To upload a custom model to RagaAI Prism, follow these steps:
from raga import *
import datetime
# Generate a unique run name
run_name = "run_name"
# Initialize a test session
test_session = TestSession(
project_name="project_name",
run_name=run_name,
access_key="", # Add your access key
secret_key="", # Add your secret key
host="host_name"
)
# Define infrastructure parameters
infra_params = {
"minReplicas": "1",
"maxReplicas": "1",
"workGroup": "cpu",
"maxMemoryLimit": "3000Mi",
"maxCpuLimit": "3000m",
"minMemoryLimit": "3000Mi",
"minCpuLimit": "3000m",
}
# Define input and output functions
def input_function():
return ""
def output_function():
return ""
# Create and load the model
model = Model(
test_session=test_session,
name="model-name",
version="v1",
description="model-description",
docker_image="model-image",
infra_params=infra_params,
config_params={},
input_func=input_function,
output_func=output_function
)
model.load()
This script sets up and uploads a custom model using the RagaAI Prism platform, allowing you to specify model details, infrastructure, and I/O functions.
Note: Currently, model upload requires the model code to be present and built locally. An upcoming feature will allow you to upload a model directly using a Docker Hub path.