Merge 6aaeffc into 73336bf

docs/core/actions.rst

@@ -6,16 +6,17 @@
 Actions
 =======
 
-.. contents::
-
 Actions are the things your bot runs in response to user input.
 There are three kinds of actions in Rasa Core:
 
- 1. **Default actions**: e.g. ``action_listen``, ``action_restart``,
-    ``action_default_fallback``
- 2. **Utterance actions**: start with ``utter_``, just send a message
+ 1. **Utterance actions**: start with ``utter_``, just send a message
     to the user
- 3. **Custom actions**: any other action, these actions can run arbitrary code
+ 2. **Custom actions**: any other action, these actions can run arbitrary code
+ 3. **Default actions**: e.g. ``action_listen``, ``action_restart``,
+    ``action_default_fallback``
+
+.. contents::
+   :local:
 
 Utterance Actions
 -----------------
@@ -66,7 +67,7 @@ other language and define your actions there - but we provide
 a small python SDK to make development there even easier.
 
 Custom Actions Written in Python
---------------------------------
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 For actions written in python, we have a convenient SDK which starts
 this action server for you.
@@ -144,6 +145,18 @@ There is an example of a ``SlotSet`` event
 :ref:`above <custom_action_example>`, and a full list of possible
 events in :ref:`Events <events>`.
 
+Execute Actions in Other Code
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Rasa Core will send an HTTP ``POST`` request to your server containing
+information on which action to run. Furthermore, this request will contain all
+information about the conversation.
+
+As a response to the action call from Core, you can modify the tracker,
+e.g. by setting slots and send responses back to the user.
+All of the modifications are done using events.
+There is a list of all possible event types in :ref:`events`.
+
 Default Actions
 ---------------
 
@@ -195,15 +208,3 @@ to the list of actions in your domain:
 
 Rasa Core will then call your action endpoint and treat it as every other
 custom action.
-
-Execute Actions in Other Code
------------------------------
-
-Rasa Core will send an HTTP ``POST`` request to your server containing
-information on which action to run. Furthermore, this request will contain all
-information about the conversation.
-
-As a response to the action call from Core, you can modify the tracker,
-e.g. by setting slots and send responses back to the user.
-All of the modifications are done using events.
-There is a list of all possible event types in :ref:`events`.

docs/core/domains.rst

@@ -11,6 +11,12 @@ It specifies the ``intents``, ``entities``, ``slots``, and ``actions``
 your bot should know about. Optionally, it can also include ``templates``
 for the things your bot can say.
 
+.. contents::
+   :local:
+
+
+An example of a Domain
+----------------------
 
 As an example, the ``DefaultDomain`` has the following yaml definition:
 
@@ -51,7 +57,7 @@ For example, an action could:
 * just about anything!
 
 Custom Actions and Slots
-^^^^^^^^^^^^^^^^^^^^^^^^
+------------------------
 
 To reference slots in your domain, you need to reference them by
 their **module path**. To reference custom actions, use their **name**.
@@ -76,7 +82,7 @@ see :ref:`custom-actions`).
 .. _utter_templates:
 
 Utterance templates
-^^^^^^^^^^^^^^^^^^^
+-------------------
 
 Utterance templates are messages the bot will send back to the user. There are
 two ways to use these templates:
@@ -270,7 +276,7 @@ multiple responses and Rasa will randomly pick one of them, e.g.:
     - text: "Hey, {name}. How is your day going?"
 
 Ignoring entities for certain intents
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+-------------------------------------
 
 If you want all entities to be ignored for certain intents, you can
 add the ``use_entities: []`` parameter to the intent in your domain

docs/core/interactive-learning.rst

@@ -22,6 +22,8 @@ Some people call this `Software 2.0 <https://medium.com/@karpathy/software-2-0-a
     Rasa X provides a UI for interactive learning, and you can use any user conversation
     as a starting point. See `Annotate Conversations <https://rasa.com/docs/rasa-x/annotate-conversations/>`_ in the Rasa X docs.
 
+.. contents::
+   :local:
 
 Running Interactive Learning
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^

docs/core/slots.rst

@@ -7,6 +7,12 @@
 Slots
 =====
 
+.. contents::
+   :local:
+
+What are slots?
+---------------
+
 **Slots are your bot's memory.** They act as a key-value store
 which can be used to store information the user provided (e.g their home city)
 as well as information gathered about the outside world (e.g. the result of a

docs/nlu/choosing-a-pipeline.rst

@@ -10,6 +10,10 @@ Choosing a Pipeline
 Choosing an NLU pipeline allows you to customize your model and finetune
 it on your dataset.
 
+.. contents::
+   :local:
+
+
 The Short Answer
 ----------------
 
@@ -154,12 +158,12 @@ final context dictionary is used to persist the model's metadata.
 
 
 
-Returned Entities Object
-------------------------
-In the object returned after parsing there are two fields that show information
-about how the pipeline impacted the entities returned. The ``extractor`` field
-of an entity tells you which entity extractor found this particular entity.
-The ``processors`` field contains the name of components that altered this
+The "entity" object explained
+-----------------------------
+After parsing, the entity is returned as a dictionary.  There are two fields that show information
+about how the pipeline impacted the entities returned: the ``extractor`` field
+of an entity tells you which entity extractor found this particular entity, and
+the ``processors`` field contains the name of components that altered this
 specific entity.
 
 The use of synonyms can also cause the ``value`` field not match the ``text``

docs/nlu/language-support.rst

@@ -14,6 +14,9 @@ pipeline in :ref:`choosing-a-pipeline`.
 Other backends have some restrictions and support those languages
 which have pre-trained word vectors available.
 
+.. contents::
+   :local:
+
 
 Training a model in any language using the ``supervised_embeddings`` pipeline
 -----------------------------------------------------------------------------

docs/nlu/training-data-format.rst

@@ -6,12 +6,12 @@
 Training Data Format
 ====================
 
-Data Format
-~~~~~~~~~~~
-
 You can provide training data as Markdown or as JSON, as a single file or as a directory containing multiple files.
 Note that Markdown is usually easier to work with.
 
+.. contents::
+   :local:
+
 
 Markdown Format
 ---------------