base

app.py

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+from transformers import AutoTokenizer, AutoModelForQuestionAnswering
+from flask import Flask, request, jsonify
+import torch
+
+# Modell betöltése
+tokenizer = AutoTokenizer.from_pretrained("nlpaueb/legal-bert-base-uncased")
+model = AutoModelForQuestionAnswering.from_pretrained("nlpaueb/legal-bert-base-uncased")
+
+app = Flask(__name__)
+
+@app.route("/answer", methods=["POST"])
+def answer():
+    data = request.json
+    context = data.get("context")
+    question = data.get("question")
+
+    # Tokenizálás és válasz előállítás
+    inputs = tokenizer.encode_plus(question, context, return_tensors="pt")
+    answer_start_scores, answer_end_scores = model(**inputs).values()
+
+    # Legjobb válasz kiválasztása
+    answer_start = torch.argmax(answer_start_scores)
+    answer_end = torch.argmax(answer_end_scores) + 1
+    answer = tokenizer.convert_tokens_to_string(
+        tokenizer.convert_ids_to_tokens(inputs["input_ids"][0][answer_start:answer_end])
+    )
+
+    return jsonify({"answer": answer})
+
+if __name__ == "__main__":
+    app.run()