commit

app.py

@@ -1,7 +1,36 @@
 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"
@@ -18,19 +47,14 @@ topic_model = pipeline(
     model="YagiASAFAS/indonesia-news-classification-bert"
 )
 
-def translate_label(label_en):
-    try:
-        return argostranslate.translate.translate(label_en, "en", "id")
-    except Exception:
-        return label_en
-
+# ----- Fungsi Analisis Teks -----
 def analyze_text(text):
     if not text or not text.strip():
         return {"error": "Teks kosong. Silakan masukkan kalimat Bahasa Indonesia."}
 
     sentiment = sentiment_model(text)[0]
     sentiment_result = {
-        "label": translate_label(sentiment["label"]),
+        "label": sentiment["label"],
         "score": round(sentiment["score"], 4)
     }
 
@@ -42,7 +66,7 @@ def analyze_text(text):
 
     topic = topic_model(text)[0]
     topic_result = {
-        "label": translate_label(topic["label"]),
+        "label": translate_label(topic["label"]),  # otomatis translate offline
         "score": round(topic["score"], 4)
     }
 
@@ -52,12 +76,13 @@ 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 (multilingual)."
+    description="Gunakan AI untuk analisis sentimen, pengenalan entitas, dan deteksi topik otomatis."
 )
 
 if __name__ == "__main__":