app.py

import gradio as gr
from llm_call import GeminiLLM
from seminar_edition_ai import upload_file_ex, predictContemplando, predictProclamando, predictFromInit, \
    downloadSermonFile, fileAddresToDownload, predictQuestionBuild, predictDevotionBuild, \
    contemplandoQuestion, proclamandoQuestion, llm, embed_model

HISTORY_ANSWER = ''

with gr.Blocks() as demo:
    gr.Markdown("SermonLab AI Demo.")
    with gr.Tab("Preparando mi Sermón"):
        text_input = gr.Textbox(label="Tópico del sermón")

        with gr.Accordion("Contemplando y Proclamando", open=False):
            checkButton = gr.Checkbox(
                value=False,
                label="Mantener historial"
            )
            with gr.Row():
                with gr.Tab("Contemplando"):
                    inbtwContemplando = gr.Button(f"Devocionalmente: {contemplandoQuestion['DEVOCIONALMENTE']}")
                    inbtwContemplandoOne = gr.Button(f"Exégesis: {contemplandoQuestion['EXÉGESIS']}")
                    inbtwContemplandoTwo = gr.Button(f"Cristo: {contemplandoQuestion['CRISTO']}")
                    inbtwContemplandoTree = gr.Button(f"Arco Redentor: {contemplandoQuestion['ARCO REDENTOR']}")
                    inbtwContemplandoFour = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION']}")
                    inbtwContemplandoFourOne = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION_TWO']}")

                with gr.Tab("Proclamando"):
                    inbtwProclamando = gr.Button(f"Público: {proclamandoQuestion['PÚBLICO']}")
                    inbtwProclamandoOne = gr.Button(f"Historia: {proclamandoQuestion['HISTORIA']}")
                    inbtwProclamandoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS']}")
                    inbtwProclamandoTwoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS_TWO']}")

        text_output = gr.Textbox(label="Respuesta", lines=10)

        text_button = gr.Button("Crear")

        text_download = gr.DownloadButton(
            label="Descargar",
            value=fileAddresToDownload,
            every=10
        )

        inbtwContemplando.click(
            fn=lambda x: predictContemplando(f"DEVOCIONALMENTE"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwContemplandoOne.click(
            fn=lambda x: predictContemplando(f"EXÉGESIS"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwContemplandoTwo.click(
            fn=lambda x: predictContemplando(f"CRISTO"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwContemplandoTree.click(
            fn=lambda x: predictContemplando(f"ARCO REDENTOR"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwContemplandoFour.click(
            fn=lambda x: predictContemplando(f"EVANGELION"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwContemplandoFourOne.click(
            fn=lambda x: predictContemplando(f"EVANGELION_TWO"),
            inputs=text_input,
            outputs=text_output
        )

        ##---------------------------------------------------------------------

        inbtwProclamando.click(
            fn=lambda x: predictProclamando(f"PÚBLICO"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwProclamandoOne.click(
            fn=lambda x: predictProclamando(f"HISTORIA"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwProclamandoTwo.click(
            fn=lambda x: predictProclamando(f"EXPECTATIVAS"),
            inputs=text_input,
            outputs=text_output
        )

        inbtwProclamandoTwoTwo.click(
            fn=lambda x: predictProclamando(f"EXPECTATIVAS_TWO"),
            inputs=text_input,
            outputs=text_output
        )

        text_button.click(
            fn=predictFromInit,
            inputs=text_input,
            outputs=text_output
        )

        text_download.click(
            fn=downloadSermonFile,
            inputs=text_output
        )
    with gr.Tab("Obtener guía de la comunidad (Preguntas)"):
        with gr.Accordion("Contemplando y Proclamando", open=False):
            checkButton = gr.Checkbox(
                value=False,
                label="Mantener historial"
            )
            with gr.Row():
                with gr.Tab("Contemplando"):
                    inbtwContemplando = gr.Button(f"Devocionalmente: {contemplandoQuestion['DEVOCIONALMENTE']}")
                    inbtwContemplandoOne = gr.Button(f"Exégesis: {contemplandoQuestion['EXÉGESIS']}")
                    inbtwContemplandoTwo = gr.Button(f"Cristo: {contemplandoQuestion['CRISTO']}")
                    inbtwContemplandoTree = gr.Button(f"Arco Redentor: {contemplandoQuestion['ARCO REDENTOR']}")
                    inbtwContemplandoFour = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION']}")
                    inbtwContemplandoFourOne = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION_TWO']}")

