Some products and features are in the process of being renamed. Generative playbook and flow features are also being migrated to a single consolidated console. See the details.
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A
Conversational Agents (Dialogflow CX) agent
is a virtual agent
that handles concurrent conversations with your end-users.
It is a natural language understanding module
that understands the nuances of human language.
Conversational Agents (Dialogflow CX) translates end-user text or audio during a conversation
to structured data that your apps and services can understand.
You design and build a Conversational Agents (Dialogflow CX) agent
to handle the types of conversations required for your system.
A Conversational Agents (Dialogflow CX) 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.
Select Auto-generate to create a
data store agent
or select Build your own to create other kinds of agents.
Complete the form for basic agent settings:
You can choose any display name.
Select your preferred
location.
Click the Edit button if you want to change advanced
location settings.
Select your preferred time zone.
Select the default language for your agent.
You cannot change the default language for an agent
once it is created.
Click Save.
API
If you have not already configured
location settings
for your project,
you must configure these settings with the console
before creating agents with the API.
Currently, you cannot configure location settings with the API.
To create an agent,
see the create method for the Agent type.
Select a protocol and version for the Agent reference:
Conversational Agents (Dialogflow CX) agents serve as top-level containers
for settings and data for virtual agents.
The following data is associated with agents:
For more information about how data is applied at varying levels, see the
data application levels.
Export and restore an agent
You can export an agent to a file,
and restore an agent with that file.
An agent export includes all agent data except the following:
Flow versions:
Only the draft flows are exported to file.
Environments:
Custom environments are not exported to file.
An agent restore overwrites all target agent data
(including all flow versions) except the following:
Environments:
All custom environments remain unchanged in the target agent.
Flow versions referenced by custom environments in the target agent
will continue to exist, as long as the associated environments exist.
However, these stale flow versions are not listed or selectable
flow versions for the agent.
Vertex AI Agents Apps:
The association to a Vertex AI Agents App remains unchanged
in the target agent. (In other words, the value of engine in
GenAppBuilderSettings)
This means that data store agents can only be restored
into other existing data store agents, because the resulting agent also needs
to have an association to a Vertex AI Agents App.
Vertex AI Agents Data Stores:
All references to data stores will be overwritten in the target agent
according to the following rules:
If the target agent isn't associated with an App, then it's not possible
to restore an agent with data store references into it. Trying to do so results
in an error message. To fix that, you can either
create a new data store agent from scratch. (Alternatively, you
can turn your existing agent into a data store agent by adding a data store
state handler
to it. In this case you'll be guided through adding an associated App to
your agent.)
If the target agent is associated with an App, then all the data store
references will be updated upon restore: their Google Cloud project ID and
location will be updated to match the App of the target agent. The
collection ID and data store ID will remain unchanged. This means that you
need to add data stores for all the IDs with matching types into the App
of the target agent prior to the restore operation.
Example: if the source agent refers to a data store named
projects/123/locations/eu-west2/collections/default_collection/dataStores/myDataStore1
and the App of the target agent is named
projects/321/locations/us-east1/collections/default_collections/engines/app123,
then the resulting data store reference in the target agent will become:
projects/321/locations/us-east1/collections/default_collection/dataStores/myDataStore1
When exporting,
you can select the export file format.
If you are using source control versioning for your agent data,
you should
export in the JSON format.
