Présentation du Projet WALL-E

Project Overview

Du Langage Naturel au Logiciel

WALL-E est une interface web innovante qui permet aux utilisateurs de décrire des projets logiciels en langage naturel, que le système génère automatiquement sans nécessiter de compétences techniques.

Décrivez simplement votre idée en français, et WALL-E gère l'intégralité du processus de développement, de l'analyse au produit final.

I need a task management app with user authentication and statistics dashboard

Automated Workflow

WALL-E analyse la description de l'utilisateur pour comprendre les besoins
Backend and frontend code is automatically generated
Comprehensive testing is performed
Project is packaged for deployment
Final product is delivered to the user

Fonctionnalités Clés

Interface React Intuitive

Interface frontend claire et conviviale construite avec React et TypeScript, stylisée avec TailwindCSS pour une expérience fluide.

Real-time Log Simulation

Interactive console that shows step-by-step progress during project generation, with animation effects.

Local Execution

Complete local operation ensures data privacy and security—no cloud dependencies required.

FastAPI Backend

Python backend processes user prompts and coordinates the generation workflow efficiently.

Responsive Design

Fully responsive interface that works perfectly on desktop, tablet, and mobile devices.

Process Control

Stop button allows users to interrupt generation at any point if needed.

Project Structure

File System Organization

wall-e/

├── frontend/ # Interface React + TailwindCSS

├── backend/ # API FastAPI

├── main.py # Lancement coordonné des 2 serveurs

├── package.json # Dépendances frontend

├── postcss.config.js

└── tailwind.config.js

Technical Stack

Frontend: React 18, TypeScript, Vite
Styling: TailwindCSS with custom animations
Backend: FastAPI (Python), Uvicorn
Communication: REST API with JSON
Launch: Unified Python script

Local Development Setup

$ git clone https://github.com/user/wall-e.git

$ cd wall-e

$ python main.py

[INFO] Backend server started on http://localhost:8000

[INFO] Frontend server started on http://localhost:5173

[INFO] Opening browser...

Frontend Architecture

React Components

App.tsx - Root component managing view modes
ChatInput.tsx - User input field with submit button
LogBuilder.tsx - Log animation with setTimeout
LogConsole.tsx - Raw log display
GenerateButton.tsx - Main action trigger

UI Techniques

Vite for ultra-fast development builds
TailwindCSS with custom animations
PostCSS with Autoprefixer
Keyframes for progress visualization

Custom Animations Configuration

// tailwind.config.js

module

.exports = {

animation: {

'fade-in': 'fadeIn 0.6s ease-out forwards',

'fade-in-up': 'fadeInUp 0.5s ease-out forwards'

}

Backend Architecture

API Endpoint

@app.post("/prompt")

async def handle_prompt(request: Request):

data = await request.json()

logs = generer_projet(data.get("prompt", ""))

return {"message": "\n".join(logs)}

This endpoint receives user prompts, processes them through the generation pipeline, and returns progress logs.

Project Generation Flow

1

🧠 Analysis of user requirements
2

📁 Project structure generation
3

🛠️ File creation with templates
4

🧪 Automated testing execution
5

📦 Packaging for deployment

Frontend-Backend Communication

Frontend sends

POST /prompt with JSON payload

Backend processes

generer_projet() simulation

Response contains

Log lines as multiline string

Démo Interactive

WALL-E Demo Interface

I need a task management app with user authentication and statistics

Understood! I'll generate a task management application with the following features:

User authentication system
Task creation/editing functionality
Statistics dashboard
Database integration

Console de Génération

$ Initializing project generation...

[1/5] Setting up authentication system...

✓ Created auth routes

✓ Set up JWT middleware

✓ Implemented user model

[2/5] Creating task management components...

[3/5] Building statistics dashboard...

[4/5] Connecting to database...

[5/5] Runing automated tests...

Évolutions Futures

AI Agent Integration

Incorporate specialized agents for different development roles (developer.py, tester.py) to create fully automated workflows.

File System Integration

Direct connection with local file system for saving generated projects and analyzing existing codebases.

Auto-KPI System

Automated performance metrics and self-evaluation based on generation logs and code quality analysis.

Project Migration

Capability to analyze and enhance existing projects, converting legacy code to modern standards.