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Talkeasy AI Language Companion

Talkeasy Dashboard

Talkeasy is a modern, AI-powered web application designed to be your personal language learning partner. Built with Next.js, Genkit, and ShadCN UI, it offers a suite of interactive tools to help users practice and improve their skills in various languages.

✨ Features

Talkeasy provides a rich, multi-faceted learning experience through a variety of specialized tools:

  • 🎮 Personalized Learning Game: An interactive, gamified journey with levels and tasks tailored to your learning style.
  • 🗣️ Pronunciation Feedback: Get real-time AI analysis and scoring on your spoken pronunciation.
  • 🤖 AI Conversational Chatbot: Practice your listening and speaking skills in realistic, AI-driven conversations.
  • 📚 Cultural Story Time: Learn language and culture simultaneously through engaging, AI-generated folktales with audio narration.
  • 🗺️ Learn by Exploring: A unique map-based feature where you can click on locations to get a real-world language mini-lesson.
  • ✍️ Grammar & Vocabulary Assistant: Get instant feedback on your writing or speech to correct grammar and improve vocabulary.
  • 🔤 Alphabet Tracing: Learn new alphabets by tracing characters and receiving AI feedback on your accuracy.
  • 📄 Document Translator: Upload a PDF or paste text to receive a concise summary translated into your target language.
  • ...and many more! Including a visual translator, scenario-based phrasebook, and a personalized study plan generator.

🛠️ Tech Stack

This project is built with a modern, powerful tech stack:

🚀 Getting Started

Follow these steps to get a local copy of the project up and running.

Prerequisites

  • Node.js (v18 or later)
  • npm, pnpm, or yarn

1. Set Up Environment Variables

First, you'll need to provide your own API keys for the various Google services used in this application.

  1. Make a copy of the .env.example file and rename it to .env.

    cp .env.example .env

  2. Open the .env file and add your API keys. You can obtain these keys from the Google Cloud Console.

    # For Google AI Studio / Gemini Models
GEMINI_API_KEY="YOUR_GEMINI_API_KEY"

# For Google Maps Platform (used in the "Explore" feature)
NEXT_PUBLIC_GOOGLE_MAPS_API_KEY="YOUR_GOOGLE_MAPS_API_KEY"

# For YouTube Data API (used in the "Study Plan" feature)
YOUTUBE_API_KEY="YOUR_YOUTUBE_API_KEY"

2. Install Dependencies

Navigate to the project directory and install the necessary packages.

npm install

3. Run the Development Server

You can now start the development server.

npm run dev

🧍‍♀ 3D Model Details

project includes a female virtual assistant 3D model in .glb format. Here are the details of the model included:

Ar Dashboard

🎨 Model Description

Format: GLB (GLTF Binary)

Character Type: Female virtual assistant / avatar

Clothing: White shirt, dark grey pants

Style: Cartoon / semi-realistic

Rigged: Yes (body rig available)

Facial Features: Eyes, eyebrows, mouth, ready for animation

Rendering: Fully compatible with Three.js GLTFLoader

🧩 Model Usage in Project

Loaded in the frontend using GLTFLoader

Rendered with Three.js inside a WebGL canvas

Used for displaying responses during TTS/STT

📌 Step 1 — Run the Backend

Open a terminal and run:

cd nurse-backend
npm install
npm run dev

The backend server will start.

📌 Step 2 — Run the TTS Frontend

Open a new terminal and run:

cd nurse-frontend
npm install
npm run dev

This starts the frontend (3D model + TTS/STT interface).

✔️ That’s it.

Your backend and frontend are now running together.

🧰 Technical Stack Used

Below is the complete list of technologies used in your project:

Backend

  • Node.js – JavaScript runtime
  • Express.js – Backend server framework
  • REST API – Communication between frontend and backend
  • npm – Package manager

Frontend (TTS App + 3D Model)

  • Vite / React or Plain JS (depending on your setup)
  • Three.js – Rendering the 3D avatar
  • GLTFLoader – Loading the .glb model
  • HTML / CSS / JavaScript – UI structure and styling

TTS (Text-to-Speech)

Your project uses one of the following:

  • Web Speech Synthesis API (browser-based TTS) OR
  • OpenAI TTS API (if configured in backend) OR
  • Google gTTS (if using Python in earlier versions)

STT (Speech-to-Text)

Your project uses:

  • Web Speech Recognition API (browser microphone → text) OR
  • OpenAI Whisper API (if configured)

Other Tools

  • VS Code – Recommended editor
  • Local Development Server – Runs using npm run dev
  • Node Package Modules – Installed per folder
    Your backend and frontend are now running together.

TraceIt ✨ - Learn Alphabets by Tracing

traceit Dashboard

A fun, interactive, and AI-powered way to learn new alphabets.

TraceIt is a web application designed to help users learn the alphabets of various languages by tracing them on a digital canvas. As a subset of the larger Talkeasy language-learning ecosystem, TraceIt provides real-time feedback using generative AI to make learning effective and engaging.

🚀 Features

  • Multi-Language Support: Practice alphabets from a growing list of languages, including English, Hindi, Malayalam, and more.
  • Interactive Tracing Canvas: A smooth and responsive canvas to practice drawing each character.
  • AI-Powered Feedback: Get instant feedback on your tracing accuracy and speed, with personalized tips for improvement powered by Google's Gemini models through Genkit.
  • Adaptive Difficulty: The tracing challenge adapts to your skill level, ensuring a continuously engaging learning curve.
  • Character Pronunciation: Hear the correct pronunciation of each alphabet with Text-to-Speech synthesis.
  • Progress Tracking: Your best score for each character is saved locally, so you can track your mastery.
  • Personalized Suggestions: Receive AI-powered suggestions for new languages to explore based on your interests.
  • Modern & Responsive UI: A clean, beautiful interface built with ShadCN UI and Tailwind CSS that works on all devices.

🛠 Tech Stack

🏁 Getting Started

Follow these steps to get the project running on your local machine.

Prerequisites

Installation

  1. Clone the repository: bash git clone https://github.com/Mohammedsanin/Talkeasy.git cd Talkeasy

  2. Install dependencies: Navigate to the project directory and install the necessary packages using npm. bash npm install

  3. Set up Environment Variables: Create a new file named .env in the root of the project and add your Google AI API key. You can get a key from Google AI Studio.

    env

    .env

    GEMINI_API_KEY=YOUR_API_KEY_HERE

  4. Run the Development Server: Start the Next.js development server. bash npm run dev

  5. Open the application: Open your browser and navigate to http://localhost:9002 to see the application running.

📂 Project Structure

  • src/app/: Contains the main pages and routes of the application.
  • src/components/: Reusable React components, including UI components from ShadCN.
  • src/ai/: Home for all AI-related logic.
    • flows/: Genkit flows that define the core AI features.
    • genkit.ts: Genkit configuration file.
  • src/lib/: Contains data (ALPHABET_DATA), utility functions, and local storage logic.
  • public/: Static assets like images and fonts.

Made with ❤ for the love of languages.

Open http://localhost:9002 with your browser to see the result. You can start editing the page by modifying src/app/page.tsx.

📜 License

This project is licensed under the MIT License. See the LICENSE file for details.

About

Talkeasy – Your AI-Powered Regional Language Learning Companion. Built with Next.js and Genkit, this app uses Google Gemini models to offer a suite of tools: conversational chatbot, pronunciation feedback, personalized study plans, gamified lessons, and cultural storytelling. A modern, all-in-one platform to make language learning immers

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