app1.py

import streamlit as st
import os
import psycopg2 as pgsql
import pandas as pd
import plotly.express as px
from dotenv import load_dotenv
import google.generativeai as genai

# Load environment variables
load_dotenv()

# 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.strip()

# Function to retrieve query from the database
def read_sql_query(sql, db_params):
    try:
        conn = pgsql.connect(**db_params)
        cur = conn.cursor()
        cur.execute(sql)
        rows = cur.fetchall()
        colnames = [desc[0] for desc in cur.description] if cur.description else []
        conn.commit()
        cur.close()
        conn.close()
        df = pd.DataFrame(rows, columns=colnames)
        
        # Convert 'price' column to numeric if it exists
        if 'price' in df.columns:
            df['price'] = pd.to_numeric(df['price'], errors='coerce')
        
        return df
    except Exception as e:
        st.error(f"An error occurred: {e}")
        return pd.DataFrame()

# Define your PostgreSQL connection parameters
db_params = {
    'dbname': 'GeminiPro',
    'user': 'postgres',
    'password': 'root',
    'host': 'localhost',
    'port': 5432
}

# Define Your Prompt
prompt = [
    """
    You are an expert in converting English questions to SQL queries!
    The SQL database has a table named 'department_store' with the following columns: 
    id, product_name, category, price, stock_quantity, supplier, last_restock_date.
    
    Examples:
    - How many products do we have in total? 
      The SQL command will be: SELECT COUNT(*) FROM department_store;
    - What are all the products in the Electronics category? 
      The SQL command will be: SELECT * FROM department_store WHERE category = 'Electronics';
    
    The SQL code should not include backticks and should not start with the word 'SQL'.
    """
]

# Streamlit App
st.set_page_config(page_title="AutomatiX - Department Store Analytics", layout="wide")

# Sidebar for user input
st.sidebar.title("AutomatiX - Department Store Chat Interface")
question = st.sidebar.text_area("Enter your question:", key="input")
submit = st.sidebar.button("Ask Me")

# Main content area
st.title("AutomatiX - Department Store Dashboard")

if submit:
    with st.spinner("Generating and fetching data..."):
        sql_query = get_gemini_response(question, prompt)
        # st.code(sql_query, language="sql")
        
        df = read_sql_query(sql_query, db_params)
        
        if not df.empty:
            st.success("Query executed successfully!")
            
            # Display data in a table
            st.subheader("Data Table")
            st.dataframe(df)
            
            # Create visualizations based on the data
            st.subheader("Data Visualizations")
            
            col1, col2 = st.columns(2)
            
            with col1:
                if 'price' in df.columns and df['price'].notna().any():
                    fig = px.histogram(df, x='price', title='Price Distribution')
                    st.plotly_chart(fig, use_container_width=True)
                
                if 'category' in df.columns:
                    category_counts = df['category'].value_counts()
                    fig = px.pie(values=category_counts.values, names=category_counts.index, title='Products by Category')
                    st.plotly_chart(fig, use_container_width=True)
            
            with col2:
                if 'last_restock_date' in df.columns:
                    df['last_restock_date'] = pd.to_datetime(df['last_restock_date'], errors='coerce')
                    df['restock_month'] = df['last_restock_date'].dt.to_period('M')
                    restock_counts = df['restock_month'].value_counts().sort_index()
                    fig = px.line(x=restock_counts.index.astype(str), y=restock_counts.values, title='Restocking Trend')
                    st.plotly_chart(fig, use_container_width=True)
                
                if 'product_name' in df.columns and 'price' in df.columns and df['price'].notna().any():
                    top_prices = df.sort_values('price', ascending=False).head(10)
                    fig = px.bar(top_prices, x='product_name', y='price', title='Top 10 Most Expensive Products')
                    st.plotly_chart(fig, use_container_width=True)
        else:
            st.warning("No data returned from the query.")

else:
    st.info("Enter a question and click 'Ask Me' to get started!")

# Footer
st.sidebar.markdown("---")
st.sidebar.info("You can ask questions like:\n"
"1.What are all the products in the Electronics category?\n"
"2.What is the average price of products in each category?\n"
"3.Which products have a stock quantity less than 30?\n"
"4.What are the top 5 most expensive products?")
st.sidebar.warning("CopyRights@AutomatiX - Powered by Streamlit and Google Gemini")