Metadata-Version: 1.2
Name: assistant_improve_toolkit
Version: 1.1.6
Summary: Assistant Improve Toolkit
Home-page: https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook
Author: IBM Watson
Author-email: watdevex@us.ibm.com
Maintainer: Zhe Zhang
Maintainer-email: zhangzhe@us.ibm.com
License: Apache 2.0
Description: Watson Assistant Improve Notebooks
        ==================================
        
        |Build Status| |Slack| |Latest Stable Version| |CLA assistant|
        
        This repository houses Watson Assistant Improve notebooks and the
        underlying assistant improve toolkit library.
        
        Introduction
        ------------
        
        To help improving your Watson Assistant after you have deployed it to
        production, we prepared the following Jupyter notebooks. These notebooks
        include practical steps for measuring, analyzing, and actively improving
        your assistant in a continuous manner. Check out `IBM Watson Assistant
        Continuous Improvement Best
        Practices <https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook/raw/master/notebook/IBM%20Watson%20Assistant%20Continuous%20Improvement%20Best%20Practices.pdf>`__
        for more details.
        
        -  **Measure notebook** contains a set of automated metrics that help
           you monitor and understand the behavior of your system. The goal is
           to understand where your assistant is doing well vs where it isn’t,
           and to focus your improvement effort to one of the problem areas
           identified.
        
        -  **Effectiveness notebook** helps you understand relative performance
           of each intent and entity as well as the confusion between your
           intents. This information helps you prioritize your improvement
           effort.
        
        -  **Customer Effort notebook** helps you measure and analyze the
           performance improvement after enabling the
           `Disambiguation <https://cloud.ibm.com/docs/assistant?topic=assistant-dialog-runtime#dialog-runtime-disambiguation>`__
           and
           `Autolearning <https://cloud.ibm.com/docs/assistant?topic=assistant-autolearn>`__
           features
        
        -  **Logs notebook** helps you fetch logs using Watson Assistant API.
           You can fetch logs with various filters, and save them as a JSON
           file, or export the utterances in the logs into a CSV file. The JSON
           file can be loaded into the Measure notebook. The CSV file can be
           used for `intent recommendation
           service <https://cloud.ibm.com/docs/assistant?topic=assistant-intent-recommendations#intent-recommendations-get-intent-recommendations-task>`__.
           Alternatively, you can run python scripts
           ```fetch_logs`` <https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook/blob/master/src/main/python/fetch_logs.py>`__
           and
           ```export_csv_for_intent_recommendation`` <https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook/blob/master/src/main/python/export_csv_for_intent_recommendation.py>`__
           to fetch logs and export them to `intent recommendation
           CSV <https://cloud.ibm.com/docs/assistant?topic=assistant-intent-recommendations#intent-recommendations-data-resources>`__,
           respectively. Run ``python get_logs -h`` and
           ``python export_csv_for_intent_recommendation.py -h`` for usage.
        
        -  **Dialog Flow Analysis notebook** help you assess and analyze user
           journeys and issues related to the dialog flow of ineffective (low
           quality) conversations based on production logs. Check out `Dialog
           Flow
           Analysis <https://github.com/watson-developer-cloud/assistant-dialog-flow-analysis>`__
           for more details.
        
        -  **Dialog Skill Analysis notebook** help you analyze characteristics
           of your data such as the number of training examples for each intent
           or the terms which seem to be characteristic of a specific intent.
           Check out `Dalog Skill
           Analysis <https://github.com/watson-developer-cloud/assistant-dialog-skill-analysis>`__
           for more details.
        
        Getting Started
        ---------------
        
        You can either run the notebooks locally or in `IBM Watson
        Studio <https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/notebooks-parent.html>`__.
        
        -  **Run locally**
        
           1. Install Jupyter Notebook, see `Jupyter/IPython Notebook Quick
              Start
              Guide <https://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/install.html>`__
              for more details.
           2. Download the Jupyter notebooks available in this repository's
              `notebook <https://github.com/watson-developer-cloud/assistant-improve-recommendations-notebook/tree/master/notebook>`__
              directory. **Note: These notebook files are not designed for
              Watson Studio environment**
           3. Start jupyter server ``jupyter notebook``
           4. Follow the instructions in each of the notebooks. Be sure to add
              your Watson Assistant credentials if necessary.
        
        -  **Run in Watson Studio**
        
           1. | Create a Watson Studio account.
              | Sign up in `Watson
                Studio <https://www.ibm.com/cloud/watson-studio>`__, or use an
                existing account. Lite plan is free to use.
        
           2. | Create a new project and add a Cloud Object Storage (COS)
                account.
              | For more information regarding COS plans, see
                `Pricing <https://www.ibm.com/cloud-computing/bluemix/pricing-object-storage>`__.
        
           3. Copy
              `Measure <https://dataplatform.cloud.ibm.com/exchange/public/entry/view/133dfc4cd1480bbe4eaa78d3f635e568>`__
              or
              `Effectiveness <https://dataplatform.cloud.ibm.com/exchange/public/entry/view/133dfc4cd1480bbe4eaa78d3f636921c>`__
              notebook from Watson Studio community into your project.
        
           4. Follow the instructions in each notebook to add project tokens and
              Watson Assistant credentials if necessary.
        
        Guides
        ------
        
        -  Learn more about our measure and effectiveness notebook on Medium:
           `Continuously Improve Your Watson Assistant with Jupyter
           Notebooks <https://medium.com/ibm-watson/continuously-improve-your-watson-assistant-with-jupiter-notebooks-60231df4f01f>`__
        
        Contributing
        ------------
        
        See `CONTRIBUTING.md <CONTRIBUTING.md>`__ for more details on how to
        contribute
        
        License
        -------
        
        This library is licensed under the `Apache 2.0
        license <http://www.apache.org/licenses/LICENSE-2.0>`__.
        
        .. |Build Status| image:: https://travis-ci.org/watson-developer-cloud/assistant-improve-recommendations-notebook.svg?branch=master
           :target: https://travis-ci.org/github/watson-developer-cloud/assistant-improve-recommendations-notebook
        .. |Slack| image:: https://wdc-slack-inviter.mybluemix.net/badge.svg
           :target: https://wdc-slack-inviter.mybluemix.net
        .. |Latest Stable Version| image:: https://img.shields.io/pypi/v/assistant-improve-toolkit
           :target: https://pypi.org/project/assistant-improve-toolkit/
        .. |CLA assistant| image:: https://cla-assistant.io/readme/badge/watson-developer-cloud/assistant-improve-recommendations-notebook
           :target: https://cla-assistant.io/watson-developer-cloud/assistant-improve-recommendations-notebook
        
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: OS Independent
Classifier: Topic :: Software Development :: Libraries :: Python Modules