When you restore an agent,
Conversational Agents (Dialogflow CX) automatically determines the file format.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-07 UTC."],[[["\u003cp\u003eConversational Agents (Dialogflow CX) agents are virtual agents that utilize natural language understanding to handle concurrent conversations with end-users, translating text or audio into structured data.\u003c/p\u003e\n"],["\u003cp\u003eCreating an agent can be done via the Dialogflow CX console or API, with options to auto-generate a data store agent or build a custom agent.\u003c/p\u003e\n"],["\u003cp\u003eAgents serve as containers for virtual agent data like intents, entity types, webhooks, flows, pages, and route groups.\u003c/p\u003e\n"],["\u003cp\u003eAgents can be exported to a file (excluding flow versions and custom environments) and restored, overwriting existing data, with specific handling for data store agent associations and Vertex AI Agents Apps.\u003c/p\u003e\n"],["\u003cp\u003eDeleting an agent is permanent, requiring proper permissions and a backup via export is recommended, and deleting a project will immediately delete all associated agents.\u003c/p\u003e\n"]]],[],null,["# Agents\n\nA\n\n*Conversational Agents (Dialogflow CX) agent*\n\nis a virtual agent\nthat handles concurrent conversations with your end-users.\nIt is a natural language understanding module\nthat understands the nuances of human language.\nConversational Agents (Dialogflow CX) translates end-user text or audio during a conversation\nto structured data that your apps and services can understand.\nYou design and build a Conversational Agents (Dialogflow CX) agent\nto handle the types of conversations required for your system.\n\nA Conversational Agents (Dialogflow CX) agent is similar to a human call center agent.\nYou train them both to handle expected conversation scenarios,\nand your training does not need to be overly explicit.\n\nCreate an agent\n---------------\n\n| **Note:** You can create multiple Conversational Agents (Dialogflow CX) agents for one [Google Cloud project](/resource-manager/docs/creating-managing-projects).\n\nTo create an agent: \n\n### Console\n\n1. Open the [Dialogflow CX console](https://dialogflow.cloud.google.com/cx/projects).\n2. Create or choose a Google Cloud project.\n3. Click **Create agent**.\n4. Select **Auto-generate** to create a [data store agent](/dialogflow/cx/docs/concept/data-store-agent) or select **Build your own** to create other kinds of agents.\n5. Complete the form for basic agent settings:\n 1. You can choose any display name.\n 2. Select your preferred [location](/dialogflow/cx/docs/how/region#avail). Click the **Edit** button if you want to change advanced [location settings](/dialogflow/cx/docs/how/region#location-settings).\n 3. Select your preferred time zone.\n 4. Select the default language for your agent. You cannot change the default language for an agent once it is created.\n6. Click **Save**.\n\n### API\n\nIf you have not already configured\n[location settings](/dialogflow/cx/docs/concept/region#location-settings)\nfor your project,\nyou must configure these settings with the console\nbefore creating agents with the API.\nCurrently, you cannot configure location settings with the API.\n\nTo create an agent,\nsee the `create` method for the `Agent` type.\n\n\nGo to the Agent API reference \n**Select a protocol and version for the Agent reference:**\n\nClose\n\n\u003cbr /\u003e\n\nAgent data\n----------\n\nConversational Agents (Dialogflow CX) agents serve as top-level containers\nfor settings and data for virtual agents.\nThe following data is associated with agents:\n\n- [Intents](/dialogflow/cx/docs/concept/intent)\n- [Entity types](/dialogflow/cx/docs/concept/entity)\n- [Webhooks](/dialogflow/cx/docs/concept/webhook)\n- [Flows](/dialogflow/cx/docs/concept/flow)\n- [Pages](/dialogflow/cx/docs/concept/page)\n- [Route groups](/dialogflow/cx/docs/concept/handler#group)\n\nFor more information about how data is applied at varying levels, see the\n[data application levels](/dialogflow/cx/docs/concept/data-level).\n\nExport and restore an agent\n---------------------------\n\n| **Warning:** We will no longer export raw value credentials for OpenAPI Tools and Webhooks, starting Aug 15, 2025. You should migrate to store your credentials in Secret Manager. See [Webhook](/dialogflow/cx/docs/concept/webhook#secret-manager-auth) and [Tool](/dialogflow/cx/docs/concept/playbook/tool#secret-manager-auth) documentations for instructions.\n\nYou can export an agent to a file,\nand restore an agent with that file.\n\nAn agent export includes all agent data except the following:\n\n- [Flow versions](/dialogflow/cx/docs/concept/version): Only the draft flows are exported to file.\n- [Environments](/dialogflow/cx/docs/concept/version): Custom environments are not exported to file.