Connection Refused

Attempting to run rasa for the first time, I get a connection refused error:

$ rasa init
Welcome to Rasa! πŸ€–

To get started quickly, an initial project will be created.
If you need some help, check out the documentation at https://rasa.com/docs/rasa.
Now let's start! πŸ‘‡πŸ½

? Please enter a path where the project will be created [default: current directory] .
Created project directory at '/home/georgej/rasa-server'.
Finished creating project structure.
Training an initial model...
Training Core model...
2019-05-25 15:11:41 INFO     root  - Generating grammar tables from /usr/lib/python3.6/lib2to3/Grammar.txt
2019-05-25 15:11:41 INFO     root  - Generating grammar tables from /usr/lib/python3.6/lib2to3/PatternGrammar.txt

WARNING: The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
  * https://github.com/tensorflow/addons
If you depend on functionality not listed there, please file an issue.

Processed Story Blocks: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4/4 [00:00<00:00, 2699.04it/s, # trackers=1]
Processed Story Blocks: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4/4 [00:00<00:00, 1674.37it/s, # trackers=4]
Processed Story Blocks: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4/4 [00:00<00:00, 574.39it/s, # trackers=12]
Processed Story Blocks: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4/4 [00:00<00:00, 807.92it/s, # trackers=7]
Processed trackers: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 4/4 [00:00<00:00, 1907.15it/s, # actions=14]
Processed actions: 14it [00:00, 7466.02it/s, # examples=14]
Processed trackers: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 94/94 [00:00<00:00, 361.82it/s, # actions=62]
2019-05-25 15:11:43.543034: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 AVX512F FMA
2019-05-25 15:11:43.547920: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2095074999 Hz
2019-05-25 15:11:43.548101: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x20ad050 executing computations on platform Host. Devices:
2019-05-25 15:11:43.548148: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
_________________________________________________________________
Layer (type)                 Output Shape              Param #
=================================================================
masking (Masking)            (None, 5, 19)             0
_________________________________________________________________
lstm (LSTM)                  (None, 32)                6656
_________________________________________________________________
dense (Dense)                (None, 13)                429
_________________________________________________________________
activation (Activation)      (None, 13)                0
=================================================================
Total params: 7,085
Trainable params: 7,085
Non-trainable params: 0
_________________________________________________________________
2019-05-25 15:11:44 INFO     rasa.core.policies.keras_policy  - Fitting model with 62 total samples and a validation split of 0.1
Epoch 1/100
62/62 [==============================] - 1s 10ms/sample - loss: 2.5998 - acc: 0.0968
Epoch 2/100
62/62 [==============================] - 0s 215us/sample - loss: 2.5648 - acc: 0.0806
Epoch 3/100
62/62 [==============================] - 0s 218us/sample - loss: 2.5093 - acc: 0.2742
Epoch 4/100
62/62 [==============================] - 0s 220us/sample - loss: 2.4905 - acc: 0.3387
Epoch 5/100
62/62 [==============================] - 0s 202us/sample - loss: 2.4609 - acc: 0.3226
Epoch 6/100
62/62 [==============================] - 0s 205us/sample - loss: 2.4401 - acc: 0.3871
Epoch 7/100
62/62 [==============================] - 0s 203us/sample - loss: 2.4056 - acc: 0.4355
Epoch 8/100
62/62 [==============================] - 0s 204us/sample - loss: 2.3645 - acc: 0.4355
Epoch 9/100
62/62 [==============================] - 0s 208us/sample - loss: 2.3377 - acc: 0.4355
Epoch 10/100
62/62 [==============================] - 0s 209us/sample - loss: 2.3043 - acc: 0.4516
Epoch 11/100
62/62 [==============================] - 0s 211us/sample - loss: 2.2655 - acc: 0.4194
Epoch 12/100
62/62 [==============================] - 0s 210us/sample - loss: 2.2345 - acc: 0.4677
Epoch 13/100
62/62 [==============================] - 0s 203us/sample - loss: 2.2159 - acc: 0.3871
Epoch 14/100
62/62 [==============================] - 0s 206us/sample - loss: 2.1521 - acc: 0.4677
Epoch 15/100
62/62 [==============================] - 0s 207us/sample - loss: 2.1051 - acc: 0.4677
