feat: upgrad to gradio 5.0

README.md

@@ -5,7 +5,7 @@ emoji: 🧬
 colorFrom: yellow
 colorTo: pink
 sdk: gradio
-sdk_version: 4.44.0
+sdk_version: 5.5.0
 app_file: app.py
 pinned: true
 license: apache-2.0

pyproject.toml

@@ -6,8 +6,8 @@ authors = [
     {name = "davidberenstein1957", email = "[email protected]"},
 ]
 dependencies = [
-    "distilabel[hf-inference-endpoints,argilla]==1.4.0",
-    "gradio[oauth]<5,>=4.38",
+    "distilabel[hf-inference-endpoints,argilla]>=1.4.1",
+    "gradio[oauth]>=5.5.0",
     "transformers>=4.44.2",
     "sentence-transformers>=3.2.0",
     "model2vec>=0.2.4",

src/distilabel_dataset_generator/apps/base.py

@@ -13,9 +13,9 @@ from huggingface_hub import HfApi, upload_file
 from src.distilabel_dataset_generator.utils import (
     _LOGGED_OUT_CSS,
     get_argilla_client,
+    get_login_button,
     list_orgs,
     swap_visibilty,
-    get_login_button,
 )
 
 TEXTCAT_TASK = "text_classification"
@@ -258,7 +258,7 @@ def get_iterate_on_sample_dataset_ui(
         with gr.Row():
             gr.Column(scale=1)
             btn_generate_system_prompt = gr.Button(
-                value="Generate system prompt and sample dataset"
+                value="Generate system prompt and sample dataset", variant="primary"
             )
             gr.Column(scale=1)
 
@@ -283,7 +283,7 @@ def get_iterate_on_sample_dataset_ui(
         with gr.Row():
             gr.Column(scale=1)
             btn_generate_sample_dataset = gr.Button(
-                value="Generate sample dataset",
+                value="Generate sample dataset", variant="primary"
             )
             gr.Column(scale=1)
 
@@ -432,17 +432,17 @@ def push_dataset_to_hub(
                 {"text": Value("string"), "label": ClassLabel(names=labels)}
             )
         else:
-            features = Features({
-                "text": Value("string"),
-                "labels": Sequence(feature=ClassLabel(names=labels))
-            })
-        distiset = Distiset({
-            "default": Dataset.from_pandas(dataframe, features=features)
-        })
+            features = Features(
+                {
+                    "text": Value("string"),
+                    "labels": Sequence(feature=ClassLabel(names=labels)),
+                }
+            )
+        distiset = Distiset(
+            {"default": Dataset.from_pandas(dataframe, features=features)}
+        )
     else:
-        distiset = Distiset({
-            "default": Dataset.from_pandas(dataframe)
-        })
+        distiset = Distiset({"default": Dataset.from_pandas(dataframe)})
     progress(0.2, desc="Pushing dataset to hub")
     distiset.push_to_hub(
         repo_id=repo_id,

src/distilabel_dataset_generator/apps/textcat.py

@@ -316,6 +316,7 @@ def validate_input_labels(labels):
         )
     return labels
 
+
 def update_max_num_labels(labels):
     return gr.update(maximum=len(labels) if labels else 1)
 
@@ -392,6 +393,7 @@ with app:
                 with gr.Blocks():
                     btn_suggested_labels = gr.Button(
                         value="Add suggested labels",
+                        variant="primary",
                         size="sm",
                     )
             num_labels = gr.Number(