Update app.py

app.py

@@ -9,7 +9,7 @@ model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloa
 
 @spaces.GPU
 def predict(input_asm):
-
+    input_asm = '\n'.join(c_func).strip()
     before = f"# This is the assembly code:\n"#prompt
     after = "\n# What is the source code?\n"#prompt
     input_prompt = before+input_asm.strip()+after
@@ -21,7 +21,27 @@ def predict(input_asm):
     return c_func_decompile
 
 demo = gr.Interface(fn=predict,
-                    examples=["void ioabs_tcp_pre_select(int *param_1,int *param_2,long param_3) { *param_1 = *param_2; *param_2 = *param_2 + 1; *(int *)((long)*param_1 * 8 + param_3 + 4) = param_1[4]; *(uint *)(param_3 + (long)*param_1 * 8) = *(uint *)(param_3 + (long)*param_1 * 8) | 1; if (((**(int **)(param_1 + 2) + *(int *)(*(long *)(param_1 + 2) + 4)) - *(int *)(*(long *)(param_1 + 2) + 8)) % *(int *)(*(long *)(param_1 + 2) + 4) != 0) { *(uint *)(param_3 + (long)*param_1 * 8) = *(uint *)(param_3 + (long)*param_1 * 8) | 4; } return; }"],
+                    examples=["""undefined4 func0(float param_1,long param_2,int param_3)
+{
+  int local_28;
+  int local_24;
+  
+  local_24 = 0;
+  do {
+    local_28 = local_24;
+    if (param_3 <= local_24) {
+      return 0;
+    }
+    while (local_28 = local_28 + 1, local_28 < param_3) {
+      if ((double)((ulong)(double)(*(float *)(param_2 + (long)local_24 * 4) -
+                                  *(float *)(param_2 + (long)local_28 * 4)) &
+                  SUB168(_DAT_00402010,0)) < (double)param_1) {
+        return 1;
+      }
+    }
+    local_24 = local_24 + 1;
+  } while( true );
+}"""],
                     inputs="text", outputs="text")
 demo.queue()
 demo.launch()