jskinner215/TAPAS_Churn

1import streamlit as st2from st_aggrid import AgGrid3import pandas as pd 4# from PIL import Image5from transformers import pipeline6st.set_page_config(layout="wide")7 8# im = Image.open("ai-favicon.png")9# st.set_page_config(page_title="Table Summarization",10#     page_icon=im,layout='wide') 11 12 13style = '''14    <style>15        body {background-color: #F5F5F5; color: #000000;}16        header {visibility: hidden;}17        div.block-container {padding-top:4rem;}18        section[data-testid="stSidebar"] div:first-child {19        padding-top: 0;20    }21     .font {                                          22    text-align:center;23    font-family:sans-serif;font-size: 1.25rem;}24    </style>25'''26st.markdown(style, unsafe_allow_html=True)27 28st.markdown('<p style="font-family:sans-serif;font-size: 1.9rem;">Table Question Answering using TAPAS</p>', unsafe_allow_html=True)29st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'>Pre-trained TAPAS model runs on max 64 rows and 32 columns data. Make sure the file data doesn't exceed these dimensions.</p>", unsafe_allow_html=True)30 31tqa = pipeline(task="table-question-answering", 32                    model="google/tapas-large-finetuned-wtq")33 34 35# st.sidebar.image("ai-logo.png",width=200)36# with open('data.csv', 'rb') as f:37#         st.sidebar.download_button('Download sample data', f, file_name='Sample Data.csv')38file_name = st.sidebar.file_uploader("Upload file:", type=['csv','xlsx'])39 40if file_name is None:41    st.markdown('<p class="font">Please upload an excel or csv file </p>', unsafe_allow_html=True)42    # st.image("loader.png")43 44else:45    try:46        df=pd.read_csv(file_name)47    except:48        df = pd.read_excel(file_name)49         50    grid_response = AgGrid(51        df.head(5),52        columns_auto_size_mode='FIT_CONTENTS',53        editable=True, 54        height=300, 55        width='100%',56        )57 58    question = st.text_input('Type your question')59    df = df.astype(str)60    61    with st.spinner():62        if(st.button('Answer')):63            answer = tqa(table=df, query=question,truncation=True)64            st.markdown("<p style='font-family:sans-serif;font-size: 0.9rem;'> Results </p>",unsafe_allow_html = True)65            st.success(answer)