from dotenv import load_dotenv load_dotenv() #load all the env variables import streamlit as st import os import sqlite3 import google.generativeai as genai # Configure Genai key genai.configure(api_key=os.getenv("GOOGLE_API_KEY")) ## Function to load Google Gemini Model and provide queries 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 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,S​​ECTION \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"; also the sql code should not have ``` in beginning or en​​d and sql word in output """ ] ## Streamlit APP st.set_page_config(page_title="Student Data Retrieval") st.header("Provide prompts based on the :red[student data]") st.subheader(":blue[to get best output] :lower_left_fountain_pen:", divider=True ) st.subheader("Try using - 'Tell me the student name with highest rank and provide his marks' ") questions = st.text_input("Input: ",key="input") submit = st.button("Ask the questions") # if submit is clicked if submit: response = get_gemini_response(questions,prompt) print(response) response = read_sql_query(response,"student.db") st.subheader("The response is") for row in response: print(row) st.header(row)