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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')
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