\n\nAn agent restore overwrites all target agent data\n(including all flow versions) except the following:\n\n- [Environments](/dialogflow/cx/docs/concept/version): All custom environments remain unchanged in the target agent. Flow versions referenced by custom environments in the target agent will continue to exist, as long as the associated environments exist. However, these stale flow versions are not listed or selectable flow versions for the agent.\n- [Vertex AI Agents Apps](/generative-ai-app-builder/docs/agent-intro): The association to a Vertex AI Agents App remains unchanged in the target agent. (In other words, the value of `engine` in [GenAppBuilderSettings](/dialogflow/cx/docs/reference/rest/v3/projects.locations.agents#GenAppBuilderSettings)) This means that data store agents can only be restored into other existing data store agents, because the resulting agent also needs to have an association to a Vertex AI Agents App.\n- [Vertex AI Agents Data Stores](/generative-ai-app-builder/docs/agent-usage):\n All references to data stores will be overwritten in the target agent\n according to the following rules:\n\n - If the target agent isn't associated with an App, then it's not possible to restore an agent with data store references into it. Trying to do so results in an error message. To fix that, you can either [create a new data store agent](/generative-ai-app-builder/docs/agent-usage#create_a_data_store_agent) from scratch. (Alternatively, you can turn your existing agent into a data store agent by adding a data store [state handler](/dialogflow/cx/docs/concept/handler) to it. In this case you'll be guided through adding an associated App to your agent.)\n - If the target agent is associated with an App, then all the data store references will be updated upon restore: their Google Cloud project ID and location will be updated to match the App of the target agent. The collection ID and data store ID will remain unchanged. This means that you need to add data stores for all the IDs with matching types into the App of the target agent prior to the restore operation.\n\n Example: if the source agent refers to a data store named\n `projects/123/locations/eu-west2/collections/default_collection/dataStores/myDataStore1`\n and the App of the target agent is named\n `projects/321/locations/us-east1/collections/default_collections/engines/app123`,\n then the resulting data store reference in the target agent will become:\n `projects/321/locations/us-east1/collections/default_collection/dataStores/myDataStore1`\n\n| **Note:** in the API and in the contents of the exported data, a Vertex AI Agents App is called a GenAppBuilder Engine. For example in an exported JSON Package you can find the name of the engine in the `agent.json` file under the key `genAppBuilderSettings.engine`.\n\nWhen exporting,\nyou can select the export file format.\nIf you are using source control versioning for your agent data,\nyou should\n[export in the JSON format](/dialogflow/cx/docs/reference/json-export).\nWhen you restore an agent,\nConversational Agents (Dialogflow CX) automatically determines the file format.\n\nTo export or restore an agent: \n\n### Console\n\n1. Open the [Dialogflow CX console](https://dialogflow.cloud.google.com/cx/projects).\n2. Choose the Google Cloud project for the agent.\n3. Click the option *more_vert* menu for an agent in the list.\n4. Click the **Export** or **Restore** button.\n5. Follow instructions to complete.\n**Note:** To restore a data store agent, make sure that the target agent was created as a [data store agent](/generative-ai-app-builder/docs/agent-usage#create_a_data_store_agent). \n\n### API\n\nSee the `export` and `restore` methods for the `Agent` type.\n\n\nGo to the Agent API reference \n**Select a protocol and version for the Agent reference:**\n\nClose\n\n\u003cbr /\u003e\n\nIf the agent size exceeds the [maximum limit](/dialogflow/quotas#size), use the\nCloud Storage option for agent export and restore.\n\nIf you use GitHub, also see the\n[GitHub export/restore guide](/dialogflow/cx/docs/concept/github).\n\nDelete an agent\n---------------\n\n| **Caution:** Deleting an agent **cannot** be undone. [Export](#export) your agent to keep a backup if necessary.\n\nIn order to delete an agent,\nyou need a role that provides full access or edit access.\nSee the\n[access control guide](/dialogflow/cx/docs/concept/access-control)\nfor more information.\n\nTo delete an agent: \n\n### Console\n\n1. Open the [Dialogflow CX console](https://dialogflow.cloud.google.com/cx/projects).\n2. Choose the Google Cloud project for the agent.\n3. Click the option *more_vert* menu for an agent in the list.\n4. Click the delete *delete* button.\n5. Confirm deletion in the dialog.\n\n### API\n\nSee the `delete` method for the `Agent` type.\n\n\nGo to the Agent API reference \n**Select a protocol and version for the Agent reference:**\n\nClose\n\n\u003cbr /\u003e\n\nIf you\n[delete your project](/resource-manager/docs/creating-managing-projects#shutting_down_projects),\nall Conversational Agents (Dialogflow CX) agents and data associated with the project\nare deleted immediately."]]
