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from dotenv import load_dotenv
load_dotenv() ## Load all the environment variables
import streamlit as st
import os
import sqlite3
import google.generativeai as genai
## Configure our API Key
genai.configure(api_key=os.getenv("GOOGLE_API_KEYS"))
# Function to Load Google Gemini Model and provide sql 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 the sql database
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
## Define Your Prompt
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 and MARKS \n\nFor example,\nExample 1 - How many entries of records are present?,
the SQL command will be something like the 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";
also the sql code should not have ```in beginning or end in sql word in output
"""
]
## Streamlit App
st.set_page_config(page_title="I can Retrieve Any SQL query")
st.header("Gemini App to Retrieve SQL Data")
question = st.text_input("Input:",key="input")
submit = st.button("Ask the question")
# if submit is clicked
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) |