wording-layout-fix-QA

app_debug.py

@@ -63,9 +63,9 @@ def get_queue_status():
         current = pipe.current
         if current is None:
             current = "None"
-        return f'<div style="padding-top: 5%">Current job: {html.escape(current)} <br/> Jobs in queue: <br/> {"".join(get_jobs_info_in_queue())}</div>'
+        return f'<div style="padding-top: 5%">Current job: {html.escape(current)} <br/> Job queue: <br/> {"".join(get_jobs_info_in_queue())}</div>'
     else:
-        return '<div style="padding-top: 5%">No jobs in queue, please submit an evaluation task from another tab.</div>'
+        return '<div style="padding-top: 5%">No jobs waiting, please submit an evaluation task from Text-Classification tab.</div>'
 
 
 def get_demo():

app_leaderboard.py

@@ -96,25 +96,25 @@ def get_demo(leaderboard_tab):
     display_df = get_display_df(default_df)  # the styled dataframe to display
 
     with gr.Row():
-        with gr.Column():
-          issue_columns_select = gr.CheckboxGroup(
-              label="Issue Columns",
-              choices=issue_columns,
-              value=[],
-              interactive=True,
-          )
         with gr.Column():
           info_columns_select = gr.CheckboxGroup(
               label="Info Columns",
               choices=info_columns,
               value=default_columns,
               interactive=True,
+        )
+        with gr.Column():
+          issue_columns_select = gr.CheckboxGroup(
+              label="Issue Columns",
+              choices=issue_columns,
+              value=[],
+              interactive=True,
           )
     
     with gr.Row():
         task_select = gr.Dropdown(
             label="Task",
-            choices=["text_classification", "tabular"],
+            choices=["text_classification"],
             value="text_classification",
             interactive=True,
         )

app_text_classification.py

@@ -92,10 +92,8 @@ def get_demo():
                     for _ in range(MAX_LABELS, MAX_LABELS + MAX_FEATURES):
                         column_mappings.append(gr.Dropdown(visible=False))
 
-    with gr.Accordion(label="Model Wrap Advance Config", open=True):
+    with gr.Accordion(label="Model Wrap Advanced Config", open=True):
         gr.HTML(USE_INFERENCE_API_TIP)
-
-        run_inference = gr.Checkbox(value=True, label="Run with Inference API")
         inference_token = gr.Textbox(
             placeholder="hf_xxxxxxxxxxxxxxxxxxxx",
             value="",
@@ -111,7 +109,7 @@ def get_demo():
             outputs=[inference_token_info],
         )
 
-    with gr.Accordion(label="Scanner Advance Config (optional)", open=False):
+    with gr.Accordion(label="Scanner Advanced Config (optional)", open=False):
         scanners = gr.CheckboxGroup(visible=True)
 
         @gr.on(triggers=[uid_label.change], inputs=[uid_label], outputs=[scanners])
@@ -145,7 +143,7 @@ def get_demo():
     with gr.Row():
         logs = gr.Textbox(
             value=CHECK_LOG_SECTION_RAW,
-            label="Giskard Bot Evaluation Guide:",
+            label="Log",
             visible=False,
             every=0.5,
         )
@@ -156,7 +154,7 @@ def get_demo():
     gr.on(
         triggers=[model_id_input.change],
         fn=get_related_datasets_from_leaderboard,
-        inputs=[model_id_input],
+        inputs=[model_id_input, dataset_id_input],
         outputs=[dataset_id_input],
     ).then(
         fn=check_dataset,
@@ -233,7 +231,6 @@ def get_demo():
             dataset_config_input,
             dataset_split_input,
             uid_label,
-            run_inference,
             inference_token,
         ],
         outputs=[
@@ -257,7 +254,6 @@ def get_demo():
             dataset_id_input,
             dataset_config_input,
             dataset_split_input,
-            run_inference,
             inference_token,
             uid_label,
         ],
@@ -274,14 +270,12 @@ def get_demo():
 
     gr.on(
         triggers=[
-            run_inference.input,
             inference_token.input,
             scanners.input,
         ],
         fn=enable_run_btn,
         inputs=[
             uid_label,
-            run_inference, 
             inference_token, 
             model_id_input, 
             dataset_id_input, 
@@ -296,7 +290,6 @@ def get_demo():
         fn=enable_run_btn,
         inputs=[
             uid_label,
-            run_inference, 
             inference_token, 
             model_id_input, 
             dataset_id_input, 

run_jobs.py

@@ -50,7 +50,6 @@ def prepare_env_and_get_command(
     d_id,
     config,
     split,
-    inference,
     inference_token,
     uid,
     label_mapping,
@@ -60,10 +59,6 @@ def prepare_env_and_get_command(
     if os.environ.get("SPACE_ID") == "giskardai/giskard-evaluator":
         leaderboard_dataset = LEADERBOARD
 
