feat: Added HNSW early termination policy by glookka · Pull Request #138 · manticoresoftware/columnar

glookka · 2026-03-05T08:31:30Z

No description provided.

github-actions · 2026-03-05T09:03:17Z

Linux debug test results

8 files 8 suites 12m 57s ⏱️
508 tests 485 ✅ 23 💤 0 ❌
522 runs 499 ✅ 23 💤 0 ❌

Results for commit dc418d9.

♻️ This comment has been updated with latest results.

github-actions · 2026-03-05T09:06:52Z

Windows test results

5 files 5 suites 18m 0s ⏱️
488 tests 471 ✅ 17 💤 0 ❌
496 runs 479 ✅ 17 💤 0 ❌

Results for commit dc418d9.

♻️ This comment has been updated with latest results.

github-actions · 2026-03-05T09:09:03Z

Linux release test results

8 files 8 suites 6m 30s ⏱️
508 tests 491 ✅ 17 💤 0 ❌
522 runs 505 ✅ 17 💤 0 ❌

Results for commit dc418d9.

♻️ This comment has been updated with latest results.

github-actions · 2026-03-05T09:28:40Z

clt

❌ CLT tests in test/clt-tests/mcl/
✅ OK: 14
❌ Failed: 2
⏳ Duration: 519s
👉 Check Action Results for commit 2482a7c

Failed tests:

🔧 Edit failed tests in UI:

test/clt-tests/mcl/auto-embeddings-from-vector-check.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd --stopwait > /dev/null; stdbuf -oL searchd ${SEARCHD_ARGS:-} > /dev/null
––– output –––
OK
––– input –––
if timeout 10 grep -qm1 'accepting connections' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Accepting connections!'; else echo 'Timeout or failed!'; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title1 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title2 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title2 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table1 FROM test_from_title1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table2 FROM test_from_title2"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title1_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title2_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(2, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print "consistent_md5: " $1}'
––– output –––
OK
––– input –––
MD5_TITLE1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_TITLE2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "title1_md5: $MD5_TITLE1"; echo "title2_md5: $MD5_TITLE2"; if [ "$MD5_TITLE1" != "$MD5_TITLE2" ]; then echo "SUCCESS: FROM clause produces different vectors"; else echo "FAIL: FROM clause produces same vectors"; fi
––– output –––
OK
––– input –––
MD5_SAME1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SAME2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "same_input_md5_1: $MD5_SAME1"; echo "same_input_md5_2: $MD5_SAME2"; if [ "$MD5_SAME1" = "$MD5_SAME2" ]; then echo "SUCCESS: Same input produces same vector"; else echo "FAIL: Same input produces different vectors"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'invalid-model-name' FROM = 'title1') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_field (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from_specified (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_set_to_empty (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = '') " 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_from_set_to_empty': 'from' setting empty for KNN attribute 'embedding_vector'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_multi_from (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1, title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_multi_from (id, title1, title2) VALUES(1, 'deep learning neural networks', 'computer vision algorithms')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "multi_field_md5: " $1}'
––– output –––
OK
––– input –––
MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Multi-field FROM produces different vector"; else echo "INFO: Multi-field vs single-field comparison"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') "
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_no_from (id, title1) VALUES(1, 'test title')"; echo $?
––– output –––
OK

test/clt-tests/mcl/auto-embeddings-error-handling.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd $SEARCHD_FLAGS > /dev/null; if timeout 10 grep -qm1 '\[BUDDY\] started' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Buddy started!'; else echo 'Timeout or failed!'; cat /var/log/manticore/searchd.log;fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' KNN_DIMS='384'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)" 2>&1
# Check if table was actually created
mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_dims'" | grep -q "test_dims" && echo "Table created" || echo "Table not created"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_auto_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_auto_dims (id, title) VALUES (1, 'Test document')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    FROM='title'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM=''
)" 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_empty_from': 'from' setting empty for KNN attribute 'vec'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='non-existent-model/invalid-name'
    FROM='title'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_prefix (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='all-MiniLM-L6-v2'
    FROM='content_text'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='non_existent_field'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_circular (
    title TEXT,
    vec1 FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='vec1'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (1, '')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (2, NULL)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_empty"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_rowwise (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_rowwise (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_rowwise; OPTIMIZE TABLE test_rowwise OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_rowwise WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_vec_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' engine='columnar'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_vec_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_vec_columnar; OPTIMIZE TABLE test_vec_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_vec_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_full_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_full_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_full_columnar; OPTIMIZE TABLE test_full_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_full_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
echo "Row-wise (default):"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_rowwise\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Vec columnar only:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_vec_columnar\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Full columnar:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_full_columnar\G" | grep -E "(vec.*float_vector|engine='columnar')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT * FROM test_auto_dims WHERE KNN(wrong_field, 1, 'test')" 2>&1 | grep -o "wrong_field.*not found"
––– output –––
OK

