Update app.py

changing 'returns' to gr.Info()

app.py

@@ -31,7 +31,7 @@ class ModelDetails:
 
 def start_compute_space():
     API.restart_space(COMPUTE_SPACE)  
-    return f"Okay! {COMPUTE_SPACE} should be running now!"
+    gr.Info(f"Okay! {COMPUTE_SPACE} should be running now!")
 
 
 def get_model_size(model_info: ModelInfo):
@@ -73,19 +73,19 @@ def add_new_eval(
     task_models = list(API.list_models(filter=task_mappings[task]))
     task_model_names = [m.id for m in task_models]
     if repo_id in model_list:
-        return 'This model has already been run!'
+        gr.Info('This model has already been run!')
     elif repo_id not in task_model_names:
-        return "This model isn't compatible with the chosen task! Pick a different model-task combination"
+        gr.Info("This model isn't compatible with the chosen task! Pick a different model-task combination")
     else:
         # Is the model info correctly filled?
         try:
             model_info = API.model_info(repo_id=repo_id)
         except Exception:
-            return "Could not find information for model %s" % (model)
+            gr.Info("Could not find information for model %s" % (model))
             
         model_size = get_model_size(model_info=model_info)
         
-        print("Adding request")
+        gr.Info("Adding request")
     
         
         request_dict = {
@@ -107,7 +107,7 @@ def add_new_eval(
         updated_dset =Dataset.from_pandas(df_final)
         updated_dset.push_to_hub("EnergyStarAI/requests_debug", split="test", token=TOKEN)
         
-        print("Starting compute space at %s " % COMPUTE_SPACE)
+        gr.Info("Starting compute space at %s " % COMPUTE_SPACE))
         return start_compute_space()
 
 def print_existing_models():
@@ -166,6 +166,6 @@ with gr.Blocks() as demo:
         with gr.Column():
                 with gr.Accordion("Models that are in the latest leaderboard version:", open = False):
                     gr.Dataframe(get_leaderboard_models())
-                with gr.Accordion("Models that have been benchmarked lately:", open = False):
+                with gr.Accordion("Models that have been benchmarked recently:", open = False):
                     gr.Dataframe(print_existing_models())
 demo.launch()