How to Optimize ChatGPT Knowledge Base using Graph RAG

We will be using an example where we will upload. a batch of research papers on GraphRAG to a ChatGPT workspace. Normally, we don't know what 's inside the files and so we don't know whether the model hallucinates or makes things up. We also don't know what questions to ask. To address these issues, we upload those files to InfraNodus and visualize them as a knowledge graph, which allows us to have a high-level overview of the main ideas in our knowledge base and also detect the structural gaps, which can be used to generate interesting research questions.

Timecodes:
0:00 Why you need to know your knowledge base?
1:13 How are we going to do that?
2:25 Analyzing Your ChatGPT Knowledge Base
4:30 How to enrich your knowledge base structure with more sources
6:28 Finding a topic to develop
8:53 Adding the research found into the knowledge base
10:27 Optimizing by removing the “obvious” ideas from the graph
14:07 Exploring peripheral ideas
16:12 Using the latent topics to augment ChatGPT prompts
17:15 Augmenting your AI Knowldege base with this generated insight
19:26 Adding instructions genated by InfraNodus to ChatGPT prompts
21:35 Generating interesting questions / prompts based on the blind spots in your knowledge base
23:25 Asking those questions to ChatGPT
26:01 Same approach with open-source OpenWebUI — same approach
27:23 Same approach with Dify for building agentic flows

#infranodus #chatgpt

[noduslabs]

Timecodes:
0:00 Why you need to know your knowledge base?
1:13 How are we going to do that?
2:25 Analyzing Your ChatGPT Knowledge Base
4:30 How to enrich your knowledge base structure with more sources
6:28 Finding a topic to develop
8:53 Adding the research found into the knowledge base
10:27 Optimizing by removing the “obvious” ideas from the graph
14:07 Exploring peripheral ideas
16:12 Using the latent topics to augment ChatGPT prompts
17:15 Augmenting your AI Knowldege base with this generated insight
19:26 Adding instructions genated by InfraNodus to ChatGPT prompts
21:35 Generating interesting questions / prompts based on the blind spots in your knowledge base
23:25 Asking those questions to ChatGPT
26:01 Same approach with open-source OpenWebUI — same approach
27:23 Same approach with Dify for building agentic flows

[crisgath]

Interesting project. For sensitive data, can this be self hosted? Thanks for sharing

[saitejasai]

how is the tool handling for inconsistencies in the input data? few papers might have mentioned a methodology like RAG and other might be doing it in Retrival Augmented Generation. wont the data be split among these 2 nodes where in really, all of them come under one umbrella?

[daspradeep]

no APIs to interact but using a KG for prompting?