Retrieve answers from Knowledge Base with InfraNodus GraphRAG chatbot

Basic AI Chatbot that Retrieves Answers From Knowledge Base Using GraphRAG.

Easiest setup, without vector database, external knowledge base, or OpenAI API keys. All you need is an [InfraNodus graph](https://infranodus.com) with your knowledge.

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In this workflow, user sends a request to the [InfraNodus GraphRAG system](https://infranodus.com/docs/graph-rag-knowledge-graph) that will extract a reasoning ontology from a graph that you create (or that you can copy from our [repository of public graphs](https://infranodus.com/knowledge-graphs)) and generate a response directly to the user.


How it works

1. Receives a request from a user (via n8n or a publicly available URL chat bot if you replace the Chat Trigger with a webhook connected to the embeddable [n8n Chat Widget](https://n8n-chat-widget.com) that you can expose via a URL or add to any website. 2. Sends the request to the knowledge graph in your InfraNodus account that contains a [reasoning ontology represented as a knowledge graph](https://support.noduslabs.com/hc/en-us/articles/24079266183196-Building-Expert-Ontology-for-InfraNodus-GraphRAG-n8n-Expert-Node). You can also use a standard graph — InfraNodus will use its underlying GraphRAG technology to generate the most relevant response. 3. Sends the answer back to the user via chat or webhook (which is then delivered back via [n8n chat widget](https://n8n-chat-widget.com)

Note: This is a simple example that will work well for occasionally providing responses to users. For a more advanced setup, you might want to build a more sophisticated workflow with AI agent node that would orchestrate among different InfraNodus expert graphs and chat memory, so the context of the conversation can be maintained. See our other workflows for examples.