Update app.py

app.py

@@ -1,56 +1,33 @@
 import streamlit as st
-import requests
-import pandas as pd
-import json
-import plotly.express as px
-import matplotlib.pyplot as plt
-from config import NREL_API_KEY, IEA_API_KEY, IRENA_API_KEY, DOE_API_KEY, GROQ_API_KEY
-from data_analysis import fetch_hydrogen_data, analyze_hydrogen_data, groq_ai_analysis
+from data_fetcher import get_hydrogen_data
+from groq_analysis import analyze_hydrogen_data
+from visuals import plot_hydrogen_capacity
 
-# Streamlit UI
-st.set_page_config(page_title="AI Hydrogen Electrolysis Dashboard", layout="wide")
+# Set page title and layout
+st.set_page_config(page_title="Hydrogen Analysis AI App", layout="wide")
 
-# Sidebar - API selection
-st.sidebar.header("🔍 Data Sources")
-api_options = ["NREL", "IEA", "IRENA", "DOE"]
-selected_api = st.sidebar.radio("Select API for Hydrogen Data:", api_options)
+# Sidebar Input
+st.sidebar.header("🔧 Fetch Real-Time Hydrogen Data")
+fetch_data = st.sidebar.button("Fetch Data from NREL API")
 
-# Fetch Data
-hydrogen_data = fetch_hydrogen_data(selected_api)
-
-# If no data, try alternative APIs
-if hydrogen_data.empty:
-    st.warning(f"No data found from {selected_api}. Fetching from alternative sources...")
-    for api in api_options:
-        if api != selected_api:
-            hydrogen_data = fetch_hydrogen_data(api)
-            if not hydrogen_data.empty:
-                st.success(f"Data successfully retrieved from {api}")
-                break
-
-# Display Data
-st.title("🚀 AI-Powered Hydrogen Electrolysis Dashboard")
-st.subheader(f"Real-Time Data from {selected_api}")
-
-if not hydrogen_data.empty:
-    st.dataframe(hydrogen_data)
+# Title
+st.title("🚀 AI-Powered Hydrogen Electrolysis Analysis")
+st.write("Fetching real-time hydrogen production data and AI-driven insights.")
 
-    # Plot Electrolysis Efficiency vs. Cost
-    st.subheader("📊 Hydrogen Production Trends")
-    fig = px.scatter(hydrogen_data, x="Efficiency (%)", y="Cost ($/kg)", color="Technology",
-                     title="Hydrogen Production Efficiency vs. Cost")
-    st.plotly_chart(fig)
-
-    # Bar Chart - Hydrogen Production Rates by Source
-    st.subheader("⚡ Hydrogen Production Rate by Technology")
-    fig2 = px.bar(hydrogen_data, x="Technology", y="Hydrogen Production Rate (kg/h)",
-                  title="Hydrogen Production Rate by Technology")
-    st.plotly_chart(fig2)
-
-    # AI Prediction & Analysis using Groq API
-    st.subheader("🤖 AI-Powered Electrolysis Analysis")
-    ai_prediction = groq_ai_analysis(hydrogen_data)
-    st.write(ai_prediction)
-
-else:
-    st.error("No data available from all sources. Please try again later.")
+# Fetch Data
+if fetch_data:
+    data = get_hydrogen_data()
+
+    if isinstance(data, dict) and "error" in data:
+        st.error(data["error"])
+    else:
+        st.subheader("📊 Hydrogen Production Data")
+        st.write(data)
+
+        # AI Analysis
+        ai_insights = analyze_hydrogen_data(data)
+        st.subheader("🧠 AI Insights from Llama 3")
+        st.write(ai_insights)
+
+        # Visualizations
+        plot_hydrogen_capacity(data)