Agents

A Dialogflow CX 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.

A Dialogflow agent is similar to a human call center agent. You train them both to handle expected conversation scenarios, and your training does not need to be overly explicit.

Create an agent

To create an agent:

Console

  1. Open the Dialogflow CX Console.
  2. Create or choose a GCP project.
  3. Click +Create.
  4. Complete the form for basic agent settings.
  5. Click Save.

API

See the create method in the

Select a protocol and version for the Agent reference:

Protocol V3beta1
REST Agent resource
RPC Agent interface
.

Agent data

Dialogflow agents serve as top-level containers for settings and data for virtual agents.

To access an agent's data:

Console

  1. Open the Dialogflow CX Console.
  2. Choose the GCP project for the agent.
  3. Find the agent in the list.
  4. Click the agent name.
  5. Update flows, pages, etc. as described in other guides.

API

See the guides for the data you want to update.

The following data is associated with agents:

Agent settings

To access agent settings:

Console

  1. Open the Dialogflow CX Console.
  2. Choose your GCP project.
  3. Select your agent.
  4. Click Agent Settings.
  5. Update the settings as desired.
  6. Click Save.

API

See the get and patch/update methods in the

Select a protocol and version for the Agent reference:

Protocol V3beta1
REST Agent resource
RPC Agent interface
.

The following subsections describe the different categories of agent settings.

General settings

The following general settings are available for agents:

  • Agent name

    A display name for your agent.

  • Time zone

    The default time zone for your agent.

  • Default language

    The default language supported by your agent.

  • Enable Stackdriver logging

    Indicates whether stackdriver logging is enabled for the agent.

ML settings

Dialogflow uses machine learning (ML) algorithms to understand end-user inputs, match them to intents, and extract structured data. Dialogflow learns from training phrases that you provide and the language models built into Dialogflow. Based on this data, it builds a model for making decisions about which intent should be matched to an end-user input. You can apply unique ML settings for each flow of an agent, and the model created by Dialogflow is unique for each flow.

The following ML settings are available:

  • NLU type

    This can be one of:

    • Standard: Standard NLU technology.
    • Advanced: Advanced NLU technology. This NLU type works better than standard, especially for large agents and flows. Model training takes longer, so you should disable automatic training.
  • Classification threshold

    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. This setting controls the minimum intent detection confidence required for an intent match.

    If the confidence score for an intent match is less than the threshold value, then a no-match event will be invoked.

  • Auto train

    If enabled, the flow is trained whenever it is updated with the console. For large flows, this may cause console UI delays, so you should disable this setting and manually train as-needed for large flows. This setting cannot be enabled for a custom NLU type.

  • Spell correction

    If this is enabled and end-user input has a spelling or grammar mistake, an intent will be matched as though it was written correctly. The detect intent response will contain the corrected end-user input. For example, if an end-user enters "I want an applle", it will be processed as though the end-user entered "I want an apple". This also applies to matches involving both system and custom entities.

    Spell correction is available for all languages supported by Dialogflow.

    Warnings and best practices:

    • Spell correction can't correct ASR (automatic speech recognition) errors, so we don't recommend enabling it for agents using ASR inputs.
    • It is possible for corrected input to match the wrong intent. You can fix this by adding commonly mismatched phrases to negative examples.
    • Spell correction increases the agent's response time slightly.
    • If an agent is defined using domain-specific jargon, the corrections may be undesired.
  • Training status

    Indicates whether the flow has been trained since the latest update to the flow data.

  • Train NLU

    Use this button to manually train the flow.

Speech settings

The following speech settings are available:

Share settings

See Access control.

Version settings

See Versions and environments.

Environment settings

See Versions and environments.

Export and restore an agent

To export or restore an agent:

Console

  1. Open the Dialogflow CX Console.
  2. Choose the GCP project for the agent.
  3. Find the agent in the list.
  4. Click the export or restore button.
  5. Follow instructions to complete.

API

See the export and restore methods in the

Select a protocol and version for the Agent reference:

Protocol V3beta1
REST Agent resource
RPC Agent interface
.

Delete an agent

To delete an agent:

Console

  1. Open the Dialogflow CX Console.
  2. Choose the GCP project for the agent.
  3. Find the agent in the list.
  4. Click .
  5. Confirm deletion in the dialog.

API

See the delete method in the

Select a protocol and version for the Agent reference:

Protocol V3beta1
REST Agent resource
RPC Agent interface
.