Update app.py

app.py

@@ -6,7 +6,7 @@ import torch.nn.functional as F
 import os
 
 # ======================
-# ENV
+# ENV (ASLI)
 # ======================
 os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
 DEBUG = True
@@ -16,7 +16,7 @@ def log(msg):
         print(msg, flush=True)
 
 # ======================
-# MODEL 1 — RATING & KATEGORI (TIDAK DIUBAH)
+# MODEL 1 — RATING & KATEGORI (ASLI, JANGAN DISENTUH)
 # ======================
 classifier = pipeline(
     "zero-shot-classification",
@@ -26,7 +26,7 @@ classifier = pipeline(
 )
 
 # ======================
-# MODEL 2 — ABUSIVE (INDOBERT)
+# TAMBAHAN MODEL 2 — ABUSIVE (BARU)
 # ======================
 ABUSIVE_MODEL_PATH = "./indoBERT_abusive"
 
@@ -90,7 +90,7 @@ THRESHOLD = {
 }
 
 # ======================
-# UTIL UMUM
+# UTIL UMUM (ASLI)
 # ======================
 def split_kalimat(text):
     return [
@@ -109,9 +109,9 @@ def rating_usia(kategori):
     return 0
 
 # ======================
-# MODE 1 — RATING & KATEGORI (ASLI, TIDAK DIUBAH)
+# MODE LAMA — RATING & KATEGORI (ASLI)
 # ======================
-def analyze_rating(judul, isi):
+def analyze_text(judul, isi):
     kalimat = split_kalimat(isi)
     detected = set()
 
@@ -131,9 +131,9 @@ def analyze_rating(judul, isi):
     return usia, ", ".join(sorted(detected))
 
 # ======================
-# MODE 2 — FILTER ABUSIVE (BARU)
+# MODE BARU — FILTER ABUSIVE (TAMBAHAN SAJA)
 # ======================
-def detect_abusive(isi):
+def filter_abusive_text(isi):
     paragraphs = re.split(r'\n+', isi)
     output = []
 
@@ -143,7 +143,6 @@ def detect_abusive(isi):
             continue
 
         sentences = re.split(r'(?<=[.!?])\s+', para)
-        abusive_found = False
         abusive_notes = []
 
         for s in sentences:
@@ -162,57 +161,46 @@ def detect_abusive(isi):
                 pred = torch.argmax(probs, dim=-1).item()
 
             if id2label[pred] == "Abusif":
-                abusive_found = True
                 abusive_notes.append(
                     f'Kalimat "{s}" mengandung kalimat abusif, tidak baik diucapkan'
                 )
 
-        if abusive_found:
-            output.append(para)
-            output.extend(abusive_notes)
-        else:
-            output.append(para)
+        output.append(para)
+        output.extend(abusive_notes)
 
     return "\n".join(output)
 
 # ======================
-# ROUTER MODE (UNTUK RAILWAY)
+# ROUTER MODE (SATU API, MODE BEDA)
 # ======================
 def router(judul, isi, mode):
     if mode == "rating":
-        return analyze_rating(judul, isi)
+        return analyze_text(judul, isi)
 
     if mode == "abusive":
-        return detect_abusive(isi)
+        return filter_abusive_text(isi)
 
     return "Invalid mode"
 
 # ======================
-# GRADIO INTERFACE (SINGLE API)
+# GRADIO (API TETAP SATU)
 # ======================
 demo = gr.Interface(
     fn=router,
     inputs=[
         gr.Textbox(label="Judul"),
         gr.Textbox(label="Isi"),
-        gr.Radio(
-            ["rating", "abusive"],
-            label="Mode",
-            value="rating"
-        )
+        gr.Radio(["rating", "abusive"], value="rating")
     ],
     outputs=gr.JSON(),
-    title="READEAR API",
-    api_name="predict"
+    api_name="predict",
+    title="READEAR"
 )
 
-# ======================
-# ENTRY POINT
-# ======================
 if __name__ == "__main__":
     demo.launch(
         server_name="0.0.0.0",
         server_port=7860,
         ssr_mode=False,
         show_error=True
-    )
+    )