Update app.py

app.py

@@ -1,39 +1,27 @@
-from transformers import MT5ForConditionalGeneration, MT5Tokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments
-from datasets import load_dataset, Dataset
-import json
+import gradio as gr
+from transformers import MT5ForConditionalGeneration, MT5Tokenizer
 
-# Загрузка данных
-with open("data/dataset_qa.json") as f:
-    data = json.load(f)
-dataset = Dataset.from_list(data)
+# Модельді жүктеу
+model = MT5ForConditionalGeneration.from_pretrained("model")
+tokenizer = MT5Tokenizer.from_pretrained("google/mt5-small")
 
-model_name = "google/mt5-small"
-tokenizer = MT5Tokenizer.from_pretrained(model_name)
-model = MT5ForConditionalGeneration.from_pretrained(model_name)
+# Сұраққа жауап беру функциясы
+def answer_question(question, context):
+    input_text = f"Сұрақ: {question} Контекст: {context}"
+    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
+    output_ids = model.generate(input_ids, max_length=128)
+    return tokenizer.decode(output_ids[0], skip_special_tokens=True)
 
-def preprocess(example):
-    input_text = "Сұрақ: " + example["question"] + " Контекст: " + example["context"]
-    target_text = example["answer"]
-    inputs = tokenizer(input_text, max_length=512, truncation=True, padding="max_length")
-    labels = tokenizer(target_text, max_length=128, truncation=True, padding="max_length")
-    inputs["labels"] = labels["input_ids"]
-    return inputs
-
-tokenized_dataset = dataset.map(preprocess)
-
-training_args = Seq2SeqTrainingArguments(
-    output_dir="./model",
-    evaluation_strategy="epoch",
-    learning_rate=2e-5,
-    per_device_train_batch_size=4,
-    num_train_epochs=5,
-    save_total_limit=1,
-)
-
-trainer = Seq2SeqTrainer(
-    model=model,
-    args=training_args,
-    train_dataset=tokenized_dataset,
+# Интерфейс
+iface = gr.Interface(
+    fn=answer_question,
+    inputs=[
+        gr.Textbox(label="Сұрақ жазыңыз"),
+        gr.Textbox(label="Контекст (мәтін үзіндісі)")
+    ],
+    outputs="text",
+    title="Қазақша AI-ассистент",
+    description="Сұрақ қойып, контекст бойынша жауап алыңыз (Мәліметтер қоры тақырыбы)"
 )
 
-trainer.train()
+iface.launch()