This program takes a JSON list of strings from standard input, sends each input string to an LLM as a prompt, and returns a list of dictionaries, with a "prompt"
and "answer"
key for each original prompt.
To execute it, run
python generate.py
And then type some prompts in list form, e.g.
["What is spaCy?", "What is Rust?"]
followed by an EOF-marker (Ctrl-d on Linux or Mac, Ctrl-z on Windows) and an enter. The output will look something like this:
[
{"prompt": "What is spaCy?",
"answer": "spaCy is a Python library for natural language processing. It is designed to be easy to use and highly customizable, making it a great tool for developers and researchers."},
{"prompt": "What is Rust?",
"answer": "Rust is a programming language that is designed to be a safe, concurrent, and efficient replacement for C++. It is a statically-typed language that is designed to be memory-safe and thread-safe, which means that it can be used to write high-performance, low-latency applications. Rust is designed to be a modern, high-performance programming language that is designed to be easy to use and easy to learn."}
]
To get the full list of options and defaults for this command, run
python generate.py --help
This program takes a JSON list of passive sentences from standard input, and returns a list of dictionaries, with a "passive"
and "active"
key for each original sentence.
To execute it, run
python passive2active.py
And then type some prompts in list form, e.g.
["The medal was won by the Dutch speed skater.", "Anita was driven to the theatre by Carla."]
followed by an EOF-marker (Ctrl-d on Linux or Mac, Ctrl-z on Windows) and an enter. The output will look something like this:
[
{
"passive": "The medal was won by the Dutch speed skater.",
"active": "The Dutch speed skater won the medal."
},
{
"passive": "Anita was driven to the theatre by Carla.",
"active": "Carla drove Anita to the theatre."
}
]
To get the full list of options and defaults for this command, run
python passive2active.py --help