Update app.py

app.py

@@ -40,23 +40,21 @@ def ocr_inference(img, lang):
 	return txts
 
 def make_flashcards(words, language):
-    cards=[]
-    for word in words:
-        system_prompt = (
-            f"Given the following {language} word, create an anki flashcard which has the word, the definition, and an example sentence using that word."
-            "return the flashcard as each field separated by colons"
-        )
-        user_prompt = f"{system_prompt}\n\nText:\n{text}"
-
-        input_ids = tokenizer.apply_chat_template([{"role": "user", "content": user_prompt}], return_tensors="pt").to(model.device)
-        output_ids = model.generate(input_ids, max_new_tokens=256)
-        output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
-
-         # Parse response: take last line, split by commas
-        last_line = output_text.strip().split("\n")[-1]
-        card = [w.strip() for w in last_line.split(":") if w.strip()]
-        cards.append(card)
-    return cards
+
+    system_prompt = (
+        f"Given the following {language} words, define each word and create an example sentence, with an explanation"
+            
+    )
+    user_prompt = f"{system_prompt}\n\nText:\n{text}"
+
+    input_ids = tokenizer.apply_chat_template([{"role": "user", "content": user_prompt}], return_tensors="pt").to(model.device)
+    output_ids = model.generate(input_ids, max_new_tokens=256)
+    output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+
+    # Parse response: take last line, split by commas
+    last_line = output_text.strip().split("\n")[-1]
+    output = [w.strip() for w in last_line.split(":") if w.strip()]
+
     
 words=text_inference(text, "korean")
 print("OUTPUT TOUT OUETOI EIFJ IEFJ",words)