Recent submissions

Comment · 4 months ago
You're right, starting with that context would have helped. It's an experimental project and of course there will be imperfections, whether written by me or with LLM assistance. I did my best.
Comment · 4 months ago
For ethical principles I 100% agree with you. I used LLMs to generate parts of the code, but the architecture, integration, debugging and testing are mine. It took me months in my free time. So, what can I say to be 100% honest?
Comment · 4 months ago
Nice! your project use smaller components (do one thing and do it well), bash4llm is more monolithic because I focus Bash-only portability and security. different approach for similar ideas, I see your repo, thank you!
Comment · 4 months ago
English idioms are hard for me (I'm Italian), so I can misunderstand your point. bash4llm is long because it uses pure Bash, and making Bash-only reasonably safe and consistent for LLM calls it's difficult. For me, that's exactly what I like in the project.
Comment · 4 months ago
I've applied a set of corrections, on Bash4LLM core, to reduce redundancy and make the flow more deterministic. Optimized safe_mkdir to eliminate superfluous calls to chmod, simplify temp file management by removing a redundant pre‑validation, remove repeated controls on ensure_run_tmpdir, unified internal standards but with backward compatibility, to correct duplications on providers management caused by a second redundant scan of provider modules, preserved diagnostic mode (CLI and environment variables). These are small jobs, but useful for clean and consistent runtime.
Comment · 4 months ago
Thank you very much for your attention and for your time. The problems that you have seen are real. Inspired by your feedback, I proceed to work on it, and I will fix the hollow redundancies and the bad duplications.
Comment · 4 months ago
I don't think it is of poor quality. I post this because I wish it is good for others. It's not auto generated, I made this.
Comment · 4 months ago
I don't think , I can pay if it's really good for this work, but I've seen the characteristics of pay plan and are not really better for my use case. The free plan is not the reason for the code size; the architecture is the reason. the best choice for me, for this work, is to have a real AI (not a toy installed on a laptop) without limitations and filters, but for this need many tens of thousands of €
Comment · 4 months ago
I work with termux on Android, and it works fine. For now, I've not tested bash4llm on other environments, but I think it does work because the required packages are the minimum common denominator for all environments, ad with this requirements installed it should work on bsd-like too. I tried python too, at the start, and it was too slow.
Comment · 4 months ago
The macro sections/sections/sub-sections in the code are not random, I intentionally decide that. In brief: PRECORE_BOOT - for initialization PRECORE_RUN - persistency, history, cache PROVIDER - embedded provider (groq) CORE_SETUP - global runtime configuration, parsing parameters, LLM whitelist, user configuration CORE_PROVIDER - providers validation, prompt assembly, chat sessions, models tuning

The macro sections has two functions: 1, for me, to navigate the code 2, for LLMs, to understand my structure

The project does many things, so i need a clear sections structure to separate responsibilities.

You can see more information on the documentation, but the architectural spec is only in Italian.

Comment · 4 months ago
Architecture and structure are my decisions, LLM are instruments, simple executors, today i think are commonly used. Write code with LLM is not "push a button", it's a technical way of work, needs study and practice. 5k lines are months of work, debug, refactor, testing. 5k lines are the result of a long (and difficult) work, but LLM helps your productivity. The most important thing, for the humans, are the architectural decisions, and understanding how your current LLM reasoning and behavior. I decide architecture and structure; LLM only writes code (that need debug and testing), LLM are executors, not automatic. LLM are only software, and are new instruments to learn. Important thing: I use only free plan, of LLMs that have a real free plan.
Comment · 4 months ago
Yes, the code is big and bulky, i know. But i am a single person, not a team. I write simple and clear for me, because i need to mantain it. Only Bash, zero dependencies, i like this.

thank you for your comment!

Comment · 4 months ago
well, i write Bash4LLM to be:

. Portable - You need only: bash, coreutils, findutils, util-linux, gawk, curl, jq. No Python (slow), no Node (heavy), no Golang (need too many binaries, one for each OS, hard to maintain for one single person like me).

. Single file - only one. I write many extras, but all are optional.

. Idempotent - you copy it where you want and go!

. Transparent - open the file and read.

. Extras for all, and all optional: help file, extra providers, improved session engine, small GUI/CGI, etc...

Default (embedded) provider is Groq, because when I start the project, was the best free API service for AI.

I'm ready to answer to your question... with my terrible english...

Cristian (kamaludu)

Live from the official Hacker News API

A modern reader for Hacker News · SvelteKit + Skeleton