feat(embeddings): support passthrough remote model ids#156
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Windows test results 5 files 5 suites 22m 40s ⏱️ For more details on these failures, see this check. Results for commit 2827b13. ♻️ This comment has been updated with latest results. |
clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI: test/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb Connection failed [IP: 185.125.190.82 80]
- 0
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not found |
1. Allow explicit provider-prefixed passthrough model ids for remote endpoints - keep the existing slash-prefixed forms (openai/..., voyage/..., jina/...) working as before - add explicit colon-prefixed forms (openai:..., voyage:..., jina:...) - when the colon form is used, pass the model id through after stripping only the provider prefix - this allows OpenAI-compatible custom endpoints to receive full upstream model ids unchanged, for example: - openai:openai/text-embedding-ada-002 - openai:jinaai/jina-embeddings-v3 - preserve strict built-in validation for default provider endpoints while allowing passthrough mode for custom API_URL-based setups 2. Allow CMake to pass optional cargo features to the embeddings crate - add EMBEDDINGS_CARGO_FEATURE_ARGS in cmake/build_embeddings.cmake - if EMBEDDINGS_CARGO_FEATURES is set, convert it to a valid cargo CLI fragment: --features <value> - this makes it possible to configure builds such as download-ort from the CMake side without hard-coding the flag in the build script Additional remote-model adjustment: - cache inferred embedding dimensionality in remote providers so passthrough/custom models can learn their vector dimension from a successful response instead of requiring a built-in static mapping - apply that caching approach consistently across OpenAI, Voyage, and Jina
donhardman
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clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI:
test/clt-tests/mcl/auto-embeddings-backup-restore.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_backup (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title, content, KNN_DIST() as distance FROM test_backup WHERE KNN(vec, 3, 'artificial intelligence') ORDER BY distance"
––– output –––
OK
––– input –––
manticore-backup --version | grep -c "Manticore Backup"
––– output –––
OK
––– input –––
mkdir -p /tmp/backup && chmod 777 /tmp/backup; echo $?
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --tables=test_backup 2>&1 | grep -c "Backing up table"
––– output –––
OK
––– input –––
ls -d /tmp/backup/backup-* | wc -l
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FREEZE test_backup"
––– output –––
+-----------------------------------------------------+-----------------------------------------------------+
| file | normalized |
+-----------------------------------------------------+-----------------------------------------------------+
| /var/lib/manticore/test_backup/test_backup.0.spc | /var/lib/manticore/test_backup/test_backup.0.spc |
| /var/lib/manticore/test_backup/test_backup.0.spd | /var/lib/manticore/test_backup/test_backup.0.spd |
| /var/lib/manticore/test_backup/test_backup.0.spds | /var/lib/manticore/test_backup/test_backup.0.spds |
| /var/lib/manticore/test_backup/test_backup.0.spe | /var/lib/manticore/test_backup/test_backup.0.spe |
| /var/lib/manticore/test_backup/test_backup.0.sph | /var/lib/manticore/test_backup/test_backup.0.sph |
| /var/lib/manticore/test_backup/test_backup.0.sphi | /var/lib/manticore/test_backup/test_backup.0.sphi |
| /var/lib/manticore/test_backup/test_backup.0.spi | /var/lib/manticore/test_backup/test_backup.0.spi |
- | /var/lib/manticore/test_backup/test_backup.0.spidx | /var/lib/manticore/test_backup/test_backup.0.spidx |
+ | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
- | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
+ | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
- | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
+ | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
- | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
+ | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
- | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
+ | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
- | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
+ | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
- | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
+ +-----------------------------------------------------+-----------------------------------------------------+
- +-----------------------------------------------------+-----------------------------------------------------+
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES (4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "UNFREEZE test_backup"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysqldump -h0 -P9306 manticore test_backup > /tmp/logical_backup.sql 2>/dev/null; echo $?
––– output –––
OK
––– input –––
grep -c "INSERT INTO" /tmp/logical_backup.sql
––– output –––
OK
––– input –––
searchd --stopwait > /dev/null 2>&1; echo $?
––– output –––
OK
––– input –––
rm -f /etc/manticoresearch/manticore.conf; rm -rf /var/lib/manticore/*; echo "Cleaned for restore"
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep -c "backup-"
––– output –––
OK
––– input –––
BACKUP_NAME=$(manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep backup- | awk '{print $1}' | head -1)
manticore-backup --backup-dir=/tmp/backup --restore=$BACKUP_NAME 2>&1 | grep -c "Starting to restore"
––– output –––
- 1
+ 0
––– input –––
searchd > /dev/null 2>&1; echo $?
