So, when I use spacy or bert configurations, the rasa intent classification works perfectly fine in command line [ie rasa shell]. However, when I publish the model together with rasa server to a url and when I call the model/parse endpoint, I receive the original text that I sent as payload. What is crazy is that when I use the default config.yml … aka I don’t use spacy and I don’t use bert … the url endpoint returns the expected response. Here are my configs: SPACY… works in command line, but not in url language: en pipeline: - name: SpacyNLP - name: "SpacyTokenizer" - name: "SpacyFeaturizer" model: "en_core_web_md" - name: DIETClassifier epochs: 50 BERT… works in command line, but not in url: language: en pipeline: - name: HFTransformersNLP - name: LanguageModelTokenizer - name: LanguageModelFeaturizer model_name: "bert" model_weights: "rasa/LaBSE" - name: DIETClassifier epochs: 50 DEFAULT… works in command line and in url: language: en pipeline: - name: WhitespaceTokenizer - name: RegexFeaturizer case_sensitive: False - name: LexicalSyntacticFeaturizer - name: CountVectorsFeaturizer analyzer: word - name: DIETClassifier epochs: 50

Is the response code still 200 with spacy and bert?

What version are you on? I tried to reproduce this on version 2.1.3, but the parse endpoint returns parse info as expected for both spacy and default models (using the configs you posted)

I would be super happy to send you a zip file which includes Rasa’s web endpoints website using my trained model so you can check it out. Or… if you want to test it for yourself … try this end point - I just published it with brand new trained model using Spacy: https://rasa-ella-50-spacy-bpslyfsgba-uc.a.run.app/model/parse I send this payload: { “text”: “test” } I receive this response: { "text": "\/test", "intent": { "name": "test", "confidence": 1.0 }, "intent_ranking": [ { "name": "test", "confidence": 1.0 } ], "entities": [] } Here is the config file contents: language: en pipeline: name: SpacyNLP name: “SpacyTokenizer” name: “SpacyFeaturizer” model: “en_core_web_lg” name: DIETClassifier epochs: 50 No domain yml contents - this is pure NLU/intent classification exercise. Using bert configuration does the same thing. Using your default settings works just fine. I tried to test this without the use of the end points, using your Python API… that just opened a brand new can of bug worms and issues with your product - I’ll be having other topics and github issues dedicated to that alone. WHAT A MESS

I’d be happy to provide the same model but with Bert training and url so you can experience it yourself.

Model/parse response is the same as the payload

Rasa Open Source

stv (Stefan Vantchev) January 6, 2021, 2:49am 3

Yes

Topic		Replies	Views
Api responses Rasa Masterclass	3	674	February 19, 2020
Custom Featurizer for finetuned BERT features based on SpaCy Rasa Open Source	19	4763	February 12, 2020
Null Response from "model/parse" endpoint Rasa Open Source	12	975	October 8, 2021
How Can we Pass the Generated Model to parse Url Rasa Open Source	1	431	August 14, 2018
Parse a message with the trained nlu model Rasa Open Source	1	3953	July 3, 2019

Model/parse response is the same as the payload

Related topics