Create hydrogen_analyzer.py

hydrogen_analyzer.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+import json
+import os
+import plotly.express as px
+from dotenv import load_dotenv
+from groq import Groq
+
+# Load environment variables
+load_dotenv()
+GROQ_API_KEY = os.getenv('GROQ_API_KEY')
+
+def show_hydrogen_analyzer():
+    st.title("🔬 Hydrogen Production Analyzer")
+    st.markdown("Analyze and optimize your hydrogen production process.")
+
+    # Sidebar inputs
+    st.sidebar.subheader("🔧 Input Parameters")
+    water_source = st.sidebar.selectbox("Water Source", ["Tap Water", "Deionized", "Seawater"])
+    production_method = st.sidebar.selectbox("Production Method", ["Alkaline", "PEM", "SOEC"])
+    current_density = st.sidebar.slider("Current Density (A/cm²)", 0.1, 2.0, 0.5)
+    voltage = st.sidebar.slider("Voltage (V)", 1.4, 5.0, 2.0)
+    energy_source = st.sidebar.selectbox("Energy Source", ["Grid", "Solar", "Wind"])
+
+    # Analysis Button
+    if st.button("Analyze Hydrogen Production"):
+        # Mock calculation
+        production_rate = np.round(current_density * voltage * 10, 2)  # Dummy formula
+        cost_per_kg = np.round(10 / production_rate, 2) if production_rate else 0
+
+        # Display Results
+        st.metric("⚡ Production Rate", f"{production_rate} g/hour")
+        st.metric("💰 Cost per kg H₂", f"${cost_per_kg}")
+
+        # AI Optimization (Mock)
+        ai_recommendations = {
+            "Efficiency Boost": "Increase voltage to 2.5V",
+            "Cost Reduction": "Use renewable energy sources",
+            "Best Electrolyzer": "PEM recommended"
+        }
+
+        st.subheader("🤖 AI Recommendations")
+        st.json(ai_recommendations)