This application predict the rice price in Madagascar.
# Rice Price Predict
This is an End-to-End application that predict the price of rice in Madagascar based on historical data and various factors like the **weather** and the **exchage rate** between the **MGA** and the **USD**.
## Stacks and tools
### Stacks
- Python
- Jupyter Notebook
- FastAPI
- Vue.js
- TypeScript
- Node.js
- Sass
### Tools
- Docker & Docker Compose
- Git & GitHub
- MLflow & Minio & PostgresSQL
- Nginx
- Prometheus
- Grafana
- Loki
- Promtail
- Nginx Prometheus Exporter
### Data sources
- World Food Programme (WFP) HumData , wfp_food_prices_mdg.csv
- World Bank World Bank Data Catalog , global_fuel_price.xlsx
- World Bank World Bank Documents , worldbank_commodity_price.xlsx
- Yahoo Finance yfinance
- Geolocation Data geopy
## π How to Run Locally
### Prerequisites
* Docker and Docker Compose installed
### Steps
1. Clone the repository:
```bash
git clone
github.com
cd rice_price_prediction
docker compose -f docker-compose.dev.yml up -d
```
## Architecture
This is a **production-ready end-to-end ML application** following the data engineering and MLOps paradigm. The system ingests data from multiple sources, performs feature engineering, trains models, and serves predictions via a REST API with a web interface.
### System Overview
The application is structured as a **3-tier architecture**:
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β Frontend (Vue.js + TypeScript) β
β Interactive UI for prediction input/output β
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| HTTP/REST |
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β Backend API (FastAPI + Python) β
β - Request validation & error handling β
β - Model inference & post-processing β
β - JSON logging for observabilit β¦