Spaces:
Sleeping
Sleeping
File size: 4,326 Bytes
0908f70 b76f199 0908f70 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 | """HTTP tests for POST /content/similar (library + draft overlap)."""
import pytest
from app.db.models import Document, IngestStatus
from app.models.schemas import SearchResult
class _FakeVS:
"""Vector store returning fixed chunks (no FAISS on disk)."""
def __init__(self, rows: list[SearchResult]) -> None:
self._rows = rows
def search(self, query: str, tenant_id: str, k: int = 10, **kwargs: object) -> list[SearchResult]:
return self._rows
@pytest.mark.asyncio
async def test_content_similar_returns_library_and_filename(
async_client: object,
test_db: object,
monkeypatch: pytest.MonkeyPatch,
) -> None:
doc_id = "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"
tenant = "tenant_test"
doc = Document(
id=doc_id,
tenant_id=tenant,
filename="rics_guidance.pdf",
file_path="/tmp/rics_guidance.pdf",
status=IngestStatus.complete,
)
test_db.add(doc)
await test_db.commit()
hits = [
SearchResult(
chunk_id="chunk-1",
doc_id=doc_id,
tenant_id=tenant,
text="Approved Document guidance on damp proof courses and minimum heights",
score=0.35,
section_type="paragraph",
),
]
monkeypatch.setattr(
"app.services.content_similarity.get_vectorstore",
lambda: _FakeVS(hits),
)
res = await async_client.post(
"/content/similar",
json={
"text": "damp proof course minimum height regulations above ground level",
"section_code": "E4",
"peer_sections": {},
},
headers={"X-Tenant-ID": tenant},
)
assert res.status_code == 200
data = res.json()
assert len(data["library_matches"]) == 1
assert data["library_matches"][0]["document_id"] == doc_id
assert data["library_matches"][0]["filename"] == "rics_guidance.pdf"
assert "damp" in data["library_matches"][0]["snippet"].lower()
@pytest.mark.asyncio
async def test_content_similar_excludes_document_ids(
async_client: object,
test_db: object,
monkeypatch: pytest.MonkeyPatch,
) -> None:
doc_id = "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb"
tenant = "tenant_test"
doc = Document(
id=doc_id,
tenant_id=tenant,
filename="survey.docx",
file_path="/tmp/survey.docx",
status=IngestStatus.complete,
)
test_db.add(doc)
await test_db.commit()
hits = [
SearchResult(
chunk_id="c1",
doc_id=doc_id,
tenant_id=tenant,
text="Only chunk from excluded survey file",
score=0.9,
section_type="paragraph",
),
]
monkeypatch.setattr(
"app.services.content_similarity.get_vectorstore",
lambda: _FakeVS(hits),
)
res = await async_client.post(
"/content/similar",
json={
"text": "matching text long enough for library search twelve",
"section_code": "D",
"peer_sections": {},
"exclude_document_ids": [doc_id],
},
headers={"X-Tenant-ID": tenant},
)
assert res.status_code == 200
data = res.json()
assert data["library_matches"] == []
assert "excluded" in data["message"].lower() or "filters" in data["message"].lower()
@pytest.mark.asyncio
async def test_content_similar_draft_overlap_without_library(
async_client: object,
monkeypatch: pytest.MonkeyPatch,
) -> None:
monkeypatch.setattr(
"app.services.content_similarity.get_vectorstore",
lambda: _FakeVS([]),
)
text = (
"planning permission required for loft conversion and rear extension "
"under permitted development rules"
)
peer = (
"planning permission required for loft conversion and rear extension "
"under permitted development rules 2024 update"
)
res = await async_client.post(
"/content/similar",
json={
"text": text,
"section_code": "E2",
"peer_sections": {"I1": peer},
},
headers={"X-Tenant-ID": "tenant_test"},
)
assert res.status_code == 200
data = res.json()
assert data["draft_overlaps"]
assert data["draft_overlaps"][0]["other_section_code"] == "I1"
|