app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Model ve tokenizer yükle
+model_name = "microsoft/DialoGPT-medium"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Sohbet fonksiyonu
+def chat_with_bot(input_text, chat_history=[]):
+    # Kullanıcı girdisini encode et
+    new_input_ids = tokenizer.encode(input_text + tokenizer.eos_token, return_tensors="pt")
+    bot_output = model.generate(
+        new_input_ids if not chat_history else torch.cat([chat_history, new_input_ids], dim=-1),
+        max_length=1000,
+        pad_token_id=tokenizer.eos_token_id,
+    )
+    # Botun yanıtını çöz
+    response = tokenizer.decode(bot_output[:, new_input_ids.shape[-1]:][0], skip_special_tokens=True)
+    chat_history.append((input_text, response))
+    return response, chat_history
+
+# Gradio arayüzü
+interface = gr.Interface(
+    fn=chat_with_bot,
+    inputs=["text", "state"],
+    outputs=["text", "state"],
+    live=True,
+    title="Sohbet Botu",
+    description="Bir chatbot ile konuşmaya başlayın!",
+)
+
+interface.launch()