The google-dialogflow2_beta1
library allows access to all features of the Google Dialogflow service.
This documentation was generated from Dialogflow crate version 1.0.7+20181009, where 20181009 is the exact revision of the dialogflow:v2beta1 schema built by the mako code generator v1.0.7.
Everything else about the Dialogflow v2_beta1 API can be found at the official documentation site.
Features
Handle the following Resources with ease from the central hub ...
- projects
- agent entity types batch delete, agent entity types batch update, agent entity types create, agent entity types delete, agent entity types entities batch create, agent entity types entities batch delete, agent entity types entities batch update, agent entity types get, agent entity types list, agent entity types patch, agent environments users sessions contexts create, agent environments users sessions contexts delete, agent environments users sessions contexts get, agent environments users sessions contexts list, agent environments users sessions contexts patch, agent environments users sessions delete contexts, agent environments users sessions detect intent, agent environments users sessions entity types create, agent environments users sessions entity types delete, agent environments users sessions entity types get, agent environments users sessions entity types list, agent environments users sessions entity types patch, agent export, agent import, agent intents batch delete, agent intents batch update, agent intents create, agent intents delete, agent intents get, agent intents list, agent intents patch, agent knowledge bases create, agent knowledge bases delete, agent knowledge bases documents create, agent knowledge bases documents delete, agent knowledge bases documents get, agent knowledge bases documents list, agent knowledge bases get, agent knowledge bases list, agent restore, agent search, agent sessions contexts create, agent sessions contexts delete, agent sessions contexts get, agent sessions contexts list, agent sessions contexts patch, agent sessions delete contexts, agent sessions detect intent, agent sessions entity types create, agent sessions entity types delete, agent sessions entity types get, agent sessions entity types list, agent sessions entity types patch, agent train, conversation profiles create, conversation profiles delete, conversation profiles get, conversation profiles list, conversation profiles patch, conversations add conversation phone number, conversations complete, conversations create, conversations get, conversations list, conversations messages list, conversations participants analyze content, conversations participants create, conversations participants get, conversations participants list, conversations participants streaming analyze content, conversations participants suggestions list, environments users conversations contexts create, environments users conversations contexts delete, environments users conversations contexts get, environments users conversations contexts list, environments users conversations contexts patch, environments users conversations delete contexts, get agent, human agent assistants compile suggestions, human agent assistants create, human agent assistants delete, human agent assistants get, human agent assistants list, human agent assistants patch, knowledge bases create, knowledge bases delete, knowledge bases documents create, knowledge bases documents delete, knowledge bases documents get, knowledge bases documents list, knowledge bases get, knowledge bases list, operations get, phone number orders cancel, phone number orders create, phone number orders get, phone number orders list, phone number orders patch, phone numbers delete, phone numbers list, phone numbers patch and phone numbers undelete
Structure of this Library
The API is structured into the following primary items:
- Hub
- a central object to maintain state and allow accessing all Activities
- creates Method Builders which in turn allow access to individual Call Builders
- Resources
- primary types that you can apply Activities to
- a collection of properties and Parts
- Parts
- a collection of properties
- never directly used in Activities
- Activities
- operations to apply to Resources
All structures are marked with applicable traits to further categorize them and ease browsing.
Generally speaking, you can invoke Activities like this:
let r = hub.resource.activity.doit
Or specifically ...
let r = hub.projects().agent_restore(...).doit()
let r = hub.projects().agent_intents_batch_delete(...).doit()
let r = hub.projects().knowledge_bases_documents_create(...).doit()
let r = hub.projects().knowledge_bases_documents_delete(...).doit()
let r = hub.projects().agent_entity_types_batch_delete(...).doit()
let r = hub.projects().agent_train(...).doit()
let r = hub.projects().agent_knowledge_bases_documents_delete(...).doit()
let r = hub.projects().agent_import(...).doit()
let r = hub.projects().agent_entity_types_batch_update(...).doit()
let r = hub.projects().agent_export(...).doit()
let r = hub.projects().agent_knowledge_bases_documents_create(...).doit()
let r = hub.projects().agent_intents_batch_update(...).doit()
let r = hub.projects().agent_entity_types_entities_batch_update(...).doit()
let r = hub.projects().agent_entity_types_entities_batch_delete(...).doit()
let r = hub.projects().operations_get(...).doit()
let r = hub.projects().agent_entity_types_entities_batch_create(...).doit()
The resource()
and activity(...)
calls create builders. The second one dealing with Activities
supports various methods to configure the impending operation (not shown here). It is made such that all required arguments have to be
specified right away (i.e. (...)