––– output –––
- 0
+ 1
––– input –––
echo "Waiting for searchd to start"; sleep 3
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 3 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- +------+
––– input –––
mysql -h0 -P9306 -e "ALTER TABLE test_backup ADD COLUMN new_field INTEGER"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "DESC test_backup" | grep "new_field"
––– output –––
- | new_field | uint | columnar fast_fetch |
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_copy (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_copy (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2),
(4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_copy"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 4 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_copy; OPTIMIZE TABLE test_copy OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+test/clt-tests/mcl/auto-embeddings-endpoints.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 185.125.190.81 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 185.125.190.81 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE emb_test (
id BIGINT,
title TEXT,
content TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO emb_test (id, title, content) VALUES
(1, 'machine learning', 'neural networks and deep learning'),
(2, 'computer vision', 'image recognition and processing'),
(3, 'natural language', 'text analysis and understanding')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK emb_test; OPTIMIZE TABLE emb_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM emb_test WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli?select%20id,%20title%20from%20emb_test%20where%20knn(vec,%202,%20'artificial%20intelligence')" | grep -v 'rows in set'
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli_json?select%20id,%20title,%20@knn_dist%20from%20emb_test%20where%20knn(vec,%201,%20'learning')" | jq -r '.[0].data[0] | "ID: \(.id)\nTitle: \(.title)\nDistance: \(.["@knn_dist"] | tostring)"'
––– output –––
- ID: 1
+ bash: line 31: jq: command not found
- Title: machine learning
- Distance: #!/1\.082[0-9]*/!#
––– input –––
curl -s -X POST "http://localhost:9308/sql?mode=raw" -d "select count(*) from emb_test where knn(vec, 2, 'neural networks')" | jq -r '.[0].data[0]."count(*)"'
––– output –––
- 3
+ bash: line 33: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"emb_test","id":10,"doc":{"title":"quantum computing","content":"quantum algorithms"}}' | jq -r '.created'
––– output –––
- true
+ bash: line 35: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query":"quantum","k":1}}' | jq -r '.hits.hits[0]._source.title'
––– output –––
- quantum computing
+ bash: line 37: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query_text":"quantum","k":1}}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE chunk_test (
id BIGINT,
title TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO chunk_test (id, title) VALUES
(1, 'machine learning'),
(2, 'deep learning'),
(3, 'reinforcement learning')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK chunk_test; OPTIMIZE TABLE chunk_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OKtest/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.23 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.23 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not foundtest/clt-tests/mcl/auto-embeddings-syntax-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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 11:38:03.675 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-voyage-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 11:38:09.473 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-openai-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title, content' API_KEY='${OPENAI_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_openai_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title' API_KEY='${OPENAI_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_openai_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "INSERT INTO test_openai_no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$OPENAI_API_KEY" ] && [ "$OPENAI_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_openai_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${OPENAI_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_plain {
type = rt
path = /var/lib/manticore/test_openai_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"openai/text-embedding-ada-002","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_openai_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_no_key {
type = rt
path = /var/lib/manticore/test_openai_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"openai/text-embedding-ada-002","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 11:37:02.940 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING |
donhardman
approved these changes
Apr 29, 2026
clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI:
test/clt-tests/mcl/auto-embeddings-backup-restore.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_backup (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title, content, KNN_DIST() as distance FROM test_backup WHERE KNN(vec, 3, 'artificial intelligence') ORDER BY distance"
––– output –––
OK
––– input –––
manticore-backup --version | grep -c "Manticore Backup"
––– output –––
OK
––– input –––
mkdir -p /tmp/backup && chmod 777 /tmp/backup; echo $?
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --tables=test_backup 2>&1 | grep -c "Backing up table"
––– output –––
OK
––– input –––
ls -d /tmp/backup/backup-* | wc -l
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FREEZE test_backup"
––– output –––
+-----------------------------------------------------+-----------------------------------------------------+
| file | normalized |
+-----------------------------------------------------+-----------------------------------------------------+
| /var/lib/manticore/test_backup/test_backup.0.spc | /var/lib/manticore/test_backup/test_backup.0.spc |
| /var/lib/manticore/test_backup/test_backup.0.spd | /var/lib/manticore/test_backup/test_backup.0.spd |
| /var/lib/manticore/test_backup/test_backup.0.spds | /var/lib/manticore/test_backup/test_backup.0.spds |
| /var/lib/manticore/test_backup/test_backup.0.spe | /var/lib/manticore/test_backup/test_backup.0.spe |
| /var/lib/manticore/test_backup/test_backup.0.sph | /var/lib/manticore/test_backup/test_backup.0.sph |
| /var/lib/manticore/test_backup/test_backup.0.sphi | /var/lib/manticore/test_backup/test_backup.0.sphi |
| /var/lib/manticore/test_backup/test_backup.0.spi | /var/lib/manticore/test_backup/test_backup.0.spi |
- | /var/lib/manticore/test_backup/test_backup.0.spidx | /var/lib/manticore/test_backup/test_backup.0.spidx |
+ | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
- | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
+ | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
- | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
+ | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
- | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
+ | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
- | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
+ | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
- | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
+ | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
- | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
+ +-----------------------------------------------------+-----------------------------------------------------+
- +-----------------------------------------------------+-----------------------------------------------------+
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES (4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "UNFREEZE test_backup"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysqldump -h0 -P9306 manticore test_backup > /tmp/logical_backup.sql 2>/dev/null; echo $?
––– output –––
OK
––– input –––
grep -c "INSERT INTO" /tmp/logical_backup.sql
––– output –––
OK
––– input –––
searchd --stopwait > /dev/null 2>&1; echo $?
––– output –––
OK
––– input –––
rm -f /etc/manticoresearch/manticore.conf; rm -rf /var/lib/manticore/*; echo "Cleaned for restore"
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep -c "backup-"
––– output –––
OK
––– input –––
BACKUP_NAME=$(manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep backup- | awk '{print $1}' | head -1)
manticore-backup --backup-dir=/tmp/backup --restore=$BACKUP_NAME 2>&1 | grep -c "Starting to restore"
––– output –––
- 1
+ 0
––– input –––
searchd > /dev/null 2>&1; echo $?
