What it does

ai_functions.py is a single function that takes a function signature as a string, a description, and arguments, ships them to OpenAI’s API, and returns whatever the model generates. It’s essentially a prompt engineering wrapper with JSON parsing on the back end. The project is inspired by Ask Marvin.

The interesting bit

The honesty in the README. The author includes a failure table showing GPT-4 flunks basic geometry (area of a triangle) and GPT-3.5-turbo can’t even format fake people correctly. Most “AI function” demos sweep this under the rug; here it’s the headline limitation.

Key highlights

• One function: ai_function(function_string, args, description, model="gpt-4")
• Relies entirely on prompt structure—no code generation, no sandboxing, no validation
• Includes test suite with explicit pass/fail matrix across models
• API key stored in keys.py or environment variable (no key management beyond that)
• ~937 stars, heavy ChatGPT/GPT-4 topic tagging

Caveats

• Mathematical precision is explicitly called out as broken; GPT-4 hallucinates float values
• No retry logic, no type enforcement on outputs, no timeout handling visible
• “Clone the repository” install instructions reference YourUsername/SuperSimpleAIFunctions—a copy-paste error suggesting low maintenance

Verdict

Worth a look if you’re prototyping LLM-as-a-service patterns and want a minimal reference point. Skip it if you need determinism, math, or anything resembling a production function call.