Tirsvad
769c777b48
- Add scripts for generating booking data, building metadata, and updating holidays - Implement public_holidays.py service with holiday lookup functionality - Update CSV data with expanded hotel booking records - Add holidays.json dataset for public holiday dates - Enhance LLM report service with improved formatting - Update metadata domain model and API dependencies - Add test coverage for dataset and public holidays
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
import httpx
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import pytest
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from nf_hotel_api.services.llm_report import LLMReportService, LLMServiceError
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def test_strip_thinking_removes_think_block():
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raw = "<think>internal reasoning that must not leak</think>## Report\nBody text"
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assert LLMReportService._strip_thinking(raw) == "## Report\nBody text"
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def test_strip_thinking_is_noop_when_no_think_block():
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raw = "## Report\nBody text"
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assert LLMReportService._strip_thinking(raw) == raw
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class _FakeResponse:
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def __init__(self, payload: dict, status_code: int = 200) -> None:
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self._payload = payload
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self.status_code = status_code
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def raise_for_status(self) -> None:
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if self.status_code >= 400:
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request = httpx.Request("POST", "http://fake/chat/completions")
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raise httpx.HTTPStatusError(
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"error", request=request, response=httpx.Response(self.status_code, request=request)
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)
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def json(self) -> dict:
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return self._payload
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class _FakeAsyncClient:
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def __init__(self, payload: dict, status_code: int = 200) -> None:
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self._payload = payload
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self._status_code = status_code
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async def __aenter__(self) -> "_FakeAsyncClient":
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return self
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async def __aexit__(self, *args) -> None:
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return None
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async def post(self, *args, **kwargs) -> _FakeResponse:
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return _FakeResponse(self._payload, self._status_code)
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@pytest.mark.asyncio
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async def test_generate_report_strips_thinking_and_returns_content(monkeypatch):
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payload = {
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"choices": [
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{"message": {"content": "<think>hidden</think>## Insights\nBook more direct."}}
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]
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}
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monkeypatch.setattr(
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"nf_hotel_api.services.llm_report.httpx.AsyncClient",
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lambda timeout: _FakeAsyncClient(payload),
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)
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service = LLMReportService(
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base_url="http://fake/v1", api_key="k", model="m", timeout_seconds=1.0
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)
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report = await service.generate_report({"adults": {"mean": 2}})
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assert report == "## Insights\nBook more direct."
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@pytest.mark.asyncio
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async def test_generate_report_raises_llm_service_error_on_bad_response(monkeypatch):
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monkeypatch.setattr(
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"nf_hotel_api.services.llm_report.httpx.AsyncClient",
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lambda timeout: _FakeAsyncClient({"unexpected": "shape"}),
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)
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service = LLMReportService(
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base_url="http://fake/v1", api_key="k", model="m", timeout_seconds=1.0
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)
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with pytest.raises(LLMServiceError):
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await service.generate_report({"adults": {"mean": 2}})
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def _service_with_context(**kwargs):
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from nf_hotel_api.domain.metadata import HotelMetadata, RoomType
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from nf_hotel_api.services.public_holidays import PublicHolidayCalendar
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metadata = HotelMetadata(
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hotel="NF Hotel",
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room_types={"A": RoomType(size="Small", standard_price_per_night=20, room_count=10)},
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)
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return LLMReportService(
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base_url="http://fake/v1", api_key="k", model="m", timeout_seconds=1.0,
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metadata=metadata, holiday_calendar=PublicHolidayCalendar(), **kwargs,
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)
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def test_prompt_lists_public_holidays_for_the_years_in_the_data():
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stats = {"arrival_date": {"min": "2024-01-03T00:00:00", "max": "2024-12-30T00:00:00"}}
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prompt = _service_with_context()._build_prompt(stats)
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assert "Public holidays:" in prompt
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assert "2024-04-13 to 2024-04-16" in prompt
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assert "2023-" not in prompt.split("We have extract")[0]
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def test_prompt_skips_holidays_when_arrival_dates_are_unknown():
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prompt = _service_with_context()._build_prompt({"adults": {"mean": 2}})
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assert "Public holidays" not in prompt
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assert "Room type A: Small" in prompt
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