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https://github.com/kilimoguard/kilimoguard_backend

The KilimoGuard backend is the core service that powers the KilimoGuard AI platform, focused on predicting and managing crop pests in East Africa. The KilimoGuard backend, built with Django, powers the platform's core services, including AI-driven pest prediction, user authentication, and data management.
https://github.com/kilimoguard/kilimoguard_backend

ai django-framework machine-learning python

Last synced: 3 months ago
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Host: GitHub
URL: https://github.com/kilimoguard/kilimoguard_backend
Owner: KilimoGuard
Created: 2024-08-05T17:25:42.000Z (5 months ago)
Default Branch: develop
Last Pushed: 2024-08-29T14:45:11.000Z (4 months ago)
Last Synced: 2024-10-11T07:04:21.693Z (3 months ago)
Topics: ai, django-framework, machine-learning, python
Language: Python
Homepage: https://kilimoguard-backend-1twn.onrender.com
Size: 750 KB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 3
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md

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README

# KilimoGuard Backend

## Overview

KilimoGuard is an innovative Pest Prediction and Management System designed to address the escalating threat of plant and crop pests in East Africa. Leveraging historical data and real-time environmental factors, KilimoGuard provides accurate predictions of potential pest outbreaks, enabling proactive decision-making and sustainable pest management practices.

## Features

* **Predictive Analytics**: Utilizes machine learning models to predict pest outbreaks.
* **Real-Time Monitoring**: Collects and analyzes real-time environmental data to provide timely alerts.
* **User-Friendly Interface**: Accessible via mobile and web applications with intuitive design.
* **Actionable Insights**: Offers recommendations for optimal pest management and sustainable farming practices.

## Directory Description

* **kilimo_guard/**: This is where the application logic is written. Contains all API end point for Kilimo Guard.
* **kilimo_project/**: This is the main project directory which contains the settings and configuration for the entire Django project.
* **media/**: This directory is used to store custom files such the datasets for the AI model and user-uploaded files.
* **static/**: This directory is for storing static files such as CSS, JavaScript, and images
* **.env**: This file contains environment variables for the project, such as database credentials, secret keys, and other configuration settings that shouldn't be hard-coded in the codebase.
* **.env_example**: A sample environment file to show what kind of environment variables are needed. It's a template for creating the `.env` file.
* **.gitignore**: This file specifies intentionally untracked files to ignore. For instance, it would typically include the virtual environment directory, compiled code, and other files that shouldn't be committed to version control.
* **db.sqlite3**: This is the SQLite database file for the project. SQLite is a lightweight database included with Python and is often used for development and testing.
* **manage.py**: A command-line utility that lets you interact with this Django project in various ways. You can use it to run the server, create apps, run tests, and more.
* **Procfile**: Configuration file for deployment.
* **README.md**: A markdown file that typically contains an introduction to the project, how to set it up, usage instructions, and other relevant information.
* **requirements.txt**: This file lists all the Python packages that your project depends on. It can be used to install all the dependencies using `pip install -r requirements.txt`.
* **start.sh**: This is a shell script to start the application in development environment.

## Installation

1. Clone the repository:

```bash
git clone https://github.com/KilimoGuard/kilimoGuard_Backend.git
```

2. Navigate to the project directory:

```bash
cd kilimoGuard_Backend
```

3. Create and activate a virtual environment:

```bash
python3 -m venv virtual
source virtual/bin/activate
```

4. Install the required dependencies:

```bash
pip install -r requirements.txt
```

## Usage

1. Run the application:

```bash
python manage.py runserver
```
or you could use the bash script __start.sh__ after making it executable once by running the command:- __chmod a+x start.sh__. After that you can run the command below any time to start the project.
```bash
./start.sh
```

2. Access the application through your web browser at ` http://0.0.0.0:8070/`.

## Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes.