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README.md

@@ -1,13 +1,13 @@
 ---
-title: Energy Optimization AI
+title: Load Energy
 emoji: 🚀
-colorFrom: green
-colorTo: purple
+colorFrom: gray
+colorTo: green
 sdk: streamlit
 sdk_version: 1.41.1
 app_file: app.py
 pinned: false
-short_description: This application leverages AI-based decision-making to analy
+short_description: Optimize energy distribution in a microgrid.
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import plotly.graph_objects as go
+
+# App Configuration
+st.set_page_config(page_title="Energy Optimization AI", layout="wide", page_icon="🌞")
+
+# App Title
+st.title("🌞⚡ Energy Optimization AI ⚡🌬️")
+st.write("""
+    Optimize your energy distribution across renewable sources in real-time 
+    to maximize efficiency, reduce costs, and promote sustainability.
+""")
+
+# Overview Section
+st.header("Project Overview")
+st.write("""
+This application leverages **AI-based decision-making** to analyze your energy usage across solar and wind energy sources. It provides recommendations for optimizing cost-effectiveness and efficiency while maintaining sustainability goals. Use this tool to make informed energy distribution decisions for homes, industries, or renewable energy setups.
+""")
+
+# Input Section
+st.header("Input Energy Details")
+col1, col2 = st.columns(2)
+
+# User Inputs
+with col1:
+    st.subheader("Solar Energy")
+    solar_usage = st.slider("Solar Energy Usage (kWh):", 0.0, 1000.0, 200.0, step=10.0)
+    solar_cost = st.slider("Solar Cost per kWh:", 0.0, 10.0, 2.5, step=0.1)
+
+with col2:
+    st.subheader("Wind Energy")
+    wind_usage = st.slider("Wind Energy Usage (kWh):", 0.0, 1000.0, 300.0, step=10.0)
+    wind_cost = st.slider("Wind Cost per kWh:", 0.0, 10.0, 1.8, step=0.1)
+
+# Optimization Logic
+if st.button("🚀 Optimize"):
+    total_usage = solar_usage + wind_usage
+
+    if total_usage == 0:
+        st.error("⚠️ Please enter energy usage for at least one source.")
+    else:
+        total_cost = (solar_usage * solar_cost) + (wind_usage * wind_cost)
+        solar_share = (solar_usage / total_usage) * 100 if solar_usage > 0 else 0
+        wind_share = (wind_usage / total_usage) * 100 if wind_usage > 0 else 0
+
+        cost_effective_source = (
+            "solar" if solar_cost < wind_cost
+            else "wind" if wind_cost < solar_cost
+            else "both sources equally"
+        )
+
+        suggestion = (
+            f"Balance usage between solar and wind energy, prioritizing {cost_effective_source} for lower costs."
+        )
+
+        # Display Results
+        st.subheader("Optimization Results")
+        col3, col4 = st.columns(2)
+        with col3:
+            st.metric("Total Energy Usage", f"{total_usage:.2f} kWh")
+            st.metric("Solar Share", f"{solar_share:.2f}%")
+        with col4:
+            st.metric("Total Cost", f"{total_cost:.2f} currency")
+            st.metric("Wind Share", f"{wind_share:.2f}%")
+
+        st.success(suggestion)
+
+        # Charts
+        st.subheader("Visualization")
+        chart_data = pd.DataFrame(
+            {
+                "Energy Source": ["Solar", "Wind"],
+                "Usage (kWh)": [solar_usage, wind_usage],
+                "Cost (Currency)": [solar_usage * solar_cost, wind_usage * wind_cost],
+            }
+        )
+
+        # Improved Visualization with Plotly
+        fig = go.Figure()
+
+        # Add Usage Bar
+        fig.add_trace(go.Bar(
+            x=chart_data["Energy Source"],
+            y=chart_data["Usage (kWh)"],
+            name="Usage (kWh)",
+            marker_color='blue'
+        ))
+
+        # Add Cost Bar
+        fig.add_trace(go.Bar(
+            x=chart_data["Energy Source"],
+            y=chart_data["Cost (Currency)"],
+            name="Cost (Currency)",
+            marker_color='green'
+        ))
+
+        fig.update_layout(
+            barmode='group',
+            title="Energy Usage and Cost Comparison",
+            xaxis_title="Energy Source",
+            yaxis_title="Value",
+            legend_title="Metrics",
+        )
+        st.plotly_chart(fig, use_container_width=True)
+
+        # Explanation
+        st.subheader("Detailed Explanation")
+        st.write(
+            f"Based on your inputs, **{cost_effective_source} energy** is more cost-effective. "
+            f"This analysis helps balance your energy sources to minimize costs and maximize efficiency."
+        )
+
+# Sidebar
+st.sidebar.header("About")
+st.sidebar.info("""
+This tool helps optimize renewable energy usage for cost savings, sustainability, 
+and better energy distribution management.
+""")
+st.sidebar.header("How It Works")
+st.sidebar.write("""
+1. **Input Energy Details**: Specify the usage and cost for solar and wind energy.
+2. **Optimization**: The tool calculates the total energy usage, cost, and shares of each source.
+3. **Visual Analysis**: Get insights into cost-effective strategies with detailed charts and recommendations.
+""")

requirements.txt

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+streamlit
+transformers
+torch
+pandas
+numpy
+scipy
+matplotlib
+plotly