First of all, we found Dialogflow to be super easy to use. Almost everything is available in the user interface and you can create a bot without writing even a single line of code. Dialogflow provides everything from Entities, Intent, Training, Analytics, History to Integrations. They are available in the user interface. It is like a full-fledged ready to use service.
In contrast, you will have to build things up on top of Rasa. Also, it requires python development for customizing the bot.
Projects providing UI in Rasa
Dialogflow meet everyone’s demand and it is more generalized. In Rasa, you can customize the bot and it requires python development. Free and paid plans are available in both.
How to migrate from Dialogflow to Rasa?
Migrating from Dialogflow to Rasa is easy. Dialogflow provides a way to export the agent in zip files. You can then train Rasa NLU using the same downloaded data. Then modify the API URL to point to Rasa NLU server.
Detailed instructions are available here.
We wanted more control over customization so went ahead with Rasa for building our custom bots such as Liz. For basic bots and customers who are already using Dialogflow, we added support for easy dialogflow integration.
How do you rate Dialogflow vs Rasa and why? Let us know in the comments below, we would love to hear them.
This article was originally posted here.