out.log

/Users/nahalam/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters

$HOME=/Users/nahalam
matplotlib data path /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data
loaded rc file /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 2.2.2
interactive is False
platform is darwin
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'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special.basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._hungarian', 'scipy.optimize._differentialevolution', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.sparse.linalg._expm_multiply', 'sklearn.exceptions', 'sklearn.externals.joblib', 'sklearn.externals.joblib.memory', 'pydoc', 'sklearn.externals.joblib.hashing', 'sklearn.externals.joblib._compat', 'sklearn.externals.joblib.func_inspect', 'sklearn.externals.joblib.logger', 'sklearn.externals.joblib.disk', 'sklearn.externals.joblib._memory_helpers', 'sklearn.externals.joblib.numpy_pickle', 'sklearn.externals.joblib.numpy_pickle_utils', 'gzip', 'sklearn.externals.joblib.numpy_pickle_compat', 'sklearn.externals.joblib.backports', 'distutils', 'distutils.version', 'sklearn.externals.joblib.parallel', 'sklearn.externals.joblib._multiprocessing_helpers', 'sklearn.externals.joblib.format_stack', 'sklearn.externals.joblib.my_exceptions', 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'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.preprocessing.label', 'sklearn.utils.multiclass', 'sklearn.preprocessing.imputation', 'sklearn.linear_model.bayes', 'sklearn.linear_model.least_angle', 'sklearn.utils.arrayfuncs', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics.ranking', 'sklearn.metrics.base', 'sklearn.metrics.classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster.supervised', 'sklearn.metrics.cluster.expected_mutual_info_fast', 'sklearn.utils.lgamma', 'sklearn.metrics.cluster.unsupervised', 'sklearn.metrics.pairwise', 'sklearn.metrics.pairwise_fast', 'sklearn.metrics.cluster.bicluster', 'sklearn.utils.linear_assignment_', 'sklearn.metrics.regression', 'sklearn.metrics.scorer', 'sklearn.model_selection._search', 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'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.framework.ops', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'tensorflow.python.framework.c_api_util', 'tensorflow.python.util.compat', 'tensorflow.python.util.all_util', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 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'tensorflow.python.keras._impl.keras.applications.inception_resnet_v2', 'tensorflow.python.keras._impl.keras.applications.inception_v3', 'tensorflow.python.keras._impl.keras.applications.mobilenet', 'tensorflow.python.keras._impl.keras.applications.nasnet', 'tensorflow.python.keras._impl.keras.applications.resnet50', 'tensorflow.python.keras._impl.keras.applications.vgg16', 'tensorflow.python.keras._impl.keras.applications.vgg19', 'tensorflow.python.keras._impl.keras.applications.xception', 'tensorflow.python.keras._impl.keras.datasets', 'tensorflow.python.keras._impl.keras.datasets.boston_housing', 'tensorflow.python.keras._impl.keras.datasets.cifar10', 'tensorflow.python.keras._impl.keras.datasets.cifar', 'tensorflow.python.keras._impl.keras.datasets.cifar100', 'tensorflow.python.keras._impl.keras.datasets.fashion_mnist', 'tensorflow.python.keras._impl.keras.datasets.imdb', 'tensorflow.python.keras._impl.keras.preprocessing', 'tensorflow.python.keras._impl.keras.preprocessing.image', 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'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.training_util', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.training.coordinator', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.saver', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.estimator.run_config', 'tensorflow.python.training.server_lib', 'tensorflow.python.util.compat_internal', 'tensorflow.python.estimator.warm_starting_util', 'tensorflow.python.training.checkpoint_ops', 'tensorflow.python.ops.gen_checkpoint_ops', 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'tensorflow.python.training.adam', 'tensorflow.python.training.ftrl', 'tensorflow.python.training.momentum', 'tensorflow.python.training.rmsprop', 'tensorflow.python.training.gradient_descent', 'tensorflow.python.training.proximal_gradient_descent', 'tensorflow.python.training.sync_replicas_optimizer', 'tensorflow.python.training.input', 'tensorflow.python.training.basic_loops', 'tensorflow.python.training.supervisor', 'tensorflow.core.example', 'tensorflow.core.example.example_pb2', 'tensorflow.core.example.feature_pb2', 'tensorflow.python.training.learning_rate_decay', 'tensorflow.python.keras._impl.keras.wrappers', 'tensorflow.python.keras._impl.keras.wrappers.scikit_learn', 'tensorflow.python.keras.applications', 