Update app.py

app.py

@@ -7,7 +7,6 @@ model_id = "lakshraina2/leetcodeAI"
 print("Loading model on CPU...")
 
 tokenizer = AutoTokenizer.from_pretrained(model_id, token=False)
-# We removed device_map to avoid the Accelerate dependency error
 model = AutoModelForCausalLM.from_pretrained(
     model_id, 
     dtype=torch.float32, 
@@ -15,6 +14,10 @@ model = AutoModelForCausalLM.from_pretrained(
 )
 
 def solve(problem_text):
+    # Basic check to ensure input isn't empty
+    if not problem_text:
+        return "No problem text detected."
+        
     prompt = f"### Instruction:\nSolve this LeetCode problem:\n{problem_text}\n\n### Response:\n"
     inputs = tokenizer(prompt, return_tensors="pt")
     
@@ -29,5 +32,12 @@ def solve(problem_text):
     solution = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return solution.split("### Response:\n")[-1].strip()
 
-iface = gr.Interface(fn=solve, inputs="text", outputs="text")
-iface.launch()
+# THE FIX: We use gr.Interface but explicitly name the API endpoint 'predict'
+demo = gr.Interface(
+    fn=solve, 
+    inputs=gr.Textbox(), 
+    outputs=gr.Textbox(),
+    api_name="predict" # This matches the /predict in your content.js URL
+)
+
+demo.launch()