Language Learner Chat Application

This project is a language learning chat application using Django, React and the turbo API. The application provides a friendly and supportive companion to help users practice and improve their language skills through interactive conversations.

Features

• Real-time Chat: Engage in conversations with an AI-powered assistant.
• Conversation History: Maintains context with session-based conversation history.
• Customizable Responses: The assistant can be fine-tuned to provide more accurate and helpful feedback.
• Friendly and Supportive Tone: The assistant is designed to be a friendly companion, providing encouragement and constructive feedback.
• Speech-to-Text: Integrates Google Cloud Speech-to-Text API for converting spoken language into text.
• Modern Frontend: Utilizes React with Vite for a fast and efficient frontend development experience.

Prerequisites

• Python 3.8+
• Django 5.0.6
• Node.js (for React and Vite)
• Google Cloud Speech-to-Text API Key

Installation

Backend Setup

1. Clone the Repository

   git clone https://github.com/4arjun/convovoice-frontend.git
   cd convovoice

2. Create a Virtual Environment

   python -m venv convovoice-env
   source convovoice-env/bin/activate  # On Windows, use `convovoice-env\Scripts\activate`

3. Install Dependencies

   pip install -r requirements.txt

4. Configure Environment Variables

   Create a .env file in the root directory and add your API keys:

   GCP_SPEECH_TO_TEXT_API_KEY=your-google-cloud-api-key
   

5. Apply Database Migrations

   python manage.py makemigrations
   python manage.py migrate

6. Run the Development Server

   python manage.py runserver

7. Access the Application Open your web browser and go to http://localhost:8000/chat.

Frontend Setup

1. Navigate to the Frontend Directory

   cd convovoice

2. Install Dependencies

   npm install

3. Run the Development Server

   npm run dev

4. Access the Frontend

   Open your web browser and go to http://localhost:3000.

Project Structure

• speechanalyser/: Main Django application directory.
• speechanalyser/views.py: Contains the chat_view function that handles chat requests.
• speechanalyser/urls.py: URL routing for the application.
• frontend/: Directory containing the React frontend.
• requirements.txt: List of dependencies required by the project.

Usage

To interact with the chat application, send a GET request to the /chat endpoint. The application will return a JSON response with the user message and the assistant's reply.

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

Contact For any questions or suggestions, please open an issue or contact me at [email protected].