app.py

import streamlit as st
import pandas as pd
import logging
from deeploy import Client
from utils import ChangeButtonColour
from utils import get_input_values, get_texts, feature_texts, example_input, response, first_five_posneg_indices

logging.basicConfig(level=logging.INFO)

st.set_page_config(layout="wide")

st.title("Observing potential fraudulent transactions")
st.divider()

st.write(
    "Fill in left hand side and click on button to observe a potential fraudulent transaction"
)

def send_evaluation(client, deployment_id, request_log_id, prediction_log_id, evaluation_input):
    """Send evaluation to Deeploy."""
    try:
        with st.spinner("Submitting response..."):
            # Call the explain endpoint as it also includes the prediction
            client.evaluate(deployment_id, request_log_id, prediction_log_id, evaluation_input)
        return True
    except Exception as e:
        logging.error(e)
        st.error(
            "Failed to submit feedback."
            + "Check whether you are using the right model URL and Token. "
            + "Contact Deeploy if the problem persists."
        )
        st.write(f"Error message: {e}")


def get_model_url():
    """Get model url and retrieve workspace id and deployment id from it"""
    model_url = st.text_area(
        "Model URL (default is the demo deployment)",
        "https://api.app.deeploy.ml/workspaces/708b5808-27af-461a-8ee5-80add68384c7/deployments/1785f8b8-c5a6-4f55-9a83-df8bdb0b9977/",
        height=125,
    )
    elems = model_url.split("/")
    try:
        workspace_id = elems[4]
        deployment_id = elems[6]
    except IndexError:
        workspace_id = ""
        deployment_id = ""
    return model_url, workspace_id, deployment_id

st.markdown("""
    <style>
        [data-testid=stSidebar] {
            background-color: #E0E0E0; ##E5E6EA
        }
    </style>
    """, unsafe_allow_html=True)

with st.sidebar:
    # Add deeploy logo
    st.image("deeploy_logo.png", width=270)
    # Ask for model URL and token
    host = st.text_input("Host (changing is optional)", "app.deeploy.ml")
    model_url, workspace_id, deployment_id = get_model_url()
    deployment_token = st.text_input("Deeploy Model Token", "my-secret-token")
    if deployment_token == "my-secret-token":
        button_clicked = st.button("Get suspicious transaction", key="get1", help="Click to get a suspicious transaction", use_container_width=True, on_click=lambda: st.experimental_rerun())

    # define client options and instantiate client
    client_options = {
    "host": host,
    "deployment_token": deployment_token,
    "workspace_id": workspace_id,
    }
    client = Client(**client_options)


ChangeButtonColour("Get suspicious transaction", '#FFFFFF', "#00052D")#'#FFFFFF', "#00052D"


positive_and_negative_indices = first_five_posneg_indices(response)
positive_texts, negative_texts = get_texts(positive_and_negative_indices, feature_texts)
positive_vals, negative_vals = get_input_values(positive_and_negative_indices, example_input)

# Create a function to generate a table
def create_table(texts, values, title):
    # TODO: change color dataframe header -> tried many different options but none worked see below
    # header_style = '''
    # <style>
    #     th{
    #         background-color: #00052D;
    #     }
    # </style>
    # '''
    df = pd.DataFrame({"Feature Explanation": texts, 'Value': values})
    # df = df.style.set_properties(**{
    #        'selector': 'th',
    #        'props': [
    #            ('background-color', 'black'),
    #            ('color', 'cyan')]
    #    })
    # df = df.style.set_properties(**{'background-color': 'black',
    #                        'color': 'green'})

    # headers = {
    #     'selector': 'th',
    #     'props': [('background-color', '#67c5a4')]#'background-color: #000066; color: white;'
    #     }
    # df = df.style.set_table_styles([headers])
    st.markdown(f'#### {title}')  # Markdown for styling
    st.dataframe(df, hide_index=True)  # Display a simple table
    # st.markdown(header_style, unsafe_allow_html=True)

# Arrange tables horizontally using Streamlit columns
col1, col2 = st.columns(2,gap="small")

# Display tables in Streamlit columns
with col1:
    create_table(positive_texts, positive_vals, 'Important Suspicious Variables')

with col2:
    create_table(negative_texts, negative_vals, 'Important Unsuspicious Variables')