> Local Setup > Prerequisites > OpenAI API Key This does not seem to be local and additionally appears to be tied to one SaaS LLM provider?
You can run OpenAI compatible servers locally. vLLM, ollama, LMStudio and others.
Show HN: Core – open source memory graph for LLMs – shareable, user owned
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Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#12Why do open source projects do not version control their CLAUDE.md?
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#13> Local Setup > Prerequisites > OpenAI API Key This does not seem to be local and additionally appears to be tied to one SaaS LLM provider?
Hey we are actively working on improving support for Llama models. At the moment, CORE does not provide optimal results with Llama-based models, but we are making progress to ensure better compatibility and output in the near future.
Also we build core first internally for our main project SOL - AI personal assistant. Along the journey of building a better memory for our assistant we realised it's importance and are of the opinion that memory should not be vendor locked. It should be pluggable and belong to the user. Hence build it as a separate service.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#14> Local Setup > Prerequisites > OpenAI API Key This does not seem to be local and additionally appears to be tied to one SaaS LLM provider?
You can run OpenAI compatible servers locally. vLLM, ollama, LMStudio and others.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#15For those asking how this is different from a simple text based memory archive, I think that is answered here: --- Unlike most memory systems—which act like basic sticky notes, only showing what’s true right now. C.O.R.E is built as a dynamic, living temporal knowledge graph: Every fact is a first-class “Statement” with full history, not just a static edge between entities. Each statement includes what was said, who…
I'm not sure the graph offers any clear advantage in the demonstrated use case.
It's overhead in coding.
The source is the doc. Raw text is as much of a fact as an abstracted data structure derived from that text (which is done by an external LLM - provenance seems to break here btw, what other context is used to support that transcription, why is it more reliable than a doc within the actual codebase?).
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#16how would you say you compare to graphiti from zep?
Hi,
There are 3 major differences between Zep and CORE 1. Market: Zep is B2B focused, CORE indvidual users 2. Portablity: Zep is locked to their platform , CORE works across claude, cursor, windsurf 3. Architecture: Zep is Temporal based vs CORE is Reified + Temporal based graph
What this means:
Zep remembers what happened when CORE remembers what happened when + why we should believe it + how facts relate
Example: You say "I love Thai food" → Later: "Actually, I hate Thai food"
Zep: "You hate Thai food" (old preference vanishes) CORE: "You currently hate Thai food. This contradicts your earlier statement from [date/source]. The change came from your correction today."
Bottom line: CORE provides full explainability and audit trails that Zep cannot.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#17It certainly looks interesting, how does this differ from a plan.md?
Hey plan.md mostly will be a static file that you manually have to maintain. It won't be relational and not be able to form connections between info. You can't recall or query intelligently? (When did my preference change?)
CORE lets you - Automatically extracts and stores facts from conversations - Builds intelligent connections between related information - Answers complex queries ("What did I say about something and when?") - Detects contradictions and explains changes with full context
For simple fact recall, plan.md should work but for complex systems a relational memory should be able to help better.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#18> Local Setup > Prerequisites > OpenAI API Key This does not seem to be local and additionally appears to be tied to one SaaS LLM provider?
Hey we are actively working on improving support for Llama models. At the moment, CORE does not provide optimal results with Llama-based models, but we are making progress to ensure better compatibility and output in the near future. Also we build core first internally for our main project SOL - AI personal assistant. Along the journey of building a better memory for our assistant we realised it's importance and are…
I definitely would not recommend llama models, they were mostly outdated by the time they released, but the likes of Qwen, deepseek etc are much more useful.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#19For those asking how this is different from a simple text based memory archive, I think that is answered here: --- Unlike most memory systems—which act like basic sticky notes, only showing what’s true right now. C.O.R.E is built as a dynamic, living temporal knowledge graph: Every fact is a first-class “Statement” with full history, not just a static edge between entities. Each statement includes what was said, who…
I'm not sure the graph offers any clear advantage in the demonstrated use case. It's overhead in coding. The source is the doc. Raw text is as much of a fact as an abstracted data structure derived from that text (which is done by an external LLM - provenance seems to break here btw, what other context is used to support that transcription, why is it more reliable than a doc within the actual codebase?).
Hey - i agree that the demonstrated use can be solved with simple plan.md file in the codebase itself.
With use-case we wanted to showcase the shareable aspect of CORE more. The main problem statement we wanted to address was "take your memory to every AI" and not repeating yourself again and again anymore.
The relational graph based aspect of CORE architecture is an overkill for simple fact recalling. But if you want an intelligent memory layer about you that can answer What, When, Why and also is accessible in all the major AI tools that you use, then CORE would make more sense.
Re: Show HN: Core – open source memory graph for LLMs – shareable, user owned
#20Earlier quoted context omitted.
Hey we are actively working on improving support for Llama models. At the moment, CORE does not provide optimal results with Llama-based models, but we are making progress to ensure better compatibility and output in the near future. Also we build core first internally for our main project SOL - AI personal assistant. Along the journey of building a better memory for our assistant we realised it's importance and are…
I definitely would not recommend llama models, they were mostly outdated by the time they released, but the likes of Qwen, deepseek etc are much more useful.
Hey we started with llama but since llama was not giving good results hence fall backed to using gpt and launch it.
We will evaluate qwen and deepseek going forward, thanks for mentioning.