands.

Tool | What it does
streamlit run app.py | Starts the Streamlit app on your computer

Example: You open the Space and look for a way to name a song or a genre you like. The app answers with a list of suggestions, and you try a few of them to see whether they suit your taste.

For newcomers and experts: If you are new, open the Space online and try one liked song or genre. Treat the answers as ideas, because the page does not explain how they are made.

If you know the field, nothing in the README describes the features, the dataset or the model behind the suggestions. Read app.py first to learn whether it uses content features, a similarity measure or something else.

Open the Space in a browser
Choose a song or genre
The app picks similar songs
You read the suggestions

Good to know:

• License: mit
• Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face
• Data it reaches: the choices you make in the app, and the data files the app itself uses
• Not for: anything that needs a documented method, since the page gives none

On Hugging Face, 13 November 2026

• Likes: 2
• Built with: streamlit
• License: mit

Links

• Space: https://huggingface.co/spaces/ibrhmyi/Spotify_Song_Recommender
• Files: https://huggingface.co/spaces/ibrhmyi/Spotify_Song_Recommender/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.