Ask a question about every row of a table, in SQL, and get a real SQL type back. A DuckDB extension over Jev, TypeSafe's model for typed answers instead of text.

The data you want to ask about already sits in a table or a Parquet file, and SQL is the query language everyone has. So ask the question where the data is, instead of pulling it out, wrapping an API in a script and writing the answer back.
Jev picks from a set you define instead of writing an answer you then check. The result is typed by construction, not by validation, and not generating is what makes it cheap enough to run on every row.
D CREATE SECRET (TYPE jev, API_KEY 'sk-...');
ENDPOINT and MODEL are optional. With no secret, queries fail when planned
rather than part-way through.
Each function takes the row's text, then a criteria literal. The criteria is both the set of permitted answers and the column's type, so it must be constant.
| Call | Criteria | Column |
|---|---|---|
jev_choice(text, MAP{option: meaning}) | what each option means | ENUM of those options |
jev_score(text, [worst, ..., best]) | an ordered rubric | DOUBLE on that scale |
jev_noul(text, MAP{'true': …, 'false': …}) | what yes and no mean | DOUBLE, probability of yes |
jev_ask(text, {name: criteria, …}) | any mix | STRUCT, one field per question |
The descriptions are the only thing telling the model what an option means.
One request carries many questions, so ask them together. Each field takes its type
from its criteria; choice and score carry a <name>_confidence beside them.
D WITH asked AS (
SELECT id, jev_ask(body, {
intent: MAP{'refund': 'wants money back', 'bug': 'something broken',
'praise': 'a compliment'},
severity: ['trivial', 'minor', 'normal', 'serious', 'critical'],
urgent: MAP{'true': 'needs a reply today', 'false': 'can wait'}
}) AS a FROM tickets)
SELECT id, a.intent, round(a.severity, 1) AS severity, round(a.urgent, 2) AS urgent
FROM asked ORDER BY id;
┌───────┬─────────────────────────────────┬──────────┬────────┐
│ id │ intent │ severity │ urgent │
│ int32 │ enum('refund', 'bug', 'praise') │ double │ double │
├───────┼─────────────────────────────────┼──────────┼────────┤
│ 1 │ refund │ 1.7 │ 0.52 │
│ 2 │ bug │ 3.0 │ 0.49 │
│ 3 │ praise │ 0.6 │ 0.46 │
└───────┴─────────────────────────────────┴──────────┴────────┘
An empty option map, a duplicate option, a one-level rubric, over 255 options or a non-constant criteria all fail when the query is planned, not on row 400,000.
One request per row, so treat these like a join against a paid service. Rows in a
chunk go out sixteen at a time. Identical requests are cached for the life of the
process. DuckDB evaluates a function once per place it appears, so without that the
same call in WHERE and SELECT bills twice per row. Rate limits, server errors and
dropped connections retry with backoff; anything else fails at once.
D SELECT * FROM jev_usage();
┌──────────┬────────────┬──────────────┬───────────────┐
│ requests │ cache_hits │ input_tokens │ output_tokens │
│ int64 │ int64 │ int64 │ int64 │
├──────────┼────────────┼──────────────┼───────────────┤
│ 3 │ 0 │ 1163 │ 208 │
└──────────┴────────────┴──────────────┴───────────────┘
SET jev_on_error = 'null' loses the row instead of the query.
MIT
6 commits
C++
57.9%
Python
30.6%
Shell
5.3%
Makefile
3.3%
CMake
2.8%
Ask a question about every row of a table, in SQL, and get a real SQL type back. A DuckDB extension over Jev, TypeSafe's model for typed answers instead of text.

The data you want to ask about already sits in a table or a Parquet file, and SQL is the query language everyone has. So ask the question where the data is, instead of pulling it out, wrapping an API in a script and writing the answer back.
Jev picks from a set you define instead of writing an answer you then check. The result is typed by construction, not by validation, and not generating is what makes it cheap enough to run on every row.
D CREATE SECRET (TYPE jev, API_KEY 'sk-...');
ENDPOINT and MODEL are optional. With no secret, queries fail when planned
rather than part-way through.
Each function takes the row's text, then a criteria literal. The criteria is both the set of permitted answers and the column's type, so it must be constant.
| Call | Criteria | Column |
|---|---|---|
jev_choice(text, MAP{option: meaning}) | what each option means | ENUM of those options |
jev_score(text, [worst, ..., best]) | an ordered rubric | DOUBLE on that scale |
jev_noul(text, MAP{'true': …, 'false': …}) | what yes and no mean | DOUBLE, probability of yes |
jev_ask(text, {name: criteria, …}) | any mix | STRUCT, one field per question |
The descriptions are the only thing telling the model what an option means.
One request carries many questions, so ask them together. Each field takes its type
from its criteria; choice and score carry a <name>_confidence beside them.
D WITH asked AS (
SELECT id, jev_ask(body, {
intent: MAP{'refund': 'wants money back', 'bug': 'something broken',
'praise': 'a compliment'},
severity: ['trivial', 'minor', 'normal', 'serious', 'critical'],
urgent: MAP{'true': 'needs a reply today', 'false': 'can wait'}
}) AS a FROM tickets)
SELECT id, a.intent, round(a.severity, 1) AS severity, round(a.urgent, 2) AS urgent
FROM asked ORDER BY id;
┌───────┬─────────────────────────────────┬──────────┬────────┐
│ id │ intent │ severity │ urgent │
│ int32 │ enum('refund', 'bug', 'praise') │ double │ double │
├───────┼─────────────────────────────────┼──────────┼────────┤
│ 1 │ refund │ 1.7 │ 0.52 │
│ 2 │ bug │ 3.0 │ 0.49 │
│ 3 │ praise │ 0.6 │ 0.46 │
└───────┴─────────────────────────────────┴──────────┴────────┘
An empty option map, a duplicate option, a one-level rubric, over 255 options or a non-constant criteria all fail when the query is planned, not on row 400,000.
One request per row, so treat these like a join against a paid service. Rows in a
chunk go out sixteen at a time. Identical requests are cached for the life of the
process. DuckDB evaluates a function once per place it appears, so without that the
same call in WHERE and SELECT bills twice per row. Rate limits, server errors and
dropped connections retry with backoff; anything else fails at once.
D SELECT * FROM jev_usage();
┌──────────┬────────────┬──────────────┬───────────────┐
│ requests │ cache_hits │ input_tokens │ output_tokens │
│ int64 │ int64 │ int64 │ int64 │
├──────────┼────────────┼──────────────┼───────────────┤
│ 3 │ 0 │ 1163 │ 208 │
└──────────┴────────────┴──────────────┴───────────────┘
SET jev_on_error = 'null' loses the row instead of the query.
MIT
6 commits
C++
57.9%
Python
30.6%
Shell
5.3%
Makefile
3.3%
CMake
2.8%