Configuring the HTTP API

Using Rasa’s HTTP API

Note
The instructions below are relevant for configuring how a model is run within a Docker container or for testing the HTTP API locally. If you want to deploy your assistant to users, see Deploying Your Rasa Assistant.

You can run a simple HTTP server that handles requests using your trained Rasa model with:

rasa run -m models --enable-api --log-file out.log

All the endpoints this API exposes are documented in HTTP API.

The different parameters are:

• -m: the path to the folder containing your Rasa model,
• --enable-api: enable this additional API, and
• --log-file: the path to the log file.

Rasa can load your model in three different ways:

1. Fetch the model from a server (see Fetching Models from a Server), or
2. Fetch the model from a remote storage (see Cloud Storage).
3. Load the model specified via -m from your local storage system,

Rasa tries to load a model in the above mentioned order, i.e. it only tries to load your model from your local storage system if no model server and no remote storage were configured.

Fetching Models from a Server

You can configure the HTTP server to fetch models from another URL:

rasa run --enable-api --log-file out.log --endpoints my_endpoints.yml

The model server is specified in the endpoint configuration (my_endpoints.yml), where you specify the server URL Rasa regularly queries for zipped Rasa models:

models:
  url: http://my-server.com/models/default@latest
  wait_time_between_pulls: 10   # [optional](default: 100)

Fetching Models from a Remote Storage

You can also configure the Rasa server to fetch your model from a remote storage:

rasa run -m 20190506-100418.tar.gz --enable-api --log-file out.log --remote-storage aws

The model will be downloaded and stored in a temporary directory on your local storage system. For more information see Cloud Storage.

Configuring SSL / HTTPS

By default the Rasa server is using HTTP for its communication. To secure the communication with SSL, you need to provide a valid certificate and the corresponding private key file.

You can specify these files as part of the rasa run command:

rasa run --ssl-certificate myssl.crt --ssl-keyfile myssl.key

If you encrypted your keyfile with a password during creation, you need to add this password to the command:

rasa run --ssl-certificate myssl.crt --ssl-keyfile myssl.key --ssl-password mypassword

Security Considerations

We recommend to not expose the Rasa Server to the outside world, but rather connect to it from your backend over a private connection (e.g. between docker containers).

Nevertheless, there are two authentication methods built in:

Token Based Auth:
Pass in the token using --auth-token thisismysecret when starting the server:

rasa run \
    -m models \
    --enable-api \
    --log-file out.log \
    --auth-token thisismysecret

Your requests should pass the token, in our case thisismysecret, as a parameter:

curl -XGET localhost:5005/conversations/default/tracker?token=thisismysecret

JWT Based Auth:
Enable JWT based authentication using --jwt-secret thisismysecret. Requests to the server need to contain a valid JWT token in the Authorization header that is signed using this secret and the HS256 algorithm.

The user must have username and role attributes. If the role is admin, all endpoints are accessible. If the role is user, endpoints with a sender_id parameter are only accessible if the sender_id matches the user’s username.

rasa run \
    -m models \
    --enable-api \
    --log-file out.log \
    --jwt-secret thisismysecret

Your requests should have set a proper JWT header:

"Authorization": "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiIxMjM0NTY3ODkwIiwibmFtZSI6IkpvaG4gRG9lIiwiYWx0IjoxNTE2MjM5MDIyfQ.qdrr2_a7Sd80gmCWjnDomOGl8eZFVfKXA6jhncgRn-I"

Endpoint Configuration

To connect Rasa to other endpoints, you can specify an endpoint configuration within a YAML file.
Then run Rasa with the flag --endpoints <path to endpoint configuration.yml>.

For example:

rasa run \
    --m <Rasa model> \
    --endpoints <path to endpoint configuration>.yml

Note
You can use environment variables within configuration files by specifying them with ${name of environment variable}. These placeholders are then replaced by the value of the environment variable.