––– output –––
- 0
+ 1
––– input –––
echo "Waiting for searchd to start"; sleep 3
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 3 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- +------+
––– input –––
mysql -h0 -P9306 -e "ALTER TABLE test_backup ADD COLUMN new_field INTEGER"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "DESC test_backup" | grep "new_field"
––– output –––
- | new_field | uint | columnar fast_fetch |
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_copy (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_copy (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2),
(4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_copy"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 4 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_copy; OPTIMIZE TABLE test_copy OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+test/clt-tests/mcl/auto-embeddings-endpoints.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.23 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.23 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE emb_test (
id BIGINT,
title TEXT,
content TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO emb_test (id, title, content) VALUES
(1, 'machine learning', 'neural networks and deep learning'),
(2, 'computer vision', 'image recognition and processing'),
(3, 'natural language', 'text analysis and understanding')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK emb_test; OPTIMIZE TABLE emb_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM emb_test WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli?select%20id,%20title%20from%20emb_test%20where%20knn(vec,%202,%20'artificial%20intelligence')" | grep -v 'rows in set'
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli_json?select%20id,%20title,%20@knn_dist%20from%20emb_test%20where%20knn(vec,%201,%20'learning')" | jq -r '.[0].data[0] | "ID: \(.id)\nTitle: \(.title)\nDistance: \(.["@knn_dist"] | tostring)"'
––– output –––
- ID: 1
+ bash: line 31: jq: command not found
- Title: machine learning
- Distance: #!/1\.082[0-9]*/!#
––– input –––
curl -s -X POST "http://localhost:9308/sql?mode=raw" -d "select count(*) from emb_test where knn(vec, 2, 'neural networks')" | jq -r '.[0].data[0]."count(*)"'
––– output –––
- 3
+ bash: line 33: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"emb_test","id":10,"doc":{"title":"quantum computing","content":"quantum algorithms"}}' | jq -r '.created'
––– output –––
- true
+ bash: line 35: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query":"quantum","k":1}}' | jq -r '.hits.hits[0]._source.title'
––– output –––
- quantum computing
+ bash: line 37: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query_text":"quantum","k":1}}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE chunk_test (
id BIGINT,
title TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO chunk_test (id, title) VALUES
(1, 'machine learning'),
(2, 'deep learning'),
(3, 'reinforcement learning')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK chunk_test; OPTIMIZE TABLE chunk_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OKtest/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.24 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 91.189.92.24 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not foundtest/clt-tests/mcl/auto-embeddings-syntax-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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 14:52:53.598 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-voyage-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 14:52:59.384 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-openai-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title, content' API_KEY='${OPENAI_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_openai_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title' API_KEY='${OPENAI_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_openai_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "INSERT INTO test_openai_no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$OPENAI_API_KEY" ] && [ "$OPENAI_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_openai_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${OPENAI_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_plain {
type = rt
path = /var/lib/manticore/test_openai_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"openai/text-embedding-ada-002","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_openai_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_no_key {
type = rt
path = /var/lib/manticore/test_openai_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"openai/text-embedding-ada-002","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Wed Apr 29 14:51:56.557 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING |
clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI:
test/clt-tests/mcl/auto-embeddings-backup-restore.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_backup (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title, content, KNN_DIST() as distance FROM test_backup WHERE KNN(vec, 3, 'artificial intelligence') ORDER BY distance"
––– output –––
OK
––– input –––
manticore-backup --version | grep -c "Manticore Backup"
––– output –––
OK
––– input –––
mkdir -p /tmp/backup && chmod 777 /tmp/backup; echo $?
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --tables=test_backup 2>&1 | grep -c "Backing up table"
––– output –––
OK
––– input –––
ls -d /tmp/backup/backup-* | wc -l
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FREEZE test_backup"
––– output –––
+-----------------------------------------------------+-----------------------------------------------------+
| file | normalized |
+-----------------------------------------------------+-----------------------------------------------------+
| /var/lib/manticore/test_backup/test_backup.0.spc | /var/lib/manticore/test_backup/test_backup.0.spc |
| /var/lib/manticore/test_backup/test_backup.0.spd | /var/lib/manticore/test_backup/test_backup.0.spd |
| /var/lib/manticore/test_backup/test_backup.0.spds | /var/lib/manticore/test_backup/test_backup.0.spds |
| /var/lib/manticore/test_backup/test_backup.0.spe | /var/lib/manticore/test_backup/test_backup.0.spe |
| /var/lib/manticore/test_backup/test_backup.0.sph | /var/lib/manticore/test_backup/test_backup.0.sph |
| /var/lib/manticore/test_backup/test_backup.0.sphi | /var/lib/manticore/test_backup/test_backup.0.sphi |
| /var/lib/manticore/test_backup/test_backup.0.spi | /var/lib/manticore/test_backup/test_backup.0.spi |
- | /var/lib/manticore/test_backup/test_backup.0.spidx | /var/lib/manticore/test_backup/test_backup.0.spidx |
+ | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
- | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
+ | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
- | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
+ | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
- | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
+ | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
- | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
+ | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
- | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
+ | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
- | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
+ +-----------------------------------------------------+-----------------------------------------------------+
- +-----------------------------------------------------+-----------------------------------------------------+
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES (4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "UNFREEZE test_backup"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysqldump -h0 -P9306 manticore test_backup > /tmp/logical_backup.sql 2>/dev/null; echo $?
––– output –––
OK
––– input –––
grep -c "INSERT INTO" /tmp/logical_backup.sql
––– output –––
OK
––– input –––
searchd --stopwait > /dev/null 2>&1; echo $?
––– output –––
OK
––– input –––
rm -f /etc/manticoresearch/manticore.conf; rm -rf /var/lib/manticore/*; echo "Cleaned for restore"
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep -c "backup-"
––– output –––
OK
––– input –––
BACKUP_NAME=$(manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep backup- | awk '{print $1}' | head -1)
manticore-backup --backup-dir=/tmp/backup --restore=$BACKUP_NAME 2>&1 | grep -c "Starting to restore"
––– output –––
- 1
+ 0
––– input –––
searchd > /dev/null 2>&1; echo $?