'tensorflow.python.keras.applications.densenet', 'tensorflow.python.keras.applications.inception_resnet_v2', 'tensorflow.python.keras.applications.inception_v3', 'tensorflow.python.keras.applications.mobilenet', 'tensorflow.python.keras.applications.nasnet', 'tensorflow.python.keras.applications.resnet50', 'tensorflow.python.keras.applications.vgg16', 'tensorflow.python.keras.applications.vgg19', 'tensorflow.python.keras.applications.xception', 'tensorflow.python.keras.backend', 'tensorflow.python.keras.callbacks', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.datasets', 'tensorflow.python.keras.datasets.boston_housing', 'tensorflow.python.keras.datasets.cifar10', 'tensorflow.python.keras.datasets.cifar100', 'tensorflow.python.keras.datasets.fashion_mnist', 'tensorflow.python.keras.datasets.imdb', 'tensorflow.python.keras.datasets.mnist', 'tensorflow.python.keras.datasets.reuters', 'tensorflow.python.keras.estimator', 'tensorflow.python.keras.initializers', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.models', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.preprocessing', 'tensorflow.python.keras.preprocessing.image', 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'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.join', 'pandas.core.indexes.frozen', 'pandas.core.ops', 'pandas.core.computation', 'numexpr', 'numexpr.__config__', 'numexpr.cpuinfo', 'numexpr.expressions', 'numexpr.interpreter', 'numexpr.necompiler', 'numexpr.utils', 'numexpr.tests', 'numexpr.tests.test_numexpr', 'numexpr.version', 'pandas.core.computation.expressions', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas.core.indexes.numeric', 'pandas.core.indexes.range', 'pandas.core.indexes.timedeltas', 'pandas.tseries', 'pandas.tseries.frequencies', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas.core.indexes.datetimelike', 'pandas._libs.period', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.period', 'pandas.core.indexes.datetimes', 'pandas.core.frame', 'pandas.core.generic', 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From /Users/nahalam/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1305: calling reduce_any (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1188: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Added 'nlp_spacy' to component cache. Key 'nlp_spacy-en'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/rasa_nlu/extractors/entity_synonyms.py:85: UserWarning: Failed to load synonyms file from 'models/nlu/default/customernlu/entity_synonyms.json'
  "".format(entity_synonyms_file))

Started http server on port 5005
Up and running
Creating a new tracker for id 'default'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 2 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_greet' with prob 0.32.
Bot utterance 'BotUttered(text: Hello! How can I help?, data: null)'
Action 'utter_greet' ended with events '[]'
Current tracker state [None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.43.
Action 'action_listen' ended with events '[]'
Current topic: None
Recreating tracker for id 'default'
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'I want to order a product' with intent '{'name': 'order_product', 'confidence': 0.7776131280368231}' and entities '[]'
Logged UserUtterance - tracker now has 6 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_ask_product_name' with prob 0.40.
Bot utterance 'BotUttered(text: Which product?, data: null)'
Action 'utter_ask_product_name' ended with events '[]'
Current tracker state [{}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_action_listen': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_utter_ask_product_name': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.91.
Action 'action_listen' ended with events '[]'
Current topic: None
Recreating tracker for id 'default'
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message '829 router' with intent '{'name': 'order_product', 'confidence': 0.7885591274736371}' and entities '[{'start': 0, 'end': 3, 'value': '829', 'entity': 'router', 'confidence': 0.7211439526856098, 'extractor': 'ner_crf'}, {'start': 4, 'end': 10, 'value': 'router', 'entity': 'product', 'confidence': 0.9185210156061923, 'extractor': 'ner_crf'}]'
Logged UserUtterance - tracker now has 12 events
Current slot values: 
	product: router
	router: 829
Current tracker state [{'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_action_listen': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_utter_ask_product_name': 1.0}, {'entity_router': 1.0, 'entity_product': 1.0, 'slot_product_0': 1.0, 'slot_router_0': 1.0, 'intent_order_product': 0.7885591274736371, 'intent_goodbye': 0.14288525686712839, 'intent_affirm': 0.034576996813454525, 'intent_greet': 0.0339786188457799, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_order_product' with prob 0.87.
