commit

app.py

@@ -1,36 +1,6 @@
 from transformers import pipeline
 import gradio as gr
-import argostranslate.package
-import argostranslate.translate
-import os
-import urllib.request
 
-# ----- Fungsi untuk download dan install Argos Translate model (en -> id) -----
-def setup_argos_translate():
-    model_path = "en_id.argosmodel"
-    if not os.path.exists(model_path):
-        print("Downloading English -> Indonesian translation model...")
-        url = "https://www.argosopentech.com/models/en_id.argosmodel"
-        urllib.request.urlretrieve(url, model_path)
-    # Install package jika belum
-    argostranslate.package.install_from_path(model_path)
-
-# Jalankan setup
-setup_argos_translate()
-
-# Load languages
-installed_languages = argostranslate.translate.get_installed_languages()
-en_lang = next(filter(lambda l: l.code == "en", installed_languages))
-id_lang = next(filter(lambda l: l.code == "id", installed_languages))
-
-# ----- Fungsi translate label -----
-def translate_label(label_en):
-    try:
-        return en_lang.get_translation(id_lang).translate(label_en)
-    except Exception:
-        return label_en
-
-# ----- Load Models -----
 sentiment_model = pipeline(
     "sentiment-analysis",
     model="w11wo/indonesian-roberta-base-sentiment-classifier"
@@ -47,7 +17,6 @@ topic_model = pipeline(
     model="YagiASAFAS/indonesia-news-classification-bert"
 )
 
-# ----- Fungsi Analisis Teks -----
 def analyze_text(text):
     if not text or not text.strip():
         return {"error": "Teks kosong. Silakan masukkan kalimat Bahasa Indonesia."}
@@ -66,7 +35,7 @@ def analyze_text(text):
 
     topic = topic_model(text)[0]
     topic_result = {
-        "label": translate_label(topic["label"]),  # otomatis translate offline
+        "label": topic["label"],
         "score": round(topic["score"], 4)
     }
 
@@ -76,13 +45,12 @@ def analyze_text(text):
         "topic": topic_result
     }
 
-# ----- Gradio UI -----
 demo = gr.Interface(
     fn=analyze_text,
     inputs=gr.Textbox(lines=3, placeholder="Masukkan kalimat Bahasa Indonesia..."),
     outputs=gr.JSON(label="Hasil Analisis"),
     title="Analisis Sentimen, Entitas, & Topik Bahasa Indonesia",
-    description="Gunakan AI untuk analisis sentimen, pengenalan entitas, dan deteksi topik otomatis."
+    description="Gunakan AI untuk analisis sentimen, pengenalan entitas, dan deteksi topik otomatis (multilingual)."
 )
 
 if __name__ == "__main__":