LLMPrompts 0.1.0

Facilitating the creation, storage, retrieval, and curation of LLM prompts.

LLMPrompts Python package

In brief

This Python package provides data and functions for facilitating the creation, storage, retrieval, and curation of Large Language Models (LLM) prompts.

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Installation

Install from GitHub

pip install -e git+https://github.com/antononcube/Python-packages.git#egg=LLMPrompts-antononcube\&subdirectory=LLMPrompts

From PyPi

pip install LLMPrompts

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Basic usage examples

Synthesizing responses

Here is an example of prompt synthesis with the function llm_synthesize using prompts from the package "LLMFunctions":

from LLMPrompts import *

print(
    llm_synthesize([
        llm_prompt("Yoda"), 
        "Hi! How old are you?",
        llm_prompt("HaikuStyled")
    ]))

Young or old, matters not
Age is just a number, hmm
The Force is with me.

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References

Articles

[AA1] Anton Antonov, "Workflows with LLM functions", (2023), RakuForPrediction at WordPress.

[SW1] Stephen Wolfram, "The New World of LLM Functions: Integrating LLM Technology into the Wolfram Language", (2023), Stephen Wolfram Writings.

[SW2] Stephen Wolfram, "Prompts for Work & Play: Launching the Wolfram Prompt Repository", (2023), Stephen Wolfram Writings.

Packages, paclets, repositories

[AAp1] Anton Antonov, LLM::Prompts Raku package, (2023), GitHub/antononcube.

[AAp2] Anton Antonov, LLM::Functions Raku package, (2023), GitHub/antononcube.

[AAp3] Anton Antonov, Jupyter::Chatbook Raku package, (2023), GitHub/antononcube.

[WRIr1] Wolfram Research, Inc., Wolfram Prompt Repository