Bot utterance 'BotUttered(text: Your product 829 is ordered for you. It will be shipped to your address. Your confirmation number is 123456, data: null)'
Action 'action_order_product' ended with events '['SlotSet(key: router, value: 829)']'
Current tracker state [{'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_action_listen': 1.0}, {'intent_order_product': 0.7776131280368231, 'intent_goodbye': 0.1367643708827961, 'intent_affirm': 0.05312369758518217, 'intent_greet': 0.03249880349519853, 'prev_utter_ask_product_name': 1.0}, {'entity_router': 1.0, 'entity_product': 1.0, 'slot_product_0': 1.0, 'slot_router_0': 1.0, 'intent_order_product': 0.7885591274736371, 'intent_goodbye': 0.14288525686712839, 'intent_affirm': 0.034576996813454525, 'intent_greet': 0.0339786188457799, 'prev_action_listen': 1.0}, {'entity_router': 1.0, 'entity_product': 1.0, 'slot_product_0': 1.0, 'slot_router_0': 1.0, 'intent_order_product': 0.7885591274736371, 'intent_goodbye': 0.14288525686712839, 'intent_affirm': 0.034576996813454525, 'intent_greet': 0.0339786188457799, 'prev_action_order_product': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.94.
Action 'action_listen' ended with events '[]'
Current topic: None
/Users/nahalam/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters

$HOME=/Users/nahalam
matplotlib data path /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data
loaded rc file /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 2.2.2
interactive is False
platform is darwin
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From /Users/nahalam/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1305: calling reduce_any (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1188: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Added 'nlp_spacy' to component cache. Key 'nlp_spacy-en'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/rasa_nlu/extractors/entity_synonyms.py:85: UserWarning: Failed to load synonyms file from 'models/nlu/default/customernlu/entity_synonyms.json'
  "".format(entity_synonyms_file))

Started http server on port 5005
Up and running
Creating a new tracker for id 'default'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 2 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_greet' with prob 0.32.
Bot utterance 'BotUttered(text: Hello! How can I help?, data: null)'
Action 'utter_greet' ended with events '[]'
Current tracker state [None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.43.
Action 'action_listen' ended with events '[]'
Current topic: None
/Users/nahalam/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters

$HOME=/Users/nahalam
matplotlib data path /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data
loaded rc file /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 2.2.2
interactive is False
platform is darwin
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'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special.basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._hungarian', 'scipy.optimize._differentialevolution', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.sparse.linalg._expm_multiply', 'sklearn.exceptions', 'sklearn.externals.joblib', 'sklearn.externals.joblib.memory', 'pydoc', 'sklearn.externals.joblib.hashing', 'sklearn.externals.joblib._compat', 'sklearn.externals.joblib.func_inspect', 'sklearn.externals.joblib.logger', 'sklearn.externals.joblib.disk', 'sklearn.externals.joblib._memory_helpers', 'sklearn.externals.joblib.numpy_pickle', 'sklearn.externals.joblib.numpy_pickle_utils', 'gzip', 'sklearn.externals.joblib.numpy_pickle_compat', 'sklearn.externals.joblib.backports', 'distutils', 'distutils.version', 'sklearn.externals.joblib.parallel', 'sklearn.externals.joblib._multiprocessing_helpers', 'sklearn.externals.joblib.format_stack', 'sklearn.externals.joblib.my_exceptions', 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'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.preprocessing.label', 'sklearn.utils.multiclass', 'sklearn.preprocessing.imputation', 'sklearn.linear_model.bayes', 'sklearn.linear_model.least_angle', 'sklearn.utils.arrayfuncs', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics.ranking', 'sklearn.metrics.base', 'sklearn.metrics.classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster.supervised', 'sklearn.metrics.cluster.expected_mutual_info_fast', 'sklearn.utils.lgamma', 'sklearn.metrics.cluster.unsupervised', 'sklearn.metrics.pairwise', 'sklearn.metrics.pairwise_fast', 'sklearn.metrics.cluster.bicluster', 'sklearn.utils.linear_assignment_', 'sklearn.metrics.regression', 'sklearn.metrics.scorer', 'sklearn.model_selection._search', 