Hi,I am new to rasa. And I train a model use the config as follows
language: “zh” pipeline:
- name: “JiebaTokenizer” dictionary_path: “userdict/”
- name: “RegexFeaturizer”
- name: “CRFEntityExtractor”
- name: “EntitySynonymMapper”
- name: “CountVectorsFeaturizer”
- name: “EmbeddingIntentClassifier”
In my case ,I put about 100M txt file in the dictionary_path which contains large number of movie_name and star_name.So every time I restart the server or fetch a new model from a server by url I set in endpoints.yml, rasa will cost about 10 second to response for the next request.What is worse is that I deploy my model with docker for about 30 containers .So I will have 30 very slow request each time I train a new model . my user_dict for jieba will change very offen,because I have to add some new move_name and star_name .So I have to train and fetch a new model very offen.Anyone can help me about this.