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TannedCung 2024-11-28 16:44:39 +07:00
parent 669bef9528
commit a282e9c505
1 changed files with 41 additions and 1 deletions
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42
cope2n-api/fwd_api/api/accuracy_view.py
View File

@ -112,6 +112,34 @@ class AccuracyViewSet(viewsets.ViewSet):
type=OpenApiTypes.FLOAT, type=OpenApiTypes.FLOAT,
required=False required=False
), ),
OpenApiParameter(
name='predict_result',
location=OpenApiParameter.QUERY,
description='Filter by predict result',
type=OpenApiTypes.STR,
required=False
),
OpenApiParameter(
name='feedback_result',
location=OpenApiParameter.QUERY,
description='Filter by feedback result',
type=OpenApiTypes.STR,
required=False
),
OpenApiParameter(
name='reviewed_result',
location=OpenApiParameter.QUERY,
description='Filter by reviewed result',
type=OpenApiTypes.STR,
required=False
),
OpenApiParameter(
name='doc_type',
location=OpenApiParameter.QUERY,
description='Filter by document type',
type=OpenApiTypes.STR,
required=False
),
], ],
responses=None, tags=['Accuracy'] responses=None, tags=['Accuracy']
) )
@ -129,7 +157,10 @@ class AccuracyViewSet(viewsets.ViewSet):
include_test = request.GET.get('includes_test', False) include_test = request.GET.get('includes_test', False)
subsidiary = request.GET.get("subsidiary", "all") subsidiary = request.GET.get("subsidiary", "all")
max_accuracy = float(request.GET.get("max_accuracy", 100)) max_accuracy = float(request.GET.get("max_accuracy", 100))
# subsidiary = map_subsidiary_long_to_short(subsidiary) predict_result = request.GET.get('predict_result', None)
feedback_result = request.GET.get('feedback_result', None)
reviewed_result = request.GET.get('reviewed_result', None)
doc_type = request.GET.get('doc_type', None)
base_query = Q(status=200) base_query = Q(status=200)
if start_date_str or end_date_str: if start_date_str or end_date_str:
@ -193,6 +224,15 @@ class AccuracyViewSet(viewsets.ViewSet):
base_query &= Q( base_query &= Q(
redemption_id__startswith=map_subsidiary_long_to_short(subsidiary)) redemption_id__startswith=map_subsidiary_long_to_short(subsidiary))
if predict_result:
base_query &= Q(predict_result__icontains=predict_result)
if feedback_result:
base_query &= Q(feedback_result__icontains=feedback_result)
if reviewed_result:
base_query &= Q(reviewed_result__icontains=reviewed_result)
if doc_type:
base_query &= Q(doc_type__icontains=doc_type)
if isinstance(max_accuracy, float): if isinstance(max_accuracy, float):
base_query &= Q(raw_accuracy__lt=( base_query &= Q(raw_accuracy__lt=(
max_accuracy/100)) | Q(raw_accuracy__isnull=True) max_accuracy/100)) | Q(raw_accuracy__isnull=True)