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Sql.py

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+import sqlite3
+
+# Connect to SQLite
+connection = sqlite3.connect("student.db")
+
+# Create a cursor object to insert records and create table
+cursor = connection.cursor()
+
+# Create the table if not exists
+table_info = """
+CREATE TABLE IF NOT EXISTS STUDENT(
+    NAME VARCHAR(25),
+    CLASS VARCHAR(25),
+    SECTION VARCHAR(25),
+    MARKS INT
+);
+"""
+cursor.execute(table_info)
+
+records = [
+    ('Saqib', 'Data Science', 'A', 90),
+    ('Subash', 'Data Science', 'B', 100),
+    ('Mandeep', 'Data Science', 'A', 86),
+    ('Vikash', 'DEVOPS', 'A', 50),
+    ('Dipesh', 'DEVOPS', 'A', 35),
+    ('Sakshi', 'Class1', 'Section1', 60),
+    ('Rajesh', 'Class2', 'Section2', 70),
+    ('Amit', 'Class3', 'Section0', 80),
+    ('Rahul', 'Class4', 'Section1', 90),
+    ('Vivek', 'Class0', 'Section2', 95),
+    ('Neha', 'Class1', 'Section0', 99),
+    ('Priya', 'Class2', 'Section1', 77),
+    ('Deepak', 'Class3', 'Section2', 66),
+    ('Pooja', 'Class4', 'Section0', 55),
+    ('Ankit', 'Class0', 'Section1', 44),
+    ('Ayesha', 'Class1', 'Section2', 33),
+    ('Aryan', 'Class2', 'Section0', 22),
+    ('Riya', 'Class3', 'Section1', 11),
+    ('Sumit', 'Class4', 'Section2', 100),
+    ('Meera', 'Class0', 'Section0', 85),
+    ('Sachin', 'Class1', 'Section1', 75),
+    ('Anjali', 'Class2', 'Section2', 65),
+    ('Rahul', 'Class3', 'Section0', 55),
+    ('Kritika', 'Class4', 'Section1', 45),
+    ('Prateek', 'Class0', 'Section2', 35),
+    ('Shreya', 'Class1', 'Section0', 25),
+    ('Amit', 'Class2', 'Section1', 15),
+    ('Roshni', 'Class3', 'Section2', 5),
+    ('Mohit', 'Class4', 'Section0', 95),
+    ('Riya', 'Class0', 'Section1', 85),
+    ('Ravi', 'Class1', 'Section2', 75),
+    ('Anu', 'Class2', 'Section0', 65),
+    ('Aman', 'Class3', 'Section1', 55),
+    ('Sana', 'Class4', 'Section2', 45),
+    ('Raj', 'Class0', 'Section0', 35),
+    ('Anushka', 'Class1', 'Section1', 25),
+    ('Ajay', 'Class2', 'Section2', 15),
+    ('Sanjay', 'Class3', 'Section0', 5),
+    ('Shivangi', 'Class4', 'Section1', 99),
+    ('Pranav', 'Class0', 'Section2', 77),
+    ('Monika', 'Class1', 'Section0', 66),
+    ('Sahil', 'Class2', 'Section1', 55),
+    ('Riya', 'Class3', 'Section2', 44),
+    ('Vikas', 'Class4', 'Section0', 33),
+    ('Muskan', 'Class0', 'Section1', 22),
+    ('Arjun', 'Class1', 'Section2', 11),
+    ('Neha', 'Class2', 'Section0', 100),
+    ('Rohit', 'Class3', 'Section1', 85),
+    ('Sonia', 'Class4', 'Section2', 75),
+    ('Manoj', 'Class0', 'Section0', 65),
+    ('Gaurav', 'Class1', 'Section1', 55),
+    ('Preeti', 'Class2', 'Section2', 45),
+    ('Karan', 'Class3', 'Section0', 35),
+    ('Manisha', 'Class4', 'Section1', 25),
+    ('Jatin', 'Class0', 'Section2', 15),
+    ('Aditi', 'Class1', 'Section0', 5),
+    ('Sandeep', 'Class2', 'Section1', 99),
+    ('Rajesh', 'Class3', 'Section2', 77),
+    ('Tanvi', 'Class4', 'Section0', 66),
+    ('Aakash', 'Class0', 'Section1', 55),
+    ('Garima', 'Class1', 'Section2', 44),
+    ('Harsh', 'Class2', 'Section0', 33),
+    ('Shivani', 'Class3', 'Section1', 22),
+    ('Rohit', 'Class4', 'Section2', 11),
+    ('Sapna', 'Class0', 'Section0', 100),
+    ('Rajat', 'Class1', 'Section1', 85),
+    ('Sneha', 'Class2', 'Section2', 75),
+    ('Vishal', 'Class3', 'Section0', 65),
+    ('Pooja', 'Class4', 'Section1', 55),
+    ('Akash', 'Class0', 'Section2', 45),
+    ('Nisha', 'Class1', 'Section0', 35),
+    ('Shubham', 'Class2', 'Section1', 25),
+    ('Sakshi', 'Class3', 'Section2', 15),
+    ('Gopal', 'Class4', 'Section0', 5),
+    ('Shweta', 'Class0', 'Section1', 99),
+    ('Mohini', 'Class1', 'Section2', 77),
+    ('Vivek', 'Class2', 'Section0', 66),
+    ('Aditya', 'Class3', 'Section1', 55),
+    ('Tanu', 'Class4', 'Section2', 44),
+    ('Aarti', 'Class0', 'Section0', 33),
+    ('Rohit', 'Class1', 'Section1', 22),
+    ('Pawan', 'Class2', 'Section2', 11),
+    ('Ankita', 'Class3', 'Section0', 99),
+    ('Komal', 'Class4', 'Section2', 77),
+    ('Nidhi', 'Class0', 'Section0', 66),
+    ('Abhishek', 'Class1', 'Section1', 55),
+    ('Sagar', 'Class2', 'Section2', 44),
+    ('Sneha', 'Class3', 'Section0', 33),
+    ('Rahul', 'Class4', 'Section1', 22),
+    ('Riya', 'Class0', 'Section2', 11)
+]
+
+
+# Add more records to make it 100
+for i in range(8, 101):
+    records.append(('Student' + str(i), 'Class' + str(i % 5), 'Section' + str(i % 3), i % 101))
+
+# Insert all records
+cursor.executemany('INSERT INTO STUDENT VALUES (?,?,?,?)', records)
+
+# Display All the records
+print("The inserted records are:")
+data = cursor.execute('SELECT * FROM STUDENT')
+for row in data:
+    print(row)
+
+# Commit your changes in the database
+connection.commit()
+connection.close()

