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agenthub.monologue_agent.agent

MonologueAgent Objects​

class MonologueAgent(Agent)

The Monologue Agent utilizes long and short term memory to complete tasks. Long term memory is stored as a LongTermMemory object and the model uses it to search for examples from the past. Short term memory is stored as a Monologue object and the model can condense it as necessary.

__init__​

def __init__(llm: LLM)

Initializes the Monologue Agent with an llm, monologue, and memory.

Arguments:

  • llm (LLM): The llm to be used by this agent

step​

def step(state: State) -> Action

Modifies the current state by adding the most recent actions and observations, then prompts the model to think about it's next action to take using monologue, memory, and hint.

Arguments:

  • state (State): The current state based on previous steps taken

Returns:

  • Action: The next action to take based on LLM response

search_memory​

def search_memory(query: str) -> List[str]

Uses VectorIndexRetriever to find related memories within the long term memory. Uses search to produce top 10 results.

Arguments:

  • query (str): The query that we want to find related memories for

Returns:

  • List[str]: A list of top 10 text results that matched the query