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 GenAI Key

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')       ## gemini-pro --> text,   gemini-pro-vision --> images/videos
    response = model.generate_content([prompt[0], question])
    return response.text

## function to retrieve the query from the 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 our prompt
prompt = [
    """
        You are an expert in converting English quetions to SQL query!
        The SQL database name is STUDENT and has the following columns - NAME, CLASS, 
        SECTION \n\nFor Example, \nExample 1- How many entries of record are present?,
        the SQL command will be something like this SELECT COUNT(*) FROM STUDENT ;
        \nExample 2 - Tell me all the students studying in DS class?,
        the SQL command will be something like this SELECT * FROM STUDENT WHERE CLASS='DS' ;
        also the sql code should not have ``` in the beginning or end and sql word in output
    """
]

st.set_page_config(page_title='I can Retrieve Any SQL query')
st.header('Gemini Pro App To Retrieve SQL Data')

question = st.text_input('Inpit', key='input')

submit = st.button('Ask the quetion')

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