Rasa NLP

Start your docker by running: docker-compose up -d from the rasa-docker directory.

Learn more about this from: https://rasa.com/docs/core/installation/

Run this to train with Markdown file:

curl --request POST --header 'content-type: application/x-yml' --data-binary @config_train_server_md.yml --url 'localhost:5000/train?project=test_model'

Then query like this:

curl 'http://localhost:5000/parse?q=bye&project=test_model'

It should reply with goodbye intent high confidence score

curl 'http://localhost:5000/parse?q=I%20really%20need%20to%20know&project=test_model'

It should reply with learning intent high confidence score

Training file (markdown format)

config_train_server_md.yml See also: https://rasa.com/docs/nlu/dataformat/ See also: https://github.com/RasaHQ/rasa-nlu-trainer

language: "en"

pipeline: "spacy_sklearn"

data: |    
  ## intent:goodbye
  - bye
  - goodbye

  ## intent:learning
  - how do I
  - teach me about
  - I need to know
  - do you know how to

Training with JSON format

curl 'https://raw.githubusercontent.com/RasaHQ/rasa_nlu/master/sample_configs/config_train_server_json.yml' | \
curl --request POST --header 'content-type: application/x-yml' --data-binary @- --url 'localhost:5000/train?project=test_model'

See file attached for a local JSON file.

curl --request POST --header 'content-type: application/x-yml' --data-binary @config_train_server_json.yml --url 'localhost:5000/train?project=test_model'

HTTP API

See: https://rasa.com/docs/nlu/http/

• delete models:

  curl -X DELETE localhost:5000/models?project=test_model&model=model_XXXX

Troubleshooting

The server can't train more models right now!

See: RasaHQ/rasa#1323

Duckling

https://hub.docker.com/r/rasa/duckling/

$ curl -XPOST http://0.0.0.0:8000/parse --data 'locale=en_GB&text=tomorrow at eight'

Rasa nlu

https://hub.docker.com/r/rasa/rasa_nlu/

If wget not installed on Mac: brew install wget --with-libressl

to check

https://github.com/paschmann/rasa-ui

https://www.quora.com/What-are-good-ways-to-automatically-find-synonyms-using-machine-learning-ML-techniques-What-are-good-ways-to-automatically-find-antonyms-using-ML-techniques