def predict_category(output: str):
from robotoff.elasticsearch.category.predict import predict_from_dataset
from robotoff.utils import dump_jsonl
from robotoff.products import ProductDataset
from robotoff import settings
dataset = ProductDataset(settings.JSONL_DATASET_PATH)
dump_jsonl(output, predict_from_dataset(dataset))
def predict_category(output: str):
from robotoff.elasticsearch.category.predict import predict_from_dataset
from robotoff.utils import dump_jsonl
from robotoff.products import ProductDataset
from robotoff import settings
dataset = ProductDataset(settings.JSONL_DATASET_PATH)
insights = predict_from_dataset(dataset)
dict_insights = (i.to_dict() for i in insights)
dump_jsonl(output, dict_insights)
def generate_insights():
"""Generate and import category insights from the latest dataset dump, for
products added at day-1."""
logger.info("Generating new category insights")
product_store: ProductStore = CACHED_PRODUCT_STORE.get()
importer = CategoryImporter(product_store)
datetime_threshold = datetime.datetime.utcnow().replace(
hour=0, minute=0, second=0, microsecond=0) - datetime.timedelta(days=1)
dataset = ProductDataset(settings.JSONL_DATASET_PATH)
category_insights_iter = predict_from_dataset(dataset, datetime_threshold)
imported = importer.import_insights(category_insights_iter)
logger.info("{} category insights imported".format(imported))
def generate_insights():
"""Generate and import category insights from the latest dataset dump, for
products added at day-1."""
logger.info("Generating new category insights")
datetime_threshold = datetime.datetime.utcnow().replace(
hour=0, minute=0, second=0, microsecond=0) - datetime.timedelta(days=1)
dataset = ProductDataset(settings.JSONL_DATASET_PATH)
product_predictions_iter = predict_from_dataset(dataset,
datetime_threshold)
imported = import_insights(
product_predictions_iter,
server_domain=settings.OFF_SERVER_DOMAIN,
automatic=False,
)
logger.info("{} category insights imported".format(imported))