Text-to-SQL-PagilaDB / streamlit_app.py
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Update streamlit_app.py
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# streamlit_app.py
import streamlit as st
import requests
import pandas as pd
st.set_page_config(page_title="Text to SQL - PagilaDB")
st.markdown("# Text to SQL - PagilaDB🤖")
st.markdown('''Your friendly assistant for converting natural language queries into SQL statements!
Ask questions about the Pagila DVD rental database.''')
# Initialize chat history
if 'chat_history' not in st.session_state:
st.session_state.chat_history = []
# Predefined queries
# Update the predefined_queries list
predefined_queries = [
'List the top 10 most rented movies with their rental counts',
'Calculate total revenue for each movie category',
'Find customers who have spent more than $150 total',
'Show all movies in the Action category with their rental rates',
]
st.markdown("### Predefined Queries")
for query in predefined_queries:
if st.button(query):
st.session_state.predefined_query = query
st.markdown("### Enter Your Question")
question = st.text_input("Input: ", key="input", value=st.session_state.get('predefined_query', ''))
if st.button("Submit"):
response = requests.post("http://localhost:8000/query",
json={"question": question})
if response.status_code == 200:
data = response.json()
st.markdown("## Generated SQL Query")
st.code(data['query'], language='sql')
st.markdown("## Query Results")
df = pd.DataFrame(data['result'])
st.dataframe(df)
# Update chat history
st.session_state.chat_history.append(f"👨‍💻: {question}")
st.session_state.chat_history.append(f"🤖: {data['query']}")
else:
st.error(f"Error: {response.text}")
st.session_state.pop('predefined_query', None)
st.markdown("## Chat History")
for message in st.session_state.chat_history:
st.text(message)
if st.button("Clear History"):
st.session_state.chat_history = []
st.success("Chat history cleared!")