Spaces:
Running
Running
File size: 1,602 Bytes
f8497b9 138e89c 1c9c9dd 16a4075 1c9c9dd f8497b9 cb437b6 16a4075 cb437b6 138e89c f8497b9 138e89c f8497b9 138e89c f8497b9 138e89c f8497b9 138e89c f8497b9 138e89c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 |
import streamlit as st
import requests
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
API_URL = "https://14d0-34-27-134-153.ngrok-free.app/query" # Replace with your ngrok public URL
st.set_page_config(
page_title="SQL Agent with Streamlit",
page_icon=":bar_chart:",
layout="wide"
)
with st.sidebar:
st.write("## About Me")
st.write("**Mahmoud Hassanen**")
st.write("**[LinkedIn Profile](https://www.linkedin.com/in/mahmoudhassanen99//)**")
st.title("SQL Agent with Streamlit")
st.header("Analyze Sales Data with Natural Language Queries")
# Input for the question
question = st.text_input("Enter your question:")
if st.button("Submit"):
if question:
response = requests.post(API_URL, json={"question": question})
if response.status_code == 200:
data = response.json()
st.write("Generated SQL Query:")
st.code(data["sql_query"], language="sql")
st.write("Query Results:")
result_df = pd.read_json(data["result"], orient='records')
st.dataframe(result_df)
# Visualize the data
if 'region' in result_df.columns and 'total_sales' in result_df.columns:
st.write("Total Sales by Region")
fig, ax = plt.subplots()
sns.barplot(x='region', y='total_sales', data=result_df, ax=ax)
st.pyplot(fig)
else:
st.error(f"Error: {response.json().get('error')}")
else:
st.warning("Please enter a question.") |