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fadc1ce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | import pickle
import numpy as np
import gym
from flask import Flask, render_template, request
app = Flask(__name__)
# Load the Q-learning model
with open("q-learning.pkl", "rb") as f:
model = pickle.load(f)
# Initialize the Taxi-v3 environment
env = gym.make("Taxi-v3")
@app.route('/')
def home():
return render_template('index.html')
@app.route('/predict', methods=['POST'])
def predict():
try:
# Get the state from the user input
state = int(request.form['state'])
# Get the action from the model
action = model.predict(np.array([state])) # This assumes model.predict can work with the state as input
# Return the result
return render_template('index.html', state=state, action=action)
except Exception as e:
return f"Error: {str(e)}"
if __name__ == '__main__':
app.run(debug=True) |