These docs are for version 1.x of Rasa Open Source.

## User Guide

- [Installation](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/installation/)
- [Tutorial: Rasa Basics](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/rasa-tutorial/)
- [Tutorial: Building Assistants](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/building-assistants/)
- [Command Line Interface](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/command-line-interface/)
- [Architecture](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/architecture/)
- [Messaging and Voice Channels](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/messaging-and-voice-channels/)
- [Testing Your Assistant](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/testing-your-assistant/)
- [Setting up CI/CD](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/setting-up-ci-cd/)
- [Validate Data](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/validate-files/)
- [Configuring the HTTP API](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/configuring-http-api/)
- [Deploying Your Rasa Assistant](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/how-to-deploy/)
- [Cloud Storage](https://legacy-docs-v1.rasa.com/1.10.20/user-guide/cloud-storage/)

## NLU

- [About](https://legacy-docs-v1.rasa.com/1.10.20/nlu/about/)
- [Using NLU Only](https://legacy-docs-v1.rasa.com/1.10.20/nlu/using-nlu-only/)
- [Training Data Format](https://legacy-docs-v1.rasa.com/1.10.20/nlu/training-data-format/)
- [Language Support](https://legacy-docs-v1.rasa.com/1.10.20/nlu/language-support/)
- [Choosing a Pipeline](https://legacy-docs-v1.rasa.com/1.10.20/nlu/choosing-a-pipeline/)
- [Components](https://legacy-docs-v1.rasa.com/1.10.20/nlu/components/)
- [Entity Extraction](https://legacy-docs-v1.rasa.com/1.10.20/nlu/entity-extraction/)

## Core

- [About](https://legacy-docs-v1.rasa.com/1.10.20/core/about/)
- [Stories](https://legacy-docs-v1.rasa.com/1.10.20/core/stories/)
- [Domains](https://legacy-docs-v1.rasa.com/1.10.20/core/domains/)
- [Responses](https://legacy-docs-v1.rasa.com/1.10.20/core/responses/)
- [Actions](https://legacy-docs-v1.rasa.com/1.10.20/core/actions/)
- [Reminders and External Events](https://legacy-docs-v1.rasa.com/1.10.20/core/reminders-and-external-events/)
- [Policies](https://legacy-docs-v1.rasa.com/1.10.20/core/policies/)
- [Slots](https://legacy-docs-v1.rasa.com/1.10.20/core/slots/)
- [Forms](https://legacy-docs-v1.rasa.com/1.10.20/core/forms/)
- [Retrieval Actions](https://legacy-docs-v1.rasa.com/1.10.20/core/retrieval-actions/)
- [Interactive Learning](https://legacy-docs-v1.rasa.com/1.10.20/core/interactive-learning/)
- [Fallback Actions](https://legacy-docs-v1.rasa.com/1.10.20/core/fallback-actions/)
- [Knowledge Base Actions](https://legacy-docs-v1.rasa.com/1.10.20/core/knowledge-bases/)

## Conversation Design

- [Dialogue Elements](https://legacy-docs-v1.rasa.com/1.10.20/dialogue-elements/dialogue-elements/)
- [Small Talk](https://legacy-docs-v1.rasa.com/1.10.20/dialogue-elements/small-talk/)
- [Completing Tasks](https://legacy-docs-v1.rasa.com/1.10.20/dialogue-elements/completing-tasks/)
- [Guiding Users](https://legacy-docs-v1.rasa.com/1.10.20/dialogue-elements/guiding-users/)

## API Reference

- [Action Server](https://legacy-docs-v1.rasa.com/1.10.20/api/action-server/)
- [HTTP API](https://legacy-docs-v1.rasa.com/1.10.20/api/http-api/)
- [Jupyter Notebooks](https://legacy-docs-v1.rasa.com/1.10.20/api/jupyter-notebooks/)
- [Agent](https://legacy-docs-v1.rasa.com/1.10.20/api/agent/)
- [Custom NLU Components](https://legacy-docs-v1.rasa.com/1.10.20/api/custom-nlu-components/)
- [Rasa SDK](https://legacy-docs-v1.rasa.com/1.10.20/api/rasa-sdk/)
- [Events](https://legacy-docs-v1.rasa.com/1.10.20/api/events/)
- [Tracker](https://legacy-docs-v1.rasa.com/1.10.20/api/tracker/)
- [Tracker Stores](https://legacy-docs-v1.rasa.com/1.10.20/api/tracker-stores/#)
- [Event Brokers](https://legacy-docs-v1.rasa.com/1.10.20/api/event-brokers/)
- [Lock Stores](https://legacy-docs-v1.rasa.com/1.10.20/api/lock-stores/)
- [Training Data Importers](https://legacy-docs-v1.rasa.com/1.10.20/api/training-data-importers/)
- [Featurization of Conversations](https://legacy-docs-v1.rasa.com/1.10.20/api/core-featurization/)
- [TensorFlow Configuration](https://legacy-docs-v1.rasa.com/1.10.20/api/tensorflow_usage/)
- [Migration Guide](https://legacy-docs-v1.rasa.com/1.10.20/migration-guide/)
- [Rasa Open Source Change Log](https://legacy-docs-v1.rasa.com/1.10.20/changelog/)

## Migrate from (beta)

- [Dialogflow](https://legacy-docs-v1.rasa.com/1.10.20/migrate-from/google-dialogflow-to-rasa/)
- [Wit.ai](https://legacy-docs-v1.rasa.com/1.10.20/migrate-from/facebook-wit-ai-to-rasa/)
- [LUIS](https://legacy-docs-v1.rasa.com/1.10.20/migrate-from/microsoft-luis-to-rasa/)
- [IBM Watson](https://legacy-docs-v1.rasa.com/1.10.20/migrate-from/ibm-watson-to-rasa/)

## Reference

- [Glossary](https://legacy-docs-v1.rasa.com/1.10.20/glossary/)

## Versions

viewing: 1.10.20

## 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.

### 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.:

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

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

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

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

``` 
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](https://redis.io/). 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.:

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

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

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

### 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`

```
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.:

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

### DynamoTrackerStore

**Description**  
`DynamoTrackerStore` can be used to store the conversation history in [DynamoDB](https://aws.amazon.com/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>
```

## 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`.