How can I migrate neo4j to this?
We've built SQL and PGVector ones already, just waiting for someone who could make use of other ones before we build them.
Let us know! Twitter in my bio
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How can I migrate neo4j to this?
We've built SQL and PGVector ones already, just waiting for someone who could make use of other ones before we build them.
Let us know! Twitter in my bio
Can I run this as an embedded DB like sqlite? Can I sidestep the DSL? I want my LLMs to generate queries and using a new language is going to make that hard or expensive.
Currently you can't run us embedded and I'm not sure how you could sidestep the DSL :/ We're working on putting our grammar in llama's cpp code so that it only outputs grammatically correct HQL. But, even without that it shouldn't be hard or expensive to do. I wrote a Claude wrapper that had our docs in its context window, it did a good job of writing queries most of the time.
Congrats on the launch! I'm one of the authors of that paper you cited, glad it was useful and inspiring to building this :) Let me know if we can support in any way!
Would love to talk to you about it and make sure we capture all of the pain points if you're open to it? :)
Congrats on the launch! I'm one of the authors of that paper you cited, glad it was useful and inspiring to building this :) Let me know if we can support in any way!
Wow! I enjoyed reading it a lot and it was definitely inspiring for this project! Would love to talk to you about it and make sure we capture all of the pain points if you're open to it? :)
This is very interesting, are there any examples of interacting with LLMs? If the queries are compiled and loaded into the database ahead of time the pattern of asking an LLM to generate a query from a natural language request seems difficult because current LLMs aren't going to know your query language yet and compiling each query for each prompt would add unnecessary overhead.
I mentioned in another comment that you can provide a grammar with constrained decoding to force the LLM to generate tokens that comply with the grammar. This ensures that only valid syntactic constructs are produced.
how did you get it 3 OOMs faster than neo4j?
My friend who I worked on this with is putting together a technical blog on those graph optimisations so I'll link it here when he's done
Earlier quoted context omitted.
have you thought about SPALDE models? ex: https://arxiv.org/abs/2109.10086
Looks really interesting, I'll have a proper read. What would be your reasoning to incorporate this if we already have vector functionality and semantic search?
Does Helix support much of the graph algorithm world? For things like GrapgRAG.
Either way, I'd be all over it if there was a python SDK witch worked with the generated types!