Quickstart

pip install plexe

import plexe

# Create a model in seconds
model_version = plexe.build(
    goal="predict house prices based on property features",
    model_name="house-price-predictor",
    data_files="housing_data.csv"
)

# Make predictions
result = plexe.infer(
    model_name="house-price-predictor",
    model_version=model_version,
    input_data={
        "square_footage": 2000,
        "bedrooms": 3,
        "location": "suburban"
    }
)

results = plexe.batch_infer(
    model_name="house-price-predictor",
    model_version=model_version,
    inputs=[
        {"square_footage": 2000, "bedrooms": 3, "location": "suburban"},
        {"square_footage": 1500, "bedrooms": 2, "location": "urban"}
    ]
)

async def main():
    model_version = await plexe.abuild(
        goal="predict house prices",
        model_name="house-price-predictor",
        data_files="housing_data.csv"
    )
    
    result = await plexe.ainfer(
        model_name="house-price-predictor",
        model_version=model_version,
        input_data={"square_footage": 2000, "bedrooms": 3}
    )

from plexe import PlexeAI

with PlexeAI(api_key="your_api_key_here") as client:
    # Upload data
    upload_id = client.upload_files("housing_data.csv")
    
    # Create and use model
    model_version = client.build(
        goal="predict house prices",
        model_name="house-price-predictor",
        upload_id=upload_id
    )