––– output –––
- 0
+ 1
––– input –––
echo "Waiting for searchd to start"; sleep 3
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 3 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- +------+
––– input –––
mysql -h0 -P9306 -e "ALTER TABLE test_backup ADD COLUMN new_field INTEGER"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "DESC test_backup" | grep "new_field"
––– output –––
- | new_field | uint | columnar fast_fetch |
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_copy (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_copy (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2),
(4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_copy"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 4 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_copy; OPTIMIZE TABLE test_copy OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+test/clt-tests/mcl/auto-embeddings-endpoints.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 172.66.152.176 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 172.66.152.176 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE emb_test (
id BIGINT,
title TEXT,
content TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO emb_test (id, title, content) VALUES
(1, 'machine learning', 'neural networks and deep learning'),
(2, 'computer vision', 'image recognition and processing'),
(3, 'natural language', 'text analysis and understanding')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK emb_test; OPTIMIZE TABLE emb_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM emb_test WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli?select%20id,%20title%20from%20emb_test%20where%20knn(vec,%202,%20'artificial%20intelligence')" | grep -v 'rows in set'
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli_json?select%20id,%20title,%20@knn_dist%20from%20emb_test%20where%20knn(vec,%201,%20'learning')" | jq -r '.[0].data[0] | "ID: \(.id)\nTitle: \(.title)\nDistance: \(.["@knn_dist"] | tostring)"'
––– output –––
- ID: 1
+ bash: line 31: jq: command not found
- Title: machine learning
- Distance: #!/1\.082[0-9]*/!#
––– input –––
curl -s -X POST "http://localhost:9308/sql?mode=raw" -d "select count(*) from emb_test where knn(vec, 2, 'neural networks')" | jq -r '.[0].data[0]."count(*)"'
––– output –––
- 3
+ bash: line 33: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"emb_test","id":10,"doc":{"title":"quantum computing","content":"quantum algorithms"}}' | jq -r '.created'
––– output –––
- true
+ bash: line 35: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query":"quantum","k":1}}' | jq -r '.hits.hits[0]._source.title'
––– output –––
- quantum computing
+ bash: line 37: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query_text":"quantum","k":1}}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE chunk_test (
id BIGINT,
title TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO chunk_test (id, title) VALUES
(1, 'machine learning'),
(2, 'deep learning'),
(3, 'reinforcement learning')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK chunk_test; OPTIMIZE TABLE chunk_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OKtest/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not foundtest/clt-tests/mcl/auto-embeddings-syntax-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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Fri May 15 16:44:28.975 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-voyage-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Fri May 15 16:44:35.999 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-openai-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title, content' API_KEY='${OPENAI_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_openai_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title' API_KEY='${OPENAI_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_openai_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "INSERT INTO test_openai_no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$OPENAI_API_KEY" ] && [ "$OPENAI_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_openai_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${OPENAI_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_plain {
type = rt
path = /var/lib/manticore/test_openai_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"openai/text-embedding-ada-002","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_openai_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_no_key {
type = rt
path = /var/lib/manticore/test_openai_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"openai/text-embedding-ada-002","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Fri May 15 16:43:30.353 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING |
clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI:
test/clt-tests/mcl/auto-embeddings-backup-restore.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_backup (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title, content, KNN_DIST() as distance FROM test_backup WHERE KNN(vec, 3, 'artificial intelligence') ORDER BY distance"
––– output –––
OK
––– input –––
manticore-backup --version | grep -c "Manticore Backup"
––– output –––
OK
––– input –––
mkdir -p /tmp/backup && chmod 777 /tmp/backup; echo $?
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --tables=test_backup 2>&1 | grep -c "Backing up table"
––– output –––
OK
––– input –––
ls -d /tmp/backup/backup-* | wc -l
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FREEZE test_backup"
––– output –––
+-----------------------------------------------------+-----------------------------------------------------+
| file | normalized |
+-----------------------------------------------------+-----------------------------------------------------+
| /var/lib/manticore/test_backup/test_backup.0.spc | /var/lib/manticore/test_backup/test_backup.0.spc |
| /var/lib/manticore/test_backup/test_backup.0.spd | /var/lib/manticore/test_backup/test_backup.0.spd |
| /var/lib/manticore/test_backup/test_backup.0.spds | /var/lib/manticore/test_backup/test_backup.0.spds |
| /var/lib/manticore/test_backup/test_backup.0.spe | /var/lib/manticore/test_backup/test_backup.0.spe |
| /var/lib/manticore/test_backup/test_backup.0.sph | /var/lib/manticore/test_backup/test_backup.0.sph |
| /var/lib/manticore/test_backup/test_backup.0.sphi | /var/lib/manticore/test_backup/test_backup.0.sphi |
| /var/lib/manticore/test_backup/test_backup.0.spi | /var/lib/manticore/test_backup/test_backup.0.spi |
- | /var/lib/manticore/test_backup/test_backup.0.spidx | /var/lib/manticore/test_backup/test_backup.0.spidx |
+ | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
- | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
+ | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
- | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
+ | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
- | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
+ | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
- | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
+ | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
- | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
+ | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
- | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
+ +-----------------------------------------------------+-----------------------------------------------------+
- +-----------------------------------------------------+-----------------------------------------------------+
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES (4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "UNFREEZE test_backup"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysqldump -h0 -P9306 manticore test_backup > /tmp/logical_backup.sql 2>/dev/null; echo $?
––– output –––
OK
––– input –––
grep -c "INSERT INTO" /tmp/logical_backup.sql
––– output –––
OK
––– input –––
searchd --stopwait > /dev/null 2>&1; echo $?
