Update app.py

app.py

@@ -1,63 +1,21 @@
 import os
-from groq import Groq
-
-# Set API Key (Replace with your actual API key)
-os.environ["GROQ_API_KEY"] = "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"
-
-# Initialize the Groq Client
-client = Groq(api_key=os.environ["GROQ_API_KEY"])
-
-# Test Query
-chat_completion = client.chat.completions.create(
-    messages=[{"role": "user", "content": "Explain the importance of fast language models"}],
-    model="llama-3.3-70b-versatile",
-)
-
-# Print response
-print(chat_completion.choices[0].message.content)
 import random
 import time
 import pandas as pd
-
-# Function to simulate data updates
-def get_real_time_data():
-    return {
-        "Heart Rate (BPM)": random.randint(60, 120),
-        "Oxygen Saturation (%)": round(random.uniform(85, 100), 1),
-        "Blood Pressure (mmHg)": f"{random.randint(90, 120)}/{random.randint(60, 80)}",
-        "Respiratory Rate (BPM)": random.randint(12, 20),
-        "Hydration Level (%)": round(random.uniform(40, 100), 1),
-        "Battery Level (%)": random.randint(10, 100),
-        "Food Supply (Days)": random.randint(1, 10),
-        "Water Supply (Liters)": random.randint(1, 50),
-    }
-
-# Testing the function
-for _ in range(5):
-    print(get_real_time_data())
-    time.sleep(1)
-
-def predict_survival_time(data):
-    oxygen_factor = data["Oxygen Saturation (%)"] / 100
-    hydration_factor = data["Hydration Level (%)"] / 100
-    battery_factor = data["Battery Level (%)"] / 100
-    food_factor = data["Food Supply (Days)"] / 10
-
-    survival_hours = (oxygen_factor + hydration_factor + battery_factor + food_factor) * 10
-    return round(survival_hours, 2)
-
-# Example test
-sample_data = get_real_time_data()
-print("Predicted Survival Time (Hours):", predict_survival_time(sample_data))
-
+import numpy as np
 import streamlit as st
-import pandas as pd
-import random
-import time
+import plotly.graph_objects as go
+from groq import Groq
+
+# Set API Key (Replace with actual key)
+os.environ["GROQ_API_KEY"] = "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"
+client = Groq(api_key=os.environ["GROQ_API_KEY"])
 
-st.title("🚀 Astronaut Survival Monitor")
+# Streamlit UI Setup
+st.set_page_config(page_title="🚀 ARMS: Astronaut Survival Monitor", layout="wide")
+st.title("🚀 ARMS: Astronaut Resource Management System")
 
-# Simulating real-time data updates
+# Real-time Data Simulation
 def get_real_time_data():
     return {
         "Heart Rate (BPM)": random.randint(60, 120),
@@ -70,25 +28,41 @@ def get_real_time_data():
         "Water Supply (Liters)": random.randint(1, 50),
     }
 
-# Survival Time Prediction
+# Survival Prediction Function
 def predict_survival_time(data):
     oxygen_factor = data["Oxygen Saturation (%)"] / 100
     hydration_factor = data["Hydration Level (%)"] / 100
     battery_factor = data["Battery Level (%)"] / 100
     food_factor = data["Food Supply (Days)"] / 10
-
     survival_hours = (oxygen_factor + hydration_factor + battery_factor + food_factor) * 10
     return round(survival_hours, 2)
 
-# Real-time simulation
+# Generate Real-Time Data
 data = get_real_time_data()
 survival_time = predict_survival_time(data)
 
-st.metric("Predicted Survival Time", f"{survival_time} Hours")
-
-# Display real-time health and resource data
-st.write("### Health Metrics")
-for key, value in data.items():
-    st.metric(key, value)
-
-st.warning("🚨 Alert: Low Oxygen or Power Levels Detected!") if data["Oxygen Saturation (%)"] < 90 or data["Battery Level (%)"] < 20 else None
+# Layout
+col1, col2 = st.columns(2)
+
+with col1:
+    st.metric("Predicted Survival Time", f"{survival_time} Hours")
+    st.subheader("🔍 Health Metrics")
+    for key, value in data.items():
+        st.metric(key, value)
+    if data["Oxygen Saturation (%)"] < 90 or data["Battery Level (%)"] < 20:
+        st.warning("🚨 Critical Alert: Oxygen or Battery Levels are Low!")
+
+with col2:
+    st.subheader("📊 Resource & Health Trends")
+    df = pd.DataFrame({"Metric": list(data.keys()), "Value": list(data.values())})
+    fig = go.Figure([go.Bar(x=df["Metric"], y=df["Value"], marker_color='crimson')])
+    fig.update_layout(title="Current Status of Astronaut Resources", xaxis_title="Metric", yaxis_title="Value")
+    st.plotly_chart(fig)
+
+# AI-generated Advisory (Groq API)
+st.subheader("🤖 AI Advisor Suggestions")
+response = client.chat.completions.create(
+    messages=[{"role": "user", "content": "Give survival improvement tips for astronauts."}],
+    model="llama-3.3-70b-versatile",
+)
+st.info(response.choices[0].message.content)