Epoch 16/100
62/62 [==============================] - 0s 216us/sample - loss: 2.0644 - acc: 0.4516
Epoch 17/100
62/62 [==============================] - 0s 212us/sample - loss: 2.0395 - acc: 0.4355
Epoch 18/100
62/62 [==============================] - 0s 209us/sample - loss: 1.9896 - acc: 0.4355
Epoch 19/100
62/62 [==============================] - 0s 212us/sample - loss: 1.9336 - acc: 0.4355
Epoch 20/100
62/62 [==============================] - 0s 212us/sample - loss: 1.8999 - acc: 0.4355
Epoch 21/100
62/62 [==============================] - 0s 209us/sample - loss: 1.8998 - acc: 0.4355
Epoch 22/100
62/62 [==============================] - 0s 226us/sample - loss: 1.8390 - acc: 0.4355
Epoch 23/100
62/62 [==============================] - 0s 216us/sample - loss: 1.7907 - acc: 0.4516
Epoch 24/100
62/62 [==============================] - 0s 213us/sample - loss: 1.7618 - acc: 0.4355
Epoch 25/100
62/62 [==============================] - 0s 213us/sample - loss: 1.7397 - acc: 0.4355
Epoch 26/100
62/62 [==============================] - 0s 211us/sample - loss: 1.7130 - acc: 0.4516
Epoch 27/100
62/62 [==============================] - 0s 211us/sample - loss: 1.6901 - acc: 0.4355
Epoch 28/100
62/62 [==============================] - 0s 210us/sample - loss: 1.6875 - acc: 0.4355
Epoch 29/100
62/62 [==============================] - 0s 210us/sample - loss: 1.6942 - acc: 0.4355
Epoch 30/100
62/62 [==============================] - 0s 206us/sample - loss: 1.6892 - acc: 0.4355
Epoch 31/100
62/62 [==============================] - 0s 210us/sample - loss: 1.6611 - acc: 0.4355
Epoch 32/100
62/62 [==============================] - 0s 218us/sample - loss: 1.6454 - acc: 0.4355
Epoch 33/100
62/62 [==============================] - 0s 209us/sample - loss: 1.6551 - acc: 0.4355
Epoch 34/100
62/62 [==============================] - 0s 213us/sample - loss: 1.6279 - acc: 0.4355
Epoch 35/100
62/62 [==============================] - 0s 209us/sample - loss: 1.6090 - acc: 0.4355
Epoch 36/100
62/62 [==============================] - 0s 211us/sample - loss: 1.5941 - acc: 0.4516
Epoch 37/100
62/62 [==============================] - 0s 217us/sample - loss: 1.6135 - acc: 0.4355
Epoch 38/100
62/62 [==============================] - 0s 211us/sample - loss: 1.6102 - acc: 0.4355
Epoch 39/100
62/62 [==============================] - 0s 212us/sample - loss: 1.5783 - acc: 0.4355
Epoch 40/100
62/62 [==============================] - 0s 212us/sample - loss: 1.5393 - acc: 0.4355
Epoch 41/100
62/62 [==============================] - 0s 211us/sample - loss: 1.5428 - acc: 0.4355
Epoch 42/100
62/62 [==============================] - 0s 211us/sample - loss: 1.5502 - acc: 0.4355
Epoch 43/100
62/62 [==============================] - 0s 210us/sample - loss: 1.5274 - acc: 0.4516
Epoch 44/100
62/62 [==============================] - 0s 206us/sample - loss: 1.5131 - acc: 0.4516
Epoch 45/100
62/62 [==============================] - 0s 211us/sample - loss: 1.4966 - acc: 0.4355
Epoch 46/100
62/62 [==============================] - 0s 215us/sample - loss: 1.4758 - acc: 0.4516
Epoch 47/100
62/62 [==============================] - 0s 210us/sample - loss: 1.4931 - acc: 0.4516
Epoch 48/100
62/62 [==============================] - 0s 207us/sample - loss: 1.4873 - acc: 0.4516
Epoch 49/100
62/62 [==============================] - 0s 213us/sample - loss: 1.4821 - acc: 0.4516
Epoch 50/100
62/62 [==============================] - 0s 207us/sample - loss: 1.4711 - acc: 0.4516
Epoch 51/100
62/62 [==============================] - 0s 206us/sample - loss: 1.4574 - acc: 0.4355
Epoch 52/100
62/62 [==============================] - 0s 206us/sample - loss: 1.4122 - acc: 0.4516
Epoch 53/100
62/62 [==============================] - 0s 209us/sample - loss: 1.4207 - acc: 0.4516
Epoch 54/100
62/62 [==============================] - 0s 205us/sample - loss: 1.4034 - acc: 0.4516
Epoch 55/100
62/62 [==============================] - 0s 205us/sample - loss: 1.3968 - acc: 0.4516
Epoch 56/100
62/62 [==============================] - 0s 208us/sample - loss: 1.4023 - acc: 0.4516
Epoch 57/100
62/62 [==============================] - 0s 208us/sample - loss: 1.3946 - acc: 0.4355
Epoch 58/100
62/62 [==============================] - 0s 208us/sample - loss: 1.3703 - acc: 0.4355
Epoch 59/100
62/62 [==============================] - 0s 207us/sample - loss: 1.3681 - acc: 0.4516
Epoch 60/100
62/62 [==============================] - 0s 206us/sample - loss: 1.3634 - acc: 0.4516
Epoch 61/100
62/62 [==============================] - 0s 204us/sample - loss: 1.3347 - acc: 0.4355
