adds pro options

app.py

@@ -103,11 +103,15 @@ def validate_request(request: GenerationRequest, oauth_token: Optional[Union[gr.
 
 
     # Check user tier and apply appropriate limits
-    is_pro = verify_pro_status(oauth_token)
+    # Anonymous users (oauth_token is None) are treated as free tier
+    is_pro = verify_pro_status(oauth_token) if oauth_token else False
     max_samples = MAX_SAMPLES_PRO if is_pro else MAX_SAMPLES_FREE
     
     if request.num_output_examples > max_samples:
-        user_tier = "PRO/Enterprise" if is_pro else "free"
+        if oauth_token is None:
+            user_tier = "anonymous"
+        else:
+            user_tier = "PRO/Enterprise" if is_pro else "free"
         raise Exception(f"Requested number of output examples {request.num_output_examples} exceeds the max limit of {max_samples} for {user_tier} users.")
 
     # check the prompt column exists in the dataset
@@ -203,10 +207,16 @@ def add_request_to_db(request: GenerationRequest):
 
 def main():
     with gr.Blocks(title="Synthetic Data Generation") as demo:
-        gr.HTML("<h3 style='text-align:center'>Generate synthetic data with AI models. PRO users get 10k samples, free users get 100 samples. <a href='http://huggingface.co/subscribe/pro?source=synthetic-data-universe' target='_blank'>Upgrade to PRO</a></h3>", elem_id="sub_title")
+        gr.HTML("<h3 style='text-align:center'>Generate synthetic data with AI models. Free to use! Sign in for PRO benefits (10k samples vs 100). <a href='http://huggingface.co/subscribe/pro?source=synthetic-data-universe' target='_blank'>Upgrade to PRO</a></h3>", elem_id="sub_title")
+        
+        # Add sign-in button at the top
+        with gr.Row():
+            gr.Markdown("")  # Empty space for alignment
+            login_button = gr.LoginButton(value="🔑 Sign in for PRO benefits", size="sm")
+            gr.Markdown("")  # Empty space for alignment
         
         pro_message = gr.Markdown(visible=False)
-        main_interface = gr.Column(visible=False)
+        main_interface = gr.Column(visible=True)
         
         # Store the current oauth token for use in submit_request
         current_oauth_token = gr.State(None)
@@ -264,8 +274,8 @@ def main():
                             # model_token = gr.Textbox(label="Model Token (Optional)", type="password", placeholder="Your HF token with read/write access to the model...")
                     with gr.Group():
                         gr.Markdown("##  Dataset information")
-                        # Dynamic user limit info
-                        user_limit_info = gr.Markdown(value="", visible=True)
+                        # Dynamic user limit info - default to anonymous user
+                        user_limit_info = gr.Markdown(value="👤 **Anonymous User**: You can generate up to 100 samples per request.", visible=True)
                         with gr.Row():
                             with gr.Column():
                                 input_dataset_name = gr.Textbox(label="Input Dataset Name", placeholder="e.g., simplescaling/s1K-1.1")
@@ -273,7 +283,7 @@ def main():
                                 
                             with gr.Column():
                                 output_dataset_name = gr.Textbox(label="Output Dataset Name", placeholder="e.g., my-generated-dataset, must be unique. Will be created under the org 'synthetic-data-universe'")
-                                num_output_samples = gr.Slider(label="Number of samples, leave as '0' for all", value=0, minimum=0, maximum=MAX_SAMPLES_PRO, step=1)
+                                num_output_samples = gr.Slider(label="Number of samples, leave as '0' for all", value=0, minimum=0, maximum=MAX_SAMPLES_FREE, step=1)
                     
                     with gr.Accordion("Advanced Options", open=False):
                         with gr.Row():
@@ -361,7 +371,7 @@ def main():
         
         def update_user_limits(oauth_token):
             if oauth_token is None:
-                return ""
+                return "👤 **Anonymous User**: You can generate up to 100 samples per request. [Sign in](javascript:void(0)) for PRO benefits (10,000 samples)."
             
             is_pro = verify_pro_status(oauth_token)
             if is_pro:
@@ -370,14 +380,25 @@ def main():
                 return "👤 **Free User**: You can generate up to 100 samples per request. [Upgrade to PRO](http://huggingface.co/subscribe/pro?source=synthetic-data-universe) for 10,000 samples."
 
         def control_access(profile: Optional[gr.OAuthProfile] = None, oauth_token: Optional[gr.OAuthToken] = None):
-            if not profile: return gr.update(visible=False), gr.update(visible=False), None, ""
-            # Allow all users but show different messaging, and store the token
+            # Always show the interface, whether user is logged in or not
             limit_msg = update_user_limits(oauth_token)
-            return gr.update(visible=True), gr.update(visible=False), oauth_token, limit_msg
+            
+            # Update slider maximum based on user tier
+            if oauth_token is None:
+                max_samples = MAX_SAMPLES_FREE
+            else:
+                is_pro = verify_pro_status(oauth_token)
+                max_samples = MAX_SAMPLES_PRO if is_pro else MAX_SAMPLES_FREE
+            
+            slider_update = gr.update(maximum=max_samples)
+            
+            return gr.update(visible=True), gr.update(visible=False), oauth_token, limit_msg, slider_update
 
-        login_button = gr.LoginButton() # this is required or AUTH will not work
 
-        demo.load(control_access, inputs=None, outputs=[main_interface, pro_message, current_oauth_token, user_limit_info])
+        # Handle login state changes - LoginButton automatically handles auth state changes
+        # The demo.load will handle both initial load and auth changes
+        
+        demo.load(control_access, inputs=None, outputs=[main_interface, pro_message, current_oauth_token, user_limit_info, num_output_samples])
         demo.queue(max_size=None, default_concurrency_limit=None).launch(show_error=True)
 
 if __name__ == "__main__":