LLMChatCompletionProvider

LLMChatCompletionProvider is an abstract base class used to structure different types of Language Learning Model (LLM) chat completion providers. The class contains four essential methods that should be implemented by any subclass. These methods include adding new chat messages and retrieving the next assistant’s completion from a chat provider. Additionally, the chat provider can be reset, and it can operate as a standalone output supplier for the LLM.

Its main function is to form the fundamental structure for various chat completion providers in the LLM by standardizing their core methods.

Overview

The LLMChatCompletionProvider class provides a blueprint for LLM chat completion providers. It comprises two primary operations – sending and receiving messages from the chat provider and managing the chat session. This is especially crucial in controlling the flow of data in and out of the chat provider, paired with the functionality to control and manipulate the chat buffer.

Related Symbols

• LLMChatMessage: This is a base class for different types of chat messages that are used by LLM and can be provided to the LLMChatCompletionProvider to add new messages to the chat buffer.

• LLMCompletionResult: This provides the structure for different types of completion results received from the LLMChatCompletionProvider.

• OpenAIChatCompletionProvider: This is a subclass of LLMChatCompletionProvider that uses the OpenAI API to provide chat messages. This class has implemented the abstract methods of the LLMChatCompletionProvider and can operate as functional completion provider.

Example

As LLMChatCompletionProvider is an abstract base class, you cannot instantiate it or use it as is. Instead, you use subclasses of LLMChatCompletionProvider that have implemented the abstract methods. One such subclass is OpenAIChatCompletionProvider. Below is an example of how to use it:

from automata.llm.providers.openai import OpenAIChatCompletionProvider
from automata.llm.foundation import LLMChatMessage

provider = OpenAIChatCompletionProvider()

# Add a new message to the provider's buffer
provider.add_message(LLMChatMessage(content="Hello World", channel="general"))

# Get the next assistant completion from the LLM.
next_message = provider.get_next_assistant_completion()
print(next_message.content)  # Prints the content of the next assistant completion message

Limitations

The LLMChatCompletionProvider only provides an abstract structure and does not implement the methods which limits its direct usage. Subclasses are required to implement the where necessary for interacting with different LLM chat completion providers.

It also assumes that a unique message can be added to the provider’s buffer and that the provider can be queried for the next assistant completion at any time. This may not align with the actual behavior of all chat completion providers.

Follow-up Questions

• Can this class be refactored further for more versatile usage?