# Basic Workflow
#Prompt -> LLM(Gemini Pro) -> Query -> SQL Database -> Response
from dotenv import load_dotenv
load_dotenv() ## load all environment variables
import streamlit as st  
import os
import sqlite3
import google.generativeai as genai

##configure api key by calling from .env file
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

# Function to load Google Gemini Model and provide 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 SQL Database. this will hit the database and get the result 

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

prompt = [
  """
  You are an expert in converting English question to SQL query! The SQL databse has the name STUDENT and has following columns - NAME, CLASS, SECTION and MARKS \n\nFor example, \nExample1 - 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 student 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 begining or end and sql word in the output.  
  """
]

#Streamlit APP

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

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

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

#get response
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)