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Commit 58b82c0

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fixed extra fetches
1 parent b9338c6 commit 58b82c0

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2 files changed

+7
-7
lines changed

2 files changed

+7
-7
lines changed

test2text/pages/reports/report_by_tc.py

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -77,11 +77,11 @@ def write_requirements(current_requirements: set[tuple]):
7777
if distance_sql:
7878
tc_dict = {
7979
f"{test_case} [smart search d={round_distance(distance)}]": tc_id
80-
for (tc_id, _, test_case, distance) in data.fetchall()
80+
for (tc_id, _, test_case, distance) in data
8181
}
8282
else:
8383
tc_dict = {
84-
test_case: tc_id for (tc_id, _, test_case) in data.fetchall()
84+
test_case: tc_id for (tc_id, _, test_case) in data
8585
}
8686

8787
st.subheader("Choose ONE of filtered test cases")

test2text/services/visualisation/visualize_vectors.py

Lines changed: 5 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -15,11 +15,11 @@
1515

1616
def extract_annotation_vectors(db: DbClient):
1717
vectors = []
18-
embeddings = db.get_column_values("embedding", "Annotations")
19-
if embeddings.fetchone() is None:
18+
embeddings = db.get_column_values("embedding", from_table="Annotations")
19+
if not embeddings:
2020
st.error("Embeddings is empty. Please fill embeddings in annotations.")
2121
return None
22-
for row in embeddings.fetchall():
22+
for row in embeddings:
2323
if row[0] is not None:
2424
vectors.append(np.array(unpack_float32(row[0])))
2525
return np.array(vectors)
@@ -38,11 +38,11 @@ def extract_closest_annotation_vectors(db: DbClient):
3838

3939
def extract_requirement_vectors(db: DbClient):
4040
vectors = []
41-
embeddings = db.get_column_values("embedding", "Requirements")
41+
embeddings = db.get_column_values("embedding", from_table="Requirements")
4242
if embeddings.fetchone() is None:
4343
st.error("Embeddings is empty. Please fill embeddings in requirements.")
4444
return None
45-
for row in embeddings.fetchall():
45+
for row in embeddings:
4646
vectors.append(np.array(unpack_float32(row[0])))
4747
return np.array(vectors)
4848

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