How can one train the NLU in real-time / live without having to restart the NLU server? So far I’m training the NLU using the following command: python -m rasa_nlu.train -c ./nlu_config.yml --data ./data/nlu_data -o models/nlu --fixed_model_name nlu --project current --verbose In the nlu_data directory I have a few training files in .md and .json format. As I’m testing the bot, I often run into bad intent identification / ner extraction issues, which I’m trying to solve by adding more samples to the training data. However, it seems like I always have to restart the NLU server to reflect the new model. Since the new model is saved under the same name (due to --fixed_model_name), I thought it may be possible to autoreload the model while the NLU server is running. I know there’s online / interactive training available for Rasa Core, but I’m interested in quickly testing and updating the NLU model by training it on a new batch of samples. Any ideas or solutions? Feel like this should be fairly simple to achieve, but can’t figure it out. Thanks a lot already!

Training nlu without restarting

huberrom (Romain Huber) December 27, 2018, 10:31am 2

Did you find a solution to this issue ? I wanted to ask the exact same question but since you already ask, I’ll not create a new topic.

If anyone has a solution for this, it would be gladly welcome.

1 Like

Train NLU server without restarting

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