Constructs the agent scratchpad based on the agent steps. It returns an array of base messages representing the thoughts of the agent.
The agent steps to construct the scratchpad from.
An array of base messages representing the thoughts of the agent.
Decide what to do given some input.
Steps the LLM has taken so far, along with observations from each.
User inputs.
Optional callbackManager: CallbackManagerCallback manager to use for this call.
Action specifying what tool to use.
Prepare the agent for output, if needed
Return response when agent has been stopped due to max iterations
Optional callbackManager: CallbackManagerStatic createCreate prompt in the style of the ChatConversationAgent.
List of tools the agent will have access to, used to format the prompt.
Optional args: ChatConversationalCreatePromptArgsArguments to create the prompt with.
Static deserializeStatic fromLLMAndCreates an instance of the ChatConversationalAgent class from a BaseLanguageModel and a set of tools. It takes optional arguments to customize the agent.
The BaseLanguageModel to create the agent from.
The set of tools to create the agent from.
Optional args: ChatConversationalCreatePromptArgs & AgentArgsOptional arguments to customize the agent.
An instance of the ChatConversationalAgent class.
Static getReturns the default output parser for the ChatConversationalAgent class. It takes optional fields as arguments to customize the output parser.
Optional fields: OutputParserArgs & { Optional fields to customize the output parser.
The default output parser for the ChatConversationalAgent class.
Static validateValidate that appropriate tools are passed in
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Agent for the MRKL chain.