from  dotenv import load_dotenv
load_dotenv()

import streamlit as st
import google.generativeai as genai
import sqlite3
import os

genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
model=genai.GenerativeModel('gemini-pro')


#dun to retrieve query from the sql database

def read_sql_query(sql,db):
    conn=sqlite3.connect(db)
    cursor=conn.cursor()
    cursor.execute(sql)
    rows=cursor.fetchall()
    conn.commit()
    conn.close()

    for row in rows:
        print(row)
    return rows

# prompt="""
# you are a professinal sql query expert, i will provide input what i want from database 
# ,you give me the query without quotes are comma or " "  double quotes or ```, just give me query
# """


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"; 
    \nExample 3-i marks should be greater 40 and atleast 2 person have score above 40 , retrive that class
    the SQL command will be something like this SELECT CLASS FROM STUDENT GROUP BY CLASS HAVING COUNT(*) >= 2 AND AVG(MARKS) > 50;
    \nExample 4-Find the names and marks of students in the Science class who have scored more than 60 marks.
    SQL Command Example: SELECT NAME, MARKS FROM STUDENT WHERE CLASS='Science' AND MARKS > 60;
    \nExample 5-List the classes with the highest average marks.
    SQL Command Example: SELECT CLASS FROM STUDENT GROUP BY CLASS HAVING AVG(MARKS) = (SELECT MAX(AVG(MARKS)) FROM STUDENT GROUP BY CLASS);
    
    also the sql code should not have ``` in beginning or end and sql word in output and 
     
    """


]

 

def gemini_sql_query(prompt,input):
    response=model.generate_content([prompt[0],input])
    return response.text


st.set_page_config("DataChat: Explore Your Database")
st.header("chat with your sql database")

input=st.text_input("enter your input/question ")

uploaded_file = st.file_uploader("Upload SQLite Database", type=["db"])

if uploaded_file is not None:
    # Read the contents of the uploaded database file
    connection = sqlite3.connect("uploaded.db")
    cursor = connection.cursor()
    cursor.executescript(uploaded_file.read().decode())
    connection.close()
    st.success("Database uploaded successfully.")

submit=st.button("submit")




if submit and uploaded_file:
    query=gemini_sql_query(prompt,input)
    response=read_sql_query(query,"uploaded.db")
    print(query)
    st.header("response")
    col1, col2 = st.columns(2)
    
    with col1:
        st.header("Response:")
        for row in response:
            st.write(row)

    with col2:
        st.header("Generated SQL Query:")
        st.code(query)
        if st.button("Copy SQL Query"):
            st.write("SQL query copied to clipboard!")
            st.text_area("SQL Query:", value=query, height=100)

if submit:
    query=gemini_sql_query(prompt,input)
    response=read_sql_query(query,"student.db")
    print(query)
    st.header("response")
    for row in response:
        values = [str(value) for value in row]
         st.write(*values)