google-dialogflow2库允许访问Google Dialogflow服务的所有功能。

本文档是从Dialogflow crate版本5.0.5+20240614生成的，其中20240614是mako代码生成器v5.0.5构建的dialogflow:v2模式的精确修订。

有关Dialogflow v2 API的所有其他信息，请参阅官方文档站点。

功能

从中心枢纽轻松处理以下资源...

• 项目
• 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 create, agent environments delete, agent environments get, agent environments get history, agent environments intents list, agent environments list, agent environments 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 get fulfillment, agent get validation result, 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 documents patch, agent knowledge bases documents reload, agent knowledge bases get, agent knowledge bases list, agent knowledge bases patch, 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, agent update fulfillment, agent versions create, agent versions delete, agent versions get, agent versions list, agent versions patch, answer records list, answer records patch, conversation datasets get, conversation datasets import conversation data, conversation datasets list, conversation models create, conversation models delete, conversation models deploy, conversation models evaluations get, conversation models evaluations list, conversation models get, conversation models list, conversation models undeploy, conversation profiles clear suggestion feature config, conversation profiles create, conversation profiles delete, conversation profiles get, conversation profiles list, conversation profiles patch, conversation profiles set suggestion feature config, 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 patch, conversations participants suggestions suggest articles, conversations participants suggestions suggest faq answers, conversations participants suggestions suggest knowledge assist, conversations participants suggestions suggest smart replies, conversations suggestions search knowledge, conversations suggestions suggest conversation summary, delete agent, generators create, generators list, get agent, knowledge bases create, knowledge bases delete, knowledge bases documents create, knowledge bases documents delete, knowledge bases documents export, knowledge bases documents get, knowledge bases documents import, knowledge bases documents list, knowledge bases documents patch, knowledge bases documents reload, knowledge bases get, knowledge bases list, knowledge bases patch, locations agent entity types batch delete, locations agent entity types batch update, locations agent entity types create, locations agent entity types delete, locations agent entity types entities batch create, locations agent entity types entities batch delete, locations agent entity types entities batch update, locations agent entity types get, locations agent entity types list, locations agent entity types patch, locations agent environments create, locations agent environments delete, locations agent environments get, locations agent environments get history, locations agent environments intents list, locations agent environments list, locations agent environments patch, locations agent environments users sessions contexts create, locations agent environments users sessions contexts delete, locations agent environments users sessions contexts get, locations agent environments users sessions contexts list, locations agent environments users sessions contexts patch, locations agent environments users sessions delete contexts, locations agent environments users sessions detect intent, locations agent environments users sessions entity types create, locations agent environments users sessions entity types delete, locations agent environments users sessions entity types get, locations agent environments users sessions entity types list, locations agent environments users sessions entity types patch, locations agent export, locations agent get fulfillment, locations agent get validation result, locations agent import, locations agent intents batch delete, locations agent intents batch update, locations agent intents create, locations agent intents delete, locations agent intents get, locations agent intents list, locations agent intents patch, locations agent restore, locations agent search, locations agent sessions contexts create, locations agent sessions contexts delete, locations agent sessions contexts get, locations agent sessions contexts list, locations agent sessions contexts patch, locations agent sessions delete contexts, locations agent sessions detect intent, locations agent sessions entity types create, locations agent sessions entity types delete, locations agent sessions entity types get, locations agent sessions entity types list, locations agent sessions entity types patch, locations agent train, locations agent update fulfillment, locations agent versions create, locations agent versions delete, locations agent versions get, locations agent versions list, locations agent versions patch, locations answer records list, locations answer records patch, locations conversation datasets create, locations conversation datasets delete, locations conversation datasets get, locations conversation datasets import conversation data, locations conversation datasets list, locations conversation models create, locations conversation models delete, locations conversation models deploy, locations conversation models evaluations create, locations conversation models evaluations get, locations conversation models evaluations list, locations conversation models get, locations conversation models list, locations conversation models undeploy, locations conversation profiles clear suggestion feature config, locations conversation profiles create, locations conversation profiles delete, locations conversation profiles get, locations conversation profiles list, locations conversation profiles patch, locations conversation profiles set suggestion feature config, locations conversations complete, locations conversations create, locations conversations get, locations conversations list, locations conversations messages list, locations conversations participants analyze content, locations conversations participants create, locations conversations participants get, locations conversations participants list, locations conversations participants patch, locations conversations participants suggestions suggest articles, locations conversations participants suggestions suggest faq answers, locations conversations participants suggestions suggest knowledge assist, locations conversations participants suggestions suggest smart replies, locations conversations suggestions search knowledge, locations conversations suggestions suggest conversation summary, locations delete agent, locations generators create, locations generators delete, locations generators get, locations generators list, locations generators patch, locations get, locations get agent, locations knowledge bases create, locations knowledge bases delete, locations knowledge bases documents create, locations knowledge bases documents delete, locations knowledge bases documents export, locations knowledge bases documents get, locations knowledge bases documents import, locations knowledge bases documents list, locations knowledge bases documents patch, locations knowledge bases documents reload, locations knowledge bases get, locations knowledge bases list, locations knowledge bases patch, locations list, locations operations cancel, locations operations get, locations operations list, locations set agent, locations stateless suggestion generate, locations suggestions generate stateless summary, locations suggestions search knowledge, operations cancel, operations get, operations list, set agent, suggestions generate stateless summary and suggestions search knowledge

