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Not able to open particular directory of rasa project #1

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Ajinkz opened this issue Jan 9, 2019 · 2 comments
Open

Not able to open particular directory of rasa project #1

Ajinkz opened this issue Jan 9, 2019 · 2 comments

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@Ajinkz
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Ajinkz commented Jan 9, 2019

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@danielgolabek
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First, you have to install the package
pip install rasa-host

Then, you can run the following python code:

from RasaHost import host
host.run()

and the app should be running on http://localhost:5005

@Ajinkz Ajinkz changed the title how to run this UI ? Not able to open particular directory of rasa project Feb 18, 2019
@Ajinkz
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Ajinkz commented Feb 18, 2019

my code

from rasa_core.interpreter import RasaNLUInterpreter
from rasa_core.agent import Agent
interpreter = RasaNLUInterpreter('models/current/nlu')
agent = Agent.load("models/dialogue", interpreter=interpreter)

from RasaHost import host
host.nlu_path = r"/home/ajinkz/Desktop/RASA/rasa_DEMO_1-2-19/nlu.md"
host.stories_path = r"/home/ajinkz/Desktop/RASA/rasa_DEMO_1-2-19/stories.md"
host.domain_path = r"/home/ajinkz/Desktop/RASA/rasa_DEMO_1-2-19/domain.yml"
host.agent = agent
if __name__ == '__main__':    
    host.run()

Error

2019-02-18 18:02:49.064460: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-02-18 18:02:58 ERROR    RasaHost  - Traceback (most recent call last):

  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/RasaHost/__init__.py", line 50, in register_channels
    if self.channels:

AttributeError: 'RasaHost' object has no attribute 'channels'

 * Serving Flask app "RasaHost" (lazy loading)
 * Environment: production
   WARNING: Do not use the development server in a production environment.
   Use a production WSGI server instead.
 * Debug mode: off
Traceback (most recent call last):
  File "rasahost.py", line 21, in <module>
    host.run()
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/RasaHost/__init__.py", line 66, in run
    self.flask.run(self.host, self.port)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/flask/app.py", line 943, in run
    run_simple(host, port, self, **options)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/werkzeug/serving.py", line 814, in run_simple
    inner()
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/werkzeug/serving.py", line 774, in inner
    fd=fd)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/werkzeug/serving.py", line 660, in make_server
    passthrough_errors, ssl_context, fd=fd)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/site-packages/werkzeug/serving.py", line 577, in __init__
    self.address_family), handler)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/socketserver.py", line 456, in __init__
    self.server_bind()
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/http/server.py", line 136, in server_bind
    socketserver.TCPServer.server_bind(self)
  File "/home/ajinkz/miniconda3/envs/rasa3/lib/python3.6/socketserver.py", line 470, in server_bind
    self.socket.bind(self.server_address)
OSError: [Errno 98] Address already in use

my directory structure

├── actions.py
├── credentials.yml
├── domain.yml
├── endpoints.yml
├── models
│ ├── current
│ │ └── nlu
│ │ ├── checkpoint
│ │ ├── crf_model.pkl
│ │ ├── intent_classifier_sklearn.pkl
│ │ ├── intent_classifier_tensorflow_embedding.ckpt.data-00000-of-00001
│ │ ├── intent_classifier_tensorflow_embedding.ckpt.index
│ │ ├── intent_classifier_tensorflow_embedding.ckpt.meta
│ │ ├── intent_classifier_tensorflow_embedding_encoded_all_intents.pkl
│ │ ├── intent_classifier_tensorflow_embedding_inv_intent_dict.pkl
│ │ ├── intent_featurizer_count_vectors.pkl
│ │ ├── metadata.json
│ │ ├── regex_featurizer.json
│ │ └── training_data.json
│ └── dialogue
│ ├── domain.json
│ ├── domain.yml
│ ├── policy_0_KerasPolicy
│ │ ├── featurizer.json
│ │ ├── keras_model.h5
│ │ └── keras_policy.json
│ ├── policy_1_FallbackPolicy
│ │ └── fallback_policy.json
│ ├── policy_2_MemoizationPolicy
│ │ ├── featurizer.json
│ │ └── memorized_turns.json
│ ├── policy_3_FormPolicy
│ │ ├── featurizer.json
│ │ └── memorized_turns.json
│ └── policy_metadata.json
├── nlu_config.yml
├── nlu.md
├── out.log

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