Update app.py

app.py

@@ -1,5 +1,7 @@
 import glob
 import gradio as gr
+import tempfile
+import os
 import sr100_model_compiler
 from huggingface_hub import HfApi
 from huggingface_hub import whoami
@@ -31,19 +33,21 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc, clock
     if oauth_info['token'] is None:
         return "ERROR - please log into HuggingFace to continue"
 
-    # Run the comparison
-    out_dir = './tmp'
-
-    # Run the model fitter
-    results = sr100_model_compiler.sr100_model_compiler(
-        model_file=model_name,
-        output_dir=f"{out_dir}",
-        model_loc=model_loc,
-        optimize=optimize,
-        arena_cache_size=int(float(tensor_size)*1.0e6)
-    )
-    print(results)
-
+    # Create a temporary directory
+    with tempfile.TemporaryDirectory() as out_dir:
+        print(f"Created temporary directory: {out_dir}")
+        
+        # Run the model fitter
+        results = sr100_model_compiler.sr100_model_compiler(
+            model_file=model_name,
+            output_dir=f"{out_dir}",
+            model_loc=model_loc,
+            optimize=optimize,
+            arena_cache_size=int(float(tensor_size)*1.0e6)
+        )
+        print(results)
+
+    # Analyze the model
     default_config = sr100_model_compiler.sr100_default_config()
 
     default_config['sram_size'] = int(float(sram_size)*1.0e6)
@@ -67,7 +71,7 @@ def compile_model(model_name, sram_size, tensor_size, optimize, model_loc, clock
 #        print(f'ERROR converting {epochs_text}, and {batch_text}')
     return output_text
 
-
+# Get all available models
 model_choices = glob.glob('models/*.tflite')
     
 def update_sliders(sram_slider_value, tensor_slider_value):