Epoch 62/100
62/62 [==============================] - 0s 204us/sample - loss: 1.3224 - acc: 0.4516
Epoch 63/100
62/62 [==============================] - 0s 210us/sample - loss: 1.3174 - acc: 0.4516
Epoch 64/100
62/62 [==============================] - 0s 206us/sample - loss: 1.3189 - acc: 0.4516
Epoch 65/100
62/62 [==============================] - 0s 210us/sample - loss: 1.3094 - acc: 0.4516
Epoch 66/100
62/62 [==============================] - 0s 207us/sample - loss: 1.2831 - acc: 0.4355
Epoch 67/100
62/62 [==============================] - 0s 212us/sample - loss: 1.2572 - acc: 0.4516
Epoch 68/100
62/62 [==============================] - 0s 206us/sample - loss: 1.2717 - acc: 0.4355
Epoch 69/100
62/62 [==============================] - 0s 195us/sample - loss: 1.2307 - acc: 0.4516
Epoch 70/100
62/62 [==============================] - 0s 195us/sample - loss: 1.2312 - acc: 0.4516
Epoch 71/100
62/62 [==============================] - 0s 196us/sample - loss: 1.1949 - acc: 0.4839
Epoch 72/100
62/62 [==============================] - 0s 196us/sample - loss: 1.1746 - acc: 0.5000
Epoch 73/100
62/62 [==============================] - 0s 203us/sample - loss: 1.1890 - acc: 0.4677
Epoch 74/100
62/62 [==============================] - 0s 203us/sample - loss: 1.1812 - acc: 0.5000
Epoch 75/100
62/62 [==============================] - 0s 207us/sample - loss: 1.1899 - acc: 0.5323
Epoch 76/100
62/62 [==============================] - 0s 198us/sample - loss: 1.1677 - acc: 0.5484
Epoch 77/100
62/62 [==============================] - 0s 203us/sample - loss: 1.1247 - acc: 0.5323
Epoch 78/100
62/62 [==============================] - 0s 202us/sample - loss: 1.1413 - acc: 0.5323
Epoch 79/100
62/62 [==============================] - 0s 202us/sample - loss: 1.1452 - acc: 0.5000
Epoch 80/100
62/62 [==============================] - 0s 203us/sample - loss: 1.0876 - acc: 0.5161
Epoch 81/100
62/62 [==============================] - 0s 205us/sample - loss: 1.0764 - acc: 0.5645
Epoch 82/100
62/62 [==============================] - 0s 203us/sample - loss: 1.0486 - acc: 0.5806
Epoch 83/100
62/62 [==============================] - 0s 202us/sample - loss: 1.0707 - acc: 0.5645
Epoch 84/100
62/62 [==============================] - 0s 201us/sample - loss: 1.0431 - acc: 0.5323
Epoch 85/100
62/62 [==============================] - 0s 200us/sample - loss: 1.0340 - acc: 0.5968
Epoch 86/100
62/62 [==============================] - 0s 202us/sample - loss: 1.0329 - acc: 0.6129
Epoch 87/100
62/62 [==============================] - 0s 200us/sample - loss: 1.0103 - acc: 0.6613
Epoch 88/100
62/62 [==============================] - 0s 201us/sample - loss: 1.0009 - acc: 0.6452
Epoch 89/100
62/62 [==============================] - 0s 201us/sample - loss: 0.9887 - acc: 0.6774
Epoch 90/100
62/62 [==============================] - 0s 200us/sample - loss: 0.9673 - acc: 0.6613
Epoch 91/100
62/62 [==============================] - 0s 199us/sample - loss: 0.9505 - acc: 0.6935
Epoch 92/100
62/62 [==============================] - 0s 203us/sample - loss: 0.9325 - acc: 0.7258
Epoch 93/100
62/62 [==============================] - 0s 208us/sample - loss: 0.9659 - acc: 0.6935
Epoch 94/100
62/62 [==============================] - 0s 209us/sample - loss: 0.9587 - acc: 0.6290
Epoch 95/100
62/62 [==============================] - 0s 202us/sample - loss: 0.9515 - acc: 0.7419
Epoch 96/100
62/62 [==============================] - 0s 199us/sample - loss: 0.9068 - acc: 0.7581
Epoch 97/100
62/62 [==============================] - 0s 199us/sample - loss: 0.9105 - acc: 0.7581
Epoch 98/100
62/62 [==============================] - 0s 196us/sample - loss: 0.9028 - acc: 0.7903
Epoch 99/100
62/62 [==============================] - 0s 196us/sample - loss: 0.8650 - acc: 0.8065
Epoch 100/100
62/62 [==============================] - 0s 198us/sample - loss: 0.8685 - acc: 0.7903
2019-05-25 15:11:47 INFO     rasa.core.policies.keras_policy  - Done fitting keras policy model
2019-05-25 15:11:47 INFO     rasa.core.agent  - Persisted model to '/tmp/tmpqyfmpal5/core'
Core model training completed.
Training NLU model...
2019-05-25 15:11:47 INFO     rasa.nlu.training_data.loading  - Training data format of /tmp/tmpq0fjo8ui/225cef8a0e7745058e9886dafe0cea2c_nlu.md is md
2019-05-25 15:11:47 INFO     rasa.nlu.training_data.training_data  - Training data stats:
        - intent examples: 39 (6 distinct intents)
        - Found intents: 'mood_unhappy', 'greet', 'goodbye', 'mood_great', 'affirm', 'deny'
        - entity examples: 0 (0 distinct entities)
        - found entities:

