Rasa Chatbot Project Guide

This guide provides a detailed walkthrough for setting up and developing a Rasa chatbot project using Visual Studio Code (VSCode).

Step 1: Install Visual Studio Code

• Download and install VSCode from the official website: https://code.visualstudio.com/

Step 2: Install Python

• Ensure Python 3.10 or newer is installed on your system. Download it from https://www.python.org/.

Step 3: Install Rasa

1. Open VSCode and start a new terminal session (Terminal > New Terminal).
2. Create a project directory for your Rasa project files.
3. Navigate to your project directory in the terminal using the cd command.
4. Create a Python virtual environment for your project:

   python3 -m venv ./rasa_venv

   On Windows, you might use python instead of python3.
5. Activate the virtual environment:
   • On Windows:

     .\rasa_venv\Scripts\activate
     

   • On macOS/Linux:

     source rasa_venv/bin/activate
     

6. Install Rasa within the virtual environment:

   pip install rasa==3.6.16

Step 4: Initialize Your Rasa Project

1. In the VSCode terminal, ensure you're in your project directory and your virtual environment is activated.
2. Run the following command to create a new Rasa project:

   rasa init

3. Follow the prompts to create the initial project structure and train a simple bot.

Step 5: Explore and Modify Your Project

• Open the project directory in VSCode (File > Open Folder) to start editing your files.
• Modify the generated files to develop your chatbot's training data and logic.

Step 6: Train Your Rasa Model

• Retrain your model by running:

  rasa train

Step 7: Test Your Bot in the Shell

• Test your chatbot by running:

  rasa shell

Step 8: Develop Custom Actions (Optional)

• Edit actions/actions.py for custom actions.
• Start the action server with rasa run actions.

Step 9: Use Version Control

• Initialize a Git repository and commit your changes:

  git init
  git add .
  git commit -m "Initial commit"

Step 10: Continuous Learning and Improvement

• Continue developing your bot by adding more training data, refining the domain, and adding custom actions as needed.

Additional Tips

• Consider installing the Python extension for VSCode.
• Refer to the Rasa Documentation for more information: https://rasa.com/docs/