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InfoRetriever

What is it?

The InfoRetriever uses Retrieval Augmented Generation or "RAG" capabilities to your workflows. Think of it as a smart researcher that can find and use relevant information to enhance AI responses.

When would I use it?

Use this node when you want to:

  • Ground AI responses in your own data sources
  • Enable agents to access and reference specific information
  • Improve response accuracy with relevant context
  • Connect knowledge bases to your conversational agents

How to use it

Basic Setup

  1. Add the InfoRetriever to your workflow
  2. Connect its output to nodes that need RAG capabilities (like an Agent)

Parameters

  • description: A description of what information this tool provides (default is "Contains information")
  • off_prompt: Whether to run RAG operations outside the main prompt (default is true)
  • rag_engine: The engine used to retrieve information (required)

Outputs

  • tool: The configured RAG tool that other nodes can use
  • rules: The ruleset used by the RAG tool

Example

Imagine you want to create an agent that can answer questions using your company documentation:

  1. Add an InfoRetriever to your workflow
  2. Connect a vector store containing your documentation to the "rag_engine" input
  3. Connect the "tool" output to an Agent's "tools" input
  4. Now that agent can retrieve and reference specific information from your documentation when answering questions