), whereas all optional ones can be build up as desired.
The doit()
method performs the actual communication with the server and returns the respective result.
Usage
Setting up your Project
To use this library, you would put the following lines into your Cargo.toml
file:
[]
= "*"
# This project intentionally uses an old version of Hyper. See
# https://github.com/Byron/google-apis-rs/issues/173 for more
# information.
= "^0.10"
= "^0.6"
= "^1.0"
= "^1.0"
= "^1.0"
A complete example
extern crate hyper;
extern crate hyper_rustls;
extern crate yup_oauth2 as oauth2;
extern crate google_dialogflow2_beta1 as dialogflow2_beta1;
use GoogleCloudDialogflowV2beta1RestoreAgentRequest;
use ;
use Default;
use ;
use Dialogflow;
// Get an ApplicationSecret instance by some means. It contains the `client_id` and
// `client_secret`, among other things.
let secret: ApplicationSecret = Default default;
// Instantiate the authenticator. It will choose a suitable authentication flow for you,
// unless you replace `None` with the desired Flow.
// Provide your own `AuthenticatorDelegate` to adjust the way it operates and get feedback about
// what's going on. You probably want to bring in your own `TokenStorage` to persist tokens and
// retrieve them from storage.
let auth = new;
let mut hub = new;
// As the method needs a request, you would usually fill it with the desired information
// into the respective structure. Some of the parts shown here might not be applicable !
// Values shown here are possibly random and not representative !
let mut req = default;
// You can configure optional parameters by calling the respective setters at will, and
// execute the final call using `doit()`.
// Values shown here are possibly random and not representative !
let result = hub.projects.agent_restore
.doit;
match result
Handling Errors
All errors produced by the system are provided either as Result enumeration as return value of the doit() methods, or handed as possibly intermediate results to either the Hub Delegate, or the Authenticator Delegate.
When delegates handle errors or intermediate values, they may have a chance to instruct the system to retry. This makes the system potentially resilient to all kinds of errors.
Uploads and Downloads
If a method supports downloads, the response body, which is part of the Result, should be
read by you to obtain the media.
If such a method also supports a Response Result, it will return that by default.
You can see it as meta-data for the actual media. To trigger a media download, you will have to set up the builder by making
this call: .param("alt", "media")
.
Methods supporting uploads can do so using up to 2 different protocols:
simple and resumable. The distinctiveness of each is represented by customized
doit(...)
methods, which are then named upload(...)
and upload_resumable(...)
respectively.
Customization and Callbacks
You may alter the way an doit()
method is called by providing a delegate to the
Method Builder before making the final doit()
call.
Respective methods will be called to provide progress information, as well as determine whether the system should
retry on failure.
The delegate trait is default-implemented, allowing you to customize it with minimal effort.
Optional Parts in Server-Requests
All structures provided by this library are made to be enocodable and decodable via json. Optionals are used to indicate that partial requests are responses are valid. Most optionals are are considered Parts which are identifiable by name, which will be sent to the server to indicate either the set parts of the request or the desired parts in the response.
Builder Arguments
Using method builders, you are able to prepare an action call by repeatedly calling it's methods. These will always take a single argument, for which the following statements are true.
- PODs are handed by copy
- strings are passed as
&str
- request values are moved
Arguments will always be copied or cloned into the builder, to make them independent of their original life times.
License
The dialogflow2_beta1 library was generated by Sebastian Thiel, and is placed under the MIT license. You can read the full text at the repository's license file.