github-actions · 2026-03-05T10:53:54Z

clt

❌ CLT tests in test/clt-tests/mcl/
✅ OK: 14
❌ Failed: 2
⏳ Duration: 536s
👉 Check Action Results for commit 2482a7c

Failed tests:

🔧 Edit failed tests in UI:

test/clt-tests/mcl/auto-embeddings-from-vector-check.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd --stopwait > /dev/null; stdbuf -oL searchd ${SEARCHD_ARGS:-} > /dev/null
––– output –––
OK
––– input –––
if timeout 10 grep -qm1 'accepting connections' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Accepting connections!'; else echo 'Timeout or failed!'; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title1 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title2 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title2 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table1 FROM test_from_title1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table2 FROM test_from_title2"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title1_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title2_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(2, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print "consistent_md5: " $1}'
––– output –––
OK
––– input –––
MD5_TITLE1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_TITLE2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "title1_md5: $MD5_TITLE1"; echo "title2_md5: $MD5_TITLE2"; if [ "$MD5_TITLE1" != "$MD5_TITLE2" ]; then echo "SUCCESS: FROM clause produces different vectors"; else echo "FAIL: FROM clause produces same vectors"; fi
––– output –––
OK
––– input –––
MD5_SAME1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SAME2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "same_input_md5_1: $MD5_SAME1"; echo "same_input_md5_2: $MD5_SAME2"; if [ "$MD5_SAME1" = "$MD5_SAME2" ]; then echo "SUCCESS: Same input produces same vector"; else echo "FAIL: Same input produces different vectors"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'invalid-model-name' FROM = 'title1') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_field (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from_specified (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_set_to_empty (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = '') " 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_from_set_to_empty': 'from' setting empty for KNN attribute 'embedding_vector'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_multi_from (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1, title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_multi_from (id, title1, title2) VALUES(1, 'deep learning neural networks', 'computer vision algorithms')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "multi_field_md5: " $1}'
––– output –––
OK
––– input –––
MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Multi-field FROM produces different vector"; else echo "INFO: Multi-field vs single-field comparison"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') "
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_no_from (id, title1) VALUES(1, 'test title')"; echo $?
––– output –––
OK

test/clt-tests/mcl/auto-embeddings-error-handling.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd $SEARCHD_FLAGS > /dev/null; if timeout 10 grep -qm1 '\[BUDDY\] started' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Buddy started!'; else echo 'Timeout or failed!'; cat /var/log/manticore/searchd.log;fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' KNN_DIMS='384'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)" 2>&1
# Check if table was actually created
mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_dims'" | grep -q "test_dims" && echo "Table created" || echo "Table not created"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_auto_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_auto_dims (id, title) VALUES (1, 'Test document')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    FROM='title'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM=''
)" 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_empty_from': 'from' setting empty for KNN attribute 'vec'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='non-existent-model/invalid-name'
    FROM='title'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_prefix (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='all-MiniLM-L6-v2'
    FROM='content_text'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='non_existent_field'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_circular (
    title TEXT,
    vec1 FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='vec1'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (1, '')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (2, NULL)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_empty"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_rowwise (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_rowwise (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_rowwise; OPTIMIZE TABLE test_rowwise OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_rowwise WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_vec_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' engine='columnar'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_vec_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_vec_columnar; OPTIMIZE TABLE test_vec_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_vec_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_full_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_full_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_full_columnar; OPTIMIZE TABLE test_full_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_full_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
echo "Row-wise (default):"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_rowwise\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Vec columnar only:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_vec_columnar\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Full columnar:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_full_columnar\G" | grep -E "(vec.*float_vector|engine='columnar')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT * FROM test_auto_dims WHERE KNN(wrong_field, 1, 'test')" 2>&1 | grep -o "wrong_field.*not found"
––– output –––
OK

github-actions · 2026-03-05T11:58:45Z

clt

❌ CLT tests in test/clt-tests/mcl/
✅ OK: 14
❌ Failed: 2
⏳ Duration: 509s
👉 Check Action Results for commit 2482a7c

