Abstract
Abstract
lc_A path to the module that contains the class, eg. ["langchain", "llms"] Usually should be the same as the entrypoint the class is exported from.
A map of aliases for constructor args. Keys are the attribute names, e.g. "foo". Values are the alias that will replace the key in serialization. This is used to eg. make argument names match Python.
A map of additional attributes to merge with constructor args. Keys are the attribute names, e.g. "foo". Values are the attribute values, which will be serialized. These attributes need to be accepted by the constructor as arguments.
The final serialized identifier for the module.
A map of secrets, which will be omitted from serialization. Keys are paths to the secret in constructor args, e.g. "foo.bar.baz". Values are the secret ids, which will be used when deserializing.
Abstract
_agentConstruct a scratchpad to let the agent continue its thought process
Abstract
llmAbstract
observationDecide 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 a prompt for this class
List of tools the agent will have access to, used to format the prompt.
Optional
_fields: Record<string, any>Additional fields used to format the prompt.
A PromptTemplate assembled from the given tools and fields.
Static
deserializeStatic
fromLLMAndConstruct an agent from an LLM and a list of tools
Optional
_args: AgentArgsStatic
getGet the default output parser for this agent.
Optional
_fields: OutputParserArgsStatic
lc_Static
validateValidate that appropriate tools are passed in
Generated using TypeDoc
Class responsible for calling a language model and deciding an action.
Remarks
This is driven by an LLMChain. The prompt in the LLMChain must include a variable called "agent_scratchpad" where the agent can put its intermediary work.