Great work! If anyone is looking for a way to integrate something like this into their own harness or the pi coding agent, then you might be interested in DeepClause [0]. It comes with a Prolog-like language implemented on top of SWI-Prolog (WASM Version). The purpose of the project is to allow for broad experimentation around the intersection of LLMs/Agents and GOFAI. So you could use it to build memory systems like OP did, create executable specs, define graphs and loops for agents and subagents... It also comes with a pi extension that greatly simplifies getting started with it.
Opposed to OP, DeepClause uses Prolog semantics, so running some more complex queries on knowledgebases might cause some issues (which is the use case where a Datalog might be more useful). For smaller scales it should be fine though.
I'm not sure if this is the right direction, but it's certainly momentarily helpful. I think the right direction would be to enable the model itself do dynamic program analysis, deterministically and dynamically via runtime-inference.
btw. your comment is grayed out, not sure what it means. However, thanks for sharing, I'll look into it.
Comments
Great work! If anyone is looking for a way to integrate something like this into their own harness or the pi coding agent, then you might be interested in DeepClause [0]. It comes with a Prolog-like language implemented on top of SWI-Prolog (WASM Version). The purpose of the project is to allow for broad experimentation around the intersection of LLMs/Agents and GOFAI. So you could use it to build memory systems like OP did, create executable specs, define graphs and loops for agents and subagents... It also comes with a pi extension that greatly simplifies getting started with it.
Opposed to OP, DeepClause uses Prolog semantics, so running some more complex queries on knowledgebases might cause some issues (which is the use case where a Datalog might be more useful). For smaller scales it should be fine though.
[0] https://github.com/deepclause/deepclause-sdk [1] https://github.com/deepclause/deepclause-pi
I'm not sure if this is the right direction, but it's certainly momentarily helpful. I think the right direction would be to enable the model itself do dynamic program analysis, deterministically and dynamically via runtime-inference.
btw. your comment is grayed out, not sure what it means. However, thanks for sharing, I'll look into it.