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()