langchain_core.runnables.base.Runnable¶
class langchain_core.runnables.base.Runnable[source]¶
A unit of work that can be invoked, batched, streamed, transformed and composed.
invoke/ainvoke: Transforms a single input into an output.
batch/abatch: Efficiently transforms multiple inputs into outputs.
stream/astream: Streams output from a single input as it’s produced.
astream_log: Streams output and selected intermediate results from an input.
Built-in optimizations:
Batch: By default, batch runs invoke() in parallel using a thread pool executor.Override to optimize batching.
Async: Methods with “a” suffix are asynchronous. By default, they executethe sync counterpart using asyncio’s thread pool.
Override for native async.
All methods accept an optional config argument, which can be used to configure
execution, add tags and metadata for tracing and debugging etc.
Runnables expose schematic information about their input, output and config via
the input_schema property, the output_schema property and config_schema method.
The LangChain Expression Language (LCEL) is a declarative way to compose Runnables
into chains. Any chain constructed this way will automatically have sync, async,
batch, and streaming support.
The main composition primitives are RunnableSequence and RunnableParallel.
RunnableSequence invokes a series of runnables sequentially, with one runnable’s
output serving as the next’s input. Construct using the | operator or by
passing a list of runnables to RunnableSequence.
RunnableParallel invokes runnables concurrently, providing the same input
to each. Construct it using a dict literal within a sequence or by passing a
dict to RunnableParallel.
For example,
from langchain_core.runnables import RunnableLambda
# A RunnableSequence constructed using the `|` operator