How do I shape my input data for use with Conv1D in keras?

I have in my dummy dataset 12 vectors of length 200, each vector representing one sample. Let's say x_train is an array with shape (12, 200).

When I do:

model = Sequential()
model.add(Conv1D(2, 4, input_shape=(1, 200)))

I get the error:

ValueError: Error when checking model input: expected conv1d_1_input to have 3 dimensions, but got array with shape (12, 200)

How do I shape my input array correctly?

Here is my updated script:

data = np.loadtxt('temp/data.csv', delimiter=' ')
trainData = []
testData = []
trainlabels = []
testlabels = []

with open('temp/trainlabels', 'r') as f:
    trainLabelFile = list(csv.reader(f))

with open('temp/testlabels', 'r') as f:
    testLabelFile = list(csv.reader(f))

for i in range(2):
    for idx in trainLabelFile[i]:
        trainData.append(data[int(idx)])
        # append 0 to labels for neg, 1 for pos
        trainlabels.append(i)

for i in range(2):
    for idx in testLabelFile[i]:
        testData.append(data[int(idx)])
        # append 0 to labels for neg, 1 for pos
        testlabels.append(i)

# print(trainData.shape)
X = np.array(trainData)
Y = np.array(trainlabels)
X2 = np.array(testData)
Y2 = np.array(testlabels)

model = Sequential()
model.add(Conv1D(1, 1, input_shape=(12, 1, 200)))

opt = 'adam'
model.compile(loss='mean_squared_error', optimizer=opt, metrics=['accuracy'])

model.fit(X, Y, epochs=epochs)

I am now getting a new error:

ValueError: Input 0 is incompatible with layer conv1d_1: expected ndim=3, found ndim=4