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predict_ranking.py
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predict_ranking.py
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import requests
import json
import argparse
parser = argparse.ArgumentParser(description="predict Recommender Model.")
parser.add_argument(
"-u",
"--user_id",
required=True,
metavar="user_id",
type=str,
help="the id of the user to predict for",
)
parser.add_argument(
"-f",
"--features",
required=True,
metavar="features",
type=str,
help="features to use for ranking",
)
args = parser.parse_args()
user_id = args.user_id
raw_features = args.products
features = raw_features.split(",")
url = "http://localhost:8501/v1/models/ranking:predict"
data = {
"instances": [
{
"user_id": str(user_id),
"product": str(features[0]),
"PRECIO": int(features[1]),
"sin_weekday": float(features[2]),
"cos_weekday": float(features[3]),
"sin_monthday": float(features[4]),
"cos_monthday": float(features[5]),
"sin_month": float(features[6]),
"cos_month": float(features[7]),
"sin_hour": float(features[8]),
"cos_hour": float(features[9]),
}
]
}
data_json = json.dumps(data)
headers = {"content-type": "application/json"}
response = requests.post(url, data=data_json, headers=headers)
test_rating = response.json()["predictions"][0]["output_2"][0]
print("Ranking:", test_rating)