As you can see below, I used mitie and jieba to deal with a Chinese bot. It works fine with rasa. My question is about how to migrate it to Rasa X. With docker-installation of rasa X, I uploaded my pre-trained model. However, there are a few things I don’t know how to handle and I couldn’t find the solution in Doc or forum. Need help here.
Rasa X contains rasa inside, if I can use rasa inside of rasa X to train my Chinese model, how to install jieba and mitie with pip as I’ve done with rasa. I think the default installation doesn’t include those packages.
The other way to train my Chinese model is to use Rasa server outside of Rasa X. In this case, how should I connect the sperate Rasa server with the Rasa X server, if it’s possible. Does rasa X support this kind of connection?
My app also has a knowledge graph engine Grakn included, which is another service. With Rasa X, should I install Grakn with Rasa X server together or separately? Right now, my setting is to install rasa and Grakn on the same EC2 instance and the test run works just fine. With the migration, I don’t know which is the best way to handle these three services: Rasa, Rasa X and Grakn.
If it’s possible to connect Rasa X with existing Rasa and Grakn, how to write the endpoints.yml?
# Configuration for Rasa NLU. # https://rasa.com/docs/rasa/nlu/components/ language: "zh" pipeline: - name: "MitieNLP" model: "data/total_word_feature_extractor_zh.dat" - name: "JiebaTokenizer" dictionary_path: "data/jieba_userdict_zh.txt" - name: "MitieEntityExtractor" - name: "EntitySynonymMapper" - name: "MitieFeaturizer" - name: "SklearnIntentClassifier" # Configuration for Rasa Core. # https://rasa.com/docs/rasa/core/policies/ policies: - name: "KerasPolicy" batch_size: 50 epochs: 200 max_training_samples: 300 - name: "MappingPolicy" - name: "MemoizationPolicy" max_history: 5 - name: "FallbackPolicy" nlu_threshold: 0.3 ambiguity_threshold: 0.1 core_threshold: 0.3 fallback_action_name: 'action_default_fallback' - name: "FormPolicy"
My last question is related to uploading the trained model to Rasa X:
- After uploading model with curl, and active it, NO story/ synonym/ lookup show up. I’m not sure what kind of information will be included in the model. In the case of rasa, the folder structure is there, and rasa is easy to find the needed information. I decompose the file like ‘20200213-102926.tar.gz’, and there’re nlu/core/fingerprint.yml and I couldn’t find nlu.md or story.md . I can upload nlu and story through UI if that’s necessay, but those pre-defined synonyms in nlu do not show up in synonym page. Do I have to add them one by one through the “+” button?
Thanks for your time and help.