Rendu Hackathonia Groupe 14: Dev,Infra,Cyber,DataIex#36
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- Remove outdated datasets and model files - Remove old training scripts and requirements - Clean up legacy documentation - Prepare for fresh infrastructure setup
- Add .gitignore and .dockerignore for proper file management - Create .env.example template for configuration - Add comprehensive README with project overview - Add QUICK_START guide for rapid deployment
- Add Dockerfile for application container setup - Configure docker-compose for multi-container orchestration - Add Modelfile for Ollama model configuration - Support for development and production environments
- Create Ansible playbook for orchestrated deployment - Add Ollama role with handlers and default variables - Configure inventory for target hosts - Support automated infrastructure provisioning
- Add deploy-docker.sh for Linux/Mac deployment - Add deploy.ps1 for Windows PowerShell deployment - Add health-check.sh for service monitoring - Add init-model.sh for model initialization - Add test-api.sh for API validation and testing
- Add Makefile for common build and deployment tasks - Add requirements.txt for Python dependencies - Support for automated workflows and scripts
Features: - Complete Docker Compose configuration (frontend + backend) - Flask proxy server for Ollama with CORS and streaming - Modern Vue.js 3 web interface - Environment-based configuration (.env) - Health checks and auto-restart - Quick-start scripts for Linux/Mac/Windows - Comprehensive documentation Ollama is managed externally by INFRA team.
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Organisation du Rendu
Le projet est organisé en quatre pôles autonomes mais intégrés:
Dev - Interface & Backend
L'équipe développement fournit une interface web moderne et un serveur API proxy. Elle crée le pont de communication entre l'utilisateur et le modèle d'inférence, avec streaming temps réel et une UX intuitive.
Infra - Orchestration & Déploiement
L'équipe infrastructure gère l'ensemble du stack Ollama: déploiement automatisé, orchestration avec Docker, monitoring, et scripts de configuration. Elle garantit que le modèle tourne de manière stable et scalable.
Cyber - Sécurité & Audit
L'équipe sécurité a effectué un audit complet de la solution, identifié les risques, et validé que l'architecture respecte les standards de sécurité pour un environnement professionnel.
Data - Modèle & Datasets
L'équipe data fournit les configurations du modèle Phi-3.5-Financial, les datasets nettoyés et validés, ainsi qu'un rapport détaillé sur la qualité des données utilisées pour le fine-tuning.
Architecture du Rendu
rendu/
├── dev/ # Interface Web & API Proxy
│ └─ UI│
├── infra/ # Orchestration & Déploiement
│ └─ Ollama + Docker Compose + Ansible
│
├── cyber/ # Audit & Sécurité
│ └─ Rapport de sécurité complète
│
└── dataia/ # Modèle & Datasets
└─ Phi-3.5 + Données nettoyées
Groupe 14 | Hackathonia YNOV Toulouse 2026