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# coding=utf-8
# ------------------------------------
# Copyright (c) Microsoft.
# Licensed under the MIT License.
# ------------------------------------
"""
FILE: sample_load_snapshot.py
DESCRIPTION:
This sample demonstrates how to load a **trained model snapshot** in a Text Authoring project.
USAGE:
python sample_load_snapshot.py
REQUIRED ENV VARS (for AAD / DefaultAzureCredential):
AZURE_TEXT_ENDPOINT
AZURE_CLIENT_ID
AZURE_TENANT_ID
AZURE_CLIENT_SECRET
NOTE:
If you want to use AzureKeyCredential instead, set:
- AZURE_TEXT_ENDPOINT
- AZURE_TEXT_KEY
OPTIONAL ENV VARS:
PROJECT_NAME # defaults to "<project-name>"
TRAINED_MODEL_LABEL # defaults to "<trained-model-label>"
"""
# [START text_authoring_load_snapshot]
import os
from azure.identity import DefaultAzureCredential
from azure.core.exceptions import HttpResponseError
from azure.ai.textanalytics.authoring import TextAuthoringClient
def sample_load_snapshot():
# settings
endpoint = os.environ["AZURE_TEXT_ENDPOINT"]
project_name = os.environ.get("PROJECT_NAME", "<project-name>")
trained_model_label = os.environ.get("TRAINED_MODEL_LABEL", "<trained-model-label>")
# create a client with AAD
credential = DefaultAzureCredential()
client = TextAuthoringClient(endpoint, credential=credential)
# project-scoped client
project_client = client.get_project_client(project_name)
# start load snapshot (LRO) and handle success/error
poller = project_client.trained_model.begin_load_snapshot(trained_model_label)
try:
poller.result() # completes with None; raises on failure
print("Load snapshot completed.")
print(f"done: {poller.done()}")
print(f"status: {poller.status()}")
except HttpResponseError as e:
print(f"Operation failed: {e.message}")
print(e.error)
# [END text_authoring_load_snapshot]
def main():
sample_load_snapshot()
if __name__ == "__main__":
main()
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