Class: ZeroShotAgent

agents.ZeroShotAgent

Agent for the MRKL chain.

Hierarchy

• Agent

  ↳ ZeroShotAgent

Constructors

constructor

• new ZeroShotAgent(input)

Parameters

Name	Type
input	AgentInput

Overrides

Agent.constructor

Defined in

langchain/src/agents/mrkl/index.ts:32

Properties

llmChain

• llmChain: LLMChain

Inherited from

Agent.llmChain

Defined in

langchain/src/agents/agent.ts:158

Accessors

allowedTools

• get allowedTools(): undefined | string[]

Returns

undefined | string[]

Inherited from

Agent.allowedTools

Defined in

langchain/src/agents/agent.ts:162

---

inputKeys

• get inputKeys(): string[]

Returns

string[]

Inherited from

Agent.inputKeys

Defined in

langchain/src/agents/agent.ts:166

---

returnValues

• get returnValues(): string[]

Returns

string[]

Inherited from

Agent.returnValues

Defined in

langchain/src/agents/agent.ts:31

Methods

_agentType

▸ _agentType(): "zero-shot-react-description"

Return the string type key uniquely identifying this class of agent.

Returns

"zero-shot-react-description"

Overrides

Agent._agentType

Defined in

langchain/src/agents/mrkl/index.ts:36

---

_stop

▸ _stop(): string[]

Returns

string[]

Inherited from

Agent._stop

Defined in

langchain/src/agents/agent.ts:231

---

constructScratchPad

▸ constructScratchPad(steps): string | BaseChatMessage[]

Construct a scratchpad to let the agent continue its thought process

Parameters

Name	Type
steps	AgentStep[]

Returns

string | BaseChatMessage[]

Inherited from

Agent.constructScratchPad

Defined in

langchain/src/agents/agent.ts:245

---

extractToolAndInput

▸ extractToolAndInput(text): Promise<null | { input: string ; tool: string }>

Extract tool and tool input from LLM output.

Parameters

Name	Type
text	string

Returns

Promise<null | { input: string ; tool: string }>

Overrides

Agent.extractToolAndInput

Defined in

langchain/src/agents/mrkl/index.ts:100

---

finishToolName

▸ finishToolName(): string

Name of tool to use to terminate the chain.

Returns

string

Inherited from

Agent.finishToolName

Defined in

langchain/src/agents/agent.ts:238

---

llmPrefix

▸ llmPrefix(): string

Prefix to append the LLM call with.

Returns

string

Overrides

Agent.llmPrefix

Defined in

langchain/src/agents/mrkl/index.ts:44

---

observationPrefix

▸ observationPrefix(): string

Prefix to append the observation with.

Returns

string

Overrides

Agent.observationPrefix

Defined in

langchain/src/agents/mrkl/index.ts:40

---

plan

▸ plan(steps, inputs): Promise<AgentAction | AgentFinish>

Decide what to do given some input.

Parameters

Name	Type	Description
steps	AgentStep[]	Steps the LLM has taken so far, along with observations from each.
inputs	ChainValues	User inputs.

Returns

Promise<AgentAction | AgentFinish>

Action specifying what tool to use.

Inherited from

Agent.plan

Defined in

langchain/src/agents/agent.ts:297

---

prepareForOutput

▸ prepareForOutput(_returnValues, _steps): Promise<Record<string, any>>

Prepare the agent for output, if needed

Parameters

Name	Type
_returnValues	Record<string, any>
_steps	AgentStep[]

Returns

Promise<Record<string, any>>

Inherited from

Agent.prepareForOutput

Defined in

langchain/src/agents/agent.ts:67

---

returnStoppedResponse

▸ returnStoppedResponse(earlyStoppingMethod, steps, inputs): Promise<AgentFinish>

Return response when agent has been stopped due to max iterations

Parameters

Name	Type
earlyStoppingMethod	StoppingMethod
steps	AgentStep[]
inputs	ChainValues

Returns

Promise<AgentFinish>

Inherited from

Agent.returnStoppedResponse

Defined in

langchain/src/agents/agent.ts:307

---

createPrompt

▸ Static createPrompt(tools, args?): PromptTemplate

Create prompt in the style of the zero shot agent.

Parameters

Name	Type	Description
tools	Tool[]	List of tools the agent will have access to, used to format the prompt.
args?	CreatePromptArgs	Arguments to create the prompt with.

Returns

PromptTemplate

Overrides

Agent.createPrompt

Defined in

langchain/src/agents/mrkl/index.ts:67

---

deserialize

▸ Static deserialize(data): Promise<ZeroShotAgent>

Load an agent from a json-like object describing it.

Parameters

Name	Type
data	Object

Returns

Promise<ZeroShotAgent>

Overrides

Agent.deserialize

Defined in

langchain/src/agents/mrkl/index.ts:120

---

fromLLMAndTools

▸ Static fromLLMAndTools(llm, tools, args?): ZeroShotAgent

Construct an agent from an LLM and a list of tools

Parameters

Name	Type
llm	BaseLanguageModel
tools	Tool[]
args?	CreatePromptArgs

Returns

ZeroShotAgent

Overrides

Agent.fromLLMAndTools

Defined in

langchain/src/agents/mrkl/index.ts:86

---

validateTools

▸ Static validateTools(tools): void

Validate that appropriate tools are passed in

Parameters

Name	Type
tools	Tool[]

Returns

void

Overrides

Agent.validateTools

Defined in

langchain/src/agents/mrkl/index.ts:48