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Browse files- STUDENT.db +0 -0
- app.py +55 -0
- requirements.txt +3 -0
STUDENT.db
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Binary file (8.19 kB). View file
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app.py
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from dotenv import load_dotenv
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import os
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import streamlit as st
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import sqlite3
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import google.generativeai as genai
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import time
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st.set_page_config(page_title = "Retrieve SQL query using text")
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os.environ['GOOGLE_API_KEY'] = "AIzaSyCaW7JGGWjiBRvq2DGl9uTIrptH7FzhFh8"
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load_dotenv()
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genai.configure()
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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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def read_and_execute_sql_query(sql, db):
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connection = sqlite3.connect(db)
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cursor = connection.cursor()
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cursor.execute(sql)
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rows = cursor.fetchall()
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connection.commit()
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connection.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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prompt = [
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"""
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You are in expert in converting English questions to SQL code!
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The SQL database has the name STUDENT.db and the table name is STUDENT and has the following columns - NAME, CLASS, SECTION \n\n
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For example, \nExample 1 - How many entries of records are present?, the SQL command will be something
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like this SELECT COUNT(*) FROM STUDENT; \nExample 2 - Tell me all the students studying in DS class? the SQL command
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will be something like this SELECT * FROM STUDENT where CLASS = 'DS';
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also the sql code should not have ''' in beginning or end and sql word in output
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"""
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]
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#Streamlit app
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st.header("Gemini app to retrieve SQL data using text")
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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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response = read_and_execute_sql_query(response, "STUDENT.db")
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st.subheader("Response : ")
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for row in response:
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print(row)
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st.write(row)
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requirements.txt
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python-dotenv
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google-generativeai
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streamlit
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