reformatted with black

app.py

@@ -5,25 +5,58 @@ from src.nlp_circle_demo.interface import GradioElementWrapper
 GradioElementWrapper.interface_from_yaml("resources/qa_interface.yml")
 
 
+robertaGer = GradioElementWrapper.interface_from_yaml(
+    "resources/legal_german_roberta_interface.yml"
+).gradio_element
+gbert = GradioElementWrapper.interface_from_yaml(
+    "resources/gbert_interface.yml"
+).gradio_element
 
-robertaGer = GradioElementWrapper.interface_from_yaml("resources/legal_german_roberta_interface.yml").gradio_element
-gbert = GradioElementWrapper.interface_from_yaml("resources/gbert_interface.yml").gradio_element
+ner = GradioElementWrapper.interface_from_yaml(
+    "resources/ner_interface.yml"
+).gradio_element
 
-ner = GradioElementWrapper.interface_from_yaml("resources/ner_interface.yml").gradio_element
 
-
-zeroShot = GradioElementWrapper.interface_from_yaml("resources/zero_shot_interface.yml").gradio_element
+zeroShot = GradioElementWrapper.interface_from_yaml(
+    "resources/zero_shot_interface.yml"
+).gradio_element
 
 legalInterface = gr.TabbedInterface([robertaGer, gbert], ["Roberta Legal", "Bert"])
 
 
-qaInterface = GradioElementWrapper.interface_from_yaml("resources/qa_interface.yml").gradio_element
-simplicationInterface = GradioElementWrapper.interface_from_yaml("resources/simplification_interface.yml").gradio_element
-gptInterface = GradioElementWrapper.interface_from_yaml("resources/gpt2_interface.yml").gradio_element
-summarizationInterface = GradioElementWrapper.interface_from_yaml("resources/summarization_interface.yml").gradio_element
-
-
-demo = gr.TabbedInterface([gptInterface, legalInterface ,qaInterface, summarizationInterface, simplicationInterface, ner, zeroShot], [
-                          "GPT", "Legal", "Question Answering", "Summarization", "Simplification", "Named Entity Recognition", "Zero-Shot-Klassifizierung"])
+qaInterface = GradioElementWrapper.interface_from_yaml(
+    "resources/qa_interface.yml"
+).gradio_element
+simplicationInterface = GradioElementWrapper.interface_from_yaml(
+    "resources/simplification_interface.yml"
+).gradio_element
+gptInterface = GradioElementWrapper.interface_from_yaml(
+    "resources/gpt2_interface.yml"
+).gradio_element
+summarizationInterface = GradioElementWrapper.interface_from_yaml(
+    "resources/summarization_interface.yml"
+).gradio_element
+
+
+demo = gr.TabbedInterface(
+    [
+        gptInterface,
+        legalInterface,
+        qaInterface,
+        summarizationInterface,
+        simplicationInterface,
+        ner,
+        zeroShot,
+    ],
+    [
+        "GPT",
+        "Legal",
+        "Question Answering",
+        "Summarization",
+        "Simplification",
+        "Named Entity Recognition",
+        "Zero-Shot-Klassifizierung",
+    ],
+)
 
 demo.launch()

src/nlp_circle_demo/interface.py

@@ -2,8 +2,8 @@ import gradio as gr
 import json
 import yaml
 
-class GradioElementWrapper:
 
+class GradioElementWrapper:
     def __init__(self, title, gradio_element):
         self.title = title
         self.gradio_element = gradio_element
@@ -20,17 +20,15 @@ class GradioElementWrapper:
         """Creates Gradio-Element containing an interface."""
         description = cls._prepend_link_to_description(name, title, description)
         element = gr.load(
-            name, 
+            name,
             title=None,  # Having the Tab-Name is sufficient.
-            description=description, 
-            examples=examples
+            description=description,
+            examples=examples,
         )
         return cls(title, element)
 
     @staticmethod
     def _prepend_link_to_description(name, title, description):
         without_huggingface = name.removeprefix("huggingface/")
-        link = f'https://huggingface.co/{without_huggingface}'
+        link = f"https://huggingface.co/{without_huggingface}"
         return f'<a href="{link}">{title}</a> </br> {description}'
-
-