'hf-models'

app.py

@@ -15,6 +15,7 @@ demo = gr.Interface(
         "Masukkan nama dan harga mobil.\n\n"
         "- Format **Nama Mobil**: '2024 Mitsubishi Pajero'\n"
         "- Format **Harga**: 'Rp. 400.000.000 atau Rp 400.000'\n"
+        "- Format **Tahun prediksi penjualan**: Jika kosong, default tahun saat ini\n"
     )
 )
 

requirements.txt

@@ -2,6 +2,7 @@ aiofiles==24.1.0
 annotated-types==0.7.0
 anyio==4.9.0
 attrs==25.3.0
+audioop-lts==0.2.1
 bleach==6.2.0
 certifi==2025.4.26
 cffi==1.17.1

utils.py

@@ -1,26 +1,13 @@
-import re, os
+import re
 import pandas as pd
-import joblib, json
+import joblib
 import numpy as np
-from pathlib import Path
 from sentence_transformers import SentenceTransformer
-from kaggle.api.kaggle_api_extended import KaggleApi
-os.environ["KAGGLE_USERNAME"] = os.getenv("KAGGLE_USERNAME", "")
-os.environ["KAGGLE_KEY"] = os.getenv("KAGGLE_KEY", "")
-
-# Verify if variables exist
-if not os.environ["KAGGLE_USERNAME"] or not os.environ["KAGGLE_KEY"]:
-    raise ValueError("KAGGLE_USERNAME or KAGGLE_KEY not set in environment!")
-
-api = KaggleApi()
-api.authenticate()
-
-MODEL_PATH = "model.pkl"
-if not os.path.exists(MODEL_PATH):
-    api.dataset_download_file("myfaizal/model", file_name="model.pkl", path=".", unzip=True)
-
+from huggingface_hub import hf_hub_download
+from datetime import datetime
 
 bert_model = SentenceTransformer('all-MiniLM-L6-v2')
+MODEL_PATH = hf_hub_download(repo_id="akhfzl/legois-models", filename="model.pkl")
 
 def CarPricePrediction(car_names, car_prices, car_sold):
     # inisialisasi
@@ -33,7 +20,7 @@ def CarPricePrediction(car_names, car_prices, car_sold):
 
     names = car_names.strip()
     prices = car_prices.strip()
-    car_sold = int(car_sold)
+    car_sold = int(car_sold) if car_sold else datetime.now().year
 
     if not pattern.match(prices):
         return 'Harga harus berformat rupiah misal: Rp. 2.000.000 atau Rp 2.000.000'