In addition to the general instructions for using an agent,
this page describes features that are specific to AG2Agent
.
Before you begin
This tutorial assumes that you have read and followed the instructions in:
- Develop an AG2 agent: to develop
agent
as an instance ofAG2Agent
. - User authentication to authenticate as a user for querying the agent.
Supported operations
The following operations are supported for AG2Agent
:
query
: for getting a response to a query synchronously.
The query
method support the arguments:
input
: the message to be sent to the agent.max_turns
: the maximum number of conversation turns allowed. When using tools, a minimum ofmax_turns=2
is required: one turn to generate tool arguments and a second to execute the tool.
Query the agent
The query()
method provides a simplified way to interact with the agent. A typical call looks like this:
response = agent.query(input="What is the exchange rate from US dollars to Swedish currency?", max_turns=2)
This method handles the underlying communication with the agent and returns the agent's final response as a dictionary. It is equivalent to the following (in full form):
from autogen import ConversableAgent
import dataclasses
import json
input_message: str = "What is the exchange rate from US dollars to Swedish currency?"
max_turns: int = 2
with agent._runnable._create_or_get_executor(
tools=agent._ag2_tool_objects, # Use the agent's existing tools
agent_name="user", # Default
agent_human_input_mode="NEVER", # query() enforces this
) as executor:
chat_result = executor.initiate_chat(
agent._runnable,
message=input_message,
max_turns=max_turns,
clear_history=False, # Default
summary_method="last_msg" # Default
)
response = json.loads(
json.dumps(dataclasses.asdict(chat_result)) # query() does this conversion
)
You can customize the agent's behavior beyond input
and max_turns
by passing additional keyword arguments to query()
.
response = agent.query(
input="What is the exchange rate from US dollars to Swedish currency?",
max_turns=2,
msg_to="user" # Start the conversation with the "user" agent
)
print(response)
See the ConversableAgent.run
documentation for a complete list of available parameters. However, keep in mind that user_input
will always be overridden to False
by the AG2Agent template.