進捗を評価し、受け入れを判断する

# Continue with a TrainingProject whose run has completed.
result = project.evaluate(split="test")
for criterion in result["criteria"]:
    print(criterion["id"], criterion["score"], criterion["accepted"])
print("Accepted:", result["accepted"], "Report:", result["report_path"])
# Scores measure the registered criteria; they do not guarantee broader capability.

import os
from fusionpointai_training import TrainingClient

client = TrainingClient(api_key=os.environ["FUSIONPOINTAI_API_KEY"])
session = client.get_session(os.environ["FUSIONPOINTAI_SESSION_ID"])
server_report = session.get("report")
runtime_report = server_report.get("runtime") if isinstance(server_report, dict) else None
if (
    session.get("status") == "completed"
    and isinstance(runtime_report, dict)
    and runtime_report.get("artifact_sha256") == os.environ["LOCAL_ARTIFACT_SHA256"]
    and server_report.get("delivery") == "runtime_local"
    and server_report.get("verification") == "runtime_reported"
):
    print("Server report matches the local artifact digest.")
else:
    print("Completion is not confirmed for this local artifact.")
# Reconcile by reading state; do not repeat training or invent a result.