FrameML

This is meant to be a markup language for interacting with machine learning models. This is written from the ground up with simplicity, minimalism, and power usage in mind.

Core features currently include:

• Variables!
  • These can be from a user supplied dictionary or special variables like: {{1}}, previous inputs
• Control flow!
  • Extremely basic if statementst are provided
  • Check TODO for more info

Included in this repo is a python library for compiling this script and using it with your own programs. Here is a simple example script:

# You can write comments like this! All blank lines are ignored.
> Create a fictional title for the {{MOVIE_ADJECTIVE}} movie ever! This should not be a real movie; only supply me with the title.

# here we refer to the output of the first prompt!
> Write a comprehensive anlaysis of {{1}}, discussing the following details: {{ANALYSIS_DETAILS}}. Make sure to sound as pedantic as possible.

# likewise, we refer to the output of the 2nd prompt here
! if 'masterpiece' in {{2}}
> Someone approaches you and says {{1}} is the worst movie ever made. How do you respond?
! elif 'worst' in {{2}}  # regex supported here!
> Some subhuman piece of garbage online actually thinks that {{1}} is the best movie made. How do you respond?
! else
> Someone feels passionately about {{1}}. They are frustrated with your apathy. What do you respond with?
! endif
 # there must always be an endif

You can check init.py for an example of how to use it!

Here's how you would use the python module:

from frameml import Frame

def llm(arg: str) -> str:
    # Simply returns the first word
    return f"{arg.split()[0]}"

test1 = Frame(script="> Create a fictional title for the {{adjective}} movie ever! This should not be a real movie; only supply me with the title.")
test1.compile(llm, adjective="most epic")

• Frame is our class that wraps this script
  • script refers to your actual text. It contains your hopefully valid frameml file.
• Frame.compile is a function for actually querying the api
  • llm is a function for querying the actual language model. It simply takes a string and returns one.
    • You can create a wrapper around the openai library for example
  • Any other arguments are kwargs.
    • These are essentially just named parameters. Check here to learn more

For more examples, check the examples folder

Setup

pip install frameml

It should be ready to use in your project now!

TODO:

• Implement other cooler control flow
  • Again, may or may not be necessary but it might be cool
• Allow user to implement their own functions in the script
  • This may be out of the scope for the project