––– output –––
OK
––– input –––
rm -f /etc/manticoresearch/manticore.conf; rm -rf /var/lib/manticore/*; echo "Cleaned for restore"
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep -c "backup-"
––– output –––
OK
––– input –––
BACKUP_NAME=$(manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep backup- | awk '{print $1}' | head -1)
manticore-backup --backup-dir=/tmp/backup --restore=$BACKUP_NAME 2>&1 | grep -c "Starting to restore"
––– output –––
- 1
+ 0
––– input –––
searchd > /dev/null 2>&1; echo $?
––– output –––
- 0
+ 1
––– input –––
echo "Waiting for searchd to start"; sleep 3
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 3 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- +------+
––– input –––
mysql -h0 -P9306 -e "ALTER TABLE test_backup ADD COLUMN new_field INTEGER"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "DESC test_backup" | grep "new_field"
––– output –––
- | new_field | uint | columnar fast_fetch |
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_copy (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_copy (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2),
(4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_copy"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 4 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_copy; OPTIMIZE TABLE test_copy OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+test/clt-tests/mcl/auto-embeddings-endpoints.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE emb_test (
id BIGINT,
title TEXT,
content TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO emb_test (id, title, content) VALUES
(1, 'machine learning', 'neural networks and deep learning'),
(2, 'computer vision', 'image recognition and processing'),
(3, 'natural language', 'text analysis and understanding')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK emb_test; OPTIMIZE TABLE emb_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM emb_test WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli?select%20id,%20title%20from%20emb_test%20where%20knn(vec,%202,%20'artificial%20intelligence')" | grep -v 'rows in set'
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli_json?select%20id,%20title,%20@knn_dist%20from%20emb_test%20where%20knn(vec,%201,%20'learning')" | jq -r '.[0].data[0] | "ID: \(.id)\nTitle: \(.title)\nDistance: \(.["@knn_dist"] | tostring)"'
––– output –––
- ID: 1
+ bash: line 31: jq: command not found
- Title: machine learning
- Distance: #!/1\.082[0-9]*/!#
––– input –––
curl -s -X POST "http://localhost:9308/sql?mode=raw" -d "select count(*) from emb_test where knn(vec, 2, 'neural networks')" | jq -r '.[0].data[0]."count(*)"'
––– output –––
- 3
+ bash: line 33: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"emb_test","id":10,"doc":{"title":"quantum computing","content":"quantum algorithms"}}' | jq -r '.created'
––– output –––
- true
+ bash: line 35: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query":"quantum","k":1}}' | jq -r '.hits.hits[0]._source.title'
––– output –––
- quantum computing
+ bash: line 37: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query_text":"quantum","k":1}}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE chunk_test (
id BIGINT,
title TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO chunk_test (id, title) VALUES
(1, 'machine learning'),
(2, 'deep learning'),
(3, 'reinforcement learning')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK chunk_test; OPTIMIZE TABLE chunk_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OKtest/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not foundtest/clt-tests/mcl/auto-embeddings-syntax-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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 15:29:46.765 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-voyage-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 15:29:58.725 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-openai-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title, content' API_KEY='${OPENAI_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_openai_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title' API_KEY='${OPENAI_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_openai_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "INSERT INTO test_openai_no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$OPENAI_API_KEY" ] && [ "$OPENAI_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_openai_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${OPENAI_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_plain {
type = rt
path = /var/lib/manticore/test_openai_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"openai/text-embedding-ada-002","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_openai_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_no_key {
type = rt
path = /var/lib/manticore/test_openai_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"openai/text-embedding-ada-002","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 15:28:45.378 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING |
clt❌ CLT tests in Failed tests:🔧 Edit failed tests in UI:
test/clt-tests/mcl/auto-embeddings-backup-restore.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_backup (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title, content, KNN_DIST() as distance FROM test_backup WHERE KNN(vec, 3, 'artificial intelligence') ORDER BY distance"
––– output –––
OK
––– input –––
manticore-backup --version | grep -c "Manticore Backup"
––– output –––
OK
––– input –––
mkdir -p /tmp/backup && chmod 777 /tmp/backup; echo $?
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --tables=test_backup 2>&1 | grep -c "Backing up table"
––– output –––
OK
––– input –––
ls -d /tmp/backup/backup-* | wc -l
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FREEZE test_backup"
––– output –––
+-----------------------------------------------------+-----------------------------------------------------+
| file | normalized |
+-----------------------------------------------------+-----------------------------------------------------+
| /var/lib/manticore/test_backup/test_backup.0.spc | /var/lib/manticore/test_backup/test_backup.0.spc |
| /var/lib/manticore/test_backup/test_backup.0.spd | /var/lib/manticore/test_backup/test_backup.0.spd |
| /var/lib/manticore/test_backup/test_backup.0.spds | /var/lib/manticore/test_backup/test_backup.0.spds |
| /var/lib/manticore/test_backup/test_backup.0.spe | /var/lib/manticore/test_backup/test_backup.0.spe |
| /var/lib/manticore/test_backup/test_backup.0.sph | /var/lib/manticore/test_backup/test_backup.0.sph |
| /var/lib/manticore/test_backup/test_backup.0.sphi | /var/lib/manticore/test_backup/test_backup.0.sphi |
| /var/lib/manticore/test_backup/test_backup.0.spi | /var/lib/manticore/test_backup/test_backup.0.spi |
- | /var/lib/manticore/test_backup/test_backup.0.spidx | /var/lib/manticore/test_backup/test_backup.0.spidx |
+ | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
- | /var/lib/manticore/test_backup/test_backup.0.spknn | /var/lib/manticore/test_backup/test_backup.0.spknn |
+ | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
- | /var/lib/manticore/test_backup/test_backup.0.spm | /var/lib/manticore/test_backup/test_backup.0.spm |
+ | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
- | /var/lib/manticore/test_backup/test_backup.0.spp | /var/lib/manticore/test_backup/test_backup.0.spp |
+ | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
- | /var/lib/manticore/test_backup/test_backup.0.spt | /var/lib/manticore/test_backup/test_backup.0.spt |
+ | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
- | /var/lib/manticore/test_backup/test_backup.meta | /var/lib/manticore/test_backup/test_backup.meta |
+ | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
- | /var/lib/manticore/test_backup/test_backup.settings | /var/lib/manticore/test_backup/test_backup.settings |
+ +-----------------------------------------------------+-----------------------------------------------------+
- +-----------------------------------------------------+-----------------------------------------------------+
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_backup (id, title, content, status) VALUES (4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "UNFREEZE test_backup"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
OK
––– input –––
mysqldump -h0 -P9306 manticore test_backup > /tmp/logical_backup.sql 2>/dev/null; echo $?
