app.py
Browse files
app.py
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import streamlit as st
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import google.generativeai as genai
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from pathlib import Path
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import sqlite3
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import pandas as pd
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st.set_page_config(page_title='SQL GENERATOR')
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st.title('SQL GENERATED WITH GENAI')
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secretKey = "AIzaSyAA_R5VXv1qjJ5jDMObkluREA8BxJO67RU"
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#from google.colab import userdata
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genai.configure(api_key = secretKey)
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# Set up the model
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generation_config = {
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"temperature": 0.4,
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"top_p": 1,
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"top_k": 32,
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"max_output_tokens": 4096,
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}
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safety_settings = [
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{
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"category": "HARM_CATEGORY_HARASSMENT",
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"threshold": "BLOCK_MEDIUM_AND_ABOVE"
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},
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{
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"category": "HARM_CATEGORY_HATE_SPEECH",
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"threshold": "BLOCK_MEDIUM_AND_ABOVE"
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},
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{
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"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
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"threshold": "BLOCK_MEDIUM_AND_ABOVE"
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},
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{
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"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
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"threshold": "BLOCK_MEDIUM_AND_ABOVE"
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}
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]
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@st.cache_resource
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def load_model(model1,config1,safety1):
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return genai.GenerativeModel(model_name = model1,
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generation_config = config1,
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safety_settings = safety1)
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model = load_model("gemini-pro",generation_config,safety_settings)
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prompt_parts_1 = [
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"You are an expert in converting English questions to SQL code! The SQL database has the name classicmodels and has the following tables - productlines, products, offices, employees, customers, payments, orders and orderdetails.\n\nFor example,\nExample 1 - How many Classic Cars are present?, the SQL command will be something like this\n SELECT COUNT(*) FROM products WHERE productLine = 'Classic Cars';\n\n\nExample 2 - What are the names of the cars having turnable front wheels?\n\nSELECT productName FROM products WHERE productDescription LIKE '%turnable front wheels%';\n\n\n Example 3 - What are the top 5 high performing products in terms of revenue?, the SQL command will be SELECT productName, SUM(quantityOrdered * priceEach) AS totalRevenue FROM orderdetails JOIN products ON products.productCode = orderdetails.productCode GROUP BY productName ORDER BY totalRevenue DESC LIMIT 5;\n\n\n Example 4 - What are the top 5 employees in terms of sales?, the SQL command will be SELECT e.employeeNumber, e.firstName || ' ' || e.lastName AS employeeName, SUM(od.quantityOrdered * od.priceEach) AS totalSales FROM employees e JOIN customers c ON e.employeeNumber = c.salesRepEmployeeNumber JOIN orders o ON c.customerNumber = o.customerNumber JOIN orderdetails od ON o.orderNumber = od.orderNumber GROUP BY e.employeeNumber, employeeName ORDER BY totalSales DESC LIMIT 5; \n\n\nExample 5 - \n\nSELECT productName FROM products WHERE quantityInStock = (SELECT MAX(quantityInStock) FROM products);\n\n\nExample 4 - \n\nSELECT productName FROM products WHERE quantityInStock = (SELECT MAX(quantityInStock) FROM products);\n\n\nDont include ``` and \\n in the output",
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]
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st.subheader('SHOW TABLE')
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input1=st.text_input("Enter table name")
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submit1=st.button("Show")
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if input1 is not None and submit1:
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conn = sqlite3.connect('data.sqlite')
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cur = conn.cursor()
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query = f"select * from {input1} limit 5"
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cur.execute(query)
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records = cur.fetchall()
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df1 = pd.read_sql_query(query, con=conn)
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conn.close()
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st.dataframe(df1)
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st.subheader("GENERATE SQL RESULT")
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question=st.text_input("Enter question related to the database")
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submit2=st.button("Run")
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if question is not None and submit2:
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prompt_parts = [prompt_parts_1[0], question]
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response = model.generate_content(prompt_parts)
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query1 = response.text
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conn1 = sqlite3.connect('data.sqlite')
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cur1 = conn1.cursor()
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cur1.execute(query1)
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records = cur1.fetchall()
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df2 = pd.read_sql_query(query1, con=conn1)
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conn1.close()
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st.dataframe(df2)
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