lobsang 0.0.5

A simple framework to interact with conversational LLMs

Lobsang

Welcome to Lobsang 🧘‍♂️

Lobsang is a framework to interact with conversational LLMs in the simplest way possible.
It's easy to get started, yet designed to scale up to complex use cases. Enjoy the ride! 🚀

Note: This project is still in early development. Expect breaking changes.

Installation

Requires Python 3.11 or higher.

pip install lobsang

Core Concepts

Lobsang is built around a few core concepts:

• Chat: The main class is the Chat class. It represents a conversation between a user and a LLM. It is the main entry point to the framework and stores the chat history for a single conversation. After creating a Chat instance, you can interact with it by calling itself with one or more messages:

  from lobsang import Chat
  from lobsang.llms import FakeLLM
  chat = Chat(llm=FakeLLM()) 
  #                 👆 FakeLLM returns dummy responses
  # Call the chat with one message
  chat("Hello!")
  chat("How are you?")
  print("Chat history:")  
  print(chat)
  
  # Call the chat with multiple messages
  res = chat.run(["What is 1+1?", "What is 2+2?"])
  print("Chat Snippet:")
  print(res)
  print("Full chat history:")
  print(chat)
  

  • Directives: Directives are used to guide the LLM to generate a specific response by embedding instructions in a corresponding message. For example, you can use the JSON directive to instruct the LLM to generate a JSON response (see examples/2_directives.ipynb for more details).

Examples

We provide a few examples to get you started. You can find them in the examples folder. The examples use the openai package, make sure to install it before running the examples (pip install openai). You will also need an OpenAI API key, which you can get here: https://platform.openai.com/account/api-keys.