Update

app.py

@@ -1,28 +1,121 @@
+import numpy as np
 import streamlit as st
 
 st.title("GCP Resource Alloctor")
 
-
 # GPU Type
 gpu_type = st.selectbox(
-    'Which type of GPU you would like to use?',
+    'GPU Type',
     (  
-        'NVIDIA H100 80GB', 
-        'NVIDIA A100 80GB',
-        'NVIDIA A100 40GB',
-        'NVIDIA V100 16GB',
-        'NVIDIA P100 16GB',
-        'NVIDIA L4 24GB',
-        'NVIDIA T4 16GB',
-        'NVIDIA P4 8GB',
+        'H100 80GB', 
+        'A100 80GB',
+        'A100 40GB',
+        'V100 16GB',
+        'P100 16GB',
+        'L4 24GB',
+        'T4 16GB',
+        'P4 8GB',
     )
 )
 
-# # GPU Numbers
-# gpu_numbers = st.slider('How many GPUs you would like to use?', 0, 8, 1)
+# Number of GPUs
+gpu_number_mapping = {
+    'H100 80GB': [8],
+    'A100 80GB': [1,2,4,8],
+    'A100 40GB': [1,2,4,8,16],
+    'V100 16GB': [1,2,4,8],
+    'P100 16GB': [1,2,4],
+    'L4 24GB': [1,2,4,8],
+    'T4 16GB': [1,2,4],
+    'P4 8GB': [1,2,4],
+}
+gpu_number = st.selectbox('Number of GPUs', gpu_number_mapping[gpu_type])
+
+# Instance Type
+gpu_type_mapping = {
+    'H100 80GB': ["A3"],
+    'A100 80GB': ["A2"],
+    'A100 40GB': ["A2"],
+    'V100 16GB': ["N1", "CUSTOM"],
+    'P100 16GB': ["N1", "CUSTOM"],
+    'L4 24GB': ["G2", "CUSTOM"],
+    'T4 16GB': ["N1", "CUSTOM"],
+    'P4 8GB': ["N1", "CUSTOM"],
+}
+instance_type = st.selectbox('Instance Type', gpu_type_mapping[gpu_type])
+
+# CPU Cores
+cpu_cores_mapping = {
+    "A3": [208],
+    "A2": [12*gpu_number],
+    "G2": [12*gpu_number] if gpu_number > 1 else [4,8,12,16,32],
+    "N1": [1,2,4,8,16,32,96],
+    "CUSTOM": [1] + [i for i in range(2, 96+1, 2)]
+}
+if gpu_type != "CUSTOM":
+    cpu_cores = st.selectbox('Cores (vCPU)', cpu_cores_mapping[instance_type])
+else:
+    cpu_cores = st.select_slider('Cores (vCPU)', cpu_cores_mapping[instance_type])
+
+# Memory Size
+memory_size_mapping = {
+    "A3": [1872],
+    "A2": [170*gpu_number],
+    "G2": [4*cpu_cores] if gpu_number > 1 else [48*gpu_number],
+    "N1": [cpu_cores*3.75],
+    "CUSTOM": [i for i in np.arange(cpu_cores, cpu_cores*6.5+1, 1)]
+}
+if gpu_type != "CUSTOM":
+    memory_size = st.selectbox('Memory (GB)', memory_size_mapping[instance_type])
+else:
+    memory_size = st.select_slider('Memory (GB)', memory_size_mapping[instance_type])
+
+# Balanced Disk
+balanced_disk_size = st.select_slider('Balanced Disk (GB)', [i for i in range(10, 65536, 10)])
+
+# SSD Disk
+ssd_disk_size = st.select_slider('SSD Disk (GB)', [i * 375 for i in [1,2,3,4,5,6,7,8,16,24]])
+
+# Pricing Estimate
+serivces_mapping = {
+    "Core": {
+        "A3": 0.029917642,
+        "A2": 0.017880447,
+        "G2": 0.016626389,
+        "N1": 0.007834495,
+        "CUSTOM": 0.00782101,
+    },
+    "RAM": {
+        "A3": 0.002605197,
+        "A2": 0.002396196,
+        "G2": 0.00194851,
+        "N1": 0.001049094,
+        "CUSTOM": 0.001047746,
+    },
+    "GPU": {
+        'H100 80GB': 12.112232328,
+        'A100 80GB': 2.61383548,
+        'A100 40GB': 1.67288707,
+        'V100 16GB': 0.997853,
+        'P100 16GB': 0.5798335,
+        'L4 24GB': 0.279501996,
+        'T4 16GB': 0.1483295,
+        'P4 8GB': 0.29800745,
+    },
+    "PD": 0.1483295 / 30 / 24,
+    "SSD": 0.108550225 / 30 / 24,
+}
 
-# # CPU Cores
-# cpu_numbers = st.slider('How many CPU Cores you would like to use?', 0, 208, 8)
+core_price = serivces_mapping['Core'][instance_type] * cpu_cores
+memory_price = serivces_mapping['RAM'][instance_type] * memory_size
+gpu_price = serivces_mapping['GPU'][gpu_type] * gpu_number
+balanced_disk_price = serivces_mapping['PD'] * balanced_disk_size
+ssd_disk_price = serivces_mapping['SSD'] * ssd_disk_size
+total_price = core_price + memory_price + gpu_price + balanced_disk_price + ssd_disk_price
 
-# # Memory
-# memory_size = st.slider('How many Memory you would like to use?', 0, 208, 8)
+st.write(core_price)
+st.write(memory_price)
+st.write(gpu_price)
+st.write(balanced_disk_price)
+st.write(ssd_disk_price)
+st.write(total_price)