What is State in Langgraph

In LangGraph, State is a fundamental concept that represents the data being passed and transformed through nodes in the workflow. It acts as a shared data container for the graph, enabling nodes to read from and write to it during execution.

Breaking Down the Example

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class State(TypedDict):

    # The operator.add reducer fn makes this append-only

    messages: Annotated[list, operator.add]

1. TypedDict

State is a subclass of Python's TypedDict. This allows you to define the expected structure (keys and types) of the state dictionary in a strongly typed manner.

Here, the state has one key, messages, which is a list.

2. Annotated

Annotated is a way to add metadata to a type. In this case:

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Annotated[list, operator.add]

It indicates that messages is a list.

The operator.add is used as a reducer function.

3. operator.add

operator.add is a Python function that performs addition for numbers or concatenation for lists.

In this context, it is used as a reducer function for the messages list.

4. Reducer Function Behavior

A reducer function specifies how new values should be combined with the existing state during updates.

By using operator.add, the messages list becomes append-only, meaning any new items added to messages will concatenate with the current list instead of replacing it.

Why Use operator.add in State?

Append-Only Behavior:

Each node in the workflow can add to the messages list without overwriting previous values. This is useful for:

Logging messages from different nodes.

Maintaining a sequential record of events.

Thread Safety:

Using a reducer function ensures that state updates are predictable and consistent, even in concurrent workflows.

Flexibility in State Updates:

Reducer functions allow complex operations during state updates, such as appending, merging dictionaries, or performing custom logic.

references:

OpenAI