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machine-learning-ui
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import streamlit as st
import numpy as np
import pandas as pd


class Dashboard:
    class Model:
        pageTitle = "Dashboard"

        documentsTitle = "Documents"
        documentsCount = "10.5K"
        documentsDelta = "125"

        annotationsTitle = "Annotations"
        annotationsCount = "510"
        annotationsDelta = "-2"

        accuracyTitle = "Accuracy"
        accuracyCount = "87.9%"
        accuracyDelta = "0.1%"

        trainingTitle = "Training Time"
        trainingCount = "1.5 hrs"
        trainingDelta = "10 mins"

        processingTitle = "Processing Time"
        processingCount = "3 secs"
        processingDelta = "-0.1 secs"

        titleDataExtraction = "## Data Extraction"
        titleModelTraining = "## Model Training"
        titleDataAnnotation = "## Data Annotation"

    def view(self, model):
        st.title(model.pageTitle)

        with st.container():
            col1, col2, col3, col4, col5 = st.columns(5)

            with col1:
                st.metric(label=model.documentsTitle, value=model.documentsCount, delta=model.documentsDelta)

            with col2:
                st.metric(label=model.annotationsTitle, value=model.annotationsCount, delta=model.annotationsDelta)

            with col3:
                st.metric(label=model.accuracyTitle, value=model.accuracyCount, delta=model.accuracyDelta)

            with col4:
                st.metric(label=model.trainingTitle, value=model.trainingCount, delta=model.trainingDelta, delta_color="inverse")

            with col5:
                st.metric(label=model.processingTitle, value=model.processingCount, delta=model.processingDelta, delta_color="inverse")

            st.markdown("---")


        with st.container():
            st.write(model.titleDataExtraction)
            chart_data = pd.DataFrame(
                np.random.randn(20, 3),
                columns=['a', 'b', 'c'])

            st.line_chart(chart_data)

        st.markdown("---")

        with st.container():
            col1, col2 = st.columns(2)

            with col1:
                with st.container():
                    st.write(model.titleModelTraining)

                    # You can call any Streamlit command, including custom components:
                    st.bar_chart(np.random.randn(50, 3))

            with col2:
                with st.container():
                    st.write(model.titleDataAnnotation)

                    chart_data = pd.DataFrame(
                        np.random.randn(20, 3),
                        columns=['a', 'b', 'c'])

                    st.area_chart(chart_data)