Visual Editor for creating NLP rules.
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Watch a live demo of the NLP editor, and learn more about our future plans in our recent IBM Data Science Community presentation.
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Walk through our Tutorial.
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Try the editor by following the instructions below.
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Clone the repository
git clone [email protected]:CODAIT/nlp-editor.git
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Navigate to the source code
cd nlp-editor
The application users a NodeJS server file as proxy, this makes it easy to replace and embed the UI with any other server - Websphere, Nginx, etc.
On a Terminal window, install the Node Version Manager (nvm) as follows:
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.0/install.sh | bash
Reference: https://github.com/nvm-sh/nvm#installing-and-updating
Verify nvm installed properly
> nvm -v
0.39.2
Next, install the required NodeJS version; currently at 18.12.0
nvm install v18.12.0
Verify node and npm installed properly
> node -v
v18.12.0
> npm -v
8.19.2
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Install the dependencies
npm install
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Build the app
npm run build
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Run the app
npm run serve
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Open http://localhost:8080 in a web browser.
Additional Prerequsites:
- Docker
- IBM Watson Discovery Backend container
01-ibm_watson_discovery_web_nlp_tool_backend-<date>.tar.gz
supplied to you
- Follow steps above to Run the editor locally
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Extract
01-ibm_watson_discovery_web_nlp_tool_backend-<date>.tar.gz
into a folder of your choice, saywatson_nlp_web_tool
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Build the container image
cd watson_nlp_web_tool docker build -t watson_nlp_web_tool:1.0 .
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Run the container image with volumes mapped. Note that
/path/to/nlp-editor
is the absolute path to thenlp-editor
repository (from Step 1).docker run -d -v /path/to/nlp-editor/Seer-Core/aql-processor/user-data-in:/app/Seer-Core/aql-processor/user-data-in -v /path/to/nlp-editor/Seer-Core/aql-processor/run-aql-result:/app/Seer-Core/aql-processor/run-aql-result --name watson_nlp_web_tool watson_nlp_web_tool:1.0
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Open http://localhost:8080 in a web browser, or use reuse session from Step 1.
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Create your NLP model. Use the Tutorial for guidance.
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When you are satisfied with your model, click Export. A
.zip
file is generated on your local file system. -
In Watson Discovery on CloudPak for Data, apply the model by following the steps in Advanced Rules Models.
We welcome your questions, ideas, and feedback. Please create an issue or a discussion thread.
If you are interested in helping make the NLP editor better, we encourage you to take a look at our Contributing page.