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'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.framework.ops', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'tensorflow.python.framework.c_api_util', 'tensorflow.python.util.compat', 'tensorflow.python.util.all_util', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 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'tensorflow.python.ops.image_ops', 'tensorflow.python.ops.image_ops_impl', 'tensorflow.python.ops.nn', 'tensorflow.python.ops.embedding_ops', 'tensorflow.python.ops.nn_impl', 'tensorflow.python.ops.candidate_sampling_ops', 'tensorflow.python.ops.gen_candidate_sampling_ops', 'tensorflow.python.ops.rnn', 'tensorflow.python.ops.rnn_cell_impl', 'tensorflow.python.ops.rnn_cell', 'tensorflow.python.training.moving_averages', 'tensorflow.python.training.slot_creator', 'tensorflow.python.keras._impl.keras.utils', 'tensorflow.python.keras._impl.keras.utils.data_utils', 'tensorflow.python.keras._impl.keras.utils.generic_utils', 'tensorflow.python.keras._impl.keras.utils.io_utils', 'tensorflow.python.keras._impl.keras.utils.layer_utils', 'tensorflow.python.keras._impl.keras.utils.conv_utils', 'tensorflow.python.keras._impl.keras.utils.multi_gpu_utils', 'tensorflow.python.keras._impl.keras.engine', 'tensorflow.python.keras._impl.keras.engine.base_layer', 'tensorflow.python.keras._impl.keras.constraints', 'tensorflow.python.keras._impl.keras.initializers', 'tensorflow.python.keras._impl.keras.regularizers', 'tensorflow.python.keras._impl.keras.engine.input_layer', 'tensorflow.python.keras._impl.keras.engine.network', 'tensorflow.python.keras._impl.keras.engine.saving', 'tensorflow.python.keras._impl.keras.optimizers', 'tensorflow.python.training.optimizer', 'tensorflow.python.eager.backprop', 'tensorflow.python.eager.imperative_grad', 'tensorflow.python.keras._impl.keras.engine.training', 'tensorflow.python.keras._impl.keras.losses', 'tensorflow.python.keras._impl.keras.metrics', 'tensorflow.python.keras._impl.keras.engine.training_arrays', 'tensorflow.python.keras._impl.keras.callbacks', 'tensorflow.python.summary', 'tensorflow.python.summary.summary', 'google.protobuf.json_format', 'tensorflow.python.ops.summary_op_util', 'tensorflow.python.ops.summary_ops', 'tensorflow.python.summary.text_summary', 'tensorflow.python.summary.writer', 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'tensorflow.python.keras._impl.keras.applications.inception_resnet_v2', 'tensorflow.python.keras._impl.keras.applications.inception_v3', 'tensorflow.python.keras._impl.keras.applications.mobilenet', 'tensorflow.python.keras._impl.keras.applications.nasnet', 'tensorflow.python.keras._impl.keras.applications.resnet50', 'tensorflow.python.keras._impl.keras.applications.vgg16', 'tensorflow.python.keras._impl.keras.applications.vgg19', 'tensorflow.python.keras._impl.keras.applications.xception', 'tensorflow.python.keras._impl.keras.datasets', 'tensorflow.python.keras._impl.keras.datasets.boston_housing', 'tensorflow.python.keras._impl.keras.datasets.cifar10', 'tensorflow.python.keras._impl.keras.datasets.cifar', 'tensorflow.python.keras._impl.keras.datasets.cifar100', 'tensorflow.python.keras._impl.keras.datasets.fashion_mnist', 'tensorflow.python.keras._impl.keras.datasets.imdb', 'tensorflow.python.keras._impl.keras.preprocessing', 'tensorflow.python.keras._impl.keras.preprocessing.image', 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'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.training_util', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.training.coordinator', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.saver', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.estimator.run_config', 'tensorflow.python.training.server_lib', 'tensorflow.python.util.compat_internal', 'tensorflow.python.estimator.warm_starting_util', 'tensorflow.python.training.checkpoint_ops', 'tensorflow.python.ops.gen_checkpoint_ops', 'tensorflow.python.training.checkpoint_utils', 'tensorflow.python.estimator.export.export', 'tensorflow.python.ops.metrics', 'tensorflow.python.ops.metrics_impl', 'tensorflow.python.ops.sets', 'tensorflow.python.ops.sets_impl', 'tensorflow.python.ops.gen_set_ops', 'tensorflow.python.ops.weights_broadcast_ops', 'tensorflow.python.saved_model.builder', 'tensorflow.python.saved_model.builder_impl', 'tensorflow.core.protobuf.saved_model_pb2', 'tensorflow.python.saved_model.constants', 'tensorflow.python.saved_model.tag_constants', 'tensorflow.python.training.device_setter', 'tensorflow.python.training.evaluation', 'tensorflow.python.training.training', 'tensorflow.python.ops.sdca_ops', 'tensorflow.python.ops.gen_sdca_ops', 