Question

A Generative AI Engineer is building a RAG chain with LangChain Expression Language (LCEL) on Databricks. They have a retriever that returns a list of Document objects and a ChatPromptTemplate that expects a single string variable named 'context'. When they wire the retriever output directly into the prompt template, the model receives a raw list of Document objects instead of clean text, producing malformed prompts. What is the most appropriate way to fix this in the LCEL chain?

Accepted Answer

Insert a RunnableLambda (or format function) between the retriever and the prompt that joins the page_content of each Document into a single formatted string assigned to 'context'.

Answer

Change the ChatPromptTemplate to accept a list variable and let LangChain automatically serialize the Document objects to text.

Answer

Increase the retriever's k value so that fewer Documents are returned and the prompt fits in the context window.

Answer

Replace the ChatPromptTemplate with a PromptTemplate, which natively converts Document objects to strings before injection.