app.py

from dotenv import load_dotenv
load_dotenv() ## Load all the environment variables

import streamlit as st
import os
import sqlite3

import google.generativeai as genai

## Configure our API Key
genai.configure(api_key=os.getenv("GOOGLE_API_KEYS"))

# Function to Load Google Gemini Model and provide sql query as response

def get_gemini_response(question,prompt):
    model = genai.GenerativeModel('gemini-pro')
    response = model.generate_content([prompt[0],question])
    return response.text

## Function to retrieve query from the sql database
def read_sql_query(sql,db):
    conn = sqlite3.connect(db)
    cur = conn.cursor()
    cur.execute(sql)
    rows = cur.fetchall()
    conn.commit()
    conn.close()
    for row in rows:
        print(row)
    return rows

## Define Your Prompt
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 and MARKS \n\nFor example,\nExample 1 - How many entries of records are present?,
    the SQL command will be something like the 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";
    also the sql code should not have ```in beginning or end in sql word in output
    """
]

## Streamlit App

st.set_page_config(page_title="I can Retrieve Any SQL query")
st.header("Gemini App to Retrieve SQL Data")

question = st.text_input("Input:",key="input")

submit = st.button("Ask the question")

# if submit is clicked
if submit:
    response = get_gemini_response(question,prompt)
    print(response)
    data = read_sql_query(response,"student.db")
    st.subheader("The Response is")
    for row in data:
        print(row)
        st.header(row)