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perf：优化webui交互体验，优化统计逻辑，优化log展示

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SengokuCola
2026-05-07 00:05:35 +08:00
parent 1bb6f514e7
commit 5846f6e0c4
41 changed files with 1723 additions and 619 deletions
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332
pytests/webui/test_statistics_service.py Normal file
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from contextlib import contextmanager
from datetime import datetime, timedelta
from types import SimpleNamespace
from typing import Any, Iterator
import pytest
from src.services import statistics_service
from src.webui.schemas.statistics import DashboardData, StatisticsSummary, TimeSeriesData
class _Result:
def __init__(self, *, first_value: Any = None, all_values: list[Any] | None = None) -> None:
self._first_value = first_value
self._all_values = all_values or []
def first(self) -> Any:
return self._first_value
def all(self) -> list[Any]:
return self._all_values
class _Session:
def __init__(self, results: list[_Result]) -> None:
self._results = results
def exec(self, statement: Any) -> _Result:
del statement
return self._results.pop(0)
class _MemoryStore:
def __init__(self) -> None:
self.store: dict[str, Any] = {}
def __getitem__(self, item: str) -> Any:
return self.store.get(item)
def __setitem__(self, key: str, value: Any) -> None:
self.store[key] = value
def _patch_session_results(monkeypatch: pytest.MonkeyPatch, results: list[_Result]) -> list[bool]:
auto_commit_calls: list[bool] = []
@contextmanager
def _fake_get_db_session(auto_commit: bool = True) -> Iterator[_Session]:
auto_commit_calls.append(auto_commit)
yield _Session([results.pop(0)])
monkeypatch.setattr(statistics_service, "get_db_session", _fake_get_db_session)
return auto_commit_calls
def _patch_session_result_group(monkeypatch: pytest.MonkeyPatch, results: list[_Result]) -> list[bool]:
auto_commit_calls: list[bool] = []
@contextmanager
def _fake_get_db_session(auto_commit: bool = True) -> Iterator[_Session]:
auto_commit_calls.append(auto_commit)
yield _Session(results)
monkeypatch.setattr(statistics_service, "get_db_session", _fake_get_db_session)
return auto_commit_calls
def _build_dashboard_data(total_requests: int = 1) -> DashboardData:
return DashboardData(
summary=StatisticsSummary(total_requests=total_requests),
model_stats=[],
hourly_data=[],
daily_data=[],
recent_activity=[],
)
def _build_dashboard_data_with_time_series() -> DashboardData:
return DashboardData(
summary=StatisticsSummary(total_requests=1),
model_stats=[],
hourly_data=[
TimeSeriesData(timestamp="2026-05-06T10:00:00", requests=0, cost=0.0, tokens=0),
TimeSeriesData(timestamp="2026-05-06T11:00:00", requests=2, cost=0.5, tokens=50),
TimeSeriesData(timestamp="2026-05-06T12:00:00", requests=0, cost=0.0, tokens=0),
],
daily_data=[
TimeSeriesData(timestamp="2026-05-05T00:00:00", requests=0, cost=0.0, tokens=0),
TimeSeriesData(timestamp="2026-05-06T00:00:00", requests=3, cost=0.7, tokens=70),
],
recent_activity=[],
)
def test_shared_fetch_queries_disable_auto_commit(monkeypatch: pytest.MonkeyPatch) -> None:
now = datetime(2026, 5, 6, 12, 0, 0)
online_record = SimpleNamespace(start_timestamp=now - timedelta(minutes=5), end_timestamp=now)
usage_record = SimpleNamespace(
timestamp=now,
request_type="chat.reply",
model_api_provider_name="provider",
model_assign_name="chat-main",
model_name="gpt-a",
prompt_tokens=10,
completion_tokens=5,
cost=0.01,
time_cost=1.2,
)
message_record = SimpleNamespace(timestamp=now, message_id="msg-1")
tool_record = SimpleNamespace(timestamp=now, tool_name="reply")
auto_commit_calls = _patch_session_results(
monkeypatch,
[
_Result(all_values=[online_record]),
_Result(all_values=[usage_record]),
_Result(all_values=[message_record]),
_Result(all_values=[tool_record]),
],
)