                with gr.Tab("Proclamando"):
                    inbtwProclamando = gr.Button(f"Público: {proclamandoQuestion['PÚBLICO']}")
                    inbtwProclamandoOne = gr.Button(f"Historia: {proclamandoQuestion['HISTORIA']}")
                    inbtwProclamandoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS']}")
                    inbtwProclamandoTwoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS_TWO']}")
        with gr.Row():
            #Bibliografy about components
            # File (https://www.gradio.app/docs/gradio/file)
            # Download Button (https://www.gradio.app/docs/gradio/downloadbutton)
            with gr.Column():
                file_input_question = gr.File()
                upload_button_question = gr.UploadButton("Click to Upload a File", file_types=['.pdf'],
                                                         file_count="multiple")
            with gr.Column():
                temp_slider_question = gr.Slider(
                    minimum=1,
                    maximum=10,
                    value=1,
                    step=1,
                    interactive=True,
                    label="Preguntas",
                )
                text_output_question = gr.Textbox(label="Respuesta", lines=10)
        text_button_question = gr.Button("Crear guía de preguntas")
        text_download_question = gr.DownloadButton(
            label="Descargar",
            value=fileAddresToDownload,
            every=10
        )

        text_button_question.click(
            fn=predictQuestionBuild,
            outputs=text_output_question
        )

        upload_button_question.upload(upload_file_ex, inputs=upload_button_question,
                                      outputs=[file_input_question, text_output_question])

    with gr.Tab("Obtener guía de la comunidad (Devocionario)"):
        with gr.Row():
            #Bibliografy about components
            # File (https://www.gradio.app/docs/gradio/file)
            # Download Button (https://www.gradio.app/docs/gradio/downloadbutton)

            with gr.Column():
                file_input_devotions = gr.File()
                upload_button_devotion = gr.UploadButton("Click to Upload a File", file_types=['.pdf'],
                                                         file_count="multiple")

            with gr.Column():
                temp_slider_question = gr.Slider(
                    minimum=1,
                    maximum=10,
                    value=1,
                    step=1,
                    interactive=True,
                    label="Cantidad",
                )
                text_output_devotions = gr.Textbox(label="Respuesta", lines=10)
        text_button_devotion = gr.Button("Crear")
        text_download_question = gr.DownloadButton(
            label="Descargar",
            value=fileAddresToDownload,
            every=10
        )

        text_button_devotion.click(
            fn=predictDevotionBuild,
            outputs=text_output_devotions
        )

        upload_button_devotion.upload(
            upload_file_ex,
            inputs=upload_button_devotion,
            outputs=
            [file_input_devotions, text_output_devotions]
        )
    with gr.Tab("Contemplando y Proclamando (Guía de preguntas)"):
        with gr.Accordion("Contemplando y Proclamando", open=False):
            checkButton = gr.Checkbox(
                value=False,
                label="Mantener historial"
            )
            with gr.Row():
                with gr.Tab("Contemplando"):
                    inbtwContemplando = gr.Button(f"Devocionalmente: {contemplandoQuestion['DEVOCIONALMENTE']}")
                    inbtwContemplandoOne = gr.Button(f"Exégesis: {contemplandoQuestion['EXÉGESIS']}")
                    inbtwContemplandoTwo = gr.Button(f"Cristo: {contemplandoQuestion['CRISTO']}")
                    inbtwContemplandoTree = gr.Button(f"Arco Redentor: {contemplandoQuestion['ARCO REDENTOR']}")
                    inbtwContemplandoFour = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION']}")
                    inbtwContemplandoFourOne = gr.Button(f"Evangelión: {contemplandoQuestion['EVANGELION_TWO']}")

                with gr.Tab("Proclamando"):
                    inbtwProclamando = gr.Button(f"Público: {proclamandoQuestion['PÚBLICO']}")
                    inbtwProclamandoOne = gr.Button(f"Historia: {proclamandoQuestion['HISTORIA']}")
                    inbtwProclamandoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS']}")
                    inbtwProclamandoTwoTwo = gr.Button(f"Expectativas: {proclamandoQuestion['EXPECTATIVAS_TWO']}")
        with gr.Row():
            with gr.Column():
                #Answer for Contemplando y Proclamando questions


                text_output_guia = gr.Textbox(label="Respuesta", lines=10)


            with gr.Column(scale = 1):
                text1 = gr.Textbox(visible = False)
                #Button for calling AI Help
                text_button = gr.Button("Buscar más información (IA)")
                text2 = gr.Textbox(visible = False)
            with gr.Column():
                text_output_aiAnswer= gr.Textbox(label="Ayuda a mi respuesta", lines=10)

if __name__ == "__main__":
    llmBuilder = GeminiLLM()

    embed_model = llmBuilder.getEmbeddingsModel()
    llm = llmBuilder.getLLM()

    demo.launch()