2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component WhitespaceTokenizer
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component RegexFeaturizer
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component CRFEntityExtractor
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component EntitySynonymMapper
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component CountVectorsFeaturizer
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:47 INFO     rasa.nlu.model  - Starting to train component EmbeddingIntentClassifier
2019-05-25 15:11:48 INFO     rasa.nlu.classifiers.embedding_intent_classifier  - Accuracy is updated every 10 epochs
Epochs: 100%|β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ| 300/300 [00:01<00:00, 212.81it/s, loss=0.094, acc=1.000]
2019-05-25 15:11:49 INFO     rasa.nlu.classifiers.embedding_intent_classifier  - Finished training embedding classifier, loss=0.094, train accuracy=1.000
2019-05-25 15:11:49 INFO     rasa.nlu.model  - Finished training component.
2019-05-25 15:11:49 INFO     rasa.nlu.model  - Successfully saved model into '/tmp/tmpqyfmpal5/nlu'
NLU model training completed.
Your Rasa model is trained and saved at '/home/georgej/rasa-server/models/20190525-151141.tar.gz'.
? Do you want to speak to the trained assistant on the command line? πŸ€–  Yes
2019-05-25 15:11:53 INFO     root  - Starting Rasa Core server on http://localhost:5005

Bot loaded. Type a message and press enter (use '/stop' to exit):
Your input ->
2019-05-25 15:11:55 ERROR    asyncio  - Task exception was never retrieved
future: <Task finished coro=<configure_app.<locals>.run_cmdline_io() done, defined at /home/georgej/.local/lib/python3.6/site-packages/rasa/core/run.py:101> exception=ClientConnectorError(111, 'Connection refused')>
Traceback (most recent call last):
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 924, in _wrap_create_connection
    await self._loop.create_connection(*args, **kwargs))
  File "uvloop/loop.pyx", line 1904, in create_connection
  File "uvloop/loop.pyx", line 1883, in uvloop.loop.Loop.create_connection
ConnectionRefusedError: [Errno 111] Connection refused