'tensorflow.python.training.adadelta', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.training.adagrad', 'tensorflow.python.training.adagrad_da', 'tensorflow.python.training.proximal_adagrad', 'tensorflow.python.training.adam', 'tensorflow.python.training.ftrl', 'tensorflow.python.training.momentum', 'tensorflow.python.training.rmsprop', 'tensorflow.python.training.gradient_descent', 'tensorflow.python.training.proximal_gradient_descent', 'tensorflow.python.training.sync_replicas_optimizer', 'tensorflow.python.training.input', 'tensorflow.python.training.basic_loops', 'tensorflow.python.training.supervisor', 'tensorflow.core.example', 'tensorflow.core.example.example_pb2', 'tensorflow.core.example.feature_pb2', 'tensorflow.python.training.learning_rate_decay', 'tensorflow.python.keras._impl.keras.wrappers', 'tensorflow.python.keras._impl.keras.wrappers.scikit_learn', 'tensorflow.python.keras.applications', 'tensorflow.python.keras.applications.densenet', 'tensorflow.python.keras.applications.inception_resnet_v2', 'tensorflow.python.keras.applications.inception_v3', 'tensorflow.python.keras.applications.mobilenet', 'tensorflow.python.keras.applications.nasnet', 'tensorflow.python.keras.applications.resnet50', 'tensorflow.python.keras.applications.vgg16', 'tensorflow.python.keras.applications.vgg19', 'tensorflow.python.keras.applications.xception', 'tensorflow.python.keras.backend', 'tensorflow.python.keras.callbacks', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.datasets', 'tensorflow.python.keras.datasets.boston_housing', 'tensorflow.python.keras.datasets.cifar10', 'tensorflow.python.keras.datasets.cifar100', 'tensorflow.python.keras.datasets.fashion_mnist', 'tensorflow.python.keras.datasets.imdb', 'tensorflow.python.keras.datasets.mnist', 'tensorflow.python.keras.datasets.reuters', 'tensorflow.python.keras.estimator', 'tensorflow.python.keras.initializers', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.models', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.preprocessing', 'tensorflow.python.keras.preprocessing.image', 'tensorflow.python.keras.preprocessing.sequence', 'tensorflow.python.keras.preprocessing.text', 'tensorflow.python.keras.regularizers', 'tensorflow.python.keras.utils', 'tensorflow.python.keras.wrappers', 'tensorflow.python.keras.wrappers.scikit_learn', 'tensorflow.python.estimator.estimator_lib', 'tensorflow.python.estimator.canned', 'tensorflow.python.estimator.canned.baseline', 'tensorflow.python.estimator.canned.head', 'tensorflow.python.estimator.canned.metric_keys', 'tensorflow.python.estimator.canned.prediction_keys', 'tensorflow.python.feature_column', 'tensorflow.python.feature_column.feature_column', 'tensorflow.python.ops.losses', 'tensorflow.python.ops.losses.losses', 'tensorflow.python.ops.losses.util', 'tensorflow.python.ops.losses.losses_impl', 'tensorflow.python.estimator.canned.optimizers', 'tensorflow.python.estimator.canned.dnn', 'tensorflow.python.estimator.canned.dnn_linear_combined', 'tensorflow.python.estimator.canned.linear', 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'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.join', 'pandas.core.indexes.frozen', 'pandas.core.ops', 'pandas.core.computation', 'numexpr', 'numexpr.__config__', 'numexpr.cpuinfo', 'numexpr.expressions', 'numexpr.interpreter', 'numexpr.necompiler', 'numexpr.utils', 'numexpr.tests', 'numexpr.tests.test_numexpr', 'numexpr.version', 'pandas.core.computation.expressions', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas.core.indexes.numeric', 'pandas.core.indexes.range', 'pandas.core.indexes.timedeltas', 'pandas.tseries', 'pandas.tseries.frequencies', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas.core.indexes.datetimelike', 'pandas._libs.period', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.period', 'pandas.core.indexes.datetimes', 'pandas.core.frame', 'pandas.core.generic', 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From /Users/nahalam/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1305: calling reduce_any (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1188: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Added 'nlp_spacy' to component cache. Key 'nlp_spacy-en'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/rasa_nlu/extractors/entity_synonyms.py:85: UserWarning: Failed to load synonyms file from 'models/nlu/default/customernlu/entity_synonyms.json'
  "".format(entity_synonyms_file))

Started http server on port 5005
Up and running
Creating a new tracker for id 'default'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 2 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_greet' with prob 0.32.
