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import gradio as gr
import librosa
from asr import transcribe, ASR_EXAMPLES, ASR_LANGUAGES, ASR_NOTE
from tts import synthesize, TTS_EXAMPLES, TTS_LANGUAGES
from lid import identify, LID_EXAMPLES
import os

# Disable HF_HUB_ENABLE_HF_TRANSFER
os.environ['HF_HUB_ENABLE_HF_TRANSFER'] = '0'

demo = gr.Blocks()

mms_select_source_trans = gr.Radio(
    ["Tak upp", "Ljóðfíla"],
    label="Ljóð til talukennara",
    value="Tak upp",
)
mms_mic_source_trans = gr.Audio(source="microphone", type="filepath", label="Brúka mikrofonina", visible=True)
mms_upload_source_trans = gr.Audio(
    source="upload", type="filepath", label="Legg ljóðfílu upp", visible=False
)

# Add back the language selection dropdown but set it to be hidden and default to Faroese
asr_language_dropdown = gr.Dropdown(
    [f"{k} ({v})" for k, v in ASR_LANGUAGES.items()],
    label="Mál",
    value="fao (Faroese)",
    visible=False,
)

mms_transcribe = gr.Interface(
    fn=transcribe,
    inputs=[
        mms_select_source_trans,
        mms_mic_source_trans,
        mms_upload_source_trans,
        asr_language_dropdown,
    ],
    outputs="text",
    examples=ASR_EXAMPLES,
    title="Talukennari",
    description=(
        "Tak upp beinleiðis úr kaganum, ella legg eina ljóðfílu upp, og fá talukennaran at avskriva tað, ið verður sagt."
    ),
    article=ASR_NOTE,
    allow_flagging="never",
)

# Add back the language selection dropdown but set it to be hidden and default to Faroese
tts_language_dropdown = gr.Dropdown(
    [f"{k} ({v})" for k, v in TTS_LANGUAGES.items()],
    label="Mál",
    value="fao (Faroese)",
    visible=False,
)

mms_synthesize = gr.Interface(
    fn=synthesize,
    inputs=[
        gr.Text(label="Tekstur at lesa upp"),
        tts_language_dropdown,
        gr.Slider(minimum=0.1, maximum=4.0, value=1.0, step=0.1, label="Ferð"),
    ],
    outputs=[
        gr.Audio(label="Ljóð frá teldutaluni", type="numpy"),
        gr.Text(label="Teksturin, sum verður lisin upp"),
    ],
    examples=TTS_EXAMPLES,
    title="Teldutala",
    description=("Fá tekstin lisnan upp við teldutalu."),
    allow_flagging="never",
)

mms_select_source_iden = gr.Radio(
    ["Tak upp frá mikrofonini", "Vel ljóðfílu"],
    label="Audio input",
    value="Tak upp frá mikrofonini",
)
mms_mic_source_iden = gr.Audio(source="microphone", type="filepath", label="Use mic", visible=True)
mms_upload_source_iden = gr.Audio(
    source="upload", type="filepath", label="Upload file", visible=False
)
mms_identify = gr.Interface(
    fn=identify,
    inputs=[
        mms_select_source_iden,
        mms_mic_source_iden,
        mms_upload_source_iden,
    ],
    outputs=gr.Label(num_top_classes=10),
    examples=LID_EXAMPLES,
    title="Máleyðmerkjari",
    description=("Tak upp ella legg eina ljóðfílu upp og fá máleyðmerkjaran at gita, hvat mál tú snakkar."),
    allow_flagging="never",
)

tabbed_interface = gr.TabbedInterface(
    [mms_transcribe, mms_synthesize, mms_identify],
    ["Talukennari", "Teldutala", "Máleyðmerkjari"],
)

with gr.Blocks() as demo:

    tabbed_interface.render()
    mms_select_source_trans.change(
        lambda x: [
            gr.update(visible=True if x == "Tak upp" else False),
            gr.update(visible=True if x == "Ljóðfíla" else False),
        ],
        inputs=[mms_select_source_trans],
        outputs=[mms_mic_source_trans, mms_upload_source_trans],
        queue=False,
    )
    mms_select_source_iden.change(
        lambda x: [
            gr.update(visible=True if x == "Tak upp frá mikrofonini" else False),
            gr.update(visible=True if x == "Vel ljóðfílu" else False),
        ],
        inputs=[mms_select_source_iden],
        outputs=[mms_mic_source_iden, mms_upload_source_iden],
        queue=False,
    )
    gr.HTML(
        """
            <div class="footer" style="text-align:center">
                <p>
                    <a href="https://ai.facebook.com" style="text-decoration: underline;" target="_blank">Meta AI</a> gjørdi málmyndilin - Koyrir á 🤗 Hugging Face 
                </p>
            </div>
           """
    )

demo.queue(concurrency_count=3)
demo.launch()