app.py

from dotenv import load_dotenv
load_dotenv() ## load all environment variables

import streamlit as st
import os
import sqlite3

import google.generativeai as genai

genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

## Function to load google gemini model and provide queries 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 db

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 the 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 \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"; 

    also the sql code should not have ``` in beginning or end and 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)
    response=read_sql_query(response,"student.db")
    st.subheader("The response is")
    for row in response:
        print(row)
        st.header(row)