OpenAIConversation

Overview

OpenAIConversation is a module provided by Automata’s OpenAI lower level model(LLM) providers. It represents a conversation with the OpenAI API. It holds a list of messages as an instance variable and provides methods to interact with this list of messages such as adding a message, getting messages for the next completion, getting the latest message, and resetting the conversation.

Main properties and methods of the OpenAIConversation include:

• messages: A list that contains all the messages in the current conversation.

• add_message(message: LLMChatMessage, session_id: Optional[str]) -> None: This method adds message to the conversation.

• get_messages_for_next_completion() -> List[Dict[str, Any]]: This method provides a list of all messages in the current conversation prepared for the next completion.

• get_latest_message() -> LLMChatMessage: This method returns the latest message in the conversation.

• reset_conversation() -> None: This method empties the list of messages, thus resetting the conversation.

Related Symbols

• automata.llm.providers.openai_llm.LLMChatMessage

• automata.llm.providers.openai_llm.OpenAIChatMessage

• automata.llm.providers.openai_llm.OpenAIIncorrectMessageTypeError

Example

Below is a simple usage example of how to interact with the OpenAI API using the OpenAIConversation class.

from automata.llm.providers.openai_llm import OpenAIConversation, OpenAIChatMessage

# Initialize the OpenAIConversation object.
conversation = OpenAIConversation()

# Create a message.
message = OpenAIChatMessage("Hello, OpenAI!")

# Add the message to the conversation.
conversation.add_message(message, None)

# Fetch the latest message in the conversation.
latest_message = conversation.get_latest_message()
print(latest_message) # Output: <LLMChatMessage: Hello, OpenAI!>

# Reset the conversation.
conversation.reset_conversation()

Limitations

A significant limitation of the OpenAIConversation class is the lack of support for asynchronous operations. All operations are performed synchronously which can lead to blocking of the entire application if the operations are time-consuming, like in a live chat implementation.

Another limitation is that the conversation is stateful. Once a message is added to the conversation, it cannot be removed. This makes it difficult to manage long conversations. While there is a method to reset the entire conversation (reset_conversation), there’s no way to manipulate individual messages within the conversation.

Follow-up Questions:

• Is there a way to support asynchronous operations with OpenAIConversation?

• Can there be methods incorporated to manage (add or remove) individual messages within the conversation?

• How can the OpenAIConversation handle much larger conversations?