Warning: This document is for an old version of Rasa Core. The latest version is 0.8.2.

Rasa Core as a HTTP server

Note

Before you can use the server, you need to define a domain, create training data, and train a model. You can then use the trained model for remote code execution! See A Quick Tour (no ML) for an introduction.

Warning

The HTTP API is still experimental and we’d appreciate your feedback (e.g. via Gitter).

The HTTP api exists to make it easy for non-python projects to use Rasa Core.

Overview

The general idea is to run the actions within your code (arbitrary language), instead of python. To do this, Rasa Core will startup a web server where you need to pass the user messages to. Rasa Core on the other side will tell you which actions you need to run. After running these actions, you need to notify the framework that you executed them, and tell the model about any update of the internal dialogue state for that user. All of these interactions are done using a HTTP REST interface.

Running the server

You can run a simple http server that handles requests using your models with

$ python -m rasa_core.server -d examples/babi/models/policy/current -u examples/babi/models/nlu/current_py2 -o out.log

The different parameters are:

  • -d, which is the path to the Rasa Core model.
  • -u, which is the path to the Rasa NLU model.
  • -o, which is the path to the log file.

Endpoints

POST /conversation/<cid>/parse

You must POST data in this format '{"query":"<your text to parse>"}', you can do this with

$ curl -XPOST localhost:5005/parse -d '{"query":"hello there"}'

POST /conversation/<cid>/continue

You can post your training data to this endpoint to train a new model. This request will wait for the server answer: either the model was trained successfully or the training errored. If you want to name your model to be able to use it during parse requests later on, you should pass the name /train?name=my_model. Any parameter passed with the query string will be treated as a configuration parameter of the model, hence you can change all the configuration values listed in the configuration section by passing in their name and the adjusted value.

$ curl -XPOST localhost:5000/train -d @data/examples/rasa/demo-rasa.json

GET /version

This will return the current version of the Rasa NLU instance.

$ curl localhost:5005/version | python -mjson.tool
{
  "version" : "0.7.2"
}

Events and Action Execution

Instead of writing the actions in python code, you can use the HTTP API to write the code that should be run in an arbitrary language.