AI-Functions

AI Functions Project Overview

The AI Functions project is a user-friendly implementation of AI-driven functions leveraging OpenAI's GPT-4 (or other versions) to execute various tasks. This project draws much of its inspiration from Ask Marvin.

Concept and Example

At its core, the AI Functions project allows users to define functions that are interpreted and executed by AI models. For instance, consider a function that generates fake people data:

function_string = "def fake_people(n: int) -> list[dict]:"
args = ["4"]
description_string = "Generates n examples of fake data representing people, each with a name and an age."

result = ai_functions.ai_function(function_string, args, description_string, model)

This example will prompt the model to output a list of dictionaries, each representing a person with a name and age.

Key Features

1. Installation: Users start by cloning the repository and installing dependencies via pip. An OpenAI API key is necessary for access to AI models.

2. Functionality: The ai_functions.py script is central to the project. It defines a method, ai_function, which takes:

   • A function signature.
   • A list of arguments.
   • A descriptive purpose.
   • Optionally, a model specifier (defaults to 'gpt-4').

3. Limitations: The project has limitations, particularly in domains requiring mathematical precision or technical specificity. For example, GPT models can miscalculate mathematical tasks such as finding a triangle's area or determining an nth prime number.

How to Use

To use the ai_function, users provide the function’s structure, necessary arguments, and a clear description of its intended use. This setup allows the AI model to execute and return a result. For example, adding two integers can be formulated as:

import ai_functions

function = "def add(a: int, b: int) -> int:"
args = ["5", "7"]
description = "Adds two integers."

result = ai_functions.ai_function(function, args, description)
print(result)  # Output: 12

Testing and Validation

A test_ai_functions.py script is supplied to run test cases on the defined AI functions. By executing this script, users can verify the performance and success rates of their functions.

Contributions

The project is open to contributions. Users are encouraged to enhance the library by introducing additional test cases or refining existing code. Contributions can be made via pull requests.

Conclusion

AI Functions is a versatile tool designed for scenarios where AI can assist in carrying out tasks defined by the user. Although there are limitations in certain technical tasks, its ease of use makes it appealing for a range of applications. For tasks requiring more precise calculations, relying on traditional methods may be advisable.