Aktualizovat z1/backend/app.py

z1/backend/app.py

@@ -2,8 +2,22 @@ from flask import Flask, request, jsonify
 from flask_cors import CORS
 import json
 
+import torch
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+
 app = Flask(__name__)
-CORS(app)  # Разрешаем CORS для фронтенда
+CORS(app)
+
+
+
+
+model_path = "./hate_speech_model/final_model"
+
+
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSequenceClassification.from_pretrained(model_path)
+model.eval()
 
 @app.route("/api/predict", methods=["POST"])
 def predict():
@@ -11,15 +25,28 @@ def predict():
         data = request.json
         text = data.get("text", "")
 
-        # Простая логика анализа текста
-        prediction = "Neutrálny text" if "dobry" in text else "Pravdepodobne toxický"
 
-        # ✅ Правильный способ вернуть JSON в UTF-8
+        inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+
+
+        with torch.no_grad():
+            outputs = model(**inputs)
+            predictions = torch.argmax(outputs.logits, dim=1).item()
+        
+        prediction_label = "Pravdepodobne toxický" if predictions == 1 else "Neutrálny text"
+
+
+
+        
         response = app.response_class(
-            response=json.dumps({"prediction": prediction}, ensure_ascii=False),
+            response=json.dumps({"prediction": prediction_label}, ensure_ascii=False),
             status=200,
             mimetype="application/json"
         )
+        
+        
+
+
         return response
     except Exception as e:
         return jsonify({"error": str(e)}), 500