online_ranges = statistics_service.fetch_online_time_since(now - timedelta(hours=1))
usage_records = statistics_service.fetch_model_usage_since(now - timedelta(hours=1))
messages = statistics_service.fetch_messages_since(now - timedelta(hours=1))
tool_records = statistics_service.fetch_tool_records_since(now - timedelta(hours=1))
assert online_ranges == [(online_record.start_timestamp, online_record.end_timestamp)]
assert usage_records == [
{
"timestamp": now,
"request_type": "chat.reply",
"model_api_provider_name": "provider",
"model_assign_name": "chat-main",
"model_name": "gpt-a",
"prompt_tokens": 10,
"completion_tokens": 5,
"cost": 0.01,
"time_cost": 1.2,
}
]
assert messages == [message_record]
assert tool_records == [tool_record]
assert auto_commit_calls == [False, False, False, False]
def test_get_earliest_statistics_time_uses_min_valid_timestamp(monkeypatch: pytest.MonkeyPatch) -> None:
fallback_time = datetime(2026, 5, 6, 12, 0, 0)
earliest_time = datetime(2026, 5, 1, 8, 30, 0)
auto_commit_calls = _patch_session_result_group(
monkeypatch,
[
_Result(first_value=datetime(2026, 5, 3, 9, 0, 0)),
_Result(first_value=earliest_time),
_Result(first_value=None),
_Result(first_value=datetime(2026, 5, 2, 9, 0, 0)),
],
)
result = statistics_service.get_earliest_statistics_time(fallback_time)
assert result == earliest_time
assert auto_commit_calls == [False]
def test_get_earliest_statistics_time_falls_back_when_query_fails(monkeypatch: pytest.MonkeyPatch) -> None:
fallback_time = datetime(2026, 5, 6, 12, 0, 0)
@contextmanager
def _fake_get_db_session(auto_commit: bool = True) -> Iterator[_Session]:
del auto_commit
raise RuntimeError("database unavailable")
yield _Session([])
monkeypatch.setattr(statistics_service, "get_db_session", _fake_get_db_session)
assert statistics_service.get_earliest_statistics_time(fallback_time) == fallback_time
def test_dashboard_statistics_cache_roundtrip(monkeypatch: pytest.MonkeyPatch) -> None:
memory_store = _MemoryStore()
now = datetime.now()
dashboard_data = _build_dashboard_data(total_requests=7)
monkeypatch.setattr(statistics_service, "local_storage", memory_store)
statistics_service.store_dashboard_statistics_cache({24: dashboard_data}, generated_at=now)
cached_data = statistics_service.get_cached_dashboard_statistics(24)
assert cached_data is not None
assert cached_data.summary.total_requests == 7
def test_dashboard_statistics_cache_stores_sparse_time_series(monkeypatch: pytest.MonkeyPatch) -> None:
memory_store = _MemoryStore()
generated_at = datetime(2026, 5, 6, 12, 0, 0)
dashboard_data = _build_dashboard_data_with_time_series()
monkeypatch.setattr(statistics_service, "local_storage", memory_store)
statistics_service.store_dashboard_statistics_cache({2: dashboard_data}, generated_at=generated_at)
raw_cache = memory_store[statistics_service.DASHBOARD_STATISTICS_CACHE_KEY]
raw_entry = raw_cache["entries"]["2"]
assert raw_entry["sparse"] is True
assert raw_entry["hourly_data"] == [
{"timestamp": "2026-05-06T11:00:00", "requests": 2, "cost": 0.5, "tokens": 50}
]
assert raw_entry["daily_data"] == [
{"timestamp": "2026-05-06T00:00:00", "requests": 3, "cost": 0.7, "tokens": 70}
]
cached_data = statistics_service.get_cached_dashboard_statistics(2, max_age_seconds=10**9)
assert cached_data is not None
assert [item.timestamp for item in cached_data.hourly_data] == [
"2026-05-06T10:00:00",
"2026-05-06T11:00:00",
"2026-05-06T12:00:00",
]
assert cached_data.hourly_data[0].requests == 0
assert cached_data.hourly_data[1].requests == 2
assert cached_data.hourly_data[2].requests == 0
@pytest.mark.asyncio
async def test_get_dashboard_statistics_prefers_cache(monkeypatch: pytest.MonkeyPatch) -> None:
memory_store = _MemoryStore()
dashboard_data = _build_dashboard_data(total_requests=9)
monkeypatch.setattr(statistics_service, "local_storage", memory_store)
