A Chatbot using GPT and a Database with a Front-End

Create and deploy a chatbot

Follow the 9 steps below to create a chatbot and deploy it on pythonanywhere.

<github codespaces>

1. Use the notebook chatbot_setup.ipynb to create a chatbot.
   
2. Download the database file database/chatbot.db.

</github codespaces>

<pythonanywhere>

3. Create an account at pythonanywhere
   https://www.pythonanywhere.com/registration/register/beginner
   Note: The user name chosen will be part of your URL (PYTHONANYWHERE_USERNAME.pythonanywhere.com)
4. Create a web application (in the Web tab)
   • Python Web Framework: Flask, choose the latest version.
   • Path: Optionally change ".../my_site/..." to meaningful PYTHONANYWHERE_WEBAPPNAME
5. Start a Bash console (in the Consoles tab) and enter the following commands:
   • pip install openai
   • cd mysite → if you have a different PYTHONANYWHERE_WEBAPPNAME, replace mysite with yours.
   • rm -r *
   • git clone https://github.com/zhaw-iwi/singlestateconversation .
     Note: The dot at the end is necessary.
6. Edit file flask_app.py (in the Files tab) and set the following values.
   PYTHONANYWHERE_USERNAME
   PYTHONANYWHERE_WEBAPPNAME
7. Edit the file chatbot/openai_template.py and save it as chatbot/openai.py. Set the following keys.
   OPENAI_KEY = "Your OpenAI API Key in quotes"
   OPENAI_MODEL = "Model name in quotes, e.g. gpt-3.5-turbo-16k"
8. Upload the database file database/chatbot.db you downloaded from GitHub Codespaces (Step 2) into the folder database/.

</pythonanywhere>

9. Access your chatbot by entering the URL into your browser.
   https://[PYTHONANYWHERE_USERNAME].pythonanywhere.com/[type_id]/[user_id]/chat

If something doesn't work as expected

• Reload your Web Application:
  Navigate to your web application (in the Web tab) and press the green button to reload it (required for all changes except for content in folder database/ and static/)
• Have a look at the Error Log:
  Navigate to your web application (in the Web tab) and scroll down to the Log files. Study the latest error at the bottom of the Error log.

A Chatbot using GPT and a Database

This allows multiple chatbot types (e.g. a health coach and a learning assistant) to be created. Multiple chatbot instances can be created per chatbot type (e.g. a health coach for user X and user Y, and a learning assistant for user P and user Q). Both, types and instances are stored with and referenced by an ID (e.g. a UUID) in the database.

This can support the deployment of chatbots in a web backend (state-less). For example, the IDs of the type and instance can be read from parameters of a URL that users have received from you.

A chatbot is created with the following arguments.

• database_file: File of SQLite (in Folder data/)
• type_id: Reference to a chatbot type (existing or new one)
• instance_id: Reference to chatbot instance (existing or new one)
• type_role: Role prompt of chatbot type (will be turned into a first prompt with role:system)
• instance_context: Context prompt of chatbot instance (will be turned into a second prompt with role:system)
• instance_starter: Prompt that will be used to generate an initial message to the user (will be turned into a third prompt with role:system)

The following functions are meant to be used from an application (e.g. from controllers of a REST API).

• conversation_retrieve(with_system=False): Retrieve the previous conversation history (default: without prompts with role:system)
• start(): Returns an initial message to the user (Resulting from instance_starter prompt)
• respond(user_says): Returns an assistance response to user_says
• info_retrieve(): Returns the chatbot name, type role and instance context
• reset(): Resets the conversation so far