Project: Simple Conversational Assistant using Rasa

Introduction

In this project, I create a simple conversational assistant using Rasa, an open-source framework for building AI assistants and chatbots.

Project Structure

• data/
  • Training data for NLU and dialogue management.
• models/
  • Stores trained models.
• actions/
  • Custom action definitions.
• domain.yml
  • Defines intents, entities, slots, responses, and actions.
• config.yml
  • Configuration for the training pipeline and policies.
• endpoints.yml
  • Configuration for bot endpoints.

Getting Started

Prerequisites

Ensure I have the following installed:

• Python 3.7+
• Rasa Open Source
• A text editor or IDE

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/your-repo-name.git
   cd your-repo-name

2. Create and activate a virtual environment:

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

3. Install the required packages:

   pip install -r requirements.txt

Training the Model

To train the NLU and dialogue management models, run:

rasa train

Running the Assistant

To start the Rasa server:

rasa shell

Custom Actions

If there are custom actions, start the action server:

rasa run actions

Testing

Test the assistant in interactive mode:

rasa interactive