This node combines an agent with a set of tools and prompts it with a user provided prompt and the conversation history in the input table.
The conversation table is expected to have at least two string columns that define previous conversation. It can be empty if this is the start of the conversation.
The agent always receives the full conversation table as context which can slow down agent execution for long conversations or even lead to execution failures if the context becomes too large for the underlying LLM. If you experience such issues, you can truncate the conversation table by only keeping the last few messages, or even use a large language model to create a summary of the conversation held so far.