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Create app.py
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app.py
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# from dotenv import load_dotenv
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# load_dotenv() #load all the env variables
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import streamlit as st
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import os
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import sqlite3
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import google.generativeai as genai
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#Configure API Key
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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#Fuction to Load Google Gemini Model that provide SQL Query as response
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def get_gemini_response(question, prompt):
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model = genai.GenerativeModel('gemini-pro')
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response = model.generate_content([prompt[0], question])
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return response.text
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#Function to retrieve query from SQL database
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def read_sql_query(sql,db):
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conn = sqlite3.connect(db)
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cur = conn.cursor()
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cur.execute(sql)
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rows = cur.fetchall()
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conn.commit()
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conn.close()
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for row in rows:
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print(row)
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return rows
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#Defining Prompt
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prompt = [
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'''
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Imagine you are an expert in converting natural language text into SQL queries. You have a table named e_com with the following columns:
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user_id (INTEGER): The unique identifier for each user, automatically incremented.
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username (VARCHAR(50)): The name of the user, required and cannot be null.
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email (VARCHAR(100)): The email address of the user, also required and cannot be null.
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address (VARCHAR(255)): The address of the user.
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order_quantity (VARCHAR(255)): The quantity of orders placed by the user.
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order_date (TIMESTAMP): The date and time of when the order was placed, with a default value set to the current timestamp.
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Your task is to convert the natural language descriptions into SQL queries that operate on the E_COM_DATA table.
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EXAMPLES -
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Tell me the usernames and email addresses of all users whose order quantity is greater than 3.
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Expected Response - SELECT username, email FROM e_com WHERE order_quantity > '3';
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Tell me the usernames and addresses of users who have placed orders after a specific date, say '2023-01-01'.
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Expected Response - SELECT username, address FROM e_com WHERE order_date > '2023-01-01';
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ALSO, the sql response should not have ``` in the beginning or end and sql word in the output.
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'''
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]
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#StreamLit App
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st.set_page_config(page_title = "Hey! I can retriece any SQL query")
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st.header("Gemini App to Retrieve SQL Data")
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question = st.text_input("Input: ", key="input")
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submit = st.button("Ask the question")
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if submit:
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response = get_gemini_response(question,prompt)
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print(response)
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data = read_sql_query(response, "e_com.db")
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st.subheader("The Response is ")
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for row in data:
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print(row)
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st.header(row)
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