Update app.py

app.py

@@ -1,21 +1,15 @@
-from dotenv import load_dotenv  # Optional: If you plan to use .env files for other secrets
+from dotenv import load_dotenv
 import streamlit as st
 import os
 import sqlite3
 import google.generativeai as genai
 
-# Load environment variables (optional, if you're using .env files for other secrets)
+# Load environment variables
 load_dotenv()
 
-# # Retrieve the API key securely from Streamlit secrets
-# GOOGLE_API_KEY = st.secrets["gemini"]["GOOGLE_API_KEY"]
-
 # Configure Gemini API
 genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
 
-# Configure Gemini API with the API Key from secrets
-# genai.configure(api_key=API_KEY)
-
 # Function to load Gemini model and generate SQL query
 def get_gemini_response(question, prompt):
     model = genai.GenerativeModel('gemini-pro')
@@ -36,7 +30,7 @@ def read_sql_query(sql, db):
     except Exception as e:
         return [("Error:", str(e))]  # Return error message if query fails
 
-# Define prompt for the Gemini API
+# Define prompt
 prompt = """
 You are an expert in SQL query generation. Your task is to convert natural language questions into valid SQL queries based on the given database schema.
 
@@ -59,23 +53,17 @@ Input: "Show the names of students in Data Science Section."
 Output: SELECT NAME FROM STUDENT_INFO WHERE SECTION = 'Data Science';
 """
 
-# Streamlit App UI
+# Streamlit App
 st.set_page_config(page_title="SQL Query Generator")
 st.header("Gemini App To Retrieve SQL Data")
 
-# Input for user's question
 question = st.text_input("Enter your question:", key="input")
 submit = st.button("Generate SQL Query")
 
-# If submit is clicked, generate and show SQL query and results
+# If submit is clicked
 if submit:
     sql_query = get_gemini_response(question, prompt)
     st.subheader("Generated SQL Query")
     st.code(sql_query, language="sql")  # Show SQL query
 
-    # Execute the SQL query and retrieve results
     response = read_sql_query(sql_query, "student.db")
-    
-    # Show the query results
-    st.subheader("Query Results")
-    st.write(response)