––– output –––
OK
––– input –––
grep -c "INSERT INTO" /tmp/logical_backup.sql
––– output –––
OK
––– input –––
searchd --stopwait > /dev/null 2>&1; echo $?
––– output –––
OK
––– input –––
rm -f /etc/manticoresearch/manticore.conf; rm -rf /var/lib/manticore/*; echo "Cleaned for restore"
––– output –––
OK
––– input –––
manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep -c "backup-"
––– output –––
OK
––– input –––
BACKUP_NAME=$(manticore-backup --backup-dir=/tmp/backup --restore 2>&1 | grep backup- | awk '{print $1}' | head -1)
manticore-backup --backup-dir=/tmp/backup --restore=$BACKUP_NAME 2>&1 | grep -c "Starting to restore"
––– output –––
- 1
+ 0
––– input –––
searchd > /dev/null 2>&1; echo $?
––– output –––
- 0
+ 1
––– input –––
echo "Waiting for searchd to start"; sleep 3
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_backup"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 3 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_backup; OPTIMIZE TABLE test_backup OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_backup WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- +------+
––– input –––
mysql -h0 -P9306 -e "ALTER TABLE test_backup ADD COLUMN new_field INTEGER"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "DESC test_backup" | grep "new_field"
––– output –––
- | new_field | uint | columnar fast_fetch |
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_copy (
title TEXT,
content TEXT,
status INTEGER,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_copy (id, title, content, status) VALUES
(1, 'machine learning', 'neural networks', 1),
(2, 'deep learning', 'transformers', 1),
(3, 'computer vision', 'image processing', 2),
(4, 'frozen insert', 'test data', 3)"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_copy"
––– output –––
- +----------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | count(*) |
- +----------+
- | 4 |
- +----------+
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_copy; OPTIMIZE TABLE test_copy OPTION sync=1, cutoff=1"; echo $?
––– output –––
- 0
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
+ 1
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_copy WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
- +------+
+ ERROR 2003 (HY000): Can't connect to MySQL server on '0:9306' (111)
- | id |
- +------+
- | 1 |
- | 3 |
- | 2 |
- | 4 |
- +------+test/clt-tests/mcl/auto-embeddings-endpoints.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE emb_test (
id BIGINT,
title TEXT,
content TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
)"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO emb_test (id, title, content) VALUES
(1, 'machine learning', 'neural networks and deep learning'),
(2, 'computer vision', 'image recognition and processing'),
(3, 'natural language', 'text analysis and understanding')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK emb_test; OPTIMIZE TABLE emb_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM emb_test WHERE KNN(vec, 2, 'artificial intelligence')"
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli?select%20id,%20title%20from%20emb_test%20where%20knn(vec,%202,%20'artificial%20intelligence')" | grep -v 'rows in set'
––– output –––
OK
––– input –––
curl -s "http://localhost:9308/cli_json?select%20id,%20title,%20@knn_dist%20from%20emb_test%20where%20knn(vec,%201,%20'learning')" | jq -r '.[0].data[0] | "ID: \(.id)\nTitle: \(.title)\nDistance: \(.["@knn_dist"] | tostring)"'
––– output –––
- ID: 1
+ bash: line 31: jq: command not found
- Title: machine learning
- Distance: #!/1\.082[0-9]*/!#
––– input –––
curl -s -X POST "http://localhost:9308/sql?mode=raw" -d "select count(*) from emb_test where knn(vec, 2, 'neural networks')" | jq -r '.[0].data[0]."count(*)"'
––– output –––
- 3
+ bash: line 33: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"emb_test","id":10,"doc":{"title":"quantum computing","content":"quantum algorithms"}}' | jq -r '.created'
––– output –––
- true
+ bash: line 35: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query":"quantum","k":1}}' | jq -r '.hits.hits[0]._source.title'
––– output –––
- quantum computing
+ bash: line 37: jq: command not found
––– input –––
curl -s -X POST http://localhost:9308/search -d '{"index":"emb_test","knn":{"field":"vec","query_text":"quantum","k":1}}'
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE chunk_test (
id BIGINT,
title TEXT,
vec FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO chunk_test (id, title) VALUES
(1, 'machine learning'),
(2, 'deep learning'),
(3, 'reinforcement learning')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK chunk_test; OPTIMIZE TABLE chunk_test OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM chunk_test WHERE KNN(vec, 1, 'learning')"
––– output –––
OKtest/clt-tests/mcl/auto-embeddings-json-api.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 –––
apt-get install jq -y > /dev/null; echo $?
