change space ui and loading dynamically

app.py

@@ -31,7 +31,7 @@ def check_model(model_id):
     try:
         from transformers import pipeline
         ppl = pipeline(task=task, model=model_id)
-        
+
         return model_id, ppl
     except Exception as e:
         return model_id, e
@@ -59,7 +59,6 @@ def check_dataset(dataset_id, dataset_config="default", dataset_split="test"):
         return dataset_id, None, None
     return dataset_id, dataset_config, dataset_split
 
-
 def try_validate(model_id, dataset_id, dataset_config, dataset_split, column_mapping):
     # Validate model
     m_id, ppl = check_model(model_id=model_id)
@@ -144,7 +143,8 @@ def try_validate(model_id, dataset_id, dataset_config, dataset_split, column_map
     gr.Info("Model and dataset validations passed. Your can submit the evaluation task.")
 
     return (
-        config, split,
+        gr.update(visible=False),       # Loading row
+        gr.update(visible=True),        # Preview row
         gr.update(interactive=True),    # Submit button
         gr.update(value=prediction_result, visible=True),   # Model prediction preview
         gr.update(value=id2label_df, visible=True), # Label mapping preview
@@ -199,52 +199,86 @@ def try_submit(m_id, d_id, config, split, column_mappings, local):
 
 
 with gr.Blocks(theme=theme) as iface:
-    with gr.Row():
-        with gr.Column():
+    with gr.Tab("Text Classification"):
+        global_ds_id = gr.State('ds')
+
+        def check_dataset_and_get_config(dataset_id):
+            global_ds_id.value = dataset_id
+            try:
+                configs = datasets.get_dataset_config_names(dataset_id)
+                print(configs)
+                return gr.Dropdown(configs, value=configs[0], visible=True)
+            except Exception:
+                # Dataset may not exist
+                pass
+
+        def check_dataset_and_get_split(choice):
+            print('choice: ',choice, global_ds_id.value)
+            try:
+                splits = list(datasets.load_dataset(global_ds_id.value, choice).keys())
+                print('splits: ',splits)
+                return gr.Dropdown(splits, value=splits[0], visible=True)
+            except Exception as e:
+                # Dataset may not exist
+                print(e)
+                pass
+        
+        def gate_validate_btn(model_id, dataset_id, dataset_config, dataset_split):
+            print('model_id: ',model_id)
+            if model_id and dataset_id and dataset_config and dataset_split:
+                return gr.update(interactive=True)
+            else:
+                return gr.update(interactive=False)
+
+        with gr.Row():
             model_id_input = gr.Textbox(
                 label="Hugging Face model id",
-                placeholder="e.g.: cardiffnlp/twitter-roberta-base-sentiment-latest",
+                placeholder="cardiffnlp/twitter-roberta-base-sentiment-latest",
             )
 
-            # TODO: Add supported model pairs: Text Classification - text-classification
-            model_type = gr.Dropdown(
-                label="Hugging Face model type",
-                choices=[
-                    ("Auto-detect", 0),
-                    ("Text Classification", 1),
-                ],
-                value=0,
-            )
-            example_labels = gr.Label(label='Model prediction result', visible=False)
-
-            id2label_mapping_dataframe = gr.DataFrame(
-                label="Preview of label mapping",
-                visible=False,
-            )
-
-        with gr.Column():
             dataset_id_input = gr.Textbox(
-                label="Hugging Face dataset id",
-                placeholder="e.g.: tweet_eval",
+                label="Hugging Face Dataset id",
+                placeholder="tweet_eval",
             )
+        with gr.Row():
+            dataset_config_input = gr.Dropdown(['default'], value=['default'], label='Dataset Config', visible=False)
+            dataset_split_input = gr.Dropdown(['default'], value=['default'], label='Dataset Split', visible=False)
+
+            dataset_id_input.change(check_dataset_and_get_config, dataset_id_input, dataset_config_input)
+            dataset_config_input.change(check_dataset_and_get_split, dataset_config_input, dataset_split_input)
+
+        with gr.Row():
+            validate_btn = gr.Button("Validate Model and Dataset", variant="primary", interactive=False)
+            model_id_input.change(gate_validate_btn, 
+                                  inputs=[model_id_input, dataset_id_input, dataset_config_input, dataset_split_input], 
+                                  outputs=[validate_btn])
+            dataset_id_input.change(gate_validate_btn, 
+                                  inputs=[model_id_input, dataset_id_input, dataset_config_input, dataset_split_input], 
+                                  outputs=[validate_btn])
+            dataset_config_input.change(gate_validate_btn,
+                                    inputs=[model_id_input, dataset_id_input, dataset_config_input, dataset_split_input],
+                                    outputs=[validate_btn])
+            dataset_split_input.change(gate_validate_btn,
+                                    inputs=[model_id_input, dataset_id_input, dataset_config_input, dataset_split_input],
+                                    outputs=[validate_btn])
+        
+        with gr.Row(visible=True) as loading_row:
+            gr.Markdown('''
+                        <h1 style="text-align: center;">
+                        Please validate your model and dataset first...
+                        </h1>
+                        ''')
 
-            dataset_config_input = gr.Dropdown(
-                label="Hugging Face dataset subset",
-                choices=[
-                    "default",
-                ],
-                allow_custom_value=True,
-                value="default",
-            )
+        with gr.Row(visible=False) as preview_row:
+            with gr.Column():
+                id2label_mapping_dataframe = gr.DataFrame(label="Preview of label mapping")
+                
+                gr.Markdown('''
+                            <span style="background-color:#5fc269; color:white">Does this look right? If not, Check and update your feature mapping -></span>
+                            ''')
+
+                example_labels = gr.Label(label='Model Prediction Sample')
 
-            dataset_split_input = gr.Dropdown(
-                label="Hugging Face dataset split",
-                choices=[
-                    "test",
-                ],
-                allow_custom_value=True,
-                value="test",
-            )
 
             with gr.Accordion("Advance", open=False):
                 run_local = gr.Checkbox(value=True, label="Run in this Space")
@@ -259,10 +293,8 @@ with gr.Blocks(theme=theme) as iface:
                                 '}',
                 )
 
-    with gr.Row():
-        validate_btn = gr.Button("Validate model and dataset", variant="primary")
         run_btn = gr.Button(
-            "Submit evaluation task",
+            "Get Evaluation Result",
             variant="primary",
             interactive=False,
         )
@@ -273,17 +305,17 @@ with gr.Blocks(theme=theme) as iface:
                 dataset_id_input,
                 dataset_config_input,
                 dataset_split_input,
-                column_mapping_input,
             ],
             outputs=[
-                dataset_config_input,
-                dataset_split_input,
+                loading_row,
+                preview_row,
                 run_btn,
                 example_labels,
                 id2label_mapping_dataframe,
                 column_mapping_input,
             ],
         )
+        
         run_btn.click(
             try_submit,
             inputs=[
@@ -299,5 +331,8 @@ with gr.Blocks(theme=theme) as iface:
             ],
         )
 
-iface.queue(max_size=20)
-iface.launch()
+    with gr.Tab("More"):
+        pass
+
+if __name__ == "__main__":
+    iface.queue(max_size=20).launch()