app.py

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}")