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app.py

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+# -*- coding: utf-8 -*-
+"""app.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1VgZCCaMxdd-9oiW3-Kme4eOwUvtDo_wr
+"""
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+
+MODEL_ID = "Yenes/flan-t5-python-explainer"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+model = AutoModelForSeq2SeqLM.from_pretrained(
+    MODEL_ID,
+    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32,
+    device_map="auto",
+)
+
+MAX_INPUT_LENGTH = 256
+
+def explain_code(code: str, max_new_tokens: int = 128):
+    """Python kodunu Türkçe ve satır satır açıklayan fonksiyon."""
+    if not code.strip():
+        return "Lütfen açıklanacak bir Python kodu girin."
+
+    instruction = (
+        "Türkçe ve anlaşılır bir şekilde, aşağıdaki Python kodunu satır satır açıkla:\n"
+        f"{code}"
+    )
+
+    inputs = tokenizer(
+        instruction,
+        return_tensors="pt",
+        truncation=True,
+        max_length=MAX_INPUT_LENGTH,
+    ).to(model.device)
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=max_new_tokens,
+            num_beams=4,
+            early_stopping=True,
+        )
+
+    explanation = tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
+    return explanation
+
+demo = gr.Interface(
+    fn=explain_code,
+    inputs=[
+        gr.Textbox(lines=10, label="Python Kodu"),
+        gr.Slider(32, 512, value=128, step=16, label="Maksimum yeni token sayısı"),
+    ],
+    outputs=gr.Textbox(lines=14, label="Türkçe Açıklama"),
+    title="Python Kod Açıklayıcı (FLAN-T5)",
+    description="FLAN-T5 tabanlı, Türkçe Python kod açıklama modeli.",
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+transformers
+torch
+accelerate
+gradio
+sentencepiece
+safetensors