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import os
import streamlit as st
from dotenv import load_dotenv
import google.generativeai as gen_ai
# Load environment variables
load_dotenv()
# Configure Streamlit page settings
st.set_page_config(
page_title="Smart Waste Management System",
page_icon="♻️",
layout="centered",
)
# Retrieve the Google API key from the environment
GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
# Check if the API key is loaded
if not GOOGLE_API_KEY:
st.error("🚨 API key not found! Please set the GOOGLE_API_KEY in your .env file.")
st.stop()
# Configure the Generative AI model
try:
gen_ai.configure(api_key=GOOGLE_API_KEY)
model = gen_ai.GenerativeModel("gemini-1.5-pro") # Updated model version
except Exception as e:
st.error(f"❌ Error initializing the Gemini-Pro model: {e}")
st.stop()
# Initialize the chat session if not already present in session state
if "chat_session" not in st.session_state:
try:
st.session_state.chat_session = model.start_chat(history=[])
except Exception as e:
st.error(f"❌ Error initializing chat session: {e}")
st.stop()
# Display the app's title
st.title("♻️ Smart Waste Management System")
# Introduction and instructions
st.markdown(
"""
Welcome to the **Smart Waste Management System**! This tool helps **citizens, municipal workers,
recycling companies, and biogas plants** collaborate efficiently for **better waste management**.
### **🌟 Key Features**
- **Citizen Role:** Report waste collection issues and track garbage pickup.
- **Municipal Workers:** Manage schedules and coordinate garbage segregation.
- **Recycling Companies:** View and respond to requests for plastic waste.
- **Biogas Plants:** Manage bio-waste for energy production.
"""
)
# User role selection
user_role = st.selectbox("🔹 Select Your Role:", ["Citizen", "Municipal Worker", "Recycling Company", "Biogas Plant"])
# Chat input
user_prompt = st.chat_input(f"💬 [{user_role}] Enter your query or task...")
if user_prompt:
# Display the user's message
st.chat_message("user").markdown(f"**{user_role}:** {user_prompt}")
# Generate a role-specific prompt
role_specific_prompt = f"You are assisting a {user_role} in a smart waste management system. The user says: {user_prompt}"
# Send the prompt to Gemini-Pro and get the response
try:
gemini_response = st.session_state.chat_session.send_message(role_specific_prompt)
# Display Gemini-Pro's response
with st.chat_message("assistant"):
st.markdown(gemini_response.text)
except Exception as e:
st.error(f"❌ Error processing your message: {e}")
# Sidebar Information
st.sidebar.title("📌 About")
st.sidebar.markdown(
"""
The **Smart Waste Management System** aims to:
- 🏡 **Improve waste collection efficiency** for citizens.
- 🚛 **Help municipal workers** manage schedules.
- 🔄 **Assist recycling companies** in waste processing.
- ⚡ **Support biogas plants** in energy production.
💡 **Need Help?** Use the chat to ask questions!
"""
)
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