Let’s say I want to ingest information from a series of interviews with multiple interviewees (multiple interviews per interviewee). It’s possible their opinions/facts change between interviews; but also each interviewee is going to have different opinions/facts.

Would it make most sense to capture this with multiple Graphiti graphs? Or would it be possible to do this in one graph?

At the end of the day the analysis would be finding insights across all interviewees and you want the cumulative knowledge…

Looks cool, would love support for RDF Graphs. The reason I prefer those is because the ontology is already well defined in a lot of cases which is 80% of the battle with Knowledge Graphs in my experience. Without a well defined Ontology I think LLM <> KG integration will not live up to its potential. LLMs have to know what nodes and edges really mean across diverse datasets

Hi :) Cool project! Just FYI, there is already a fairly well-established project with that name.

https://www.graphiti.dev

Looks very interesting, will check it out, also it would likely be much more adoptable if standards based.

Any tips for someone who’d like to try implementing something like this in TypeScript?

Than you for open sourcing this!

You are definitely onto something here.