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AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

Using the knowledge graphs instead of RAG vector stores This workflow creates an AI chatbot agent that has access to several knowledge bases at the same time (used as "experts"). These knowledge ba...

Best for

  • Internal Wiki automation workflows
  • AI RAG automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.httprequesttool

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by InfraNodus.

Original n8n.io source

1.1 Workflow description

Title
AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge
Workflow name
AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge

Using the knowledge graphs instead of RAG vector stores

This workflow creates an AI chatbot agent that has access to several knowledge bases at the same time (used as "experts").

These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows.

The advantages of using GraphRAG instead of the standard vector stores for knowledge are:

  • Easy and quick to set up (no complex data import workflows needed)
  • A knowledge graph has a holistic view of your knowledge base
  • Better retrieval of relations between the document chunks = higher quality responses

How it works

This template uses the n8n AI agent node as an orchestrating agent that decides which tool (knowledge graph) to use based on the user's prompt.

Here's a description step by step:

  • The user submits a question using the AI chatbot (n8n interface, in this case, which can be accessed via a URL or embedded to any website)
  • The AI agent node checks a list of tools it has access to. Each tool has a description of the knowledge it has auto-generated by InfraNodus.
  • The AI agent decides which tool should be used to generate a response. It may reformulate user's query to be more suitable for the expert.
  • The query is then sent to the InfraNodus HTTP node endpoint, which will query the graph that corresponds to that expert.
  • Each InfraNodus GraphRAG expert provides a rich response that takes the whole context into account and provides a response from each expert (graph) along with a list of relevant statements retrieved using a combination or RAG and GraphRAG.
  • The n8n AI Agent node integrates the responses received from the experts to produce the final answer.
  • The final answer is sent back to the user's chat (or a webhook endpoint)

How to use

You need an InfraNodus GraphRAG API account and key to use this workflow.

  • Create an InfraNodus account
  • Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes.
  • Create a separate knowledge graph for each expert (using PDF / content import options) in InfraNodus
  • For each graph, go to the workflow, paste the name of the graph into the body name field.
  • Keep other settings intact or learn more about them at the InfraNodus access points page.
  • Once you add one or more graphs as experts to your flow, add the LLM key to the OpenAI node and launch the workflow

Requirements

  • An InfraNodus account and API key
  • An OpenAI (or any other LLM) API key

Customizing this workflow

You can use this same workflow with a Telegram bot, so you can interact with it using Telegram. There are many more customizations available.

Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n

Also check out the video tutorial with a demo:

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Simple Memory

Type / Role
@n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices
Version 1.3

Block 2 - When chat message received

Type / Role
@n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices
Version 1.1

Block 3 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 4 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 5 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 6 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 7 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 8 - Sticky Note6

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 9 - Sticky Note7

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 10 - AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 1.9

Block 11 - OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 12 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 13 - EightOS Expert

Type / Role
n8n-nodes-base.httpRequestTool - httpRequestTool
Config choices
Version 4.2

Block 14 - Polysingularity Expert

Type / Role
n8n-nodes-base.httpRequestTool - httpRequestTool
Config choices
Version 4.2

3. Summary Table

Workflow AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge
Complexity intermediate
Nodes 14
Categories Internal Wiki, AI RAG
Author InfraNodus
Published 26 May 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/4402/4402.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge do?

Using the knowledge graphs instead of RAG vector stores This workflow creates an AI chatbot agent that has access to several knowledge bases at the same time (used as "experts"). These knowledge ba...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Internal Wiki, AI RAG use case.