Running in Docker ¶

Contents

Running in Docker

Images ¶

Rasa NLU docker images are provided for different backends:

spacy: If you use the spacy_sklearn pipeline
tensorflow: If you use the tensorflow_embedding pipeline
mitie: If you use the mitie pipeline
bare: If you want to take a base image and enhance it with your custom dependencies
full (default): If you use components from different pre-defined pipelines and want to have everything included in the image.

Note

For the tensorflow and the full image a x86_64 CPU with AVX support is required.

Training NLU ¶

To train a NLU model you need to mount two directories into the Docker container:

a directory containing your project which in turn includes your NLU configuration and your NLU training data
a directory which will contain the trained NLU model

docker run \
    -v <project_directory>:/app/project \
    -v <model_output_directory>:/app/model \
    rasa/rasa_nlu:latest \
    run \
        python -m rasa_nlu.train \
            -c /app/project/<nlu configuration>.yml \
            -d /app/project/<nlu data> \
            -o /app/model \
            --project <nlu project name>

Running NLU with Rasa Core ¶

See this guide which describes how to set up all Rasa components as Docker containers and how to connect them.

Running NLU as Standalone Server ¶

To run NLU as server you have to

mount a directory with the trained NLU models
expose a port

docker run \
    -p 5000:5000 \
    -v <directory with nlu models>:/app/projects \
    rasa/rasa_nlu:latest \
    start \
        --path /app/projects
        --port 5000

You can then send requests to your NLU server as it is described in the HTTP API, e.g. if it is running on the localhost:

curl --request GET \
     --url 'http://localhost:5000/parse?q=Hello%20world!'

We have a very active support community on Rasa Community Forum that is happy to help you with your questions. If you have any feedback for us or a specific suggestion for improving the docs, feel free to share it by creating an issue on Rasa NLU GitHub repository.

Running in Docker¶

Images¶

Training NLU¶

Running NLU with Rasa Core¶

Running NLU as Standalone Server¶

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