本库结构

API结构如下主要项

• 枢纽
  • 一个中心对象，用于维护状态并允许访问所有活动
  • 创建方法构建器，这反过来又允许访问单个调用构建器
• 资源
  • 主要类型，可以将活动应用于
  • 属性和部分的集合
  • 部分
    • 属性集合
    • 永远不会直接在活动中使用
• 活动
  • 应用于资源的操作

所有结构都带有适用的特性和属性，以进一步分类它们并简化浏览。

一般来说，你可以像这样调用活动：

let r = hub.resource().activity(...).doit().await

或者具体来说...

let r = hub.projects().agent_entity_types_entities_batch_create(...).doit().await
let r = hub.projects().agent_entity_types_entities_batch_delete(...).doit().await
let r = hub.projects().agent_entity_types_entities_batch_update(...).doit().await
let r = hub.projects().agent_entity_types_batch_delete(...).doit().await
let r = hub.projects().agent_entity_types_batch_update(...).doit().await
let r = hub.projects().agent_intents_batch_delete(...).doit().await
let r = hub.projects().agent_intents_batch_update(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_create(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().agent_knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().agent_export(...).doit().await
let r = hub.projects().agent_import(...).doit().await
let r = hub.projects().agent_restore(...).doit().await
let r = hub.projects().agent_train(...).doit().await
let r = hub.projects().conversation_datasets_import_conversation_data(...).doit().await
let r = hub.projects().conversation_models_create(...).doit().await
let r = hub.projects().conversation_models_delete(...).doit().await
let r = hub.projects().conversation_models_deploy(...).doit().await
let r = hub.projects().conversation_models_undeploy(...).doit().await
let r = hub.projects().conversation_profiles_clear_suggestion_feature_config(...).doit().await
let r = hub.projects().conversation_profiles_set_suggestion_feature_config(...).doit().await
let r = hub.projects().knowledge_bases_documents_create(...).doit().await
let r = hub.projects().knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().knowledge_bases_documents_export(...).doit().await
let r = hub.projects().knowledge_bases_documents_import(...).doit().await
let r = hub.projects().knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_create(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_delete(...).doit().await
let r = hub.projects().locations_agent_entity_types_entities_batch_update(...).doit().await
let r = hub.projects().locations_agent_entity_types_batch_delete(...).doit().await
let r = hub.projects().locations_agent_entity_types_batch_update(...).doit().await
let r = hub.projects().locations_agent_intents_batch_delete(...).doit().await
let r = hub.projects().locations_agent_intents_batch_update(...).doit().await
let r = hub.projects().locations_agent_export(...).doit().await
let r = hub.projects().locations_agent_import(...).doit().await
let r = hub.projects().locations_agent_restore(...).doit().await
let r = hub.projects().locations_agent_train(...).doit().await
let r = hub.projects().locations_conversation_datasets_create(...).doit().await
let r = hub.projects().locations_conversation_datasets_delete(...).doit().await
let r = hub.projects().locations_conversation_datasets_import_conversation_data(...).doit().await
let r = hub.projects().locations_conversation_models_evaluations_create(...).doit().await
let r = hub.projects().locations_conversation_models_create(...).doit().await
let r = hub.projects().locations_conversation_models_delete(...).doit().await
let r = hub.projects().locations_conversation_models_deploy(...).doit().await
let r = hub.projects().locations_conversation_models_undeploy(...).doit().await
let r = hub.projects().locations_conversation_profiles_clear_suggestion_feature_config(...).doit().await
let r = hub.projects().locations_conversation_profiles_set_suggestion_feature_config(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_create(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_delete(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_export(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_import(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_patch(...).doit().await
let r = hub.projects().locations_knowledge_bases_documents_reload(...).doit().await
let r = hub.projects().locations_operations_get(...).doit().await
let r = hub.projects().operations_get(...).doit().await

resource() 和 activity(...) 调用创建 构建器。第二个处理 Activities，支持各种配置即将进行的操作的方法（此处未显示）。它被设计成必须立即指定所有必需的参数（即 (...)），而所有可选参数都可以根据需要 构建。doit() 方法执行与服务器的实际通信，并返回相应的结果。

