Update app.py

app.py

@@ -1,14 +1,15 @@
-import os
 import gradio as gr
-from transformers import pipeline
+from transformers import AutoTokenizer, Gemma3ForConditionalGeneration
 from deep_translator import GoogleTranslator
+import torch
 
-# تولید موضوع به انگلیسی
-text_generator = pipeline("text-generation", model="tiiuae/falcon-rw-1b")
+# بارگذاری توکنایزر و مدل
+tokenizer = AutoTokenizer.from_pretrained("google/gemma-3-4b-it")
+model = Gemma3ForConditionalGeneration.from_pretrained("google/gemma-3-4b-it", torch_dtype=torch.bfloat16)
+model.eval()
 
 def generate_topics(field, major, keywords, audience, level):
-    prompt = f"""
-Suggest 3 academic thesis topics based on the following information:
+    prompt = f"""Suggest 3 academic thesis topics based on the following information:
 Field: {field}
 Specialization: {major}
 Keywords: {keywords}
@@ -16,7 +17,11 @@ Target audience: {audience}
 Level: {level}
 """
 
-    english_output = text_generator(prompt, max_new_tokens=256)[0]['generated_text']
+    inputs = tokenizer(prompt, return_tensors="pt")
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_new_tokens=256)
+    english_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
     translated_output = GoogleTranslator(source='en', target='fa').translate(english_output)
 
     final_output = translated_output.strip() + "\n\n📢 برای مشاوره و راهنمایی تخصصی با گروه مشاوره کاسپین تماس بگیرید:\n02188252497"
@@ -35,4 +40,4 @@ iface = gr.Interface(
     title="🎓 پیشنهادگر موضوع پایان‌نامه کاسپین"
 )
 
-iface.launch()
+iface.launch()