AI Module

[Interpreted]

import ai

# Create tensors
let t1 = ai.tensor([[1, 2], [3, 4]], dtype:"f32")
let t2 = ai.tensor([[5, 6], [7, 8]], dtype:"f32")

# Operations
let result = ai.matmul(t1, t2)
let sum = ai.sum(t1)
let mean = ai.mean(t1)

# Load ONNX model (coming soon)
let model = ai.load_model("resnet50.onnx")
let output = model.predict(input_tensor)

# Classify images (coming soon)
let image = ai.load_image("cat.jpg")
let label = ai.classify(image, model:"clip")
print("Label:", label)

# Generate text (coming soon)
let prompt = "Write a story about"
let text = ai.generate(prompt, model:"gpt-4")
print(text)

# Use Python libraries via FFI
ffi python {
  import numpy as np
  import torch
}

let arr = np.array([[1, 2], [3, 4]])
let mean = np.mean(arr)
print("Mean:", mean)

[Interpreted]

import ai

let x = ai.tensor([[1, 2], [3, 4]], dtype:"f32")
let y = ai.tensor([[5, 6], [7, 8]], dtype:"f32")

let z = ai.matmul(x, y)
print("Result:", z)