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from dotenv import load_dotenv
import streamlit as st
import os
import sqlite3
import google.generativeai as genai
# Configure API key
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
def get_gemini_response(question, prompt):
model = genai.GenerativeModel('gemini-pro')
response = model.generate_content([prompt[0], question])
return response.text.strip()
def read_sql_query(sql, db):
conn = sqlite3.connect(db)
cur = conn.cursor()
cur.execute(sql)
rows = cur.fetchall()
conn.commit()
conn.close()
return rows
# Prompt for the application
prompt = [
"""
You are an expert in converting English questions to SQL query!
The SQL database has the name STUDENT and has the following columns - NAME, CLASS,
SECTION \n\nFor example,\nExample 1 - How many entries of records are present?,
the SQL command will be something like this SELECT COUNT(*) FROM STUDENT ;
\nExample 2 - Tell me all the students studying in Data Science class?,
the SQL command will be something like this SELECT * FROM STUDENT
where CLASS="Data Science";
"""
]
# Streamlit app
st.set_page_config(page_title="Text to SQL Query Converter")
st.title("Text to SQL Query Converter")
# User input
question = st.text_input("Enter your question:", key="input")
# Submit button
if st.button("Convert to SQL Query"):
if not question:
st.error("Please enter a question.")
else:
# Generate SQL query from the question
sql_query = get_gemini_response(question, prompt)
st.write("SQL Query:")
st.code(sql_query)
# Execute the SQL query and display results
try:
results = read_sql_query(sql_query, "student.db")
if results:
st.success("Query executed successfully. Results:")
st.table(results)
else:
st.warning("No results found.")
except Exception as e:
st.error(f"An error occurred: {e}")
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