Hello, I’m trying to deploy an instance of Rasa X 0.24.6 with Rasa 1.6.1 using Docker. The model has been trained on a different machine using local Rasa 1.6.1 installation without Docker and is loaded into Rasa X. docker-compose.yml is the default version, the contents of docker-compose.override.yml version: '3.4' services: app: image: myimage:latest environment: - PYTHONPATH=/app/ volumes: - ./actions:/app/actions expose: - "5055" The app uses a custom component customNLU.py and is packed with the following Dockerfile: FROM rasa/rasa-sdk:1.6.1 COPY ./* /app/ ENV PYTHONPATH=$PYTHONPATH:/app/ That is, the structure of the app is pretty flat: - app - __init__.py - actions - __init__.py - actions.py - customNLU.py - config.yml - [everything else] The content of config.yml: language: de_core_news_sm pipeline: - name: "SpacyNLP" - name: "SpacyTokenizer" - name: "SpacyFeaturizer" - name: "RegexFeaturizer" - name: "CRFEntityExtractor" - name: "EntitySynonymMapper" - name: "SklearnIntentClassifier" - name: "customNLU.MinimalKeywordSearch" policies: - name: MemoizationPolicy - name: MappingPolicy - name: KerasPolicy Every docker-compose up call throws a sequence of errors: rasa-production_1 | 2020-01-29 14:58:02 DEBUG rasa.core.agent - Found new model with fingerprint f31b006c6e2504bcdc051c4b3f532bb6. Loading... rasa-x_1 | INFO:rasax.community.services.event_consumers.pika_consumer:Start consuming queue 'rasa_production_events' on pika host 'rabbit'. rabbit_1 | 14:58:11.73 INFO ==> Stopping RabbitMQ... rasa-production_1 | 2020-01-29 14:58:12 ERROR rasa.core.agent - Could not load model due to Failed to find module 'customNLU'. rasa-production_1 | No module named 'customNLU'. rasa-production_1 | [2020-01-29 14:58:12 +0000] [1] [ERROR] Experienced exception while trying to serve rasa-production_1 | Traceback (most recent call last): rasa-production_1 | File "/build/lib/python3.6/site-packages/rasa/nlu/registry.py", line 154, in get_component_class rasa-production_1 | return class_from_module_path(component_name) rasa-production_1 | File "/build/lib/python3.6/site-packages/rasa/utils/common.py", line 195, in class_from_module_path rasa-production_1 | m = importlib.import_module(module_name) rasa-production_1 | File "/usr/local/lib/python3.6/importlib/__init__.py", line 126, in import_module rasa-production_1 | return _bootstrap._gcd_import(name[level:], package, level) rasa-production_1 | File "<frozen importlib._bootstrap>", line 994, in _gcd_import rasa-production_1 | File "<frozen importlib._bootstrap>", line 971, in _find_and_load rasa-production_1 | File "<frozen importlib._bootstrap>", line 953, in _find_and_load_unlocked rasa-production_1 | ModuleNotFoundError: No module named 'customNLU' rasa-production_1 | rasa-production_1 | During handling of the above exception, another exception occurred: rasa-pro…

Helm charts are used to create a kubernetes deployment. They still use docker images, so passing the same custom image in the helm chart as you were passing in docker-compose should work fine. In that case, you would update your values.yml like this: rasa: name: "<your-custom-image-name e.g. mydockerhubaccount/rasa" # tag of the Rasa Open Source image to use tag: "<your-custom-image-tag e.g. lexicon" Alternatively, this PR on the helm charts: Add support for extra volumes by tczekajlo · Pull Request #74 · RasaHQ/rasa-x-helm · GitHub made it possible to mount extra volumes on the containers in helm. Then you’d put something like this in values.yml: rasa: ... extraVolumeMounts: - name: lexicon mountPath: <path> I believe you’d need to use a configMap to create the volume to mount.

Rasa X Docker ModuleNotFoundError with a Custom Component

[Deprecated] Rasa X Community Edition

sureshvarman (suresh varman) February 11, 2020, 10:17am 3

+1 for this.

Basic question regarding custom connectors/channels and Kubernetes deployment

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Rasa X Docker ModuleNotFoundError with a Custom Component

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