agent_optimizer
autogen.agentchat.contrib.agent_optimizer.AgentOptimizer
AgentOptimizer
Base class for optimizing AutoGen agents. Specifically, it is used to optimize the functions used in the agent. More information could be found in the following paper: https://arxiv.org/abs/2402.11359.
(These APIs are experimental and may change in the future.)
Parameters:Name | Description |
---|---|
max_actions_per_step | the maximum number of actions that the optimizer can take in one step. Type: int |
llm_config | llm inference configuration. Please refer to OpenAIWrapper.create for available options. When using OpenAI or Azure OpenAI endpoints, please specify a non-empty ‘model’ either in llm_config or in each config of ‘config_list’ in llm_config .Type: dict |
optimizer_model | the model used for the optimizer. Type: str | None Default: ‘gpt-4-1106-preview’ |
Instance Methods
record_one_conversation
Record one conversation history.
Parameters:Name | Description |
---|---|
conversation_history | the chat messages of the conversation. Type: list[dict] |
is_satisfied | whether the user is satisfied with the solution. If it is none, the user will be asked to input the satisfaction. Type: bool Default: None |
reset_optimizer
Reset the optimizer.
step
One step of training. It will return register_for_llm and register_for_executor at each iteration, which are subsequently utilized to update the assistant and executor agents, respectively. See example: https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_agentoptimizer.ipynb