Google Dialogflow API

Name: Dialogflow API
Brand: Dialogflow API
Availability: InStock

✓ Official Vendor SpecAI/MLLanguage Modelsoauth263 EndpointsREST

For Agents

Build, test, and operate conversational AI agents — flows, intents, entities, and test cases — for chatbots and voice bots.

Install Jentic One Beta

Connect the Dialogflow API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Dialogflow API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with Dialogflow API.

Author Dialogflow CX agents with structured flows and pages

Define intents and entity types for natural language understanding

Run conversational test cases and calculate intent coverage

GET STARTED

Start building with Dialogflow API

Explore with Jentic

View OpenAPI Document

Use Cases

Patterns agents use Dialogflow API for, with concrete tasks.

★ Programmatic Agent Authoring

Engineering teams use the CX API to define agents in code rather than the console — versioning flows, pages, and intents in Git. The agents.create endpoint provisions the shell, then flows.create, pages.create, and intents.create populate the conversational graph. CI pipelines push agent updates and run testCases:calculateCoverage before merging.

Create a Dialogflow CX agent named SupportBot in location us-central1, then create one flow named Triage with two pages and three intents.

Continuous Conversation Testing

Run regression tests against a Dialogflow agent before each deploy. Use environments:runContinuousTest to execute every test case against the latest version, and testCases:calculateCoverage to verify intents and transitions are exercised. Gating deploys on coverage thresholds prevents conversation regressions.

Run continuous tests on environment staging for agent SupportBot, then calculate intent coverage and fail the build if coverage is below 0.8.

Version Comparison Before Deploy

Before promoting a new flow version, call versions:compareVersions to surface what changed in the conversational graph. Reviewers see added or removed intents, transition changes, and response differences side-by-side. The compare output drives change-management approvals.

Compare version 5 against version 4 of flow Triage in agent SupportBot and return a summary of added or modified intents.

Agent-Driven Conversation QA

Through Jentic, an AI agent can search for the runContinuousTest operation, kick it off against a target environment, and summarise failing test cases for a human reviewer. The agent operates with scoped Dialogflow OAuth credentials managed in the Jentic vault.

Use Jentic to search 'run Dialogflow continuous tests', load the schema, and execute environments:runContinuousTest for environment staging, then list failed test case names.

Key Endpoints

63 endpoints — google dialogflow is a conversational ai platform for building chatbots, voice bots, and ivr experiences.

METHOD

PATH

DESCRIPTION

GET

/v3/{+name}

Get a Dialogflow resource (agent, flow, page, intent) by name

POST

/v3/{+agent}/testCases:calculateCoverage

Calculate test case coverage for an agent

POST

/v3/{+environment}:runContinuousTest

Run continuous test cases against an environment

POST

/v3/{+environment}:deployFlow

Deploy a flow version to an environment

POST

/v3/{+baseVersion}:compareVersions

Compare two versions of a flow

GET

/v3/{+name}

Get a Dialogflow resource (agent, flow, page, intent) by name

POST

/v3/{+agent}/testCases:calculateCoverage

Calculate test case coverage for an agent

POST

/v3/{+environment}:runContinuousTest

Run continuous test cases against an environment

POST

/v3/{+environment}:deployFlow

Deploy a flow version to an environment

POST

/v3/{+baseVersion}:compareVersions

Compare two versions of a flow

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Google OAuth tokens for Dialogflow are stored encrypted in the Jentic vault (MAXsystem). Agents receive scoped, short-lived tokens with the dialogflow scope only — service-account keys never enter the agent context.

Intent-based discovery

Agents search by intent (e.g., 'run Dialogflow regression tests') and Jentic returns the matching environments:runContinuousTest operation with its parameter schema across the 63-endpoint surface.

Time to first call

Direct Dialogflow CX integration: 2-4 days for OAuth, agent/flow/intent CRUD wrappers, and test orchestration. Through Jentic: under 1 hour — search, load schema, execute.

FAQs

Specific to using Dialogflow API through Jentic.

What authentication does the Dialogflow API use?

OAuth 2.0 with the cloud-platform and dialogflow scopes. Through Jentic, OAuth tokens are scoped per agent run and stored encrypted in the MAXsystem vault, so service-account JSON keys never enter the agent runtime.

Can I run regression tests on a Dialogflow agent via the API?

Yes. The environments:runContinuousTest endpoint executes all test cases against an agent environment, and testCases:calculateCoverage returns intent and transition coverage so you can gate CI on threshold.

What are the rate limits for the Dialogflow API?

Dialogflow CX enforces per-project quotas: design-time edit operations are limited to 60 per minute per agent, runtime detect-intent calls scale with quota request. Check current quotas in the Google Cloud Console under APIs and Services.

How do I compare two Dialogflow versions through Jentic?

Search 'compare Dialogflow versions', load the schema for v3:compareVersions, then execute it with the base and target version names. Jentic returns the diff payload.

Does Dialogflow API v3 support voice and telephony?

Yes. CX agents can be wired to Google Cloud Telephony or third-party SIP providers, with speech recognition and text-to-speech configured per flow. The API manages the agent definition; runtime audio is handled at the integration layer.

Is the Dialogflow API free?

Dialogflow CX has a paid pricing model based on requests per session-minute, with separate rates for text and audio. Dialogflow ES (v2) is generally cheaper but less capable. Check current pricing in the Google Cloud Console.

Google Dialogflow API

Connect the Dialogflow API to your agent

Capabilities

Start building with Dialogflow API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs