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import gradio as gr

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

ner = GradioElementWrapper.interface_from_yaml("resources/ner_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"])

demo.launch()