一个项目的基类工程

JavaScript / TypeScript Library

convert CSV to pydantic.BaseModel and vice versa

An application that facilitates frequently used operations with different tools

Welcome to my FastAPI playground where I took my first spin with FastAPI and went from uvicorn confusion to full-blown route domination.

MemoKeep - A memory based Notes taking web application made using Fast-API, mongodb, Bootstrap

AI-powered article analysis engine orchestrating Zero-Shot Classification (Hugging Face) and Contextual Synthesis (Gemini). Features a secure JWT-authenticated API and structured data management.

Mini Project Base Model Best Hypertuned Model for Metrik Penting pada Algoritma Random Forest

This FastAPI app includes a GET endpoint at / and a POST endpoint at /send to receive user input. It retrieves data from a simulated database implemented as a Python dictionary. The app uses Pydantic's BaseModel to validate input data and ensure type safety.

Transform your camelCase query parameters into a model using snake_case fields

A secure backend user authentication system using FastAPI, JWT, and MongoDB Atlas. It supports user signup, login, JWT-based session management, and CRUD operations for user profiles. Passwords are hashed for security. MongoDB Cloud ensures scalable data storage with fast and reliable access.

Infer a Pydantic BaseModel from any JSON object instantly. Zero dependencies.

🚀 Freecel Telecom API

A secure, production-ready API for French-English translation. Features JWT authentication to ensure reliable and authorized access to translation services.

Une application d’aide à la décision RH combinant machine learning supervisé et intelligence artificielle générative. Ce backend expose une API sécurisée permettant de prédire le risque de départ d’un employé et de générer des plans de rétention personnalisés.

Improving retrieval quality for trading documents using all-MiniLM-L6-v2

Web App for receive json post from clients, this app is using fastapi as core code

An RL-powered Ticket Routing system implementing the OpenEnv framework, including custom environment, agent design, reward optimization, and scalable customer support automation.

V.3.0 - This module focuses on data validation using Pydantic, covering field constraints, optional fields, enums, nested models, and model-level validation. It includes practical examples of validating structured data, handling errors, and enforcing business rules in increasingly complex scenarios.