Create app.py

app.py

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+import torch
+import gradio as gr
+import spaces
+import re # Metin temizleme için eklendi
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# --- Model Ayarları ---
+base_model_name = "unsloth/gpt-oss-20b"
+adapter_model_name = "userdotcs/gpt-oss-20b-turkish-foreign-origin-translator-adapter"
+
+print("Model yükleniyor...")
+tokenizer = AutoTokenizer.from_pretrained(base_model_name)
+
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+
+model = PeftModel.from_pretrained(base_model, adapter_model_name)
+model.eval()
+
+@spaces.GPU(duration=120)
+def fix_text(input_text):
+    if not input_text or input_text.strip() == "":
+        return ""
+
+    messages = [
+        {
+            "role": "system",
+            "content": "You are a helpful assistant that translates foreign-origin words in Turkish sentences."
+        },
+        {
+            "role": "user",
+            "content": f"Translate foreign-origin words in the text:\n{input_text}"
+        }
+    ]
+
+    inputs = tokenizer.apply_chat_template(
+        messages,
+        add_generation_prompt=True,
+        return_tensors="pt",
+    ).to("cuda")
+
+    with torch.no_grad():
+        outputs = model.generate(
+            input_ids=inputs,
+            max_new_tokens=16_384,
+            pad_token_id=tokenizer.eos_token_id
+        )
+
+    input_length = inputs.shape[1]
+    full_response = tokenizer.decode(outputs[0][input_length:], skip_special_tokens=True)
+
+    # --- Ayıklama Mantığı ---
+    # Modelin çıktısında "assistantfinal" anahtar kelimesini arıyoruz
+    separator = "assistantfinal"
+    
+    if separator in full_response:
+        # Metni separator'a göre böl ve en son (sağdaki) parçayı al
+        clean_response = full_response.split(separator)[-1]
+    else:
+        # Eğer separator yoksa ama "analysis" varsa, analizi temizlemeye çalışalım
+        # Genellikle asıl cevap en sonda olur. 
+        # Alternatif olarak son satırı almayı deneyebiliriz:
+        lines = full_response.strip().split('\n')
+        clean_response = lines[-1] if lines else full_response
+
+    return clean_response.strip()
+
+# Arayüz
+demo = gr.Interface(
+    fn=fix_text,
+    inputs=gr.Textbox(label="Input", lines=3),
+    outputs=gr.Textbox(label="Output", lines=3),
+    title="gpt-oss-20b Turkish Foreign Word Translation"
+)
+
+if __name__ == "__main__":
+    demo.launch()