YossoufBouzir/made-in-rwanda-recommender
Domain:
digital infrastructureRecord type:
software
Creator:
Yos
Host:
# Made in Rwanda Content Recommender
**AIMS KTT Hackathon · Challenge S2.T1.3**
**Author:** Youssouf Bouzir
**Email:** bouzir.youssouf@students.jkuat.ac.ke
**Date:** 2026-04-22
---
## Overview
A CPU-friendly content-based recommender for Made-in-Rwanda products. The system uses TF-IDF over product metadata, cosine similarity for retrieval, a local-boost rule that prioritises Rwandan-made items, and a curated fallback when no strong local match is found.
**Final metrics on the provided query set:**
- NDCG@5: _(0.0808 0.0808 (expected 0.0808))_
- Local-presence rate (top-3): _(1.0000 (expected 1.0000 = 100.0%))_
- Curated-fallback rate : 0.0000 (expected 0.0000)
**4-minute demo video:** _(............................)_
---
## Repository structure
```
made-in-rwanda-recommender/
├── recommender.py # main retrieval pipeline + CLI
├── eval.ipynb # evaluation notebook (NDCG@5 + local-presence rate)
├── dispatcher.md # product & business adaptation artifact
├── process_log.md # timeline + declared LLM/tool use
├── SIGNED.md # signed honor code
├── README.md # this file
├── requirements.txt # Python dependencies
├── LICENSE # MIT
├── data/
│ ├── catalog.csv # product catalog (400 SKUs)
│ ├── queries.csv # evaluation queries
│ └── click_log.csv # user click events
└── generator/
└── synthetic_generator.py # script to regenerate synthetic data
```
---
## Quick start (local)
```bash
# 1. Install dependencies
pip install -r requirements.txt
# 2. Run a query
python recommender.py --q "leather boots"
# 3. French / code-switched query (required demo)
python recommender.py --q "cadeau en cuir pour femme" --top_k 5
```
## Quick start (Google Colab)
Open a new Colab notebook and run:
```python
# Cell 1
!git clone github.com
%cd made-in-rwanda-recommender
!pip in …