A platform for building language / NLP-based applications using NuPIC and CEPT.
Requirements:
To install, run:
python setup.py install
Then, set up the following environment variables with your CEPT API credentials:
export CEPT_APP_ID=app_id
export CEPT_APP_KEY=app_key
from fluent.model import Model
from fluent.term import Term
model = Model()
term1 = Term().createFromString("coyote")
term2 = Term().createFromString("eats")
term3 = Term().createFromString("mouse")
# Train
for _ in range(3):
model.feedTerm(term1)
model.feedTerm(term2)
model.feedTerm(term3)
model.resetSequence()
# Test
term4 = Term().createFromString("wolf")
model.feedTerm(term4)
prediction = model.feedTerm(term2)
print prediction.closestString()
# => "mouse"
The read tool can read a text document word-by-word, predicting each next word as it goes. You can find it at tools/read.py.
Here is an example (after some training):
=> ./tools/read.py data/childrens_stories.txt --checkpoint=cache/model
Sequence # | Term # | Current Term | Predicted Term
----------------------------------------------------------------------
1 | 1 | The | woods
1 | 2 | Ugly | duckling
1 | 3 | Duckling |
3 | 1 | A | duck
3 | 2 | duck | the
3 | 3 | made | her
3 | 4 | her | nest
3 | 5 | nest | under
3 | 6 | under | some
3 | 7 | some | leaves
3 | 8 | leaves | she
4 | 1 | She | sat
4 | 2 | sat | unpopular
4 | 3 | on | the
4 | 4 | the | eggs
4 | 5 | eggs |
4 | 6 | to | keep
4 | 7 | keep | them
4 | 8 | them | warm
...
To run the Fox demo:
=> ./tools/read.py data/associations/foxeat.txt -r
Sequence # | Term # | Current Term | Predicted Term
----------------------------------------------------------------------
1 | 1 | frog |
1 | 2 | eat |
1 | 3 | flies |
2 | 1 | cow |
2 | 2 | eat | flies
2 | 3 | grain |
3 | 1 | elephant |
3 | 2 | eat | grain
3 | 3 | leaves |
4 | 1 | goat |
4 | 2 | eat | grain
4 | 3 | grass |
5 | 1 | wolf |
5 | 2 | eat | grass
5 | 3 | rabbit |
6 | 1 | cat |
6 | 2 | likes |
6 | 3 | ball |
7 | 1 | elephant | eat
7 | 2 | likes |
7 | 3 | water |
8 | 1 | sheep |
8 | 2 | eat | grass
8 | 3 | grass |
9 | 1 | cat | likes
9 | 2 | eat |
9 | 3 | salmon |
10 | 1 | wolf | eat
10 | 2 | eat | rabbit
10 | 3 | mice |
11 | 1 | lion |
11 | 2 | eat | grass
11 | 3 | cow | eat
12 | 1 | dog |
12 | 2 | likes | water
12 | 3 | sleep |
13 | 1 | coyote |
13 | 2 | eat | grass
13 | 3 | mice |
14 | 1 | coyote | eat
14 | 2 | eat | mice
14 | 3 | rodent |
15 | 1 | coyote | eat
15 | 2 | eat | rodent
15 | 3 | rabbit |
16 | 1 | wolf | eat
16 | 2 | eat | mice
16 | 3 | squirrel |
17 | 1 | cow | eat
17 | 2 | eat | grain
...
If you want to use a different CEPT retina, you'll have to make changes in the following places:
- Specify which retina you want to use in
pycept.Cept(...)influent/cept.py. - Update
numberOfColsinfluent/model.py.