Reinforced Learning : TypeError: predict() missing 1 required positional argument: 'x'

I got an error from the `epsilon_greedy_policy` saying : `TypeError: predict() missing 1 required positional argument: 'x'`:

```python
def epsilon_greedy_policy(state, epsilon =0):
if np.random.rand() < epsilon:
return np.random.randint(2)

else:
Q_values = model.predict(state[np.newaxis])
return np.argmax(Q_values[0])

def play_one_step(env, state, epsilon):
action = epsilon_greedy_policy(state, epsilon)
next_state, reward, done, info = env.step(action)
replay_buffer.append((state, action, reward, next_state, done))
return next_state, reward, done ,info
```

when i tried starting the algorithm according to the book:

```python
for episode in range(600):
obs = env.reset()
for step in range(200):
epsilon = max(1 - episode/500, 0.01)
obs, reward, done, info = play_one_step(env, obs, epsilon)
if done:
break

if episode > 50:
training_step(batch_size)
```

i got an error saying : **`TypeError: predict() missing 1 required positional argument: 'x'`** and the error was pointing towards the line : `Q_values = model.predict(state[np.newaxis])` from the `epsilon_greedy_policy`

I copied everything according to the book and it still didn't work.
can you help me? thanks in advance.