How to

📄️ Bind runtime args

Sometimes we want to invoke a Runnable within a Runnable sequence with constant arguments that are not part of the output of the preceding Runnable in the sequence, and which are not part of the user input. We can use Runnable.bind() to easily pass these arguments in.

📄️ Add fallbacks

There are many possible points of failure in an LLM application, whether that be issues with LLM API's, poor model outputs, issues with other integrations, etc. Fallbacks help you gracefully handle and isolate these issues.

📄️ Run arbitrary functions

You can use arbitrary functions in the pipeline

📄️ Use RunnableMaps

RunnableMaps make it easy to execute multiple Runnables in parallel, and to return the output of these Runnables as a map.

📄️ Route between multiple Runnables

This notebook covers how to do routing in the LangChain Expression Language.