RunnableBinding

Wrap a Runnable with additional functionality.

A RunnableBinding can be thought of as a "runnable decorator" that preserves the essential features of Runnable; i.e., batching, streaming, and async support, while adding additional functionality.

Any class that inherits from Runnable can be bound to a RunnableBinding. Runnables expose a standard set of methods for creating RunnableBindings or sub-classes of RunnableBindings (e.g., RunnableRetry, RunnableWithFallbacks) that add additional functionality.

These methods include:

• bind: Bind kwargs to pass to the underlying Runnable when running it.
• with_config: Bind config to pass to the underlying Runnable when running it.
• with_listeners: Bind lifecycle listeners to the underlying Runnable.
• with_types: Override the input and output types of the underlying Runnable.
• with_retry: Bind a retry policy to the underlying Runnable.
• with_fallbacks: Bind a fallback policy to the underlying Runnable.

Example: bind: Bind kwargs to pass to the underlying Runnable when running it.

# Create a Runnable binding that invokes the chat model with the
# additional kwarg `stop=['-']` when running it.
from langchain_openai import ChatOpenAI

model = ChatOpenAI()
model.invoke('Say "Parrot-MAGIC"', stop=["-"])  # Should return `Parrot`
# Using it the easy way via `bind` method which returns a new
# RunnableBinding
runnable_binding = model.bind(stop=["-"])
runnable_binding.invoke('Say "Parrot-MAGIC"')  # Should return `Parrot`

Can also be done by instantiating a RunnableBinding directly (not recommended):

from langchain_core.runnables import RunnableBinding

runnable_binding = RunnableBinding(
    bound=model,
    kwargs={"stop": ["-"]},  # <-- Note the additional kwargs
)
runnable_binding.invoke('Say "Parrot-MAGIC"')  # Should return `Parrot`