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A demo application for the ENEXA Knowledge Extraction use case

screenshot

Installation

pip install -r requirements.txt

Configuration

The application needs to know where the ENEXA service is running, etc. To do so, you need to set the environment variable ENEXA_SERVICE_URL to the URL of the service.

The following parameters are required and can be defined in the .env file or as environment variables:

  • SERVER_ENDPOINT

  • ENEXA_SHARED_DIRECTORY

  • ENEXA_WRITEABLE_DIRECTORY

  • SLEEP_IN_SECONDS

Note, for all of these variables defaults are defined in the app.py that are intended to be used for development purposes only.

Usage

streamlit run app.py

If you worked on the localhost and everything went well, you should see a frontend at http://localhost:8501.

Docker

You can also run the application in a Docker container. To do so, you need to build the Docker image first:

docker build -t enexa-knowledge-extraction-demo:latest .

Then you can run the container:

docker run -p 8501:8501 enexa-knowledge-extraction-demo:latest

For Developers

If you want to develop on the frontend, you can use the following commands to start the required services:

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Frontend for knowledge extraction demonstration

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