Package dialogflow_v2beta1 (0.8.0)

Agents are best described as Natural Language Understanding (NLU) modules that transform user requests into actionable data. You can include agents in your app, product, or service to determine user intent and respond to the user in a natural way.

After you create an agent, you can add Intents, Contexts, Entity Types, Webhooks, and so on to manage the flow of a conversation and match user input to predefined intents and actions.

You can create an agent using both Dialogflow Standard Edition and Dialogflow Enterprise Edition. For details, see Dialogflow Editions <https://cloud.google.com/dialogflow/docs/editions>__.

You can save your agent for backup or versioning by exporting the agent by using the ExportAgent method. You can import a saved agent by using the ImportAgent method.

Dialogflow provides several prebuilt agents <https://cloud.google.com/dialogflow/docs/agents-prebuilt>__ for common conversation scenarios such as determining a date and time, converting currency, and so on.

For more information about agents, see the Dialogflow documentation <https://cloud.google.com/dialogflow/docs/agents-overview>__.

A context represents additional information included with user input or with an intent returned by the Dialogflow API. Contexts are helpful for differentiating user input which may be vague or have a different meaning depending on additional details from your application such as user setting and preferences, previous user input, where the user is in your application, geographic location, and so on.

You can include contexts as input parameters of a DetectIntent (or StreamingDetectIntent) request, or as output contexts included in the returned intent. Contexts expire when an intent is matched, after the number of DetectIntent requests specified by the lifespan_count parameter, or after 20 minutes if no intents are matched for a DetectIntent request.

For more information about contexts, see the Dialogflow documentation <https://cloud.google.com/dialogflow/docs/contexts-overview>__.

Manages documents of a knowledge base.

Entities are extracted from user input and represent parameters that are meaningful to your application. For example, a date range, a proper name such as a geographic location or landmark, and so on. Entities represent actionable data for your application.

When you define an entity, you can also include synonyms that all map to that entity. For example, "soft drink", "soda", "pop", and so on.

There are three types of entities:

• System - entities that are defined by the Dialogflow API for common data types such as date, time, currency, and so on. A system entity is represented by the EntityType type.

• Custom - entities that are defined by you that represent actionable data that is meaningful to your application. For example, you could define a pizza.sauce entity for red or white pizza sauce, a pizza.cheese entity for the different types of cheese on a pizza, a pizza.topping entity for different toppings, and so on. A custom entity is represented by the EntityType type.

• User - entities that are built for an individual user such as favorites, preferences, playlists, and so on. A user entity is represented by the SessionEntityType type.

For more information about entity types, see the Dialogflow documentation <https://cloud.google.com/dialogflow/docs/entities-overview>__.

An intent represents a mapping between input from a user and an action to be taken by your application. When you pass user input to the DetectIntent (or StreamingDetectIntent) method, the Dialogflow API analyzes the input and searches for a matching intent. If no match is found, the Dialogflow API returns a fallback intent (is_fallback = true).

You can provide additional information for the Dialogflow API to use to match user input to an intent by adding the following to your intent.

• Contexts - provide additional context for intent analysis. For example, if an intent is related to an object in your application that plays music, you can provide a context to determine when to match the intent if the user input is "turn it off". You can include a context that matches the intent when there is previous user input of "play music", and not when there is previous user input of "turn on the light".

• Events - allow for matching an intent by using an event name instead of user input. Your application can provide an event name and related parameters to the Dialogflow API to match an intent. For example, when your application starts, you can send a welcome event with a user name parameter to the Dialogflow API to match an intent with a personalized welcome message for the user.

• Training phrases - provide examples of user input to train the Dialogflow API agent to better match intents.

For more information about intents, see the Dialogflow documentation <https://cloud.google.com/dialogflow/docs/intents-overview>__.

Manages knowledge bases.

Allows users to setup and maintain knowledge bases with their knowledge data.

Entities are extracted from user input and represent parameters that are meaningful to your application. For example, a date range, a proper name such as a geographic location or landmark, and so on. Entities represent actionable data for your application.

Session entity types are referred to as User entity types and are entities that are built for an individual user such as favorites, preferences, playlists, and so on. You can redefine a session entity type at the session level.

Session entity methods do not work with Google Assistant integration. Contact Dialogflow support if you need to use session entities with Google Assistant integration.

For more information about entity types, see the Dialogflow documentation <https://cloud.google.com/dialogflow/docs/entities-overview>__.

A session represents an interaction with a user. You retrieve user input and pass it to the DetectIntent (or StreamingDetectIntent) method to determine user intent and respond.

API documentation for types module.