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

a close up of a person holding a cell phone

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.
    Open Notebook in GitHub Codespaces
  2. Download the database file database/chatbot.db.

</github codespaces>

<pythonanywhere>

  1. 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)
  2. 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
  3. 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.
  4. Edit file flask_app.py (in the Files tab) and set the following values.
    PYTHONANYWHERE_USERNAME
    PYTHONANYWHERE_WEBAPPNAME
  5. 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"
  6. Upload the database file database/chatbot.db you downloaded from GitHub Codespaces (Step 2) into the folder database/.

</pythonanywhere>

  1. 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