Failed tests:

🔧 Edit failed tests in UI:

test/clt-tests/mcl/auto-embeddings-from-vector-check.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd --stopwait > /dev/null; stdbuf -oL searchd ${SEARCHD_ARGS:-} > /dev/null
––– output –––
OK
––– input –––
if timeout 10 grep -qm1 'accepting connections' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Accepting connections!'; else echo 'Timeout or failed!'; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title1 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title2 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title2 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table1 FROM test_from_title1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table2 FROM test_from_title2"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title1_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title2_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(2, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print "consistent_md5: " $1}'
––– output –––
OK
––– input –––
MD5_TITLE1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_TITLE2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "title1_md5: $MD5_TITLE1"; echo "title2_md5: $MD5_TITLE2"; if [ "$MD5_TITLE1" != "$MD5_TITLE2" ]; then echo "SUCCESS: FROM clause produces different vectors"; else echo "FAIL: FROM clause produces same vectors"; fi
––– output –––
OK
––– input –––
MD5_SAME1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SAME2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "same_input_md5_1: $MD5_SAME1"; echo "same_input_md5_2: $MD5_SAME2"; if [ "$MD5_SAME1" = "$MD5_SAME2" ]; then echo "SUCCESS: Same input produces same vector"; else echo "FAIL: Same input produces different vectors"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'invalid-model-name' FROM = 'title1') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_field (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from_specified (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_set_to_empty (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = '') " 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_from_set_to_empty': 'from' setting empty for KNN attribute 'embedding_vector'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_multi_from (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1, title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_multi_from (id, title1, title2) VALUES(1, 'deep learning neural networks', 'computer vision algorithms')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "multi_field_md5: " $1}'
––– output –––
OK
––– input –––
MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Multi-field FROM produces different vector"; else echo "INFO: Multi-field vs single-field comparison"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') "
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_no_from (id, title1) VALUES(1, 'test title')"; echo $?
––– output –––
OK

test/clt-tests/mcl/auto-embeddings-error-handling.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd $SEARCHD_FLAGS > /dev/null; if timeout 10 grep -qm1 '\[BUDDY\] started' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Buddy started!'; else echo 'Timeout or failed!'; cat /var/log/manticore/searchd.log;fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' KNN_DIMS='384'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)" 2>&1
# Check if table was actually created
mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_dims'" | grep -q "test_dims" && echo "Table created" || echo "Table not created"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_auto_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_auto_dims (id, title) VALUES (1, 'Test document')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    FROM='title'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM=''
)" 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_empty_from': 'from' setting empty for KNN attribute 'vec'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='non-existent-model/invalid-name'
    FROM='title'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_prefix (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='all-MiniLM-L6-v2'
    FROM='content_text'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='non_existent_field'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_circular (
    title TEXT,
    vec1 FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='vec1'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (1, '')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (2, NULL)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_empty"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_rowwise (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_rowwise (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_rowwise; OPTIMIZE TABLE test_rowwise OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_rowwise WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_vec_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' engine='columnar'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_vec_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_vec_columnar; OPTIMIZE TABLE test_vec_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_vec_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_full_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_full_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_full_columnar; OPTIMIZE TABLE test_full_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_full_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
echo "Row-wise (default):"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_rowwise\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Vec columnar only:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_vec_columnar\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Full columnar:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_full_columnar\G" | grep -E "(vec.*float_vector|engine='columnar')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT * FROM test_auto_dims WHERE KNN(wrong_field, 1, 'test')" 2>&1 | grep -o "wrong_field.*not found"
––– output –––
OK

github-actions · 2026-03-06T10:49:20Z

clt

❌ CLT tests in test/clt-tests/mcl/
✅ OK: 14
❌ Failed: 2
⏳ Duration: 508s
👉 Check Action Results for commit 9a600cc

Failed tests:

🔧 Edit failed tests in UI:

test/clt-tests/mcl/auto-embeddings-from-vector-check.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd --stopwait > /dev/null; stdbuf -oL searchd ${SEARCHD_ARGS:-} > /dev/null
––– output –––
OK
––– input –––
if timeout 10 grep -qm1 'accepting connections' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Accepting connections!'; else echo 'Timeout or failed!'; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title1 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title2 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title2 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table1 FROM test_from_title1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table2 FROM test_from_title2"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title1_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title2_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(2, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print "consistent_md5: " $1}'
––– output –––
OK
––– input –––
MD5_TITLE1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_TITLE2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "title1_md5: $MD5_TITLE1"; echo "title2_md5: $MD5_TITLE2"; if [ "$MD5_TITLE1" != "$MD5_TITLE2" ]; then echo "SUCCESS: FROM clause produces different vectors"; else echo "FAIL: FROM clause produces same vectors"; fi
––– output –––
OK
––– input –––
MD5_SAME1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SAME2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "same_input_md5_1: $MD5_SAME1"; echo "same_input_md5_2: $MD5_SAME2"; if [ "$MD5_SAME1" = "$MD5_SAME2" ]; then echo "SUCCESS: Same input produces same vector"; else echo "FAIL: Same input produces different vectors"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'invalid-model-name' FROM = 'title1') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_field (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from_specified (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_set_to_empty (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = '') " 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_from_set_to_empty': 'from' setting empty for KNN attribute 'embedding_vector'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_multi_from (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1, title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_multi_from (id, title1, title2) VALUES(1, 'deep learning neural networks', 'computer vision algorithms')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "multi_field_md5: " $1}'
––– output –––
OK
––– input –––
MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Multi-field FROM produces different vector"; else echo "INFO: Multi-field vs single-field comparison"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') "
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_no_from (id, title1) VALUES(1, 'test title')"; echo $?
––– output –––
OK

test/clt-tests/mcl/auto-embeddings-error-handling.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd $SEARCHD_FLAGS > /dev/null; if timeout 10 grep -qm1 '\[BUDDY\] started' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Buddy started!'; else echo 'Timeout or failed!'; cat /var/log/manticore/searchd.log;fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' KNN_DIMS='384'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)" 2>&1
# Check if table was actually created
mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_dims'" | grep -q "test_dims" && echo "Table created" || echo "Table not created"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_auto_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_auto_dims (id, title) VALUES (1, 'Test document')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    FROM='title'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM=''
)" 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_empty_from': 'from' setting empty for KNN attribute 'vec'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='non-existent-model/invalid-name'
    FROM='title'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_prefix (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='all-MiniLM-L6-v2'
    FROM='content_text'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='non_existent_field'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_circular (
    title TEXT,
    vec1 FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='vec1'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (1, '')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (2, NULL)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_empty"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_rowwise (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_rowwise (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_rowwise; OPTIMIZE TABLE test_rowwise OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_rowwise WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_vec_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' engine='columnar'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_vec_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_vec_columnar; OPTIMIZE TABLE test_vec_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_vec_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_full_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_full_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_full_columnar; OPTIMIZE TABLE test_full_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_full_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
echo "Row-wise (default):"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_rowwise\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Vec columnar only:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_vec_columnar\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Full columnar:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_full_columnar\G" | grep -E "(vec.*float_vector|engine='columnar')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT * FROM test_auto_dims WHERE KNN(wrong_field, 1, 'test')" 2>&1 | grep -o "wrong_field.*not found"
––– output –––
OK

github-actions · 2026-03-06T16:36:47Z

clt

❌ CLT tests in test/clt-tests/mcl/
✅ OK: 14
❌ Failed: 2
⏳ Duration: 508s
👉 Check Action Results for commit 9a600cc

Failed tests:

🔧 Edit failed tests in UI:

test/clt-tests/mcl/auto-embeddings-from-vector-check.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd --stopwait > /dev/null; stdbuf -oL searchd ${SEARCHD_ARGS:-} > /dev/null
––– output –––
OK
––– input –––
if timeout 10 grep -qm1 'accepting connections' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Accepting connections!'; else echo 'Timeout or failed!'; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title1 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_title2 (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title2 (id, title1, title2) VALUES(1, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table1 FROM test_from_title1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count_table2 FROM test_from_title2"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title1_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "title2_vector_md5: " $1}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_from_title1 (id, title1, title2) VALUES(2, 'machine learning artificial intelligence', 'banana fruit sweet yellow')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print "consistent_md5: " $1}'
––– output –––
OK
––– input –––
MD5_TITLE1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_TITLE2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title2 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "title1_md5: $MD5_TITLE1"; echo "title2_md5: $MD5_TITLE2"; if [ "$MD5_TITLE1" != "$MD5_TITLE2" ]; then echo "SUCCESS: FROM clause produces different vectors"; else echo "FAIL: FROM clause produces same vectors"; fi
––– output –––
OK
––– input –––
MD5_SAME1=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SAME2=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=2" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "same_input_md5_1: $MD5_SAME1"; echo "same_input_md5_2: $MD5_SAME2"; if [ "$MD5_SAME1" = "$MD5_SAME2" ]; then echo "SUCCESS: Same input produces same vector"; else echo "FAIL: Same input produces different vectors"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'invalid-model-name' FROM = 'title1') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_field (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from_specified (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_from_set_to_empty (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = '') " 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_from_set_to_empty': 'from' setting empty for KNN attribute 'embedding_vector'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_multi_from (title1 TEXT, title2 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2' FROM = 'title1, title2') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_multi_from (id, title1, title2) VALUES(1, 'deep learning neural networks', 'computer vision algorithms')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print "multi_field_md5: " $1}'
––– output –––
OK
––– input –––
MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_multi_from WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding_vector FROM test_from_title1 WHERE id=1" | grep -v embedding_vector | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Multi-field FROM produces different vector"; else echo "INFO: Multi-field vs single-field comparison"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (title1 TEXT, embedding_vector FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'sentence-transformers/all-MiniLM-L6-v2') "
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_no_from (id, title1) VALUES(1, 'test title')"; echo $?
––– output –––
OK

test/clt-tests/mcl/auto-embeddings-error-handling.rec

––– input –––
rm -f /var/log/manticore/searchd.log; stdbuf -oL searchd $SEARCHD_FLAGS > /dev/null; if timeout 10 grep -qm1 '\[BUDDY\] started' <(tail -n 1000 -f /var/log/manticore/searchd.log); then echo 'Buddy started!'; else echo 'Timeout or failed!'; cat /var/log/manticore/searchd.log;fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' KNN_DIMS='384'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)" 2>&1
# Check if table was actually created
mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_dims'" | grep -q "test_dims" && echo "Table created" || echo "Table not created"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_auto_dims (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='title'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_auto_dims (id, title) VALUES (1, 'Test document')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    FROM='title'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_from (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM=''
)" 2>&1
––– output –––
- ERROR 1064 (42000) at line 1: error adding table 'test_empty_from': 'from' setting empty for KNN attribute 'vec'
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_model (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='non-existent-model/invalid-name'
    FROM='title'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_no_prefix (
    content_text TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='all-MiniLM-L6-v2'
    FROM='content_text'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_bad_from (
    title TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='non_existent_field'
)"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_circular (
    title TEXT,
    vec1 FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='vec1'
)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_empty (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (1, '')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_empty (id, content) VALUES (2, NULL)" 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_empty"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_rowwise (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_rowwise (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_rowwise; OPTIMIZE TABLE test_rowwise OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_rowwise WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_vec_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' engine='columnar'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_vec_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_vec_columnar; OPTIMIZE TABLE test_vec_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_vec_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_full_columnar (
    content TEXT,
    vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
    MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
    FROM='content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_full_columnar (id, content) VALUES
    (1, 'machine learning'),
    (2, 'deep learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_full_columnar; OPTIMIZE TABLE test_full_columnar OPTION sync=1, cutoff=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_full_columnar WHERE KNN(vec, 1, 'artificial intelligence')"
––– output –––
OK
––– input –––
echo "Row-wise (default):"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_rowwise\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Vec columnar only:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_vec_columnar\G" | grep -E "vec.*float_vector"
––– output –––
OK
––– input –––
echo "Full columnar:"
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_full_columnar\G" | grep -E "(vec.*float_vector|engine='columnar')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT * FROM test_auto_dims WHERE KNN(wrong_field, 1, 'test')" 2>&1 | grep -o "wrong_field.*not found"
––– output –––
OK

feat: Added HNSW early termination policy

47eaf9e

tuned hnsw early termination params

dc418d9

glookka merged commit a3c6569 into master Mar 7, 2026
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feat: Added HNSW early termination policy#138

feat: Added HNSW early termination policy#138
glookka merged 2 commits intomasterfrom
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