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/georgej/.local/lib/python3.6/site-packages/rasa/core/run.py", line 105, in run_cmdline_io
    server_url=constants.DEFAULT_SERVER_FORMAT.format(port)
  File "/home/georgej/.local/lib/python3.6/site-packages/rasa/core/channels/console.py", line 115, in record_messages
    async for response in bot_responses:
  File "/home/georgej/.local/lib/python3.6/site-packages/async_generator/_impl.py", line 366, in step
    return await ANextIter(self._it, start_fn, *args)
  File "/home/georgej/.local/lib/python3.6/site-packages/async_generator/_impl.py", line 205, in throw
    return self._invoke(self._it.throw, type, value, traceback)
  File "/home/georgej/.local/lib/python3.6/site-packages/async_generator/_impl.py", line 209, in _invoke
    result = fn(*args)
  File "/home/georgej/.local/lib/python3.6/site-packages/rasa/core/channels/console.py", line 80, in send_message_receive_stream
    async with session.post(url, json=payload, raise_for_status=True) as resp:
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/client.py", line 1005, in __aenter__
    self._resp = await self._coro
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/client.py", line 476, in _request
    timeout=real_timeout
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 522, in connect
    proto = await self._create_connection(req, traces, timeout)
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 854, in _create_connection
    req, traces, timeout)
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 992, in _create_direct_connection
    raise last_exc
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 974, in _create_direct_connection
    req=req, client_error=client_error)
  File "/home/georgej/.local/lib/python3.6/site-packages/aiohttp/connector.py", line 931, in _wrap_create_connection
    raise client_error(req.connection_key, exc) from exc
aiohttp.client_exceptions.ClientConnectorError: Cannot connect to host localhost:5005 ssl:None [Connection refused]

Hello, for me sudo apt-get upgrade and sudo apt-get update worked.

@gj0 did @gsp0din’s suggestion help?

Although it worked for the rasa run, I can’t rasa shell, the error is the same.

which Rasa version are you running? Can you update to the latest?

Hey guys,

I’m running to the same issue when I’m running it from GCP Compute Engine. Rasa shell is returning similar issue.

This is fresh latest install of Rasa, with python 3.7.3 and running on Debian 9.

Thoughts? :slight_smile:

Similar setup done on local VM seems to work fine with an issue that it won’t talk back after saying bye bye… lol

Pls try to run

rasa shell --cors "*"

May be it helps!

I’m also getting channel 3: open failed: connect failed: Connection refused when I try to access rasa x at the provided URL. Rasa version 1.2.8. Python 3.7.4 Still happens after apt-get update and upgrade.

Solved I was using EXPOSE in my dockerfile rather than the -p/ports flag when running the container. Learned it here