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import streamlit as st
import pandas as pd
import requests
import io
# Configure Streamlit page
st.set_page_config(
page_title="SuperKart Sales Prediction",
page_icon="🛒",
layout="wide"
)
# Add custom CSS
st.markdown("""
<style>
.stButton>button {
width: 100%;
background-color: #4CAF50;
color: white;
padding: 10px;
border: none;
border-radius: 4px;
cursor: pointer;
}
.stButton>button:hover {
background-color: #45a049;
}
</style>
""", unsafe_allow_html=True)
st.title("SuperKart Sales Prediction")
st.write("Upload your CSV file to get sales predictions")
# File uploader
uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
if uploaded_file is not None:
try:
# Display the uploaded data
df = pd.read_csv(uploaded_file)
st.write("Preview of uploaded data:")
st.dataframe(df.head())
# Add a button for predictions
if st.button("Get Predictions", key="predict_button"):
with st.spinner("Getting predictions..."):
# Prepare the file for API request
files = {"file": ("data.csv", uploaded_file.getvalue(), "text/csv")}
try:
# Make request to the backend API
response = requests.post("https://huggingface.co/spaces/abhishek-kumar/superkart_sales_backend/predict", files=files)
if response.status_code == 200:
predictions = response.json()["predictions"]
# Add predictions to the dataframe
df["Predicted_Sales"] = predictions
st.success("Predictions generated successfully!")
st.write("Predictions:")
st.dataframe(df)
# Download button for results
csv = df.to_csv(index=False)
st.download_button(
label="Download predictions",
data=csv,
file_name="predictions.csv",
mime="text/csv"
)
else:
st.error(f"Error getting predictions from the API. Status code: {response.status_code}")
except Exception as e:
st.error(f"Error: {str(e)}")
except Exception as e:
st.error(f"Error reading the CSV file: {str(e)}") |