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.

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
    ```

2. To start the Rasa server using your SQL backend,
   add the `--endpoints` flag, e.g.:

```bash
    rasa run -m models --endpoints endpoints.yml
    ```

3. If deploying your model in Docker Compose, add the service to your `docker-compose.yml`:

```yaml
    postgres:
      image: postgres:latest
    ```

To route requests to the new service, make sure that the `url` in your `endpoints.yml`
references the service name:

```yaml
  tracker_store:
      type: SQL
      dialect: "postgresql"  # the dialect used to interact with the db
      url: "postgres"
      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

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`>
    ```

3. To start the Rasa server using your configured Redis instance,
   add the `--endpoints` flag, e.g.:

```bash
    rasa run -m models --endpoints endpoints.yml
    ```

4. If deploying your model in Docker Compose, add the service to your `docker-compose.yml`:

```yaml
    redis:
      image: redis:latest
    ```

To route requests to the new service, make sure that the `url` in your `endpoints.yml`
references the service name:

## MongoTrackerStore

Description

`MongoTrackerStore` can be used to store the conversation history in [Mongo](https://www.mongodb.com/). 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`:

```yaml
    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>
    ```

3. To start the Rasa server using your configured MongoDB instance,
   add the `--endpoints` flag, e.g.:

```bash
    rasa run -m models --endpoints endpoints.yml
    ```

4. If deploying your model in Docker Compose, add the service to your `docker-compose.yml`:

```yaml
    mongo:
      image: mongo
      environment:
        MONGO_INITDB_ROOT_USERNAME: rasa
        MONGO_INITDB_ROOT_PASSWORD: example
    mongo-express:  # this service is a MongoDB UI, and is optional
      image: mongo-express
      ports:
        - 8081:8081
      environment:
        ME_CONFIG_MONGODB_ADMINUSERNAME: rasa
        ME_CONFIG_MONGODB_ADMINPASSWORD: example
    ```

To route requests to this database, make sure to set the `url` in your `endpoints.yml` as the service name,
   and specify the user and password:

```yaml
  tracker_store:
      type: mongod
      url: mongodb://mongo: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>

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>
    ```

3. To start the Rasa server using your configured `DynamoDB` instance,
   add the `--endpoints` flag, e.g.:

```bash
    rasa run -m models --endpoints endpoints.yml
    ```

## 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:

```yaml
    tracker_store:
      type: path.to.your.module.Class
      url: localhost
      a_parameter: a value
      another_parameter: another value
    ```

3. If you are deploying in Docker Compose, you have two options to add this store to Rasa Open Source:

- extending the Rasa image to include the module
   - mounting the module as volume

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

```yaml
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

endpoints.yml:

tracker_store:
  type: path.to.your.module.Class
  url: custom-tracker-store
  a_parameter: a value
  another_parameter: another value