Odstranit sk1/backend/app.py

sk1/backend/app.py

@@ -1,132 +0,0 @@
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-import json
-
-import torch
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-from flask_caching import Cache
-import hashlib
-import re
-from datetime import datetime
-import os
-from flask import Response
-import pytz
-
-app = Flask(__name__)
-CORS(app)
-
-app.config['CACHE_TYPE'] = 'SimpleCache' 
-cache = Cache(app)
-
-model_path = "tetianamohorian/hate_speech_model"
-HISTORY_FILE = "history.json"
-
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = AutoModelForSequenceClassification.from_pretrained(model_path)
-model.eval()
-
-
-def generate_text_hash(text):
-    return hashlib.md5(text.encode('utf-8')).hexdigest()
-
-def get_current_time():
-    tz = pytz.timezone('Europe/Bratislava')
-    now = datetime.now(tz)
-    return now.strftime("%d.%m.%Y %H:%M:%S")
-
-def save_to_history(text, prediction_label):
-    entry = {
-        "text": text,
-        "prediction": prediction_label,
-        "timestamp": get_current_time()
-    }
-
-    if os.path.exists(HISTORY_FILE):
-        with open(HISTORY_FILE, "r", encoding="utf-8") as f:
-            history = json.load(f)
-    else:
-        history = []
-
-    history.append(entry)
-    with open(HISTORY_FILE, "w", encoding="utf-8") as f:
-        json.dump(history, f, ensure_ascii=False, indent=2)
-
-@app.route("/api/predict", methods=["POST"])
-def predict():
-    try:
-        data = request.json
-        text = data.get("text", "")
-
-        if not text:
-            return jsonify({"error": "Text nesmie byť prázdny."}), 400
-        if len(text) > 512:
-            return jsonify({"error": "Text je príliš dlhý. Maximálne 512 znakov."}), 400
-        if re.search(r"[а-яА-ЯёЁ]", text):
-            return jsonify({"error": "Text nesmie obsahovať azbuku (cyriliku)."}), 400
-
-        
-        text_hash = generate_text_hash(text)
-        cached_result = cache.get(text_hash)
-        if cached_result:
-            save_to_history(text, cached_result)
-            return jsonify({"prediction": cached_result}), 200
-
-        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"
-        cache.set(text_hash, prediction_label)
-
-        save_to_history(text, prediction_label)
-
-        return jsonify({"prediction": prediction_label}), 200
-
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-
-
-@app.route("/api/history", methods=["GET"])
-def get_history():
-    try:
-        if os.path.exists(HISTORY_FILE):
-            with open(HISTORY_FILE, "r", encoding="utf-8") as f:
-                history = json.load(f)
-            return Response(
-                json.dumps(history, ensure_ascii=False, indent=2),
-                mimetype="application/json"
-            )
-        else:
-            return jsonify([]), 200
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-
-@app.route("/api/history/raw", methods=["GET"])
-def get_raw_history():
-    try:
-        if os.path.exists(HISTORY_FILE):
-            with open(HISTORY_FILE, "r", encoding="utf-8") as f:
-                content = f.read()
-            return Response(content, mimetype="application/json")
-        else:
-            return jsonify({"error": "history.json not found"}), 404
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-
-@app.route("/api/history/reset", methods=["POST"])
-def reset_history():
-    try:
-        with open(HISTORY_FILE, "w", encoding="utf-8") as f:
-            json.dump([], f, ensure_ascii=False, indent=2)
-        return jsonify({"message": "History reset successful."}), 200
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-if __name__ == "__main__":
-    port = int(os.environ.get("PORT", 5000))
-    app.run(host="0.0.0.0", port=port)