Dialogflow CX NLU

Manage intents and entity types in Google Dialogflow CX via REST API for natural language understanding.

Prerequisites

• Google Cloud project with Dialogflow CX API enabled
• Service account or OAuth credentials with Dialogflow API access
• gcloud CLI authenticated OR bearer token

Authentication

Option 1: gcloud CLI (recommended)

gcloud auth application-default login
TOKEN=$(gcloud auth print-access-token)

Option 2: Service Account

export GOOGLE_APPLICATION_CREDENTIALS="/path/to/service-account.json"
TOKEN=$(gcloud auth application-default print-access-token)

API Base URL

https://dialogflow.googleapis.com/v3beta1

Regional endpoints available:

• https://{region}-dialogflow.googleapis.com (e.g., us-central1, europe-west1)

Common Operations

List Intents

curl -X GET \
  "https://dialogflow.googleapis.com/v3beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents/${AGENT_ID}/intents" \
  -H "Authorization: Bearer ${TOKEN}"

Create Intent

curl -X POST \
  "https://dialogflow.googleapis.com/v3beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents/${AGENT_ID}/intents" \
  -H "Authorization: Bearer ${TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "displayName": "Book Flight",
    "trainingPhrases": [
      {
        "parts": [{"text": "I want to book a flight"}],
        "repeatCount": 1
      }
    ]
  }'

List Entity Types

curl -X GET \
  "https://dialogflow.googleapis.com/v3beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents/${AGENT_ID}/entityTypes" \
  -H "Authorization: Bearer ${TOKEN}"

Create Entity Type

curl -X POST \
  "https://dialogflow.googleapis.com/v3beta1/projects/${PROJECT_ID}/locations/${LOCATION}/agents/${AGENT_ID}/entityTypes" \
  -H "Authorization: Bearer ${TOKEN}" \
  -H "Content-Type: application/json" \
  -d '{
    "displayName": "Cities",
    "kind": "KIND_LIST",
    "entities": [
      {"value": "New York"},
      {"value": "Los Angeles"}
    ]
  }'

Key Resources

Resource	Description
Intents	Classify user utterances and extract parameters
Entity Types	Define structured data extraction patterns

Quick Reference

For detailed API reference:

• Intents: See references/intents.md
• Entity Types: See references/entities.md

Scripts

• scripts/nlu.py — CLI wrapper for intents and entity types operations

Usage

python scripts/nlu.py list-intents --agent AGENT_NAME
python scripts/nlu.py create-intent --agent AGENT_NAME --intent "Book Flight" --phrases "book a flight,I want to fly"
python scripts/nlu.py list-entities --agent AGENT_NAME
python scripts/nlu.py create-entity --agent AGENT_NAME --name "Cities" --values "New York,Los Angeles"

Tips

• Use training phrases that cover various ways users might express the intent
• Entity types can be system (built-in) or custom
• Use KIND_MAP for entities with synonyms, KIND_LIST for simple lists