akashic_records is a Python package that dynamically generates functions using OpenAI code completion based on what is imported and how it is used.
To install the akashic_records package, you can use pip:
pip install akashic_recordsBehaviour of the akashic_records package is based on what you import from it, and how you use it.
The package generates functions on the fly based on the name you import and the way you call it.
from akashic_records import quick_sort
arr = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
result = quick_sort(arr)
print(result) # Output: [1, 1, 2, 3, 3, 4, 5, 5, 5, 6, 9]The package will end up making requests to the OpenAI completions endpoint with the code-davinci-002 model.
The above code will end up generating this prompt:
def quick_sort(arr: list):
Note that the parameter name matches the name of the argument that was passed in. If a constant is passed in instead of an identifier, generic names such as p0 and p1 will be used. To have a useful name with a constant argument, use keyword arguments.
This package (ab)uses type hints to give more information to the completion process.
from typing import Annotated
from akashic_records import merge_sort
unsorted_list = [3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]
result: Annotated[list, """
Sorts the input list using the mergesort algorithm.
Parameters:
-----------
unsorted_list : list
The input list to be sorted.
Returns:
--------
list
The sorted list.
"""] = merge_sort(unsorted_list)
print(result) # Output: [1, 1, 2, 3, 3, 4, 5, 5, 5, 6, 9]Generates the following prompt:
def merge_sort(unsorted_list: list) -> list:
"""
Sorts the input list using the mergesort algorithm.
Parameters:
-----------
unsorted_list : list
The input list to be sorted.
Returns:
--------
list
The sorted list.
"""
If you would like to include a docstring but not a return type, only use a string for the type annotation instead of using typing.Annotated.
If you don't like the somewhat magical mechanisms by which the above functionality works (extracting type hints and argument variable names), the package also supplies a decorator with the same functionality.
from akashic_records import generate
@generate(n=1, temperature=0.1, max_tokens=256)
def merge_sort(unsorted_list: list) -> list:
"""
Sorts the input list using the mergesort algorithm.
Parameters:
-----------
unsorted_list : list
The input list to be sorted.
Returns:
--------
list
The sorted list.
"""
print(merge_sort([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5])) # Output: [1, 1, 2, 3, 3, 4, 5, 5, 5, 6, 9]The OpenaAI completions endpoint has many options. Some of these are available for tweaking.
from akashic_records import config
config.n = 3 # https://platform.openai.com/docs/api-reference/completions/create#completions/create-n
config.max_tokens = 512 # https://platform.openai.com/docs/api-reference/completions/create#completions/create-max_tokens
config.temperature = 0.2 # https://platform.openai.com/docs/api-reference/completions/create#completions/create-temperatureSome additional options are available to control the prompt generation process.
from akashic_records import config
config.type_hint = True # Set to False to disable all type hints in prompts
# The package isn't always able to get a working completion from the API.
# In the event that something goes wrong (syntax error in the generated code, runtime error trying to run it, etc)
# The package will try to generate new completions.
# The `attempts` value controls how many times it will try.
config.attempts = 5 # Set to -1 for unlimited tries.The very neat sorcery package by Alex Hall.
The name akashic_records is inspired by the spiritual belief of the Akashic Records. In this belief, the Akashic Records are a repository all universal events, thoughts, words, emotions and intent ever to have occurred in the past, present, or future in terms of all entities and life forms.
This seemed fitting for a package that in some sense contains the implementation of "every function".