add app.py

app.py

@@ -0,0 +1,36 @@
+from flask import Flask, request, jsonify
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+app = Flask(__name__)
+
+# Load model dan tokenizer
+tokenizer = AutoTokenizer.from_pretrained("./hate_speech_model")
+model = AutoModelForSequenceClassification.from_pretrained("./hate_speech_model")
+
+@app.route("/")
+def home():
+    return jsonify({"message": "Hate Speech API is running!"})
+
+@app.route("/predict", methods=["POST"])
+def predict():
+    data = request.get_json()
+
+    if not data or "text" not in data:
+        return jsonify({"error": "Please provide 'text'"}), 400
+
+    text = data["text"]
+
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.nn.functional.softmax(outputs.logits, dim=1)
+        label = "Hate" if torch.argmax(probs).item() == 1 else "Non-Hate"
+
+    return jsonify({
+        "label": label,
+        "confidence": float(probs.max())
+    })
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860)