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unslothai--unsloth/studio/backend/tests/test_training_history_update.py
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chore: import upstream snapshot with attribution
2026-07-13 12:59:56 +08:00

137 lines
4.3 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
import asyncio
import os
import sys
import pytest
from pydantic import ValidationError
_backend = os.path.join(os.path.dirname(__file__), "..")
sys.path.insert(0, _backend)
from models.training import TrainingRunUpdateRequest
from routes import training_history
BASE_RUN = {
"id": "run-1",
"status": "stopped",
"model_name": "unsloth/test-model",
"dataset_name": "test-dataset",
"display_name": "Existing name",
"started_at": "2026-01-01T00:00:00Z",
"ended_at": "2026-01-01T00:01:00Z",
"total_steps": 10,
"final_step": 5,
"output_dir": "/tmp/run-1",
"resumed_later": False,
}
def _patch_run(monkeypatch: pytest.MonkeyPatch, payload: TrainingRunUpdateRequest):
stored = dict(BASE_RUN)
calls: list[str | None] = []
def fake_get_run(run_id: str):
assert run_id == "run-1"
return dict(stored)
def fake_update_run_display_name(run_id: str, display_name: str | None):
assert run_id == "run-1"
calls.append(display_name)
stored["display_name"] = display_name
monkeypatch.setattr(training_history, "get_run", fake_get_run)
monkeypatch.setattr(
training_history,
"update_run_display_name",
fake_update_run_display_name,
)
monkeypatch.setattr(training_history, "can_resume_run", lambda run: True)
result = asyncio.run(
training_history.update_training_run(
"run-1",
payload,
current_subject = "test-user",
)
)
return result, calls
def test_update_run_omitted_display_name_is_noop(monkeypatch: pytest.MonkeyPatch):
result, calls = _patch_run(monkeypatch, TrainingRunUpdateRequest.model_validate({}))
assert calls == []
assert result.display_name == "Existing name"
assert result.can_resume is True
def test_update_run_explicit_null_clears_display_name(monkeypatch: pytest.MonkeyPatch):
result, calls = _patch_run(
monkeypatch,
TrainingRunUpdateRequest.model_validate({"display_name": None}),
)
assert calls == [None]
assert result.display_name is None
assert result.can_resume is True
def test_update_run_whitespace_clears_display_name(monkeypatch: pytest.MonkeyPatch):
result, calls = _patch_run(
monkeypatch,
TrainingRunUpdateRequest.model_validate({"display_name": " "}),
)
assert calls == [None]
assert result.display_name is None
def test_get_run_detail_includes_preview_fields(monkeypatch: pytest.MonkeyPatch):
# Regression: detail/update must pass the sharing flag into _preview_fields;
# a missing arg used to surface as a 500 TypeError after get_run succeeded.
monkeypatch.setattr(training_history, "get_run", lambda run_id: dict(BASE_RUN))
monkeypatch.setattr(training_history, "get_run_metrics", lambda run_id: {})
monkeypatch.setattr(training_history, "can_resume_run", lambda run: False)
monkeypatch.setattr(training_history, "get_preview_sharing_enabled", lambda: True)
detail = asyncio.run(
training_history.get_training_run_detail("run-1", current_subject = "test-user")
)
assert detail.run.id == "run-1"
# Not a previewable dir, so no signed ref - but the field is built without error.
assert detail.run.preview_sig is None
def test_update_run_rejects_unknown_fields():
with pytest.raises(ValidationError):
TrainingRunUpdateRequest.model_validate({"unknown": "value"})
def test_update_run_rejects_overlong_display_name():
with pytest.raises(ValidationError):
TrainingRunUpdateRequest.model_validate({"display_name": "x" * 121})
def test_sanitize_db_config_strips_subject_and_secrets():
# config_json is returned by run-history GET to any authenticated user, so the run
# owner's subject (username / API-key id) and secrets must never be persisted.
from core.training.training import _sanitize_db_config
db = _sanitize_db_config(
{
"model_name": "unsloth/test-model",
"subject": "alice@example.com",
"hf_token": "hf_secret",
"wandb_token": "wb_secret",
"lora_r": 16,
}
)
assert "subject" not in db
assert "hf_token" not in db and "wandb_token" not in db
assert db["model_name"] == "unsloth/test-model" and db["lora_r"] == 16