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---
title: Ai Academy 2024 Gr8 Recommender Api
emoji: 📉
colorFrom: green
colorTo: pink
sdk: docker
pinned: false
license: mit
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference.
# ai-academy-2024-group8
A lightweight backend API for song recommender
Dataset used in this project is public and available from [online](https://www.kaggle.com/datasets/undefinenull/million-song-dataset-spotify-lastfm)
## What's in here
- `data/`: Contains the trained `model.pkl` and related `model.csv` that has the training set in csv format
- `notebooks/`: Contains any jupyter notebooks used in the project
- `recommendation-api/`: A FastAPI app to serve user recommendations
## Running service locally
1. (Optional) Create an activate python venv
2. Install the requirements `pip install -r requirements.txt`
3. Start the service `python recommendation-api/server.py`
Then
- `curl http://localhost:7860/users` to fetch list of supported users
- `curl http://localhost:7860/users/<id>` to fetch track history for individual user
- `curl http://localhost:7860/recommend/<id>` to recommend tracks for the specific user
## Running in Huggingface
Application is built and started on push to master.
Application is available from [here](https://schibsted-ai-academy-2024-gr8-recommender-api.hf.space/docs)
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