Currently we have a feature in our web application that user rasa nlu from rasa nlu 0.9. Rasa NLU is used for search rather than chat. I was trying to see if there are similar libraries in rasa 3.* Since rasa 1.* it appears that we should have converted to using http api or nlu only server. What is the best way to upgrade our current features to rasa 3.* version. Is there a way to still use python api?
Hi Ravi - yes you can still use the python API to build apps. Possibly a good way to discover the relevant high level functions is to look at how the cli commands are implemented
Thanks Alan. I have one more question: We were json format for generating our training data. I don’t see a mention of json formats in documentation since 2.*. Is Json for training data still supported? or do we need to create a yaml file?
yes, we’ve deprecated the json format in favour of yaml.
Thanks Alan. I was able to upgrade and app is working as intended. One more question: I see that model file is like over 100GB in size is there a way to reduce this?
wow, that is huge! can you try unzipping the model folder and seeing which files are so big?
My bad the size was 170 MB. The file that is big: DIETClassifier.tf_model.data-00000-of-00001
ok yeah that’s more reasonable. If you want to get a smaller model, you can play around with the DIET hyperparameters. We have a bunch of great resources on youtube like the algorithm whiteboard , which can help you understand how the model works and make informed decisions