diff --git a/docs/conversations.rst b/docs/conversations.rst index 86cd6b981..4564fc0c9 100644 --- a/docs/conversations.rst +++ b/docs/conversations.rst @@ -8,7 +8,7 @@ Statements ========== ChatterBot's statement objects represent either an input statement that the -chat bot has recieved from a user, or an output statement that the chat bot +chat bot has received from a user, or an output statement that the chat bot has returned based on some input. .. autoclass:: chatterbot.conversation.Statement @@ -63,7 +63,7 @@ ChatterBot uses :code:`Statement` objects to hold information about things that can be said. An important part of how a chat bot selects a response is based on it's ability to compare two statements to each other. There is a number of ways to do this, and ChatterBot -comes with a handfull of method built in for you to use. +comes with a handful of method built in for you to use. .. automodule:: chatterbot.comparisons :members: @@ -73,7 +73,7 @@ Use your own comparison function You can create your own comparison function and use it as long as the function takes two statements as parameters and returns a numeric value between 0 and 1. A 0 should represent the lowest possible -similarity and a 1 should represent the highest possibel similarity. +similarity and a 1 should represent the highest possible similarity. .. code-block:: python diff --git a/docs/django/index.rst b/docs/django/index.rst index c8655c5fc..bdcc19db5 100644 --- a/docs/django/index.rst +++ b/docs/django/index.rst @@ -41,7 +41,7 @@ Add `chatterbot.ext.django_chatterbot` to your `INSTALLED_APPS` API view -------- -If you need a ChatterBot API endpont you will want to add the following to your urls.py +If you need a ChatterBot API endpoint you will want to add the following to your urls.py .. code-block:: python diff --git a/docs/django/views.rst b/docs/django/views.rst index 976250c85..9ab3d7445 100644 --- a/docs/django/views.rst +++ b/docs/django/views.rst @@ -17,5 +17,5 @@ The endpoint expects a JSON request with the following data: .. note:: You will need to include ChatterBot's urls in your django url configuration - before you can make requests to these views. See the setup instructons for + before you can make requests to these views. See the setup instructions for more details. diff --git a/docs/filters/create_a_new_filter.rst b/docs/filters/create_a_new_filter.rst index efbe2e3aa..d7f230db9 100644 --- a/docs/filters/create_a_new_filter.rst +++ b/docs/filters/create_a_new_filter.rst @@ -3,7 +3,7 @@ How to create a new filter for ChatterBot ========================================= This is the basic outline of the code that your filter will need to follow. -Each filter shold inherit from ChatterBot's `Filter` class and implement a +Each filter should inherit from ChatterBot's `Filter` class and implement a method called `filter_selection`. Everything else that your filter does is up to you. diff --git a/docs/index.rst b/docs/index.rst index 1a29b9f1e..e4546d8aa 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -5,7 +5,7 @@ About ChatterBot ChatterBot is a Python library that makes it easy to generate automated responses to a user's input. ChatterBot uses a selection of machine learning -algorithms to produce different types of responces. This makes it easy for +algorithms to produce different types of responses. This makes it easy for developers to create chat bots and automate conversations with users. For more details about the ideas and concepts behind ChatterBot see the :ref:`process flow diagram `. diff --git a/docs/input/create-an-input-adapter.rst b/docs/input/create-an-input-adapter.rst index 2700f23d4..7a022c71c 100644 --- a/docs/input/create-an-input-adapter.rst +++ b/docs/input/create-an-input-adapter.rst @@ -2,7 +2,7 @@ Creating a new input adapter ============================== You can write your own storage adapters by creating a new class that -inherits from :code:`InputAdapter` and overides the overrides necessary +inherits from :code:`InputAdapter` and overrides the overrides necessary methods established in the base :code:`InputAdapter` class. .. autofunction:: chatterbot.input.InputAdapter diff --git a/docs/input/index.rst b/docs/input/index.rst index e085ee4fa..4bea068df 100644 --- a/docs/input/index.rst +++ b/docs/input/index.rst @@ -89,7 +89,7 @@ Mailgun input adapter .. autofunction:: chatterbot.input.Mailgun -The Mailgun adapter allows a chat bot to recieve emails using +The Mailgun adapter allows a chat bot to receive emails using the `Mailgun API`_. .. literalinclude:: ../../examples/mailgun.py diff --git a/docs/logic/create-a-logic-adapter.rst b/docs/logic/create-a-logic-adapter.rst index 6ed5625a2..24e7c2cb7 100644 --- a/docs/logic/create-a-logic-adapter.rst +++ b/docs/logic/create-a-logic-adapter.rst @@ -3,7 +3,7 @@ Creating a new logic adapter ============================ You can write your own logic adapters by creating a new class that -inherits from :code:`LogicAdapter` and overides the necessary +inherits from :code:`LogicAdapter` and overrides the necessary methods established in the :code:`LogicAdapter` base class. Logic adapter methods @@ -41,7 +41,7 @@ Example logic adapter Directory structure =================== -If you create your own logic adapter you will need to have it in a seperate