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Framework for maintaining Watson Assistant data in github repository with bundle of tools for generating, testing and uploading. Travis: https://travis-ci.com/IBM/watson-assistant-workbench. Artifactory (will be deleted after 25 Nov 2019): https://na.artifactory.swg-devops.com/artifactory/webapp/#/artifacts/browse/tree/General/iot-waw-trevis-generic-local.

License: Apache License 2.0

Batchfile 0.03% JavaScript 0.04% Python 97.19% Shell 2.57% Go 0.06% PHP 0.03% Ruby 0.02% Swift 0.05%

watson-assistant-workbench's Introduction


WAW-version Python

About

WAW is a toolkit for maintaining Watson Assistant data in github repository. It aims at

  • structured data-driven approach, with easy diffs visible in GitHub
  • easy collaboration among large teams
  • improved dialog tree representation resulting in greater readability and easier updates compared to the original WA JSON format
  • easy-to-use XML format and tools that make authoring of Watson Conversation workspaces easier using standard text editors
  • ability to easily include and combine pieces of dialog together
  • full compatibility with the WA JSON workspace format
  • easy Continuous Integration - each commit to GitHub runs tests and updates conversation workspace if all succeed
  • automatic dialog code generation (go back, abort, etc. - actions needed in each dialog step)
  • support for internationalization
  • and more :)

It contains a bundle of tools for generating WA workspace from the structure data (and viceversa), testing and uploading (working with the WCS API).

Currently supported conversation version is 2017-02-03 except:

  • Fuzzy matching, Folders and Digression are not supported.
  • A name of a dialog node still has to be unique as it is used as node ID.
  • Missing "slot_in_focus" property.
  • Slots are not supported in json to xml conversion scripts.

Prerequisites

Scripts use python 3.5, used modules are listed in the requirements.txt file. To satisfy all requirements run

pip install -r requirements.txt

For brief summary how to run scripts please see scripts.md.

Description of T2C and xml/csv WAW formats can be found in doc folder.

Release notes can be found in release_notes.md.

Instructions on how to use logging can be found in logging.md.


Testing

If you want to run unit tests locally, you first need to install development dependencies from requirements_dev.txt. You can run

pip install -r requirements_dev.txt

Then set following environment variables (i.e. run export VARIABLE_NAME="VARIABLE_VALUE")

  • WA_USERNAME (Watson Assistant username - ALWAYS USE INSTANCE DEDICATED FOR TESTING ONLY! ALL CONTENT WILL BE DELETED DURING TESTING PROCESS!)
  • WA_PASSWORD (Watson Assistant password)
  • CLOUD_FUNCTIONS_USERNAME (Cloud Functions username)
  • CLOUD_FUNCTIONS_PASSWORD (Cloud Functions password)
  • CLOUD_FUNCTIONS_URL (Cloud Functions namespace - it should contain https:// at the beginning and /api/v1/namespaces at the end)
  • CLOUD_FUNCTIONS_NAMESPACE (Cloud Functions namespace - don't forget enclosing it in apostrophes if it contains spaces)

The unit tests and app tests can be started with these commands (from the top directory of this repository)

PYTHONPATH=./scripts:$PYTHONPATH pytest ci/unit_tests
PYTHONPATH=./scripts:$PYTHONPATH pytest ci/app_tests

watson-assistant-workbench's People

Contributors

tereza-pytelova avatar ondrejtomas avatar tomasmacek avatar ota-sandr avatar kseii avatar balatjan avatar michalpospech avatar kant avatar cclauss avatar hcicenter-research avatar marek-danel avatar stevemart avatar erezbi avatar

Watchers

James Cloos avatar

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