Bot utterance 'BotUttered(text: Hello! How can I help?, data: null)'
Action 'utter_greet' ended with events '[]'
Current tracker state [None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.43.
Action 'action_listen' ended with events '[]'
Current topic: None
Recreating tracker for id 'default'
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 6 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_ask_product_name' with prob 0.42.
Bot utterance 'BotUttered(text: Which product?, data: null)'
Action 'utter_ask_product_name' ended with events '[]'
Current tracker state [{}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_ask_product_name': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.88.
Action 'action_listen' ended with events '[]'
Current topic: None
/Users/nahalam/anaconda3/lib/python3.6/site-packages/h5py/__init__.py:34: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.
  from ._conv import register_converters as _register_converters

$HOME=/Users/nahalam
matplotlib data path /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data
loaded rc file /Users/nahalam/anaconda3/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
matplotlib version 2.2.2
interactive is False
platform is darwin
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From /Users/nahalam/anaconda3/lib/python3.6/site-packages/tensorflow/contrib/learn/python/learn/datasets/base.py:198: retry (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Use the retry module or similar alternatives.
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1305: calling reduce_any (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
From /Users/nahalam/anaconda3/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:1188: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Added 'nlp_spacy' to component cache. Key 'nlp_spacy-en'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/rasa_nlu/extractors/entity_synonyms.py:85: UserWarning: Failed to load synonyms file from 'models/nlu/default/customernlu/entity_synonyms.json'
  "".format(entity_synonyms_file))

Started http server on port 5005
Up and running
Creating a new tracker for id 'default'.
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 2 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_greet' with prob 0.32.
Bot utterance 'BotUttered(text: Hello! How can I help?, data: null)'
Action 'utter_greet' ended with events '[]'
Current tracker state [None, None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.43.
Action 'action_listen' ended with events '[]'
Current topic: None
Recreating tracker for id 'default'
/Users/nahalam/anaconda3/lib/python3.6/site-packages/sklearn/preprocessing/label.py:151: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
  if diff:

Received user message 'Hello' with intent '{'name': 'affirm', 'confidence': 0.7271094983922496}' and entities '[]'
Logged UserUtterance - tracker now has 6 events
Current slot values: 
	product: None
	router: None
Current tracker state [None, {}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'utter_ask_product_name' with prob 0.42.
Bot utterance 'BotUttered(text: Which product?, data: null)'
Action 'utter_ask_product_name' ended with events '[]'
Current tracker state [{}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_greet': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_action_listen': 1.0}, {'intent_affirm': 0.7271094983922496, 'intent_greet': 0.13576093371153003, 'intent_goodbye': 0.10598609127859003, 'intent_order_product': 0.031143476617630377, 'prev_utter_ask_product_name': 1.0}]
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Couldn't set most probable feature 'intent_affirm', it wasn't found in the feature list of the domain. Make sure you added all intents and entities to the domain.
Predicted next action 'action_listen' with prob 0.88.
Action 'action_listen' ended with events '[]'
Current topic: None