📖 AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge
⚡ 8,600 views · 📖 Internal Wiki & Knowledge Base
Description
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
bodynamefield. - 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:
🔗 Nodes Used
AI Agent, OpenAI Chat Model, Simple Memory, Chat Trigger
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File