my_model/tabs/results.py

import pandas as pd
from fuzzywuzzy import fuzz
from collections import Counter
from nltk.stem import PorterStemmer
from ast import literal_eval
from typing import Union, List
import streamlit as st
from my_model.results.evaluation import KBVQAEvaluator

class ResultDemonstrator(KBVQAEvaluator):



    def run(self):
       
        import pandas as pd
        import altair as alt
        
        # Sample data
        data = pd.DataFrame({
            'x': range(10),
            'y': [2, 1, 4, 3, 5, 6, 9, 7, 10, 8]
        })
        
        # Create a scatter plot
        chart = alt.Chart(data).mark_point().encode(
            x='x',
            y='y'
        )
        
        # Display the chart in Streamlit
        st.altair_chart(chart, use_container_width=True)
        # Display the chart in Streamlit
        st.altair_chart(chart, use_container_width=True)

        import matplotlib.pyplot as plt
        import numpy as np
        
        # Data
        x = np.random.randn(100)
        y = np.random.randn(100)
        
        # Create a scatter plot
        fig, ax = plt.subplots()
        ax.scatter(x, y)
        
        # Display the plot in Streamlit
        st.pyplot(fig)

        import plotly.express as px
      
        
        # Data
        df = pd.DataFrame({
            "x": range(10),
            "y": [2, 1, 4, 3, 5, 6, 9, 7, 10, 8],
            "color": ["red"] * 5 + ["blue"] * 5
        })
        
        # Create an interactive scatter plot
        fig = px.scatter(df, x='x', y='y', color='color')
        
        # Display the plot in Streamlit
        st.plotly_chart(fig)