file from your chat bot. +If you create your own logic adapter you will need to have it in a separate file from your chat bot. Your directory setup should look something like the following: .. code-block:: text @@ -87,7 +87,7 @@ but statements such as "Do you know what time it is?" will not be processed. Interacting with services ========================= -In some cases, it is usefull to have a logic adapter that can interact with an external service or +In some cases, it is useful to have a logic adapter that can interact with an external service or api in order to complete it's task. Here is an example that demonstrates how this could be done. For this example we will use a fictitious API endpoint that returns the current temperature. diff --git a/docs/logic/index.rst b/docs/logic/index.rst index a39d29c1e..ad58738af 100644 --- a/docs/logic/index.rst +++ b/docs/logic/index.rst @@ -118,7 +118,7 @@ Low confidence response example Specific Response Adapter ========================= -If the input that the chat bot recieves, matches the input text specified +If the input that the chat bot receives, matches the input text specified for this adapter, the specified response will be returned. .. autofunction:: chatterbot.logic.SpecificResponseAdapter diff --git a/docs/output/create-an-output-adapter.rst b/docs/output/create-an-output-adapter.rst index 3c234fb0d..0c40f9c9e 100644 --- a/docs/output/create-an-output-adapter.rst +++ b/docs/output/create-an-output-adapter.rst @@ -2,7 +2,7 @@ Creating a new output adapter ============================== You can write your own storage adapters by creating a new class that -inherits from :code:`chatterbot.output.OutputAdapter` and overides the +inherits from :code:`chatterbot.output.OutputAdapter` and overrides the necessary methods established in the :code:`OutputAdapter` class. To create your own output adapter you must override the :code:`process_response` diff --git a/docs/sessions.rst b/docs/sessions.rst index 5c3fe87e6..201dce433 100644 --- a/docs/sessions.rst +++ b/docs/sessions.rst @@ -14,8 +14,8 @@ conversations with different people at the same time. :members: Each session object holds a queue of the most recent communications that have -occured durring that session. The queue holds tuples with two values each, -the first value is the input that the bot recieved and the second value is the +occurred during that session. The queue holds tuples with two values each, +the first value is the input that the bot received and the second value is the response that the bot returned. .. autoclass:: chatterbot.queues.ResponseQueue @@ -34,7 +34,7 @@ Session example The following example is taken from the Django :code:`ChatterBotView` built into ChatterBot. In this method, the unique identifiers for each chat session are being stored in Django's session objects. This allows different users who interact with the bot through different -web browsers to have seperate conversations with the chat bot. +web browsers to have separate conversations with the chat bot. .. literalinclude:: ../chatterbot/ext/django_chatterbot/views.py :language: python diff --git a/docs/storage/create-a-storage-adapter.rst b/docs/storage/create-a-storage-adapter.rst index 002caf148..98b3000cf 100644 --- a/docs/storage/create-a-storage-adapter.rst +++ b/docs/storage/create-a-storage-adapter.rst @@ -2,7 +2,7 @@ Creating a new storage adapter ============================== You can write your own storage adapters by creating a new class that -inherits from :code:`StorageAdapter` and overides the overrides necessary +inherits from :code:`StorageAdapter` and overrides the overrides necessary methods established in the base :code:`StorageAdapter` class. .. autofunction:: chatterbot.storage.StorageAdapter diff --git a/docs/training.rst b/docs/training.rst index 6dff813c2..0bfd28fc3 100644 --- a/docs/training.rst +++ b/docs/training.rst @@ -13,7 +13,7 @@ inputs and responses are correctly represented. :alt: ChatterBot training statement graph Several training classes come built-in with ChaterBot. These utilities range from allowing -you to update the chat bot's databse knowledge graph based on a list of statements +you to update the chat bot's database knowledge graph based on a list of statements representing a conversation, to tools that allow you to train your bot based on a corpus of pre-loaded training data. @@ -126,7 +126,7 @@ Training with the Twitter API .. autofunction:: chatterbot.trainers.TwitterTrainer -Create an new app using your twitter acccount. Once created, +Create an new app using your twitter account. Once created, it will provide you with the following credentials that are required to work with the Twitter API. diff --git a/docs/tutorial.rst b/docs/tutorial.rst index 8e0925886..7185cfab6 100644 --- a/docs/tutorial.rst +++ b/docs/tutorial.rst @@ -149,7 +149,7 @@ You can speed up this process by training him with examples of existing conversa 'You are welcome.', ]) -You can run the training process multiple times to reinforce prefered responses +You can run the training process multiple times to reinforce preferred responses to particular input statements. You can also run the train command on a number of different example dialogs to increase the breadth of inputs that your chat bot can respond to.