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README.md
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# ARAI
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# ARAI — Legal Mediation Assistant
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A web application built in **48 hours** at a legal-tech hackathon that helps users resolve disputes through mediation instead of court.
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Describe your case in plain language, and the app will:
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1. **Categorise** the dispute (civil, labour, commercial, etc.)
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2. **Estimate** the likely court cost and duration based on real court statistics
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3. **Score and recommend** mediators suited to the case
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## Tech Stack
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| Layer | Technology |
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|---|---|
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| Frontend | Angular 17, Angular Material, SCSS |
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| Backend | Python, Flask, pandas |
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| AI | OpenAI API (case categorisation & mediator scoring) |
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| Real-time | WebSocket relay (Node.js) |
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## Project Structure
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```
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arai-frontend/ Angular SPA — form wizard, results display, Material UI
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Backend_correct/ Flask API — categorisation, cost estimation, mediator scoring
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simple-ws/ Lightweight WebSocket relay server (Node.js)
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statystyki/ Court statistics data pipeline (pandas + Excel)
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franek/ ML experiments — case scoring prototypes
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```
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## Quick Start
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### Backend
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```bash
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cd Backend_correct
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pip install flask flask-cors pandas openpyxl openai
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python app.py
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```
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### Frontend
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```bash
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cd arai-frontend
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pnpm install
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pnpm start # serves on http://localhost:4200
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```
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The frontend proxies API requests to the Flask backend via `proxy.conf.json`.
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## Team
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Built by 5 contributors during the hackathon:
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- Krzysztof Rudnicki — frontend & integration
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- Franciszek Michalowski — ML & scoring
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- Jakub Jarzembowski — backend
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- Mateusz Szpyruk — data & statistics
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- + 1 contributor
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