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Question and Answer Chain#

Use the Question and Answer Chain node to use a vector store as a retriever.

On this page, you'll find the node parameters for the Question and Answer Chain node, and links to more resources.

Node parameters#

Query#

The question you want to ask.

Templates and examples#

Ask questions about a PDF using AI

by David Roberts

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AI Crew to Automate Fundamental Stock Analysis - Q&A Workflow

by Derek Cheung

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Advanced AI Demo (Presented at AI Developers #14 meetup)

by Max Tkacz

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Browse Question and Answer Chain integration templates, or search all templates

Refer to LangChain's documentation on retrieval chains for examples of how LangChain can use a vector store as a retriever.

View n8n's Advanced AI documentation.

  • completion: Completions are the responses generated by a model like GPT.
  • hallucinations: Hallucination in AI is when an LLM (large language model) mistakenly perceives patterns or objects that don't exist.
  • vector database: A vector database stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.
  • vector store: A vector store, or vector database, stores mathematical representations of information. Use with embeddings and retrievers to create a database that your AI can access when answering questions.