def test_query_properties_match_and_rank(self):
query_model = QueryModel(
query_properties=[
QueryRankingFeature(name="query_vector",
mapping=lambda x: [1, 2, 3])
],
match_phase=OR(),
rank_profile=RankProfile(name="bm25", list_features=True),
)
self.assertDictEqual(
query_model.create_body(query=self.query),
{
"yql":
'select * from sources * where ([{"grammar": "any"}]userInput("this is a test"));',
"ranking": {
"profile": "bm25",
"listFeatures": "true"
},
"ranking.features.query(query_vector)": "[1, 2, 3]",
},
)
query_model = QueryModel(
query_properties=[
QueryRankingFeature(name="query_vector",
mapping=lambda x: [1, 2, 3])
],
match_phase=ANN(
doc_vector="doc_vector",
query_vector="query_vector",
hits=10,
label="label",
),
rank_profile=RankProfile(name="bm25", list_features=True),
)
self.assertDictEqual(
query_model.create_body(query=self.query),
{
"yql":
'select * from sources * where ([{"targetNumHits": 10, "label": "label", "approximate": true}]nearestNeighbor(doc_vector, query_vector));',
"ranking": {
"profile": "bm25",
"listFeatures": "true"
},
"ranking.features.query(query_vector)": "[1, 2, 3]",
},
)
def test_collect_training_data_point(self):
self.app.query = Mock(side_effect=[
VespaResult(self.raw_vespa_result_recall),
VespaResult(self.raw_vespa_result_additional),
])
query_model = QueryModel(rank_profile=RankProfile(list_features=True))
data = self.app.collect_training_data_point(
query="this is a query",
query_id="123",
relevant_id="abc",
id_field="vespa_id_field",
query_model=query_model,
number_additional_docs=2,
fields=["rankfeatures", "title"],
timeout="15s",
)
self.assertEqual(self.app.query.call_count, 2)
self.app.query.assert_has_calls([
call(
query="this is a query",
query_model=query_model,
recall=("vespa_id_field", ["abc"]),
timeout="15s",
),
call(
query="this is a query",
query_model=query_model,
hits=2,
timeout="15s",
),
])
expected_data = [
{
"document_id": "abc",
"query_id": "123",
"label": 1,
"a": 1,
"b": 2,
"title": "this is a title",
},
{
"document_id": "def",
"query_id": "123",
"label": 0,
"a": 3,
"b": 4,
"title": "this is a title 2",
},
{
"document_id": "ghi",
"query_id": "123",
"label": 0,
"a": 5,
"b": 6,
"title": "this is a title 3",
},
]
self.assertEqual(data, expected_data)
def test_query(self):
app = Vespa(url="http://localhost", port=8080)
body = {"yql": "select * from sources * where test"}
self.assertDictEqual(
app.query(body=body, debug_request=True).request_body, body)
self.assertDictEqual(
app.query(
query="this is a test",
query_model=Query(match_phase=OR(),
rank_profile=RankProfile()),
debug_request=True,
hits=10,
).request_body,
{
"yql":
'select * from sources * where ([{"grammar": "any"}]userInput("this is a test"));',
"ranking": {
"profile": "default",
"listFeatures": "false"
},
"hits": 10,
},
)
self.assertDictEqual(
app.query(
query="this is a test",
query_model=Query(match_phase=OR(),
rank_profile=RankProfile()),
debug_request=True,
hits=10,
recall=("id", [1, 5]),
).request_body,
{
"yql":
'select * from sources * where ([{"grammar": "any"}]userInput("this is a test"));',
"ranking": {
"profile": "default",
"listFeatures": "false"
},
"hits": 10,
"recall": "+(id:1 id:5)",
},
)
def test_collect_training_data(self):
mock_return_value = [
{
"document_id": "abc",
"query_id": "123",
"relevant": 1,
"a": 1,
"b": 2,
},
{
"document_id": "def",
"query_id": "123",
"relevant": 0,
"a": 3,
"b": 4,
},
{
"document_id": "ghi",
"query_id": "123",
"relevant": 0,
"a": 5,
"b": 6,
},
]
self.app.collect_training_data_point = Mock(
return_value=mock_return_value)
labelled_data = [{
"query_id": 123,
"query": "this is a query",
"relevant_docs": [{
"id": "abc",
"score": 1
}],
}]
query_model = Query(rank_profile=RankProfile(list_features=True))
data = self.app.collect_training_data(
labelled_data=labelled_data,
id_field="vespa_id_field",
query_model=query_model,
number_additional_docs=2,
timeout="15s",
)
self.app.collect_training_data_point.assert_has_calls([
call(
query="this is a query",
query_id=123,
relevant_id="abc",
id_field="vespa_id_field",
query_model=query_model,
number_additional_docs=2,
relevant_score=1,
default_score=0,
timeout="15s",
)
])
assert_frame_equal(data, DataFrame.from_records(mock_return_value))
def test_collect_training_data_point_0_recall_hits(self):
self.raw_vespa_result_recall = {
"root": {
"id": "toplevel",
"relevance": 1.0,
"fields": {
"totalCount": 0
},
"coverage": {
"coverage": 100,
"documents": 62529,
"full": True,
"nodes": 2,
"results": 1,
"resultsFull": 1,
},
}
}
self.app.query = Mock(side_effect=[
VespaQueryResponse(
self.raw_vespa_result_recall, status_code=None, url=None),
VespaQueryResponse(
self.raw_vespa_result_additional, status_code=None, url=None),
])
query_model = QueryModel(rank_profile=RankProfile(list_features=True))
data = self.app.collect_training_data_point(
query="this is a query",
query_id="123",
relevant_id="abc",
id_field="vespa_id_field",
query_model=query_model,
number_additional_docs=2,
fields=["rankfeatures"],
timeout="15s",
)
self.assertEqual(self.app.query.call_count, 1)
self.app.query.assert_has_calls([
call(
query="this is a query",
query_model=query_model,
recall=("vespa_id_field", ["abc"]),
timeout="15s",
),
])
expected_data = []
self.assertEqual(data, expected_data)
def test_match_and_rank(self):
query = Query(
match_phase=ANN(
doc_vector="doc_vector",
query_vector="query_vector",
embedding_model=lambda x: [1, 2, 3],
hits=10,
label="label",
),
rank_profile=RankProfile(name="bm25", list_features=True),
)
self.assertDictEqual(
query.create_body(query=self.query),
{
"yql":
'select * from sources * where ([{"targetNumHits": 10, "label": "label"}]nearestNeighbor(doc_vector, query_vector));',
"ranking": {
"profile": "bm25",
"listFeatures": "true"
},
"ranking.features.query(query_vector)": "[1, 2, 3]",
},
)
def test_rank_profile(self):
rank_profile = RankProfile(name="rank_profile", list_features=True)
self.assertEqual(rank_profile.name, "rank_profile")
self.assertEqual(rank_profile.list_features, "true")