Show HN: ThoughtDAG – An editable context graph for LLM conversations
chatchan · 105 points · 48 comments · 17 ore fa · Open original
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EMembedding-shape11 ore fa
This seems like a really interesting idea and something I've basically been doing myself manually so far, with a DESIGN.md document with "one concept/decision per line, built in a tree" basically, where all decisions that needs to be remembered gets noted down for future reference.
Not a fan of ThoughtDAG being a complete separate application rather than built into the tools I use every day, like my text editor or other planning tool. But neat that you've seemingly integrated a bunch of LLM providers, including letting us use local models, sufficiently sweet :)
Some security "nitpicks": I'm fairly sure you have a critical security issue in the "execSync(`pdftoppm -png -r ${dpi} ...`)" call you do, which I don't think would have been a issue if the local web server you start listened to 127.0.0.1 or some other local IP, but instead it seems the server binds to 0.0.0.0, meaning all network interfaces. Put together, anyone who runs this application effectively gives anyone else a free shell to your computer :)
Tiny nitpicks about the AppImage specifically, seems it's missing publisher details/signing (not a huge deal, just something you might want to look into) and also it's using "--no-sandbox", don't think you need that, let it be sandboxed instead, and the remote vulnerability above might also become less of an issue :)
I'll hold off a bit to play around with it, because of the issue above, but I'm curious to see if it does provide something more than what I manage with my ASCII Markdown tree of decisions. Maybe there is potential for ThoughtDAG in the future to be better integrated with other tools, and end up mostly being the management/viewer of things, so I can continue using vim and codex as today, but they can read/write via ThoughtDAG perhaps, or some other approach.
Regardless, thanks for sharing it and good luck! :)
DEDenisM6 ore fa
Sometimes I ask the agent why it gave a certain answer, when I feel it overly fixated on something. It would be cool if the ui hilighted the poisonous part of the conversation somehow.
FLfloriangoebel5 ore fa
Nice work! Recently I prototyped a harness for structured agentic research work and I arrived at something very similar.
I found it especially useful for balancing research breadth vs research width when exploring new topics.
A graph structure makes it easier for me to identify potential blind spots in the research process and allows me to be more confident that no promising alternative solutions were left out while at the same time not getting too stuck in rabbit holes of subquestions.
When I built my prototype I had this image of a physarum slime mold [0] in my head that branches off into all directions first, then reinforces potential paths while starving off all other branches.
In the end that path that survives is the result.
[0] https://carolinalombardi.com/physarum-polycephalum
URurvader14 ore fa
What about cache? When you change the context the prefill stage will be much slower?
_B_boffin_5 ore fa
Nice. seems like this converges on something i built called https://Tangents.chat, specifically the "Context complier", which can be seen here (https://tangents.chat/demo) (click Context in the top right after entering the demo).
Looking forward to looking more at ThoughtDAG.
Visual: https://i.ibb.co/NRHSFrg/tangents-context-complier.png
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This seems like a really interesting idea and something I've basically been doing myself manually so far, with a DESIGN.md document with "one concept/decision per line, built in a tree" basically, where all decisions that needs to be remembered gets noted down for future reference. Not a fan of ThoughtDAG being a complete separate application rather than built into the tools I use every day, like my text editor or other planning tool. But neat that you've seemingly integrated a bunch of LLM providers, including letting us use local models, sufficiently sweet :) Some security "nitpicks": I'm fairly sure you have a critical security issue in the "execSync(`pdftoppm -png -r ${dpi} ...`)" call you do, which I don't think would have been a issue if the local web server you start listened to 127.0.0.1 or some other local IP, but instead it seems the server binds to 0.0.0.0, meaning all network interfaces. Put together, anyone who runs this application effectively gives anyone else a free shell to your computer :) Tiny nitpicks about the AppImage specifically, seems it's missing publisher details/signing (not a huge deal, just something you might want to look into) and also it's using "--no-sandbox", don't think you need that, let it be sandboxed instead, and the remote vulnerability above might also become less of an issue :) I'll hold off a bit to play around with it, because of the issue above, but I'm curious to see if it does provide something more than what I manage with my ASCII Markdown tree of decisions. Maybe there is potential for ThoughtDAG in the future to be better integrated with other tools, and end up mostly being the management/viewer of things, so I can continue using vim and codex as today, but they can read/write via ThoughtDAG perhaps, or some other approach. Regardless, thanks for sharing it and good luck! :)
Sometimes I ask the agent why it gave a certain answer, when I feel it overly fixated on something. It would be cool if the ui hilighted the poisonous part of the conversation somehow.
Nice work! Recently I prototyped a harness for structured agentic research work and I arrived at something very similar. I found it especially useful for balancing research breadth vs research width when exploring new topics. A graph structure makes it easier for me to identify potential blind spots in the research process and allows me to be more confident that no promising alternative solutions were left out while at the same time not getting too stuck in rabbit holes of subquestions. When I built my prototype I had this image of a physarum slime mold [0] in my head that branches off into all directions first, then reinforces potential paths while starving off all other branches. In the end that path that survives is the result. [0] https://carolinalombardi.com/physarum-polycephalum
What about cache? When you change the context the prefill stage will be much slower?
Nice. seems like this converges on something i built called https://Tangents.chat, specifically the "Context complier", which can be seen here (https://tangents.chat/demo) (click Context in the top right after entering the demo). Looking forward to looking more at ThoughtDAG. Visual: https://i.ibb.co/NRHSFrg/tangents-context-complier.png