app.py

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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 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()
+    return rows
+
+## Define Your Prompt
+## 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 \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 end and sql word in output
+
+    """
+]
+
+## Streamlit App
+
+st.set_page_config(page_title="Gemini SQL Assistant", page_icon=":gemini:")
+st.title("🔮 Gemini SQL Assistant 🔍")
+
+
+st.sidebar.title("🚀 Ask a Question 📝")
+question = st.sidebar.text_input("Enter your question here:")
+
+submit = st.sidebar.button("🔎 Get SQL Query")
+
+# Main content area
+st.markdown("---")
+
+if submit:
+    response = get_gemini_response(question, prompt)
+    st.subheader("🔍 Generated SQL Query:")
+    st.code(response, language="sql")
+    
+    # Execute SQL query
+    try:
+        rows = read_sql_query(response, "student.db")
+        if rows:
+            st.subheader("📊 Query Result:")
+            st.dataframe(rows)
+        else:
+            st.warning("❗ No results found for this query.")
+    except Exception as e:
+        st.error(f"❌ An error occurred: {e}")
+
+# Main content area
+st.write("""
+🎓 **About Gemini SQL Assistant**
+
+Gemini SQL Assistant is an intelligent tool that helps you convert English questions into SQL queries. 
+Whether you're a beginner or an expert in SQL, Gemini can assist you in generating SQL queries to retrieve data from the STUDENT database.
+
+Simply enter your question in the sidebar, click on the 'Get SQL Query' button, and Gemini will generate the corresponding SQL query for you. 
+You can then execute the query to retrieve the desired data from the database.
+
+🔧 **How to Use**
+
+1. Enter your question in the sidebar.
+2. Click on the 'Get SQL Query' button.
+3. View the generated SQL query in the main area.
+4. Execute the query to retrieve data from the database.
+5. Explore the query results and analyze the data as needed.
+
+📊 **Example Questions**
+
+- How many entries of records are present?
+- Tell me all the students studying in Data Science class.
+- Show me the students with marks above 80.
+
+Feel free to ask any question related to the STUDENT database, and Gemini will assist you in generating the SQL query to retrieve the data.
+
+👩‍💻 **Powered By**
+
+Gemini 💫 - A powerful generative AI model developed by Google.
+Streamlit 🚀 - An open-source app framework for Machine Learning and Data Science.
+
+""")
+
+# Footer
+footer_with_image_light_blue = """
+<style>
+.footer {
+    background-color: #f0f0f0;
+    padding: 20px;
+    text-align: center;
+    border-top: 1px solid #ccc;
+}
+
+.footer img {
+    max-width: 100%;
+    margin-top: 10px;
+}
+
+.footer .connect-text {
+    color: #333;
+    font-weight: bold;
+    margin-bottom: 10px;
+}
+
+.footer a {
+    margin: 0 10px;
+    color: #333;
+}
+
+.footer .powered-by {
+    color: #333;
+    font-size: 14px;
+    margin-top: 10px;
+}
+
+.bright-text {
+    color: #004D40;
+}
+</style>
+<div class="footer">
+    <div class="connect-text">Connect with me at</div>
+    <a href="https://github.com/FasilHameed" target="_blank"><img src="https://img.icons8.com/plasticine/30/000000/github.png" alt="GitHub"></a>
+    <a href="https://www.linkedin.com/in/faisal--hameed/" target="_blank"><img src="https://img.icons8.com/plasticine/30/000000/linkedin.png" alt="LinkedIn"></a>
+    <a href="tel:+917006862681"><img src="https://img.icons8.com/plasticine/30/000000/phone.png" alt="Phone"></a>
+    <a href="mailto:faisalhameed763@gmail.com"><img src="https://img.icons8.com/plasticine/30/000000/gmail.png" alt="Gmail"></a>
+    <div class="powered-by">Powered By <img src="https://img.icons8.com/clouds/30/000000/gemini.png" alt="Gemini"> Gemini 💫 and Streamlit 🚀</div>
+</div>
+"""
+
+# Render Footer
+st.markdown(footer_with_image_light_blue, unsafe_allow_html=True)

requirements.txt

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+streamlit
+google-generativeai
+python-dotenv