Question

You are building a RAG chain with LangChain Expression Language (LCEL) on Databricks. Your chain retrieves context from a Vector Search index and formats a prompt that needs BOTH the retrieved context AND the user's original question. You write a retrieval step that takes the incoming question string, embeds it, and returns formatted document text. However, when you compose the chain, the prompt template's `{question}` variable ends up empty because the retriever consumed the input and only passed forward the document text. What is the most idiomatic LCEL construct to fix this so the prompt receives both the context and the original question?

Accepted Answer

Wrap the retrieval in a `RunnableParallel` (dict) that maps `context` to the retriever and `question` to `RunnablePassthrough()`, so both keys flow into the prompt.

Answer

Add a `RunnableLambda` after the prompt template that re-injects the question from a global variable captured at chain-build time.

Answer

Call the retriever with `.batch()` instead of `.invoke()` so it returns the question alongside the documents automatically.

Answer

Set `return_source_documents=True` on the retriever so the original question is preserved in the chain output metadata.