![]() It is recommended to use an automated CI/CD process to keep your action server up to date in a production environment. Once you have confirmed that the container works as it should, you can push the container image to a registry with docker push To test the container locally, you can then run the action server container with: See the Dockerfile for what is included in the action server image, If you haven’t made any changes to the action code, you can also use the public image on Dockerhub instead of building it yourself. You will need to have docker installed in order to build the action server image. Using the default set up, the handoff skill enables this kind of conversation with two bots: See the chatroom README for more details on channel-side configuration. This demo relies on this fork of chatroom to work, however you could implement similar behaviour in another channel and then use that instead. This bot includes a simple skill for handing off the conversation to another bot or a human. You can change any of these by modifying actions.py and the corresponding NLU data. It recognises the following vendors (for spending history): from typing import Any, Text, Dict, List from rasasdk import Action, Tracker from rasasdk.executor import CollectingDispatcher import csv import pandas as pd class ActionReadCSV (Action): def name (self) -> Text: return 'actioncsv' def run (self, dispatcher. It recognises the following payment amounts (besides actual currency amounts): Use the below code in the action.py file. It also has a limited ability to switch skills mid-transaction and then return to the transaction at hand. Answer a question about transfer charges.Check your earning or spending history (with a specific vendor or overall).Data/nlu/nlu.yml – contains NLU training dataĭata/nlu/rules.yml – contains rules training dataĭata/stories/stories*.yml – contains stories training dataĪctions.py – contains custom action/api codeĭomain.yml – the domain file, including bot response templatesĬonfig.yml – training configurations for the NLU pipeline and policy ensemble
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