Agent Args
A Dialogflow agent is a virtual agent that handles conversations with your end-users. It is a natural language understanding module that understands the nuances of human language. Dialogflow translates end-user text or audio during a conversation to structured data that your apps and services can understand. You design and build a Dialogflow agent to handle the types of conversations required for your system. To get more information about Agent, see:
How-to Guides
Example Usage
Dialogflow Agent Full
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const fullAgent = new gcp.diagflow.Agent("full_agent", {
displayName: "dialogflow-agent",
defaultLanguageCode: "en",
supportedLanguageCodes: [
"fr",
"de",
"es",
],
timeZone: "America/New_York",
description: "Example description.",
avatarUri: "https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png",
enableLogging: true,
matchMode: "MATCH_MODE_ML_ONLY",
classificationThreshold: 0.3,
apiVersion: "API_VERSION_V2_BETA_1",
tier: "TIER_STANDARD",
});
import pulumi
import pulumi_gcp as gcp
full_agent = gcp.diagflow.Agent("full_agent",
display_name="dialogflow-agent",
default_language_code="en",
supported_language_codes=[
"fr",
"de",
"es",
],
time_zone="America/New_York",
description="Example description.",
avatar_uri="https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png",
enable_logging=True,
match_mode="MATCH_MODE_ML_ONLY",
classification_threshold=0.3,
api_version="API_VERSION_V2_BETA_1",
tier="TIER_STANDARD")
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;
return await Deployment.RunAsync(() =>
{
var fullAgent = new Gcp.Diagflow.Agent("full_agent", new()
{
DisplayName = "dialogflow-agent",
DefaultLanguageCode = "en",
SupportedLanguageCodes = new[]
{
"fr",
"de",
"es",
},
TimeZone = "America/New_York",
Description = "Example description.",
AvatarUri = "https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png",
EnableLogging = true,
MatchMode = "MATCH_MODE_ML_ONLY",
ClassificationThreshold = 0.3,
ApiVersion = "API_VERSION_V2_BETA_1",
Tier = "TIER_STANDARD",
});
});
package main
import (
"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/diagflow"
"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)
func main() {
pulumi.Run(func(ctx *pulumi.Context) error {
_, err := diagflow.NewAgent(ctx, "full_agent", &diagflow.AgentArgs{
DisplayName: pulumi.String("dialogflow-agent"),
DefaultLanguageCode: pulumi.String("en"),
SupportedLanguageCodes: pulumi.StringArray{
pulumi.String("fr"),
pulumi.String("de"),
pulumi.String("es"),
},
TimeZone: pulumi.String("America/New_York"),
Description: pulumi.String("Example description."),
AvatarUri: pulumi.String("https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png"),
EnableLogging: pulumi.Bool(true),
MatchMode: pulumi.String("MATCH_MODE_ML_ONLY"),
ClassificationThreshold: pulumi.Float64(0.3),
ApiVersion: pulumi.String("API_VERSION_V2_BETA_1"),
Tier: pulumi.String("TIER_STANDARD"),
})
if err != nil {
return err
}
return nil
})
}
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.diagflow.Agent;
import com.pulumi.gcp.diagflow.AgentArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var fullAgent = new Agent("fullAgent", AgentArgs.builder()
.displayName("dialogflow-agent")
.defaultLanguageCode("en")
.supportedLanguageCodes(
"fr",
"de",
"es")
.timeZone("America/New_York")
.description("Example description.")
.avatarUri("https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png")
.enableLogging(true)
.matchMode("MATCH_MODE_ML_ONLY")
.classificationThreshold(0.3)
.apiVersion("API_VERSION_V2_BETA_1")
.tier("TIER_STANDARD")
.build());
}
}
resources:
fullAgent:
type: gcp:diagflow:Agent
name: full_agent
properties:
displayName: dialogflow-agent
defaultLanguageCode: en
supportedLanguageCodes:
- fr
- de
- es
timeZone: America/New_York
description: Example description.
avatarUri: https://cloud.google.com/_static/images/cloud/icons/favicons/onecloud/super_cloud.png
enableLogging: true
matchMode: MATCH_MODE_ML_ONLY
classificationThreshold: 0.3
apiVersion: API_VERSION_V2_BETA_1
tier: TIER_STANDARD
Import
Agent can be imported using any of these accepted formats:
{{project}}
When using thepulumi import
command, Agent can be imported using one of the formats above. For example:
$ pulumi import gcp:diagflow/agent:Agent default {{project}}
Constructors
Properties
API version displayed in Dialogflow console. If not specified, V2 API is assumed. Clients are free to query different service endpoints for different API versions. However, bots connectors and webhook calls will follow the specified API version.
The URI of the agent's avatar, which are used throughout the Dialogflow console. When an image URL is entered into this field, the Dialogflow will save the image in the backend. The address of the backend image returned from the API will be shown in the avatarUriBackend field.
To filter out false positive results and still get variety in matched natural language inputs for your agent, you can tune the machine learning classification threshold. If the returned score value is less than the threshold value, then a fallback intent will be triggered or, if there are no fallback intents defined, no intent will be triggered. The score values range from 0.0 (completely uncertain) to 1.0 (completely certain). If set to 0.0, the default of 0.3 is used.
The default language of the agent as a language tag. See Language Support for a list of the currently supported language codes. This field cannot be updated after creation.
The description of this agent. The maximum length is 500 characters. If exceeded, the request is rejected.
The name of this agent.
Determines whether this agent should log conversation queries.
The list of all languages supported by this agent (except for the defaultLanguageCode).
The time zone of this agent from the time zone database, e.g., America/New_York, Europe/Paris.