使用方法

设置你的项目

要使用此库，您需要将以下行放入您的 Cargo.toml 文件中

[dependencies]
google-dialogflow2 = "*"
serde = "^1.0"
serde_json = "^1.0"

完整示例

extern crate hyper;
extern crate hyper_rustls;
extern crate google_dialogflow2 as dialogflow2;
use dialogflow2::api::GoogleCloudDialogflowV2Document;
use dialogflow2::{Result, Error};
use std::default::Default;
use dialogflow2::{Dialogflow, oauth2, hyper, hyper_rustls, chrono, FieldMask};

// Get an ApplicationSecret instance by some means. It contains the `client_id` and 
// `client_secret`, among other things.
let secret: oauth2::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 = oauth2::InstalledFlowAuthenticator::builder(
        secret,
        oauth2::InstalledFlowReturnMethod::HTTPRedirect,
    ).build().await.unwrap();
let mut hub = Dialogflow::new(hyper::Client::builder().build(hyper_rustls::HttpsConnectorBuilder::new().with_native_roots().unwrap().https_or_http().enable_http1().build()), auth);
// 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 = GoogleCloudDialogflowV2Document::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_knowledge_bases_documents_patch(req, "name")
             .update_mask(FieldMask::new::<&str>(&[]))
             .doit().await;

match result {
    Err(e) => match e {
        // The Error enum provides details about what exactly happened.
        // You can also just use its `Debug`, `Display` or `Error` traits
         Error::HttpError(_)
        |Error::Io(_)
        |Error::MissingAPIKey
        |Error::MissingToken(_)
        |Error::Cancelled
        |Error::UploadSizeLimitExceeded(_, _)
        |Error::Failure(_)
        |Error::BadRequest(_)
        |Error::FieldClash(_)
        |Error::JsonDecodeError(_, _) => println!("{}", e),
    },
    Ok(res) => println!("Success: {:?}", res),
}

处理错误

系统产生的所有错误都作为 Result 枚举提供，作为 doit() 方法的返回值，或者作为可能的中继结果传递给 Hub Delegate 或 Authenticator Delegate。

当代理处理错误或中间值时，它们可能会有机会指示系统重试。这使得系统可能对各种错误都具有弹性。

上传和下载

如果方法支持下载，则应读取响应体（它是 Result 的一部分）以获取媒体。如果此类方法还支持 Response Result，则默认返回该结果。您可以将其视为实际媒体的元数据。要触发媒体下载，您将必须通过此调用设置构建器：.param("alt", "media")。

支持上传的方法可以使用最多 2 种不同的协议：简单 和 可恢复。每种协议的独特性由定制的 doit(...) 方法表示，分别命名为 upload(...) 和 upload_resumable(...)。

自定义和回调

您可以通过向 Method Builder 提供一个 代理 来在最终调用 doit() 之前改变 doit() 方法的调用方式。相应的方方法将被调用来提供进度信息，以及确定系统在失败时是否应该重试。

delegate trait 有默认实现，允许您以最小的努力进行自定义。

服务器请求中的可选部分

本库提供的所有结构都是设计为可以通过 编码 和 解码 为 json 格式。使用可选参数来表示部分请求或响应是有效的。大多数可选参数被视为 Parts，可以通过名称识别，这些部分将被发送到服务器以指示请求的设置部分或响应中所需的部分。

构建器参数

使用 方法构建器，可以通过多次调用其方法来准备动作调用。这些方法始终接受单个参数，以下陈述适用于这些参数。

• PODs 通过复制传递
• 字符串作为 &str 传递
• 请求值 被移动

参数将始终被复制或克隆到构建器中，以确保它们与其原始生命周期独立。

Cargo 功能

• utoipa - 添加对 utoipa 的支持，并在所有类型上派生 utoipa::ToSchema。您必须在 #[openapi(schemas(...))] 中导入和注册所需类型，否则生成的 openapi 规范将无效。

许可

dialogflow2 库由 Sebastian Thiel 生成，并置于 MIT 许可证之下。您可以在存储库的 许可证文件 中阅读全文。