Auto commit at 07-2025-08 0:14:35

README.md

@@ -8,6 +8,7 @@ sdk_version: 5.41.0
 app_file: app.py
 pinned: false
 license: mit
+multimodal: true
 ---
 
 # 🧮 Lily Math RAG System

app.py

@@ -94,7 +94,15 @@ def chat_with_model(message, history):
     try:
         inputs = tokenizer(message, return_tensors="pt")
         with torch.no_grad():
-            outputs = model.generate(**inputs, max_new_tokens=200, temperature=0.7, do_sample=True, pad_token_id=tokenizer.eos_token_id)
+            # 멀티모달 모델의 generate 메서드 사용 (이미지 없이 텍스트만)
+            outputs = model.generate(
+                input_ids=inputs["input_ids"],
+                attention_mask=inputs["attention_mask"],
+                max_new_tokens=200,
+                temperature=0.7,
+                do_sample=True,
+                pad_token_id=tokenizer.eos_token_id
+            )
         response = tokenizer.decode(outputs[0], skip_special_tokens=True)
         if message in response:
             response = response.replace(message, "").strip()
@@ -109,7 +117,15 @@ def solve_math_problem(problem):
         prompt = f"다음 수학 문제를 단계별로 풀어주세요: {problem}"
         inputs = tokenizer(prompt, return_tensors="pt")
         with torch.no_grad():
-            outputs = model.generate(**inputs, max_new_tokens=300, temperature=0.3, do_sample=True, pad_token_id=tokenizer.eos_token_id)
+            # 멀티모달 모델의 generate 메서드 사용 (이미지 없이 텍스트만)
+            outputs = model.generate(
+                input_ids=inputs["input_ids"],
+                attention_mask=inputs["attention_mask"],
+                max_new_tokens=300,
+                temperature=0.3,
+                do_sample=True,
+                pad_token_id=tokenizer.eos_token_id
+            )
         response = tokenizer.decode(outputs[0], skip_special_tokens=True)
         if prompt in response:
             response = response.replace(prompt, "").strip()