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creating flask api
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import pickle
from flask import Flask, request, jsonify
from transformers import AutoTokenizer
app = Flask(__name__)
with open("../models/logistic_regression.pkl", "rb") as f:
model = pickle.load(f)
tokenizer = AutoTokenizer.from_pretrained("moussaKam/AraBART")
@app.route("/classify", methods=["POST"])
def classify_arabic_dialect():
try:
data = request.json
text = data.get("text")
if not text:
return jsonify({"error": "No text has been received"}), 400
text_embeddings = tokenizer(text, padding=True)
predicted_class = model.predict(text_embeddings)
return jsonify({"class": predicted_class}), 200
except Exception as e:
return jsonify({"error": str(e)}), 500
def main():
app.run(debug=True)
if __name__ == "__main__":
main()