data_juicer_agents.core.agent_factory module#

Agent Factory

Factory functions for creating and configuring agents with standardized toolkits.

data_juicer_agents.core.agent_factory.get_default_model() → OpenAIChatModel[source]#

Create default OpenAI model instance.

data_juicer_agents.core.agent_factory.create_agent(name: str, sys_prompt: str, toolkit: Toolkit, description: str | None = None, model: ChatModelBase | None = None, formatter: FormatterBase | None = None, memory: MemoryBase | None = None, max_iters: int = 10, parallel_tool_calls: bool = False, **kwargs) → ReActAgent[source]#

Create a ReActAgent with standardized configuration.

Parameters:

  • name – Agent identifier

  • sys_prompt – System prompt template (supports {name} placeholder)

  • toolkit – Toolkit instance

  • model – Language model (defaults to GPT-4o)

  • formatter – Message formatter (defaults to OpenAIChatFormatter)

  • memory – Memory instance (defaults to InMemoryMemory)

  • max_iters – Maximum reasoning iterations

  • parallel_tool_calls – Enable parallel tool execution

  • **kwargs – Additional ReActAgent arguments

Returns:

Configured ReActAgent instance

Example

>>> agent = create_agent(
...     name="sql_expert",
...     sys_prompt="You are {name}, a SQL database expert",
...     tools=sql_tools
... )