curl --request GET \
--url https://{tenant}-api.mathfi.ai/api/v1/feature-refinery/{featureRefinementKey}/progress \
--header 'Authorization: Bearer <token>'import requests
url = "https://{tenant}-api.mathfi.ai/api/v1/feature-refinery/{featureRefinementKey}/progress"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text){
"featureRefinementKey": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"state": "<string>",
"createdOn": "<string>",
"elapsedSeconds": 123,
"progressCompleted": 123,
"progressTotal": 123,
"cancelRequested": true,
"errorReason": "<string>",
"recentActivities": [
{
"timestamp": "<string>",
"state": "<string>"
}
],
"baselineTopPerformances": [
{
"falseDecisions": 123,
"accuracy": 123,
"f1Score": 123,
"precision": 123,
"recall": 123,
"best": true
}
],
"currentTopPerformances": [
{
"falseDecisions": 123,
"accuracy": 123,
"f1Score": 123,
"precision": 123,
"recall": 123,
"best": true
}
]
}Feature refinement progress
curl --request GET \
--url https://{tenant}-api.mathfi.ai/api/v1/feature-refinery/{featureRefinementKey}/progress \
--header 'Authorization: Bearer <token>'import requests
url = "https://{tenant}-api.mathfi.ai/api/v1/feature-refinery/{featureRefinementKey}/progress"
headers = {"Authorization": "Bearer <token>"}
response = requests.get(url, headers=headers)
print(response.text){
"featureRefinementKey": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
"state": "<string>",
"createdOn": "<string>",
"elapsedSeconds": 123,
"progressCompleted": 123,
"progressTotal": 123,
"cancelRequested": true,
"errorReason": "<string>",
"recentActivities": [
{
"timestamp": "<string>",
"state": "<string>"
}
],
"baselineTopPerformances": [
{
"falseDecisions": 123,
"accuracy": 123,
"f1Score": 123,
"precision": 123,
"recall": 123,
"best": true
}
],
"currentTopPerformances": [
{
"falseDecisions": 123,
"accuracy": 123,
"f1Score": 123,
"precision": 123,
"recall": 123,
"best": true
}
]
}Authorizations
Bearer authentication header of the form Bearer <token>, where <token> is your auth token.
Path Parameters
Response
Progress
Progress of a feature refinement — the current state, elapsed time, a recent activity trail, and the baseline vs current top performances, which together show how refinement is improving the model.
The run's lifecycle state. It advances PENDING → SETUP_* → MEASURE_INITIAL_THRESHOLD* → BASELINE_RUN_* → REFINING_LOOP_* → CREATING_RESULT → REFINEMENT_COMPLETED. The terminal states are REFINEMENT_COMPLETED (success), ERROR and TIMEOUT (failures), and CANCELLED; once terminal, the state no longer changes and elapsedSeconds is frozen. Poll until the state is terminal.
When the refinement was created, ISO-8601 UTC. Present from creation, so a run's age is available while it is still pending.
Seconds the run has been processing — counted from when it started, not from creation. 0 while pending.
Units of processing work completed so far, out of progressTotal. It increases by one as each unit finishes and never decreases; it is null (or 0) until the work has begun, and equals progressTotal once the run completes. Pair it with progressTotal for a determinate progress ratio. The unit is an internal measure with no standalone meaning and may change, so rely only on the ratio of the two and never on the raw numbers.
Total units of processing work for the run — the denominator for progressCompleted. Fixed for the life of the run once it is known; null while it is not yet known, in which case treat progress as indeterminate.
True once a cancel has been requested for this run, and it stays set — it is NOT cleared when the run reaches its terminal CANCELLED state, so a cancelled run keeps cancelRequested=true. It is therefore safe to rely on after a restart, rather than remembering the request locally. Treat it as meaningful only while the state is non-terminal; once terminal, state is authoritative. Omitted (null) when no cancel was ever requested.
Why the run stopped — present only when state is ERROR or TIMEOUT, null otherwise. Taken from the failure entry on the activity trail.
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Top model performances before refining, using all columns. Empty until the baseline is computed.
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Top model performances on the feature set as it currently stands. Equals the baseline at the start and improves as the run progresses.
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