statistics_service.store_dashboard_statistics_cache({24: dashboard_data}, generated_at=datetime.now())
async def _fail_compute_dashboard_statistics(hours: int = 24) -> DashboardData:
del hours
raise AssertionError("cache should be used")
monkeypatch.setattr(statistics_service, "compute_dashboard_statistics", _fail_compute_dashboard_statistics)
result = await statistics_service.get_dashboard_statistics(24)
assert result.summary.total_requests == 9
@pytest.mark.asyncio
async def test_get_dashboard_statistics_returns_empty_when_cache_missing(monkeypatch: pytest.MonkeyPatch) -> None:
memory_store = _MemoryStore()
monkeypatch.setattr(statistics_service, "local_storage", memory_store)
async def _fail_compute_dashboard_statistics(hours: int = 24) -> DashboardData:
del hours
raise AssertionError("dashboard API should not compute fallback data")
monkeypatch.setattr(statistics_service, "compute_dashboard_statistics", _fail_compute_dashboard_statistics)
result = await statistics_service.get_dashboard_statistics(24)
assert result.summary.total_requests == 0
assert result.model_stats == []
@pytest.mark.asyncio
async def test_get_summary_statistics_aggregates_database_and_message_counts(monkeypatch: pytest.MonkeyPatch) -> None:
start_time = datetime(2026, 5, 6, 10, 0, 0)
end_time = datetime(2026, 5, 6, 12, 0, 0)
online_records = [
SimpleNamespace(
start_timestamp=start_time - timedelta(minutes=30),
end_timestamp=start_time + timedelta(minutes=30),
),
SimpleNamespace(
start_timestamp=start_time + timedelta(hours=1),
end_timestamp=end_time + timedelta(minutes=30),
),
]
auto_commit_calls = _patch_session_results(
monkeypatch,
[
_Result(first_value=(3, 1.5, 900, 2.5)),
_Result(all_values=online_records),
],
)
def _fake_count_messages(**kwargs: Any) -> int:
return 5 if kwargs.get("has_reply_to") is None else 2
monkeypatch.setattr(statistics_service, "count_messages", _fake_count_messages)
summary = await statistics_service.get_summary_statistics(start_time, end_time)
assert summary.total_requests == 3
assert summary.total_cost == 1.5
assert summary.total_tokens == 900
assert summary.avg_response_time == 2.5
assert summary.online_time == 5400
assert summary.total_messages == 5
assert summary.total_replies == 2
assert summary.cost_per_hour == pytest.approx(1.0)
assert summary.tokens_per_hour == pytest.approx(600.0)
assert auto_commit_calls == [False, False]
@pytest.mark.asyncio
async def test_get_model_statistics_groups_by_display_model_name(monkeypatch: pytest.MonkeyPatch) -> None:
now = datetime(2026, 5, 6, 12, 0, 0)
records = [
SimpleNamespace(
model_assign_name="chat-main",
model_name="gpt-a",
cost=0.4,
total_tokens=100,
time_cost=2.0,
),
SimpleNamespace(
model_assign_name="chat-main",
model_name="gpt-a",
cost=0.6,
total_tokens=200,
time_cost=4.0,
),
SimpleNamespace(
model_assign_name=None,
model_name="gpt-b",
cost=0.2,
total_tokens=50,
time_cost=0.0,
),
]
_patch_session_results(monkeypatch, [_Result(all_values=records)])
stats = await statistics_service.get_model_statistics(now - timedelta(hours=24))
assert [item.model_name for item in stats] == ["chat-main", "gpt-b"]
assert stats[0].request_count == 2
assert stats[0].total_cost == pytest.approx(1.0)
assert stats[0].total_tokens == 300
assert stats[0].avg_response_time == pytest.approx(3.0)
assert stats[1].avg_response_time == 0.0

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pytests/webui/test_system_routes.py Normal file
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from src.webui.routers import system
def test_is_newer_version_detects_patch_update() -> None:
assert system._is_newer_version("1.0.7", "1.0.6") is True
def test_is_newer_version_ignores_same_version_with_shorter_parts() -> None:
assert system._is_newer_version("1.0.0", "1.0") is False
def test_is_newer_version_handles_unknown_current_version() -> None:
assert system._is_newer_version("1.0.7", "unknown") is False