SPARC-Frontend

This is the official frontend for the SPARC (SME Disaster Preparedness and Resilience Check) tool. It allows users to assess their resilience using the CASE Equation and receive personalized insights and recommendations.

🔍 Purpose

To deliver a user-friendly interface for SME users to input their disaster preparedness data and visualize their results.

✨ Features

• Full CASE Equation survey with detailed inputs
• Personal information collection with consent
• Responsive UI with styled form and results
• Result breakdown by Coping, Adaptability, Sensitivity, Exposure

🛠️ Technologies

• HTML5
• CSS3
• JavaScript (Vanilla)
• Chart.js (optional)
• Rasa Webchat (optional)

🚀 How to Use

# Clone repo
git clone https://github.com/YourOrg/SPARC-Frontend.git

Open index.html in a browser or deploy to GitHub Pages, Netlify, or your server.

📦 Deployment

# Static hosting suggestion
npm install -g serve
serve .

---

```markdown
# SPARC-Backend

The server-side logic for SPARC, responsible for processing assessments, calculating scores, storing results, sending emails, and interacting with the AI layer.

## 📌 Features

- API for receiving and processing submissions
- CASE Equation calculations and validation
- Email integration via SendGrid or Mailgun
- Calls SPARC-AI for tailored guidance
- Optional login/auth system for admins

## ⚙️ Tech Stack

- Python (Flask)
- PostgreSQL or MySQL
- SQLAlchemy
- SendGrid or SMTP
- CORS + REST API

## 🚀 Getting Started

```bash
git clone https://github.com/YourOrg/SPARC-Backend.git
cd SPARC-Backend
pip install -r requirements.txt
python app.py

Configure .env for DB and email credentials.

🔌 API Routes

• POST /submit-assessment
• GET /results/:id (optional)

---

```markdown
# SPARC-AI

An AI microservice that uses a fine-tuned GPT-Neo (or similar) model to generate personalized resilience recommendations based on SPARC scoring inputs.

## 🤖 Features

- Predictive, context-aware disaster guidance
- Custom prompts aligned with CASE Equation
- API-first design, integrated with SPARC-Backend

## 💡 Model

- HuggingFace Transformers (GPT-Neo or GPT-2)
- Trained on SME disaster response best practices

## 🧠 Inputs

```json
{
  "coping": 3.8,
  "adaptability": 4.1,
  "sensitivity": 2.6,
  "exposure": 3.0
}

✉️ Output

Natural language paragraph with tailored suggestions.

🛠️ Setup

git clone https://github.com/YourOrg/SPARC-AI.git
cd SPARC-AI
pip install -r requirements.txt
python app.py

Use ngrok or deploy on HuggingFace Spaces, AWS, or Render.

---

```markdown
# SPARC-NLG

This repo contains training data, prompt templates, and scripts for fine-tuning a GPT-based model to produce resilience recommendations.

## 🧠 Purpose

To supply SPARC-AI with domain-specific data so it can generate high-quality, SME-tailored disaster preparedness advice.

## 📁 Structure

- `data/`: JSON, CSV with case studies & insights
- `prompts/`: Scoring prompt templates
- `fine_tune_config.json`: HuggingFace Trainer settings

## 🧪 Fine-Tuning

Use Google Colab, HuggingFace Trainer, or local GPU:

```bash
transformers-cli train \
  --model_name gpt2 \
  --train_file ./data/resilience_cases.json \
  --config ./fine_tune_config.json

🔍 Licensing

Use responsibly for non-commercial purposes unless fine-tuned model is publicly released.

---

```markdown
# SPARC-Chatbot

A conversational AI assistant built with Rasa to provide dynamic support to SME users during their resilience assessment.

## 💬 Capabilities

- Guide users through survey sections
- Answer disaster-related FAQs
- Expand on recommendations from SPARC-AI
- Multi-intent & context-aware support

## 🧠 Stack

- Rasa (NLU + Core)
- YAML stories
- Python custom actions (optional)

## 🚀 Setup

```bash
git clone https://github.com/YourOrg/SPARC-Chatbot.git
cd SPARC-Chatbot
pip install -r requirements.txt
rasa train
rasa run actions
rasa shell

Or deploy with Rasa X.

📦 Integration

Embed Rasa Webchat into SPARC-Frontend using:

<script src="https://cdn.jsdelivr.net/npm/rasa-webchat/lib/index.min.js"></script>
---

# SPARC-Dashboard

This repo includes data visualization tools and components to graphically present SPARC resilience scores, trends, and improvements.

## 📊 Features

- Bar/Line charts for CASE component averages
- Comparative risk overlays (optional)
- Mobile-friendly dashboard layout
- Can connect live to SPARC-Backend API

## 🔧 Technologies

- Chart.js
- D3.js (optional)
- Bootstrap or Tailwind UI

## 🔌 Example Usage

```javascript
const ctx = document.getElementById("chart").getContext("2d");
new Chart(ctx, {
  type: "bar",
  data: { ... },
  options: { responsive: true }
});

📦 Hosting

Can be embedded in SPARC-Frontend or hosted as a separate admin view.