––– output –––
- debconf: delaying package configuration, since apt-utils is not installed
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/libjq1_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
- 0
+ E: Failed to fetch http://security.ubuntu.com/ubuntu/pool/main/j/jq/jq_1.7.1-3ubuntu0.24.04.1_amd64.deb 404 Not Found [IP: 104.20.28.246 80]
+ E: Unable to fetch some archives, maybe run apt-get update or try with --fix-missing?
+ 100
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_columnar (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='columnar'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_columnar" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 19: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_columnar WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_columnar","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_columnar","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 26: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_columnar","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 30: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_columnar WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_columnar (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_columnar","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_columnar WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_columnar"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_columnar; OPTIMIZE TABLE test_json_columnar OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_columnar\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 46: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE no_auto_embed (title TEXT, vec FLOAT_VECTOR KNN_TYPE='hnsw' KNN_DIMS='384' HNSW_SIMILARITY='l2') engine='columnar'"
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/insert -d "{\"index\":\"no_auto_embed\",\"id\":1,\"doc\":{\"title\":\"test\",\"vec\":[$VECTOR]}}" | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 51: jq: command not found
––– input –––
QUERY_VEC=$(python3 -c "print(','.join(['0.5']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"no_auto_embed\",\"knn\":{\"field\":\"vec\",\"query_vector\":[$QUERY_VEC],\"k\":1}}" | jq -r '.hits.total // "0"'
––– output –––
- 1
+ bash: line 54: jq: command not found
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_json_rowwise (
title TEXT,
content TEXT,
embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2'
MODEL_NAME='sentence-transformers/all-MiniLM-L6-v2'
FROM='title, content'
) engine='rowwise'"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_json_rowwise" | grep -o "model_name='sentence-transformers/all-MiniLM-L6-v2'"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"machine learning","content":"neural networks"}}' | jq -r 'if ._id then ._id else "inserted" end'
––– output –––
- inserted
+ bash: line 66: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT id FROM test_json_rowwise WHERE KNN(embedding, 1, 'machine learning neural networks')"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/bulk -H "Content-Type: application/x-ndjson" -d '
{"insert":{"index":"test_json_rowwise","id":2,"doc":{"title":"computer vision","content":"image recognition"}}}
{"insert":{"index":"test_json_rowwise","id":3,"doc":{"title":"NLP","content":"text processing"}}}
' | jq '{created: .items[0].bulk.created}'
––– output –––
- {
+ bash: line 73: jq: command not found
- "created": 2
- }
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise WHERE id IN (2,3)"
––– output –––
OK
––– input –––
curl -s -X POST http://localhost:9308/replace -d '{"index":"test_json_rowwise","id":1,"doc":{"title":"updated ML","content":"updated networks"}}' | jq -r '.result'
––– output –––
- updated
+ bash: line 77: jq: command not found
––– input –––
mysql -h0 -P9306 -e "SELECT title FROM test_json_rowwise WHERE id=1 AND KNN(embedding, 1, 'updated ML networks')"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_json_rowwise (id, title, content) VALUES (100, 'test', 'data')";
curl -s -X POST http://localhost:9308/insert -d '{"index":"test_json_rowwise","id":101,"doc":{"title":"test","content":"data"}}' > /dev/null
––– output –––
OK
––– input –––
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=100" > /tmp/v1.txt
mysql -h0 -P9306 --batch --skip-column-names -e "SELECT embedding FROM test_json_rowwise WHERE id=101" > /tmp/v2.txt
diff -q /tmp/v1.txt /tmp/v2.txt > /dev/null && echo "Vectors identical" || echo "Vectors differ"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) FROM test_json_rowwise"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "FLUSH RAMCHUNK test_json_rowwise; OPTIMIZE TABLE test_json_rowwise OPTION sync=1, cutoff=1"; echo $?
––– output –––
OK
––– input –––
VECTOR=$(python3 -c "print(','.join(['0.01']*384))")
curl -s -X POST http://localhost:9308/search -d "{\"index\":\"test_json_rowwise\",\"knn\":{\"field\":\"embedding\",\"query_vector\":[$VECTOR],\"k\":2}}" | jq -r '.hits.total // "0"'
––– output –––
- 5
+ bash: line 93: jq: command not foundtest/clt-tests/mcl/auto-embeddings-syntax-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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 19:37:28.425 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-voyage-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title, content' API_KEY='${VOYAGE_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SHOW CREATE TABLE test_voyage_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_voyage_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_voyage_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/voyage-3.5-lite' FROM = 'title' API_KEY='${VOYAGE_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_voyage_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_voyage_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test__invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'voyage/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_voyage_no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "INSERT INTO test__no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test__no_from'" | grep -q test_voyage_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_voyage_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$VOYAGE_API_KEY" ] && [ "$VOYAGE_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_voyage_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${VOYAGE_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_plain {
type = rt
path = /var/lib/manticore/test_voyage_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"voyage/voyage-3.5-lite","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_voyage_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_voyage_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_voyage_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_voyage_no_key {
