---
title: Question and Answer Chain node common issues
description: Documentation for common issues and questions in the Question and Answer Chain node in n8n, a workflow automation platform. Includes details of the issue and suggested solutions.
contentType: [integration, reference]
priority: high
---

# Question and Answer Chain node common issues

Here are some common errors and issues with the [Question and Answer Chain node](/08-0-0-Workflow/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainretrievalqa/index.md) and steps to resolve or troubleshoot them.

## No prompt specified error

This error displays when the **Prompt** is empty or invalid.

You might see this in one of two scenarios:

1. When you've set the **Prompt** to **Define below** and have an expression in your **Text** that isn't generating a value.
    * To resolve, enter a valid prompt in the **Text** field.
    * Make sure any expressions reference valid fields and that they resolve to valid input rather than null.
2. When you've set the **Prompt** to **Connected Chat Trigger Node** and the incoming data has null values.
    * To resolve, make sure your input contains a `chatInput` field. Add an [Edit Fields (Set)](/08-0-0-Workflow/integrations/builtin/core-nodes/n8n-nodes-base.set.md) node to edit an incoming field name to `chatInput`.
    * Remove any null values from the `chatInput` field of the input node.

<!-- vale from-write-good.Passive = NO -->
## A Retriever sub-node must be connected error
<!-- vale from-write-good.Passive = YES -->

This error displays when n8n tries to execute the node without having a Retriever connected.

To resolve this, click the + Retriever button at the bottom of your screen when the node is open, or click the Retriever + connector when the node isn't open. n8n will then open a selection of possible Retrievers to pick from.

## Can't produce longer responses

If you need to generate longer responses than the Question and Answer Chain node produces by default, you can try one or more of the following techniques:

* **Connect a more verbose model**: Some AI models produce more terse results than others. Swapping your model for one with a larger context window and more verbose output can increase the word length of your responses.
* **Increase the maximum number of tokens**: Many model nodes (for example the [OpenAI Chat Model](/08-0-0-Workflow/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatopenai/index.md#maximum-number-of-tokens)) include a **Maximum Number of Tokens** option. You can set this to increase the maximum number of tokens the model can use to produce a response.
* **Build larger responses in stages**: For more detailed answers, you may want to construct replies in stages using a variety of AI nodes. You can use AI split up a single question into multiple prompts and create responses for each. You can then compose a final reply by combining the responses again. Though the details are different, you can find a good example of the general idea in this [template for writing a WordPress post with AI](https://n8n.io/workflows/2187-write-a-wordpress-post-with-ai-starting-from-a-few-keywords/).