Create bot_bert.py

services/bot_bert.py

@@ -0,0 +1,91 @@
+# =========================
+# 🤖 BOT DETECTION (BERT)
+# =========================
+
+from transformers import pipeline
+
+# =========================
+# LOAD MODEL (SAFE)
+# =========================
+try:
+    bot_model = pipeline(
+        "text-classification",
+        model="unitary/toxic-bert",   # ringan & cepat
+        device=-1  # CPU (HF aman)
+    )
+    print("✅ BERT bot model loaded")
+
+except Exception as e:
+    print("⚠️ BERT model gagal load:", e)
+    bot_model = None
+
+
+# =========================
+# 🔥 FALLBACK RULE-BASED
+# =========================
+def fallback_bot_detection(text):
+    score = 0
+
+    if len(text) < 20:
+        score += 1
+
+    if text.count("!") > 2:
+        score += 1
+
+    if len(set(text.split())) < 4:
+        score += 1
+
+    if text.isupper():
+        score += 1
+
+    label = "Bot" if score >= 2 else "Human"
+
+    return {
+        "text": text,
+        "score": score / 4,
+        "label": label,
+        "method": "fallback"
+    }
+
+
+# =========================
+# 🔥 MAIN FUNCTION
+# =========================
+def detect_bot_bert(texts):
+    results = []
+
+    # 🔥 jika model gagal → fallback semua
+    if bot_model is None:
+        print("⚠️ fallback mode aktif")
+        return [fallback_bot_detection(t) for t in texts[:20]]
+
+    try:
+        for t in texts[:20]:
+
+            # batasi panjang (biar tidak error)
+            t_clean = t[:512]
+
+            res = bot_model(t_clean)[0]
+
+            score = float(res["score"])
+
+            # interpretasi label
+            if res["label"].lower() in ["toxic", "toxic"]:
+                label = "Bot" if score > 0.6 else "Human"
+            else:
+                label = "Human"
+
+            results.append({
+                "text": t,
+                "score": round(score, 3),
+                "label": label,
+                "method": "bert"
+            })
+
+        return results
+
+    except Exception as e:
+        print("❌ BERT inference error:", e)
+
+        # fallback kalau inference gagal
+        return [fallback_bot_detection(t) for t in texts[:20]]