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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import streamlit as st
import os
from trainer import train
from tester import test
def main():
st.title("Beyond the Anti-Jam: Integration of DRL with LLM")
st.sidebar.header("Make Your Environment Configuration")
mode = st.sidebar.radio("Choose Mode", ["Auto", "Manual"])
if mode == "Auto":
jammer_type = "dynamic"
channel_switching_cost = 0.1
else:
jammer_type = st.sidebar.selectbox("Select Jammer Type", ["constant", "sweeping", "random", "dynamic"])
channel_switching_cost = st.sidebar.selectbox("Select Channel Switching Cost", [0, 0.05, 0.1, 0.15, 0.2])
st.sidebar.subheader("Configuration:")
st.sidebar.write(f"Jammer Type: {jammer_type}")
st.sidebar.write(f"Channel Switching Cost: {channel_switching_cost}")
train_button = st.sidebar.button('Train')
test_button = st.sidebar.button('Test')
if train_button or test_button:
agent_name = f'DDQNAgent_{jammer_type}_csc_{channel_switching_cost}'
if os.path.exists(agent_name):
if train_button:
st.warning("Agent has been trained already! Do you want to retrain?")
retrain = st.sidebar.button('Yes')
if retrain:
perform_training(jammer_type, channel_switching_cost)
elif test_button:
perform_testing(jammer_type, channel_switching_cost)
else:
if train_button:
perform_training(jammer_type, channel_switching_cost)
elif test_button:
st.warning("Agent has not been trained yet. Click Train First!!!")
def perform_training(jammer_type, channel_switching_cost):
train(jammer_type, channel_switching_cost)
def perform_testing(jammer_type, channel_switching_cost):
test(jammer_type, channel_switching_cost)
if __name__ == "__main__":
main()
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