type = rt
path = /var/lib/manticore/test_voyage_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"voyage/voyage-3.5-lite","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 19:37:35.243 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_voyage_no_key': prealloc: Invalid API key for remote model - NOT SERVINGtest/clt-tests/mcl/auto-embeddings-openai-remote.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 –––
cosine_similarity() {
local file1="$1" file2="$2"
awk '
NR==FNR { a[NR]=$1; suma2+=$1*$1; next }
{
dot += a[FNR]*$1
sumb2 += $1*$1
}
END {
print dot / (sqrt(suma2) * sqrt(sumb2))
}' "$file1" "$file2"
}
––– output –––
OK
––– input –––
export -f cosine_similarity
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_invalid_model (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/invalid-model-name-12345' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_valid_model_no_api_key (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title') " 2>&1
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_remote (title TEXT, content TEXT, description TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title, content' API_KEY='${OPENAI_API_KEY}') "; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_remote"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(1, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'advanced AI research')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as record_count FROM test_openai_remote WHERE id=1"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_remote (id, title, content, description) VALUES(2, 'machine learning algorithms', 'deep neural networks and artificial intelligence', 'different description')"
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector1.txt
mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=2" | \
grep -v embedding | \
sed 's/[0-9]\+\(\.[0-9]\+\)\?/\n&\n/g' | \
grep -E '^[0-9]+(\.[0-9]+)?$' | \
awk '{printf "%.5f\n", $1}' > /tmp/vector2.txt
SIMILARITY=$(cosine_similarity /tmp/vector1.txt /tmp/vector2.txt)
echo "Cosine similarity: $SIMILARITY"
RESULT=$(awk -v sim="$SIMILARITY" 'BEGIN {
if (sim > 0.99)
print "SUCCESS: Same FROM fields produce similar vectors (similarity: " sim ")"
else
print "FAIL: Different vectors (FROM does not include description field and should not change generated vector value) (similarity: " sim ")"
}')
echo "$RESULT"
rm -f /tmp/vector1.txt /tmp/vector2.txt
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_title_only (title TEXT, content TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'title' API_KEY='${OPENAI_API_KEY}') "; mysql -h0 -P9306 -e "INSERT INTO test_openai_title_only (id, title, content) VALUES(1, 'machine learning algorithms', 'completely different content here')"; MD5_MULTI=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_remote WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); MD5_SINGLE=$(mysql -h0 -P9306 -e "SELECT embedding FROM test_openai_title_only WHERE id=1" | grep -v embedding | md5sum | awk '{print $1}'); echo "multi_field_md5: $MD5_MULTI"; echo "single_field_md5: $MD5_SINGLE"; if [ "$MD5_MULTI" != "$MD5_SINGLE" ]; then echo "SUCCESS: Different FROM specifications produce different vectors"; else echo "INFO: FROM field comparison result"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "CREATE TABLE test_openai_invalid_field (title TEXT, embedding FLOAT_VECTOR KNN_TYPE='hnsw' HNSW_SIMILARITY='l2' MODEL_NAME = 'openai/text-embedding-ada-002' FROM = 'nonexistent_field') " 2>&1
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "INSERT INTO test_openai_no_from (id, title, embedding) VALUES(1, 'test title', '(0.1, 0.2, 0.3, 0.4, 0.5)')"; echo "insert_result: $?"; else echo "insert_result: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if mysql -h0 -P9306 -e "SHOW TABLES LIKE 'test_openai_no_from'" | grep -q test_openai_no_from; then mysql -h0 -P9306 -e "SHOW CREATE TABLE test_openai_no_from"; else echo "table_structure: skipped (table not created)"; fi
––– output –––
OK
––– input –––
if [ -n "$OPENAI_API_KEY" ] && [ "$OPENAI_API_KEY" != "dummy_key_for_testing" ]; then echo "API key is available for testing"; else echo "API key not available - using dummy for error testing"; fi
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT id, knn_dist() FROM test_openai_remote WHERE knn(embedding, 3, 'machine learning and artificial intelligence')\G"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_remote WHERE knn(embedding, 5, 'technology and AI') AND id > 0"
––– output –––
OK
––– input –––
API_KEY_VAL="${OPENAI_API_KEY}"; cat > /etc/manticoresearch/manticore.conf << CONFEOF
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_plain {
type = rt
path = /var/lib/manticore/test_openai_plain
rt_field = title
rt_field = content
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","hnsw_m":16,"hnsw_ef_construction":200,"model_name":"openai/text-embedding-ada-002","from":"title,content","api_key":"${API_KEY_VAL}"}]}
}
CONFEOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– 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 "SHOW TABLES"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "INSERT INTO test_openai_plain (id, title, content) VALUES(1, 'bread', 'food item'), (2, 'cat', 'animal pet')"; echo $?
––– output –––
OK
––– input –––
mysql -h0 -P9306 -e "SELECT COUNT(*) as count FROM test_openai_plain"
––– output –––
OK
––– input –––
mysql -h0 -P9306 -E -e "SELECT id, title FROM test_openai_plain WHERE knn(embedding, 2, 'dog')"
––– output –––
OK
––– input –––
cat > /etc/manticoresearch/manticore.conf << 'EOF'
searchd {
listen = 127.0.0.1:9306:mysql41
listen = 127.0.0.1:9308:http
log = /var/log/manticore/searchd.log
pid_file = /var/run/manticore/searchd.pid
}
table test_openai_no_key {
type = rt
path = /var/lib/manticore/test_openai_no_key
rt_field = title
rt_attr_float_vector = embedding
knn = {"attrs":[{"name":"embedding","type":"hnsw","hnsw_similarity":"L2","model_name":"openai/text-embedding-ada-002","from":"title"}]}
}
EOF
––– output –––
OK
––– input –––
searchd --stopwait --quiet
––– output –––
OK
––– input –––
searchd 2>&1|grep WARNING
––– output –––
- WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING
+ [Mon May 18 19:36:32.283 2026] [134] WARNING: Error initializing secondary index: daemon requires secondary library v19 (trying to load v20)
+ WARNING: table 'test_openai_no_key': prealloc: Invalid API key for remote model - NOT SERVING |
Linux debug test results 8 files 8 suites 15m 18s ⏱️ For more details on these failures, see this check. Results for commit 2827b13. |
Linux release test results 8 files 8 suites 8m 45s ⏱️ For more details on these failures, see this check. Results for commit 2827b13. |
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Additional remote-model adjustment:
Related issue #155