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/ TextUs Public

Customer service training simulator with agentic AI customers, in collaboration with CPF Board

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pyraxo/TextUs

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CPF Board TextUs

A training simulator designed to help CPF Board customer service officers master concepts and improve their customer service skills through AI-powered simulated conversations.

Overview

TextUs is a comprehensive training platform that enables customer service officers to:

  • Practice handling various customer inquiries in a safe, simulated environment
  • Receive real-time feedback on performance metrics (comprehension, tone, accuracy, rubrics)
  • Trainers can now provide structured feedback using rubrics after each session
  • Access a variety of scenarios covering different CPF-related topics
  • Track progress and improvements over time

Project Structure

  • frontend/ - Next.js web application with Tailwind CSS
  • backend/ - FastAPI Python server with SQLModel
  • docs/ - Project documentation and changelog

Getting Started

Prerequisites

  • Docker and Docker Compose
  • Node.js 18+
  • Python 3.11+
  • uv package manager

Installation

  1. Set up environment variables:
# Backend
cd backend
cp .env.example .env
# Edit .env with your configuration
# Frontend
cd ../frontend
cp .env.example .env
# Edit .env with your configuration
  1. Start the development environment:
docker-compose up -d

The application will be available at:

Development

Backend Development

See backend/README.md for detailed backend setup and development instructions.

Frontend Development

See frontend/README.md for detailed frontend setup and development instructions.

Documentation

Features

  • User authentication and role management
  • Interactive practice sessions with AI-simulated customers
  • Real-time performance metrics and feedback
  • Customizable scenarios and customer profiles
  • Comprehensive analytics and reporting
  • Responsive web interface
  • Rubrics management for structured evaluation
  • Trainer feedback system for session reviews

Contributing

  1. Create a feature branch (git checkout -b feature/new-feature)
  2. Commit your changes (git commit -m 'Add new feature')
  3. Push to the branch (git push origin feature/new-feature)
  4. Open a Pull Request

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