Tracker Stores

Tracker Stores

All conversations are stored within a tracker store. Rasa Open Source provides implementations for different store types out of the box. If you want to use another store, you can also build a custom tracker store by extending the TrackerStore class.

Contents

InMemoryTrackerStore (default)

Description

InMemoryTrackerStore is the default tracker store. It is used if no other tracker store is configured. It stores the conversation history in memory.

Note

As this store keeps all history in memory, the entire history is lost if you restart the Rasa server.

Configuration

To use the InMemoryTrackerStore no configuration is needed.

SQLTrackerStore

Description

SQLTrackerStore can be used to store the conversation history in an SQL database. Storing your trackers this way allows you to query the event database by sender_id, timestamp, action name, intent name and typename.

Configuration

To set up Rasa Open Source with SQL the following steps are required:

  1. Add required configuration to your endpoints.yml:
   tracker_store:
       type: SQL
       dialect: "postgresql"  # the dialect used to interact with the db
       url: ""  # (optional) host of the sql db, e.g. "localhost"
       db: "rasa"  # path to your db
       username:  # username used for authentication
       password:  # password used for authentication
       query: # optional dictionary to be added as a query string to the connection URL
         driver: my-driver
  1. To start the Rasa server using your SQL backend, add the --endpoints flag, e.g.:
   rasa run -m models --endpoints endpoints.yml
  1. If deploying your model in Docker Compose, add the service to your docker-compose.yml:
   postgres:
     image: postgres:latest

Parameters

Officially Compatible Databases

RedisTrackerStore

Description

RedisTrackerStore can be used to store the conversation history in Redis. Redis is a fast in-memory key-value store which can optionally also persist data.

Configuration

To set up Rasa Open Source with Redis the following steps are required:

  1. Start your Redis instance

  2. Add required configuration to your endpoints.yml:

   tracker_store:
       type: redis
       url: <url of the redis instance, e.g. localhost>
       port: <port of your redis instance, usually 6379>
       db: <number of your database within redis, e.g. 0>
       password: <password used for authentication>
       use_ssl: <whether or not the communication is encrypted, default `false`>

Parameters

MongoTrackerStore

Description

MongoTrackerStore can be used to store the conversation history in Mongo. MongoDB is a free and open-source cross-platform document-oriented NoSQL database.

Configuration

  1. Start your MongoDB instance.

  2. Add required configuration to your endpoints.yml

   tracker_store:
       type: mongod
       url: <url to your mongo instance, e.g. mongodb://localhost:27017>
       db: <name of the db within your mongo instance, e.g. rasa>
       username: <username used for authentication>
       password: <password used for authentication>
       auth_source: <database name associated with the user’s credentials>

Parameters

DynamoTrackerStore

Description

DynamoTrackerStore can be used to store the conversation history in DynamoDB. DynamoDB is a hosted NoSQL database offered by Amazon Web Services (AWS).

Configuration

  1. Start your DynamoDB instance.

  2. Add required configuration to your endpoints.yml:

   tracker_store:
       type: dynamo
       tablename: <name of the table to create, e.g. rasa>
       region: <name of the region associated with the client>

Parameters

Custom Tracker Store

Description

If you require a tracker store which is not available out of the box, you can implement your own. This is done by extending the base class TrackerStore.

Steps

  1. Extend the TrackerStore base class. Note that your constructor has to provide a parameter url.

  2. In your endpoints.yml put in the module path to your custom tracker store and the parameters you require:

   tracker_store:
     type: path.to.your.module.Class
     url: localhost
     a_parameter: a value
     another_parameter: another value
  1. If you are deploying in Docker Compose, you have two options to add this store to Rasa Open Source:

Make sure to add the corresponding service as well. For example, mounting it as a volume would look like so:

rasa:
  <existing rasa service configuration>
  volumes:
    - <existing volume mappings, if there are any>
    - ./path/to/your/module.py:/app/path/to/your/module.py
custom-tracker-store:
  image: custom-image:tag

👋 I can help you get started with Rasa and answer your technical questions.