GitHub - vkataev/ai-cli: command line assistant smoothly connecting your requests with LLM of your choice and executing directly returned actions · GitHub
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ai-cli
command line assistant smoothly connecting your requests with LLM of your choice and executing directly returned actions, all in a single C file
MOTIVATION
Free yourself from writing all those complex actions in command line shell, instead ai assistant will do it for you based on your requests.
Your choices are: accept actions (by just pressing Enter ) with opportunity to edit assistan's answer first or reject actions by pressing Ctrl+C .
EXAMPLES
If for example, you want to know who did run jobs on a particular Slurm node, you may ask:
$ ./ai who was running jobs on a slurm node 39 between 1 and 2 hours ago<br>user847<br>uset20499
The action assitant returned might look like:
sacct --format="JobID,JobName,User,NodeList,Start,End,State" --allusers --starttime=$(date -d "-2 hours" "+%Y-%m-%dT%H:%M:%S") --endtime=$(date -d "-1 hours" "+%Y-%m-%dT%H:%M:%S") --allocations --node=39 | tail -n +3 | awk '{print $3}' | sort | uniq
Other examples:
$ ./ai replace Solar with solar in every python file in this folder<br>Done
$ ./ai modify permissions of this folder so no other user can read anything here<br>Done
$ ./ai find all occurances of subword "perform" in words.txt and print their line numbers<br>1881<br>10046<br>10047<br>40358
$ ./ai math log of 4096<br>8.317766166719343
$ ./ai show me last 3 lines in each c file in current folder<br>buffer_free(&original);<br>return exit_code;
$ ./ai what is IP address of somewebsite<br>xxx.xx.xx.xxx
WARNING
Be careful, because this tool executes actions returned by LLM directly in your shell.
Authors are not responsible for any damage this program can cause.
If you are not familiar with shell commands, do not use this assistant.
BUILD
sh run.build_ai.sh
or directly
gcc ai.c -o ai
INSTALL
This will copy ai into your ~/.local/bin and man page into ~/.local/share/man/man1/
sh run.build_ai.sh
PORTABILITY
You can build and run this tool on literally any platform, fully supported:
Linux
macOS
Android
FreeBSD
iOS
OpenBSD
NetBSD
QNX Neutrino
Windows (MSYS2 or Cygwin)
WebOS
Haiku
SerenityOS
DragonFly BSD
illumos
Solaris
AIX
HP-UX
Tru64 UNIX
IRIX
UnixWare
SCO OpenServer
Redox OS
VxWorks
RTEMS
INTEGRITY
Most LLM engines are fully supported:
Engine<br>/v1/chat/completions
llama.cpp<br>Yes
vLLM<br>Yes
TensorRT-LLM<br>Yes
Ollama<br>Yes
LM Studio<br>Yes
SGLang<br>Yes
Text Generation Inference (TGI)<br>Yes
Aphrodite Engine<br>Yes
LocalAI<br>Yes
Xinference<br>Yes
FastChat<br>Yes
MLC LLM<br>Yes
KoboldCpp<br>Partial
DEPENDENCIES
You need an LLM engine running locally or remotely.
Example how you may run llama.cpp with Gemma-4 model:
llama-server --host 0.0.0.0 \<br>--model unsloth/gemma-4-12B-it-qat-UD-Q4_K_XL.gguf \<br>--temp 1.0 \<br>--top-p 0.95 \<br>--top-k 64 \<br>--port 8001 \<br>--chat-template-kwargs '{"enable_thinking":false}'
Remember to disable thinking mode - answers model provides will be direct shell actions.
USAGE
$ export AI_URL="http://127.0.0.1:8001"<br>$ ./ai which file in this folder is to build ai tool<br>./run.build_ai.sh
You can accept answer by pressing Enter and actions will be executed in shell or you can press Ctrl+C to reject entire actions.
You can edit returned answer just like in any editor - use arrow keys to navigate.
To execute actions place cursor to the end of the entire answer and press Enter or reject at any time by pressing Ctrl+C.
MEMORY USAGE
You can enable assistant's memory with --memory flag, in this case it will update AI_MEMORY.md in the current directory.<br>This helps solving more complex tasks,...