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

## User Guide

- [Installation](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/installation/)
- [Tutorial: Rasa Basics](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/rasa-tutorial/)
- [Tutorial: Building Assistants](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/building-assistants/)
- [Command Line Interface](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/command-line-interface/)
- [Architecture](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/architecture/)
- [Messaging and Voice Channels](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/messaging-and-voice-channels/)
- [Testing Your Assistant](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/testing-your-assistant/)
- [Setting up CI/CD](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/setting-up-ci-cd/)
- [Validate Data](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/validate-files/)
- [Configuring the HTTP API](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/configuring-http-api/)
- [Deploying Your Rasa Assistant](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/how-to-deploy/)
- [Cloud Storage](https://legacy-docs-v1.rasa.com/1.10.6/user-guide/cloud-storage/)

## NLU

- [About](https://legacy-docs-v1.rasa.com/1.10.6/nlu/about/)
- [Using NLU Only](https://legacy-docs-v1.rasa.com/1.10.6/nlu/using-nlu-only/)
- [Training Data Format](https://legacy-docs-v1.rasa.com/1.10.6/nlu/training-data-format/)
- [Language Support](https://legacy-docs-v1.rasa.com/1.10.6/nlu/language-support/)
- [Choosing a Pipeline](https://legacy-docs-v1.rasa.com/1.10.6/nlu/choosing-a-pipeline/)
- [Components](https://legacy-docs-v1.rasa.com/1.10.6/nlu/components/)
- [Entity Extraction](https://legacy-docs-v1.rasa.com/1.10.6/nlu/entity-extraction/)

## Core

- [About](https://legacy-docs-v1.rasa.com/1.10.6/core/about/)
- [Stories](https://legacy-docs-v1.rasa.com/1.10.6/core/stories/)
- [Domains](https://legacy-docs-v1.rasa.com/1.10.6/core/domains/)
- [Responses](https://legacy-docs-v1.rasa.com/1.10.6/core/responses/)
- [Actions](https://legacy-docs-v1.rasa.com/1.10.6/core/actions/)
- [Reminders and External Events](https://legacy-docs-v1.rasa.com/1.10.6/core/reminders-and-external-events/)
- [Policies](https://legacy-docs-v1.rasa.com/1.10.6/core/policies/)
- [Slots](https://legacy-docs-v1.rasa.com/1.10.6/core/slots/)
- [Forms](https://legacy-docs-v1.rasa.com/1.10.6/core/forms/)
- [Retrieval Actions](https://legacy-docs-v1.rasa.com/1.10.6/core/retrieval-actions/)
- [Interactive Learning](https://legacy-docs-v1.rasa.com/1.10.6/core/interactive-learning/)
- [Fallback Actions](https://legacy-docs-v1.rasa.com/1.10.6/core/fallback-actions/)
- [Knowledge Base Actions](https://legacy-docs-v1.rasa.com/1.10.6/core/knowledge-bases/)

## Conversation Design

- [Dialogue Elements](https://legacy-docs-v1.rasa.com/1.10.6/dialogue-elements/dialogue-elements/)
- [Small Talk](https://legacy-docs-v1.rasa.com/1.10.6/dialogue-elements/small-talk/)
- [Completing Tasks](https://legacy-docs-v1.rasa.com/1.10.6/dialogue-elements/completing-tasks/)
- [Guiding Users](https://legacy-docs-v1.rasa.com/1.10.6/dialogue-elements/guiding-users/)

## API Reference

- [Action Server](https://legacy-docs-v1.rasa.com/1.10.6/api/action-server/)
- [HTTP API](https://legacy-docs-v1.rasa.com/1.10.6/api/http-api/)
- [Jupyter Notebooks](https://legacy-docs-v1.rasa.com/1.10.6/api/jupyter-notebooks/)
- [Agent](https://legacy-docs-v1.rasa.com/1.10.6/api/agent/)
- [Custom NLU Components](https://legacy-docs-v1.rasa.com/1.10.6/api/custom-nlu-components/)
- [Rasa SDK](https://legacy-docs-v1.rasa.com/1.10.6/api/rasa-sdk/)
- [Events](https://legacy-docs-v1.rasa.com/1.10.6/api/events/)
- [Tracker](https://legacy-docs-v1.rasa.com/1.10.6/api/tracker/)
- [Tracker Stores](https://legacy-docs-v1.rasa.com/1.10.6/api/tracker-stores/)
- [Event Brokers](https://legacy-docs-v1.rasa.com/1.10.6/api/event-brokers/)
- [Lock Stores](https://legacy-docs-v1.rasa.com/1.10.6/api/lock-stores/)
- [Training Data Importers](https://legacy-docs-v1.rasa.com/1.10.6/api/training-data-importers/)
- [Featurization of Conversations](https://legacy-docs-v1.rasa.com/1.10.6/api/core-featurization/#)
- [TensorFlow Configuration](https://legacy-docs-v1.rasa.com/1.10.6/api/tensorflow_usage/)
- [Migration Guide](https://legacy-docs-v1.rasa.com/1.10.6/migration-guide/)
- [Rasa Open Source Change Log](https://legacy-docs-v1.rasa.com/1.10.6/changelog/)

## Migrate from (beta)

- [Dialogflow](https://legacy-docs-v1.rasa.com/1.10.6/migrate-from/google-dialogflow-to-rasa/)
- [Wit.ai](https://legacy-docs-v1.rasa.com/1.10.6/migrate-from/facebook-wit-ai-to-rasa/)
- [LUIS](https://legacy-docs-v1.rasa.com/1.10.6/migrate-from/microsoft-luis-to-rasa/)
- [IBM Watson](https://legacy-docs-v1.rasa.com/1.10.6/migrate-from/ibm-watson-to-rasa/)

## Reference

- [Glossary](https://legacy-docs-v1.rasa.com/1.10.6/glossary/)

## Versions

viewing: 1.10.6

## Featurization of Conversations

In order to apply machine learning algorithms to conversational AI, we need to build up vector representations of conversations.

Each story corresponds to a tracker which consists of the states of the conversation just before each action was taken.

### State Featurizers

Every event in a tracker’s history creates a new state (e.g., running a bot action, receiving a user message, setting slots). Featurizing a single state of the tracker has a couple of steps:

1. **Tracker provides a bag of active features**:
   - features indicating intents and entities.
   - features indicating which slots are currently defined.
   - features indicating the results of any API calls stored in slots.
   - features indicating what the last action was.

2. **Convert all the features into numeric vectors**:
> We use the `X, y` notation that’s common for supervised learning.
>
> The target labels correspond to actions taken by the bot.
>
> To convert the features into vector format, there are different featurizers available:
>
> - `BinarySingleStateFeaturizer` creates a binary one-hot encoding.
> - `LabelTokenizerSingleStateFeaturizer` creates a vector based on the feature label.

### Tracker Featurizers

It’s often useful to include a bit more history than just the current state when predicting an action. The `TrackerFeaturizer` iterates over tracker states and calls a `SingleStateFeaturizer` for each state. There are two different tracker featurizers:

1. **Full Dialogue** - creates numerical representation of stories.
2. **Max History** - creates an array of previous tracker states for each bot action or utterance.