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  • So is this kind of like a super-powered tealdeer ?
    by indigodaddy
  • tealdeer just shows you a cheatsheet, termy can effectively take a prompt and execute a command, example:

    $ termy create file test.txt and write Hello

    TERMy | template match | Confidence: 100.00%

    Thinking: Ok, I am asked to create the file test.txt.

    echo 'Hello' > 'test.txt' && termy_set_context 'active_file' 'test.txt'

    Description: Writes Hello in file test.txt.

    Response: Affirmative

    Now that I think about it, I should let TERMy use tldr...

    by gioscarab
  • That's impressive! Seems like we're back to ELIZA again, only with a more versatile dataset format and better NLP/search
    by zserge
  • Just at the right time, will be trying this out. I see it as an addition to local LLM, where on a job cycle it can learn from the LLMs contexts and free it up and help it in the more complex work.
    by dsemakin
  • I like the project. I see a lot of potential integrating it with LLM providers in an effort to lower token usage for repetitive tasks. Your solution becomes the "main model" and the LLM the fallback
    by paguasmar
  • I'll be the first to admit I burn too many tokens on the command line. Some form of LLM harness has been my new shell for the past 3+ years, they are much better at *sh then me, and I prefer not context switching from my terminal when I don't have to. In a way the rise of agent harnesses and their shell expertise has opened up apis and command line tools which have always been pain points for a terminal user.

    Great, simple idea applied in a novel way. Peak engineering if I ever seen it and I don't even have to look at the code. Nice work!

    by _superposition_
  • Very interesting project, I like it. Just wanted to clarify though the sentiment analysis is just the count of stripped words and used to tag things with the emoji? I was initially expecting it to be a part of the actual command construction process (even though I couldn't figure out how that would be relevant) given how it was listed.
    by Alpha3031
  • Ciao, yes for now the sentiment analysis is used only to provide an emoji related to the response. In the future I would like also to influence the choices of adjectives and interjections according to the sentiment.

    For now it is a bit of a gimmick I agree :)

    by gioscarab
  • Hi, I am the creator, feel free to ask any questions :)

    What do you think about it?

    by gioscarab
  • is it supported to have it propose a command for approval rather than running autmatically? in the YT video it looks likw it ran the cpu temp command on its own

    love the idea/simplicity of this tool!

    by cyberclimb
  • Cool project! How does it differ from warp terminals ai mode where you can ask it questions and it responds back
    by registereduser1
  • What dataset does step 5 rely on? Is it from your own terminal history, man pages, scrapped dataset from e.g. StackOverflow, sth else?
    by utopiah
  • > Models like ornith:9b, mistral:7b or cogito:14b can get the job done sometimes, but they are not fast and reliable enough for general use, specially if you have only 4GB of VRAM.

    Have you considered/tried using a model that's, well, more appropriate size-wise for an use case like this? These are relatively big. Something like FunctionGemma [1] finetuned for a given set of tasks would be a lot more speedy.

    [1] https://blog.google/innovation-and-ai/technology/developers-...

    by kouteiheika
  • At first blush, it is a really persuasive compromise between full-on LLM inference and boring old fuzzy history search!

    I really like it, this flavor of specialization gives the user a win on privacy and speed. Seems like the right idea for such a tool.

    by mpalmer
  • Cool, but system and user should probably stick to short, clear commands. E.g., I see you do some anaphora resolution (in particular: find what "it" refers to), but in a complex dialog, the human intention can differ from the machine's understanding. That will give problems when you end your dialog with "delete it".

    Adding more sentences to your data set will slowly degrade performance. It's a delicate system.

    Source: I have written software with similar functionality (NLP search) in SaaS form, a long time ago. It required quite a bit of work to configure.

    by tgv
  • I haven't evaluated it yet, but I love the fact that the output is (at least claimed to be) deterministic. I can't trust an LLM to do the right thing after I deploy it to production, because their output is non-deterministic by design.

    TERMy (or is it the NPC-forge) seems to be worth a try.

    by gurjeet
  • If you could get Termy to code, you'd be a rich man
    by vegnus
  • That would be so amazing. Even if it just helped with repetitive or hard to remember patterns.
    by stefanka
  • It would make sense to have this integrate with a self-learning routine for an agent: e.g. at night it looks through what it did and writes NPC-Forge recipes. Tomorrow it can answer queries (which he turned added to NPC-Forge) without an LLM. Of course this implies a branching where a query is either processed by NPC-Forge or an LLM, depending on some measure of confidence that NPC-Forge can answer it well.
    by dmos62
  • Yeah would be a nice experiment, if you are interested to contribute to NPC-Forge please open an issue, I would be happy to discuss about that.
    by gioscarab
  • It's kind of antithetical to the tool's deterministic positioning, but have you considered making TERMy leverage an LLM for unseen or low-confidence queries, and then generate the config and update itself to make future similar queries deterministic?
    by mbil
  • This is such a nice idea! I could add a fallback towards LLMs, it was present but I removed it. Would you be interested to help me implement the auto-update? I must admit, the LLMs are very useful for this kind of work. I think that TERMY's design is now feasible BECAUSE OF the availability of LLMs. They make the dataset development feasible.
    by gioscarab
  • cf. https://github.com/TellinaTool/nl2bash

    paper: https://arxiv.org/abs/1802.08979

    by nateb2022
  • Any similar data sets for coding?
    by stefanka
  • Thank you very much for the link.

    WOW! With that dataset the capabilities of TERMy could be vastly extended!

    Thank you.

    by gioscarab
  • This is a cool project; I think it's wonderful that traditional NLP methods are being used, rather than reaching straight for an LLM.

    One significant advantage of not using a local LLM is the significantly simplified dependency stack.

    by publlus_enigma