-    inference_type = "hf_pipeline"
-    if inference and inference_token:
-        inference_type = "hf_inference_api"
-
     executable = "giskard_scanner"
     try:
         # Copy the current requirements (might be changed)
@@ -100,7 +95,7 @@ def prepare_env_and_get_command(
         "--scan_config",
         get_submitted_yaml_path(uid),
         "--inference_type",
-        inference_type,
+        "hf_inference_api",
         "--inference_api_token",
         inference_token,
     ]

text_classification_ui_helpers.py

@@ -43,7 +43,7 @@ MAX_FEATURES = 20
 ds_dict = None
 ds_config = None
 
-def get_related_datasets_from_leaderboard(model_id):
+def get_related_datasets_from_leaderboard(model_id, dataset_id_input):
     records = leaderboard.records
     model_id = strip_model_id_from_url(model_id)
     model_records = records[records["model_id"] == model_id]
@@ -52,7 +52,10 @@ def get_related_datasets_from_leaderboard(model_id):
     if len(datasets_unique) == 0:
         return gr.update(choices=[])
     
-    return gr.update(choices=datasets_unique)
+    if dataset_id_input in datasets_unique:
+        return gr.update(choices=datasets_unique)
+    
+    return gr.update(choices=datasets_unique, value="")
 
 
 logger = logging.getLogger(__file__)
@@ -249,7 +252,6 @@ def align_columns_and_show_prediction(
     dataset_config,
     dataset_split,
     uid,
-    run_inference,
     inference_token,
 ):
     model_id = strip_model_id_from_url(model_id)
@@ -344,7 +346,7 @@ def align_columns_and_show_prediction(
             gr.update(value=prediction_input, lines=min(len(prediction_input)//225 + 1, 5), visible=True),
             gr.update(value=prediction_response, visible=True),
             gr.update(visible=True, open=True),
-            gr.update(interactive=(run_inference and inference_token != "")),
+            gr.update(interactive=(inference_token != "")),
             "",
             *column_mappings,
         )
@@ -354,7 +356,7 @@ def align_columns_and_show_prediction(
         gr.update(value=prediction_input, lines=min(len(prediction_input)//225 + 1, 5), visible=True),
         gr.update(value=prediction_response, visible=True),
         gr.update(visible=True, open=False),
-        gr.update(interactive=(run_inference and inference_token != "")),
+        gr.update(interactive=(inference_token != "")),
         "",
         *column_mappings,
     )
@@ -372,8 +374,8 @@ def check_column_mapping_keys_validity(all_mappings):
 
     return True
 
-def enable_run_btn(uid, run_inference, inference_token, model_id, dataset_id, dataset_config, dataset_split):
-    if not run_inference or inference_token == "":
+def enable_run_btn(uid, inference_token, model_id, dataset_id, dataset_config, dataset_split):
+    if inference_token == "":
         logger.warn("Inference API is not enabled")
         return gr.update(interactive=False)
     if model_id == "" or dataset_id == "" or dataset_config == "" or dataset_split == "":
@@ -419,7 +421,7 @@ def show_hf_token_info(token):
         return gr.update(visible=True)
     return gr.update(visible=False)
 
-def try_submit(m_id, d_id, config, split, inference, inference_token, uid):
+def try_submit(m_id, d_id, config, split, inference_token, uid):
     all_mappings = read_column_mapping(uid)
     if not check_column_mapping_keys_validity(all_mappings):
         return (gr.update(interactive=True), gr.update(visible=False))
@@ -437,7 +439,6 @@ def try_submit(m_id, d_id, config, split, inference, inference_token, uid):
             d_id,
             config,
             split,
-            inference,
             inference_token,
             uid,
             label_mapping,

wordings.py

@@ -1,7 +1,9 @@
 INTRODUCTION_MD = """
+                <div style="display: flex; justify-content: center;">
                 <h1 style="text-align: center;">
                 🐢Giskard Evaluator - Text Classification
                 </h1>
+                </div>
                 Welcome to the Giskard Evaluator Space! Get a model vulnerability report immediately by simply sharing your model and dataset id below. 
                 You can also checkout our library documentation <a href="https://docs.giskard.ai/en/latest/getting_started/quickstart/index.html">here</a>.
                 """
@@ -26,9 +28,7 @@ CHECK_CONFIG_OR_SPLIT_RAW = """
                             Please check your dataset config or split.
                             """
 
-CHECK_LOG_SECTION_RAW = """
-                          Your have successfully submitted a Giskard evaluation. Further details are available in the Logs tab. You can find your report will be posted to your model's community discussion.
-                        """
+CHECK_LOG_SECTION_RAW = """Your have successfully submitted a Giskard evaluation job. Further details are available in the Logs tab. You can find your report posted in your model's community discussion section."""
 
 PREDICTION_SAMPLE_MD = """
                         <h1 style="text-align: center;">
@@ -58,7 +58,7 @@ USE_INFERENCE_API_TIP = """
                 <a href="https://huggingface.co/docs/api-inference/detailed_parameters#text-classification-task">
                     Hugging Face Inference API
                 </a>
-                . Please input your <a href="https://huggingface.co/settings/tokens">Hugging Face token</a> to do so. You can find it <a href="https://huggingface.co/settings/tokens">here</a>.
+                . Please input your <a href="https://huggingface.co/docs/hub/security-tokens#user-access-tokens">Hugging Face token</a> to do so. You can find it <a href="https://huggingface.co/settings/tokens">here</a>.
             """
 
 HF_TOKEN_INVALID_STYLED= """