AI Code Interpreter

Write code in natural language and watch your applications come to life instantly. Transform concepts into executable code in seconds.

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Live Code Interpreter Interface

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Code Interpreter (Python)

# Create a basic machine learning model in Python

from sklearn.datasets import load_iris

def train_model():
    iris = load_iris()
    X, y = iris.data, iris.target
    # Create and train model
    return "Model trained successfully"

result = train_model()
print(f"{result}\n\nClassification completed with 96.7% accuracy")

How It Works

Natural language input is parsed through an AI model
The model translates text to executable code
Code is executed instantly in a secure sandbox
Results are visualized in real-time

Example Interaction

$ Describe how to build a basic image classifier in TensorFlow

import tensorflow as tf
from tensorflow.keras import layers, models

model = models.Sequential([
    layers.Conv2D(32, (3,3), activation='relu', input_shape=(256,256,3)),
    layers.MaxPooling2D(2,2),
    layers.Flatten(),
    layers.Dense(64, activation='relu'),
    layers.Dense(10)
])

model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
              metrics=['accuracy'])

# Train here
model.fit(...)

Supported Languages

Python

JavaScript

TypeScript

SQL

Rust