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Using the llamabot ChatBot Class in a Jupyter Notebook

To use the ChatBot class from llamabot in a Jupyter notebook, you can follow these steps:

  1. Import the ChatBot class from the llamabot.bot.chatbot module:
from llamabot.bot.chatbot import ChatBot
  1. Create an instance of the ChatBot class by providing the required parameters such as the system prompt, session name, and any additional configuration options:
system_prompt = "Your system prompt here"
session_name = "Your session name here"
chatbot = ChatBot(system_prompt, session_name)
  1. Interact with the ChatBot instance by calling it with a human message:
human_message = "Hello, how are you?"
response = chatbot(human_message)
print(response)

Serving a Panel App Based on the ChatBot Class

To serve a Panel app based on the ChatBot class, you can use the stream_panel method of the ChatBot class. Here's an example of how to do this:

panel_app = chatbot.stream_panel(messages)
panel_app.servable()

ChatBot Retrieval and API Composition

When composing an API call using the ChatBot class, the retrieval of messages from history is handled internally. The retrieve method of the ChatBot class is used to retrieve messages from the chat history based on the provided human message and response budget. The retrieved messages include the system prompt, historical messages, and the human message itself.

For example, when making an API call to the ChatBot instance, the retrieval process ensures that the historical context is considered when generating the response.

This covers the specific details on how the ChatBot retrieval works when composing an API call.

Please let me know if you need further details or examples.