启动
在上述所有都训练完成后,需要启动的内容包括:
bert classifier (通过bert-as-service),这个可以用macanv重新封装过的
bert ner(通过bert-as-service),这个也是用macanv的
rasa actions,用来处理自定义动作
rasa ,这个是所有处理的入口,rasa本身提供http的接口
官方的介绍是这样的:
rasa http
Rasa启动后的提示,包括了可以调用的各个HTTP请求
/conversations/<conversation_id>/messages POST add_message
/conversations/<conversation_id>/tracker/events POST append_events
/webhooks/rest GET custom_webhook_RestInput.health
/webhooks/rest/webhook POST custom_webhook_RestInput.receive
/model/test/intents POST evaluate_intents
/model/test/stories POST evaluate_stories
/conversations/<conversation_id>/execute POST execute_action
/domain GET get_domain
/ GET hello
/model PUT load_model
/model/parse POST parse
/conversations/<conversation_id>/predict POST predict
/conversations/<conversation_id>/tracker/events PUT replace_events
/conversations/<conversation_id>/story GET retrieve_story
/conversations/<conversation_id>/tracker GET retrieve_tracker
/status GET status
/model/predict POST tracker_predict
/model/train POST train
/conversations/<conversation_id>/trigger_intent POST trigger_intent
/model DELETE unload_model
/version GET version
我们主要用到的入口就是/webhooks/rest/webhook,默认的端口是5005
HTTP请求的调用格式:
headers = {'Content-Type':'application/json'} payload = { "sender": "whatisyourname", "message": "whateveryouwanttosendtoyourrobot" } resp = >requests.post(url='http://localhost:5005/webhooks/rest/webhook',json=payload,headers=headers)