Wrong arithmetic
Model input
Task: return 17 + 25. Candidate: 43.
Verify candidate task outputs against explicit evidence and expected behavior.
Step 01
Upload sample data, define your output schema, and provide feedback on the hardest cases.
Whether the candidate satisfies the expected task behavior.
Correctness failures found; empty when the output passes.
Whether the task explicitly requires a particular output order.
Verify candidate task outputs against explicit evidence and expected behavior.
Task: return 17 + 25. Candidate: 43.
Sutro can now generalize the rules based on your feedback.
Step 02
Compare quality and cost on your examples, then choose a model or use Sutro’s default.
Compare models on expert agreement and cost. The interactive chart uses illustrative measurements.
Illustrative sweep · select Value or Best to use that model in your function.
Step 03
Call Sutro Functions like any other software. Swap the model as soon as something more performant is released.
import sutro as so
input_data = {
"text": "Task: return 17 + 25. Candidate: 43."
}
result = so.run_function(
"training-task-verifier-evaluation",
input_data,
)curl --fail-with-body -X POST "${SUTRO_API_URL%/}/v1/functions/training-task-verifier-evaluation/run" \
-H "Authorization: Key $SUTRO_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"input": {
"text": "Task: return 17 + 25. Candidate: 43."
}
}'import sutro as so
job_id = so.batch_run_function(
name="training-task-verifier-evaluation",
data="training_task_verifier_evaluation.csv",
)
results = so.await_job_completion(job_id)curl --fail-with-body -X POST "${SUTRO_API_URL%/}/v1/batch-inference" \
-H "Authorization: Key $SUTRO_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "training-task-verifier-evaluation",
"inputs": [
{
"text": "Task: return 17 + 25. Candidate: 43."
}
]
}'