Actions
Note

Actions are the core building block of Burr. They read from state and write to state. They can be synchronous and asynchonous, and have both a sync and async API. There are both function and class-based APIs.

Actions do the heavy-lifting in a workflow. They should contain all complex compute. You can define actions either through a class-based or function-based API. If actions implement async def run then will be run in an asynchronous context (and thus require one of the async application functions).

Actions have two primary responsibilities:

run – compute a result

update – modify the state

The run method should return a dictionary of the result and the update method should return the updated state, given the results of the run method. They declare their dependencies so the framework knows which state variables they read and write. This allows the framework to optimize the execution of the workflow. We call (1) a Function and (2) a Reducer (similar to Redux, if you’re familiar with frontend UI technology).

There are two APIs for defining actions: class-based and function-based. They are largely equivalent, but differ in use.

use the function-based API when you want to write something quick and terse that reads from a fixed set of state variables

use the class-based API when you want to leverage inheritance or parameterize the action in more powerful ways

Function-based actions
You can define actions by decorating a function with the @action decorator. These can return either just the updated state or a tuple of the result and the state. For example:

from burr.core import action, State

@action(reads=["var_from_state"], writes=["var_to_update"])
def custom_action(state: State) -> State:
    return state.update(var_to_update=state["var_from_state"] + 1)

app = ApplicationBuilder().with_actions(
    custom_action=custom_action
)...
Conceptually, these combine the update and run methods into a single function, and they’re both executed at the same time. You also have the option of returning the intermediate results, which is useful for tracking/debugging. The code above is equivalent to returning an empty dictionary instead of the results.

from burr.core import action, State

@action(reads=["var_from_state"], writes=["var_to_update"])
def custom_action(state: State) -> State
    return results, state.update(var_to_update=var_from_state + 1)

app = ApplicationBuilder().with_actions(
    custom_action=custom_action
)...
Function-based actions can take in parameters which are akin to passing in constructor parameters. This is done through the bind method:

@action(reads=["var_from_state"], writes=["var_to_update"])
def custom_action(state: State, increment_by: int) -> State:
    return state.update(var_to_update=state["var_from_state"] + increment_by)

app = ApplicationBuilder().with_actions(
    custom_action=custom_action.bind(increment_by=2)
)...
This is the same as functools.partial, but it is more explicit and easier to read. If an action has parameters that are not bound, they will be referred to as inputs. For example:

@action(reads=["var_from_state"], writes=["var_to_update"])
def custom_action(state: State, increment_by: int) -> State:
    return state.update(var_to_update=state["var_from_state"] + increment_by)

app = ApplicationBuilder().with_actions(
    custom_action=custom_action
)...
Will require the inputs to be passed in at runtime. See below for how to do that. You can use default values to set optional inputs as well:

@action(reads=["var_from_state"], writes=["var_to_update"])
def custom_action(state: State, increment_by: int = 1) -> State:
    result = {"var_to_update": state["var_from_state"] + increment_by}
    return state.update(var_to_update=state["var_from_state"] + increment_by)

app = ApplicationBuilder().with_actions(
    custom_action=custom_action
)...
This means that the application does not need the inputs to be set.

Class-Based Actions
You can define an action by implementing the Action class:

from burr.core import Action, State

class CustomAction(Action):
    @property
    def reads(self) -> list[str]:
        return ["var_from_state"]

    def run(self, state: State) -> dict:
        return {"var_to_update": state["var_from_state"] + 1}

    @property
    def writes(self) -> list[str]:
        return ["var_to_update"]

    def update(self, result: dict, state: State) -> State:
        return state.update(**result)
You then pass the action to the ApplicationBuilder:

from burr.core import ApplicationBuilder

app = ApplicationBuilder().with_actions(
    custom_action=CustomAction()
)...
Note that if the action has inputs, you have to define the optional inputs property:

from burr.core import Action, State

class CustomAction(Action):
    @property
    def reads(self) -> list[str]:
        return ["var_from_state"]

    def run(self, state: State, increment_by: int) -> dict:
        return {"var_to_update": state["var_from_state"] + increment_by}

    @property
    def writes(self) -> list[str]:
        return ["var_to_update"]

    def update(self, result: dict, state: State) -> State:
        return state.update(**result)

    @property
    def inputs(self) -> list[str]:
        return ["increment_by"]
See below for how to pass in inputs at runtime. If you want to use optional inputs with the class-based API, inputs will return a tuple of (required, optional) inputs. For example:

from burr.core import Action, State

class CustomAction(Action):
    ...
    def inputs(self) -> Tuple[list[str], list[str]]:
        return ["increment_by"], ["optional_input"]
Note your code will have to handle the case where optional_input is not passed in (e.g. by setting the appropriate kwargs to the run(…) method.

Refer to actions for more documentation.

Runtime Inputs
Actions can declare parameters that are not part of the state. Use this to:

Provide variables that can be bound to an action. E.g. API clients, DB clients, etc.

Provide inputs that are required as part of the application to function, e.g. human input, configuration, etc.

For example using the function based API, consider the following action:

@action(reads=["..."], writes=["..."])
def my_action(state: State, client: Client, prompt: str) -> State:
    """client & `prompt` here are something we need to pass in."""
    context = client.get_data(state["..."])
    result = llm_call(prompt, context) # some LLM call...
    return state.update(**result)
We need to pass in client and prompt somehow. Here are the ways to do that:

# (1) bind values
app = (
    ApplicationBuilder()
      # we can "bind" values to an action
      .with_actions(my_action=my_action.bind(client=client))
    ...
    .build()
)

# (2) pass them in at runtime
app.run( # or app.step, app.iterate, app.astep, etc.\n"
    halt_..., # your halt logic\n"
    inputs={"prompt": "this will be passed into `prompt`"} # <-- we pass in values here
)
For instance, say you have a chatbot. The first step will likely declare the input parameter prompt – it will take that, process it, and put the result in state. The subsequent steps will read the result of that from state.
