For the team working on Rasa Open Source it is important to understand how the product is used. It allows us to properly prioritize our research efforts and feature development.
You will be notified about the telemetry reporting when running Rasa Open Source for the first time.
How to opt-out
You can opt out of telemetry reporting at any time by running the command:
or by defining
RASA_TELEMETRY_ENABLED=false as an environment variable.
If you want to enable reporting again, you can run:
Why do we use telemetry reporting?
Anonymous telemetry data allow us to prioritize our research efforts and feature development based on usage. We want to collect aggregated information on usage and reliability so that we can ensure a high-quality product.
So how will we use the reported telemetry data? Here are some examples of what we use the data for:
- We will be able to know which languages, pipelines and policies are used. This will enable us to direct our research efforts towards text and dialogue handling projects that will have the biggest impact for our users.
- We will be able to know data set sizes and general structure (e.g. the number of intents). This allows us to better test our software on different types of data sets and optimize the frameworks performance.
- We will be able to get more detail on the types of errors you are running into while building an assistant (e.g. initialization, training, etc.). This will let us improve the quality of our framework and better focus our time on solving more common, frustrating issues.
What about sensitive data?
Your sensitive data never leaves your machine. We:
- don't report any personal identifiable information
- don't report your training data
- don't report any messages your assistant receives or sends
Inspect what is reported
You can view all the telemetry information that is reported
by defining the environment variable
RASA_TELEMETRY_DEBUG=true, for example when running the train command:
When you set
RASA_TELEMETRY_DEBUG no information will be sent to any server,
instead it will be logged to the commandline as a json dump for you to inspect.
What do we report?
Rasa reports aggregated usage details, command invocations, performance measurements and errors. We use the telemetry data to better understand usage patterns. The reported data will directly allow us to better decide how to design future features and prioritize current work.
Specifically, we collect the following information for all telemetry events:
- Type of the reported event (e.g. Training Started)
- Rasa machine ID: This is generated with a UUID and stored in the global Rasa
~/.config/rasa/global.ymland sent as
- One-way hash of the current working directory or a hash of the git remote
- General OS level information (operating system, number of CPUs, number of GPUs and whether the command is run inside a CI)
- Current Rasa Open Source and Python version
Here is an example report that shows the data reported to Rasa after running
We cannot identify individual users from the dataset. It is anonymized and untraceable back to the user.