Optional memoryRun the core logic of this chain and add to output if desired.
Wraps _call and handles memory.
Optional config: BaseCallbackConfig | CallbacksOptional tags: string[]Invoke the chain with the provided input and returns the output.
Input values for the chain run.
Optional config: BaseCallbackConfigOptional configuration for the Runnable.
Promise that resolves with the output of the chain run.
Return a json-like object representing this chain.
Static deserializeLoad a chain from a json-like object describing it.
Static fromLLMAndStatic method that creates a new PlanAndExecuteAgentExecutor from a given LLM, a set of tools, and optionally a human message template. It uses the getDefaultPlanner and getDefaultStepExecutor methods to create the planner and step executor for the new agent executor.
A new PlanAndExecuteAgentExecutor instance.
Static getStatic method that returns a default planner for the agent. It creates a new LLMChain with a given LLM and a fixed prompt, and uses it to create a new LLMPlanner with a PlanOutputParser.
The Large Language Model (LLM) used to generate responses.
A new LLMPlanner instance.
Static getStatic method that returns a default step executor for the agent. It creates a new ChatAgent from a given LLM and a set of tools, and uses it to create a new ChainStepExecutor.
Optional humanA new ChainStepExecutor instance.
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Class representing a plan-and-execute agent executor. This agent decides on the full sequence of actions upfront, then executes them all without updating the plan. This is suitable for complex or long-running tasks that require maintaining long-term objectives and focus.