notice
This is unreleased documentation for Rasa Documentation Main/Unreleased version.
For the latest released documentation, see the latest version (3.x).
Rasa HTTP API
You can use the HTTP API to interact with a running Rasa server. With the API, you can train models, send messages, run tests, and more.
Looking for API endpoints?
Check out the API Spec for all of the available endpoints as well as their request and response formats.
Enabling the HTTP API
By default, running a Rasa server does not enable the API endpoints. Interactions
with the bot can happen over the exposed webhooks/<channel>/webhook endpoints.
To enable the API for direct interaction with conversation trackers and other
bot endpoints, add the --enable-api parameter to your run command:
Note that you start the server with an NLU-only model, not all the available endpoints can be called. Some endpoints will return a 409 status code, as a trained dialogue model is needed to process the request.
caution
Make sure to secure your server, either by restricting access to the server (e.g. using firewalls), or by enabling an authentication method. See Security Considerations.
By default, the HTTP server runs as a single process. You can change the number
of worker processes using the SANIC_WORKERS environment variable. It is
recommended that you set the number of workers to the number of available CPU cores
(check out the
Sanic docs
for more details). This will only work in combination with the
RedisLockStore (see Lock Stores.
caution
The SocketIO channel does not support multiple worker processes.
Security Considerations
We recommend that you don't expose the Rasa Server to the outside world directly, but rather connect to it via e.g. Nginx.
Nevertheless, there are two authentication methods built in:
Token Based Auth
To use a plaintext token to secure your server, specify the token in the argument --auth-token thisismysecret when starting
the server:
You can also use environment variable AUTH_TOKEN to set the auth token:
Security best practice
We recommend that you use environment variables to store and share sensitive information such as tokens and secrets when deploying Rasa as Docker container as they will not be stored in your shell history.
Any clients sending requests to the server must pass the token as a query parameter, or the request will be rejected. For example, to fetch a tracker from the server:
JWT Based Auth
To use JWT based authentication, specify the JWT secret in the argument --jwt-secret thisismysecret
on startup of the server:
You can also use environment variable JWT_SECRET to set the JWT secret:
Security best practice
We recommend that you use environment variables to store and share sensitive information such as tokens and secrets when deploying Rasa as Docker container as they will not be stored in your shell history.
If you want to sign a JWT token with asymmetric algorithms, you can specify the JWT private key to the --jwt-private-key
CLI argument. You must pass the public key to the --jwt-secret argument, and also specify the algorithm to the
--jwt-method argument:
You can also use environment variables to configure JWT:
Security best practice
We recommend that you use environment variables to store and share sensitive information such as tokens and secrets when deploying Rasa as Docker container as they will not be stored in your shell history.
Client requests to the server will need to contain a valid JWT token in
the Authorization header that is signed using this secret
and the HS256 algorithm e.g.
The token's payload must contain an object under the user key,
which in turn must contain the username and role attributes.
The following is an example payload for a JWT token:
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 payload's username property.
To create and encode the token, you can use tools such as the JWT Debugger, or a Python module such as PyJWT.