class langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.AgentState[source][source]

Bases: MessagesState

State for Knowledge Base agent.

remaining_steps: Annotated[int, RemainingStepsManager]
retrieved_documents: list[dict[str, Any]]
kb_documents: str
__init__(*args, **kwargs)
clear() → None.  Remove all items from D.
copy() → a shallow copy of D
classmethod fromkeys(iterable, value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items
keys() → a set-like object providing a view on D's keys
pop(k[, d]) → v, remove specified key and return the corresponding value.

If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None.  Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values
messages: _add_messages at 0x7f79ec099e40>]
langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.get_kb_retriever()[source][source]

Create and return a Knowledge Base retriever instance.

langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.wrap_model(model)[source][source]

Wrap the model with a system prompt for the Knowledge Base agent.

Parameters:

model (BaseChatModel)

Return type:

RunnableSerializable[AgentState, AIMessage]

async langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.retrieve_documents(state, config)[source][source]

Retrieve relevant documents from the knowledge base.

Parameters:
Return type:

AgentState

async langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.prepare_augmented_prompt(state, config)[source][source]

Prepare a prompt augmented with retrieved document content.

Parameters:
Return type:

AgentState

async langgraph_agent_toolkit.agents.blueprints.knowledge_base_agent.agent.acall_model(state, config)[source][source]

Generate a response based on the retrieved documents.

Parameters:
Return type:

AgentState