A truly natural scripting language
hi runs your natural language
You can see it in action here:
hi script is provided in python-hi pip package
pip install -U python-hi
you can also clone this repository and run "poetry install"
Be careful The converted bash can contain weird things. you can run hi script initially with HI_EXECUTE=false to check the resulting code before executing.
hi could you list current dir
since ? is special character in shell, if you want to use ?, just add quotation mark around it,like this
hi "could you list current dir?"
hi can also be used as shellbang interpreter create a file: progressbar.hi
#!/usr/bin/env hi
could you display a progress bar from 1 to 100?
and chmod +x ./progressbar.hi then ./progressbar.hi It can be executed like any other script.
$ ./progressbar.hi
#!/usr/bin/env bash
echo "Progress:"
for ((i=1; i<=100; i++))
do
echo -ne "$i%\r"
sleep 0.1
done
echo "Complete!"%
The code is sent to LLM and then convert to bash and then execute, while also cache for next time fast reexecute(then it doesn't need to query the LLM again)
We need to add it to ~/.hi
HI_API_KEY: sk-xxx
HI_MODEL: gpt-4
#HI_API: if you have a different base to forward other than https://api.openai.com/v1, it's set using openai.openai_api_base=this value
Now you can run hi script either from command line or as an shellbang interpreter(check out samples/*.hi)
list.hi,progressbar.hi,spinner.hi should be self explanatory, tidy.hi tidys a directory by file's date(year-month)
./tidy.hi some_dir
after you first run the script, the converted bash code will be cached in ~/.hicache/ , you can run
hi cache clear
to completely clear the cache.
you can set the following variables in ~/.hi(in yaml format) or use in command line like
$ HI_API_KEY="sk-xxx" hi ...
you can use HI_EXECUTE to control the execution of the hi script
$ HI_EXECUTE="false" hi ...
Default: https://api.openai.com/v1
A server following OpenAI's Chat Completion API.
Many local proxies exist that implement this API in front of locally running LLMs like Llama 2. LM Studio is a good option.
HI_API="http://localhost:1234/v1"
Default: unset
The API key to be sent to the LLM backend. Only needed when using OpenAI.
HI_API_KEY="sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX"
Default: gpt-4
The model to use for inference.
HI_MODEL="gpt-3.5"
Default: true
Whether or not the hi interpreter should automatically execute the generated code on the fly.
If false the generated code will not be executed and instead be streamed to stdout.
HI_EXECUTE="false"
Default: false
Whether or not the hi interpreter should regenerate a cached hiscript.
If true the hiscript will be reinterpreted and the cache entry will be replaced with the newly generated code. Due to the nondeterministic nature of LLMs each time you reinferpret a hiscript you will get a similar but slightly different output.
HI_REGENERATE="true"
This project is highly inspired by humanscript project(https://github.com/lukechilds/humanscript), but I think hi is a better name, also hi can be interpreted as short for human input, human inteprete,human interface, human inferenceinterpreter etc, and just for fun. Also using python is easier for plugin architecture, the way I think is in different project/workspace, maybe there will be different 'hi' implementations, so .hi in that directory with plugin_type="metagpt" will run some metagpt command at that directory.
MIT © femto Zheng