merge and resolve conflicts

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

@@ -36,6 +36,10 @@ def get_demo():
         uid_label = gr.Textbox(
             label="Evaluation ID:", value=uuid.uuid4, visible=False, interactive=False
         )
+    
+    with gr.Accordion(label="Login to Use This Space", open=True):
+        gr.HTML(LOG_IN_TIPS)
+        gr.LoginButton()
     with gr.Row():
         model_id_input = gr.Textbox(
             label="Hugging Face Model id",
@@ -90,11 +94,7 @@ 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):
-        gr.HTML(LOG_IN_TIPS)
-        gr.LoginButton()
-
-    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])
@@ -128,7 +128,7 @@ 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,
         )
@@ -139,7 +139,7 @@ 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,

requirements.txt

@@ -1,4 +1,4 @@
-giskard
+-e git+https://github.com/Giskard-AI/giskard.git@b4849c93e1b40f5597d6509c4e9c58b0fff10483#egg=giskard
 huggingface_hub
 hf-transfer
 torch==2.0.1

run_jobs.py

@@ -98,6 +98,7 @@ def prepare_env_and_get_command(
         "hf_inference_api",
         "--inference_api_token",
         inference_token,
+        "--persist_scan",
     ]
     # The token to publish post
     if os.environ.get(HF_WRITE_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__)

wordings.py

@@ -26,9 +26,7 @@ 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 +56,7 @@ 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>.
             """
 
 LOG_IN_TIPS = """