truss

import truss import os import pathlib import shutil # Define model name and directory model_name = "my_truss_model" model_dir = pathlib.Path(f"./{model_name}") # Clean up previous runs if any if model_dir.exists(): shutil.rmtree(model_dir) # Initialize a new Truss model structure, creating the directory truss.init(model_name) # Modify the model.py file to add a simple predict function model_py_path = model_dir / "model" / "model.py" with open(model_py_path, "w") as f: f.write(""" import os class Model: def __init__(self): self._data = None def load(self): # Simulate loading a model artifact or configuration self._data = os.environ.get("TRUSS_MODEL_CONFIG", "default_config_value") def predict(self, model_input): return f"Hello, {model_input}! Model loaded with config: {self._data}" """) print(f"Truss model initialized in: {model_dir.resolve()}") print(f"To serve locally: Change directory to '{model_name}' (cd {model_name}) and run 'truss serve' in your terminal.") # To clean up the created model directory (uncomment to run): # shutil.rmtree(model_dir)