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Module airbyte_agent_sdk.connectors.google_ads

Google-Ads connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules​

  • airbyte_agent_sdk.connectors.google_ads.connector
  • airbyte_agent_sdk.connectors.google_ads.connector_model
  • airbyte_agent_sdk.connectors.google_ads.models
  • airbyte_agent_sdk.connectors.google_ads.types

Classes​

AccountsSearchData(**data: Any) : Search result data for accounts entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

customer_auto_tagging_enabled: bool | None : Whether auto-tagging is enabled for the account

customer_call_reporting_setting_call_conversion_action: str | None : Call conversion action resource name

customer_call_reporting_setting_call_conversion_reporting_enabled: bool | None : Whether call conversion reporting is enabled

customer_call_reporting_setting_call_reporting_enabled: bool | None : Whether call reporting is enabled

customer_conversion_tracking_setting_conversion_tracking_id: int | None : Conversion tracking ID

customer_conversion_tracking_setting_cross_account_conversion_tracking_id: int | None : Cross-account conversion tracking ID

customer_currency_code: str | None : Currency code for the account (e.g., USD)

customer_descriptive_name: str | None : Descriptive name of the customer account

customer_final_url_suffix: str | None : URL suffix appended to final URLs

customer_has_partners_badge: bool | None : Whether the account has a Google Partners badge

customer_id: int | None : Unique customer account ID

customer_manager: bool | None : Whether this is a manager (MCC) account

customer_optimization_score: float | None : Optimization score for the account (0.0 to 1.0)

customer_optimization_score_weight: float | None : Weight of the optimization score

customer_pay_per_conversion_eligibility_failure_reasons: list[typing.Any] | None : Reasons why pay-per-conversion is not eligible

customer_remarketing_setting_google_global_site_tag: str | None : Google global site tag snippet

customer_resource_name: str | None : Resource name of the customer

customer_test_account: bool | None : Whether this is a test account

customer_time_zone: str | None : Time zone of the account

customer_tracking_url_template: str | None : Tracking URL template for the account

model_config : The type of the None singleton.

segments_date: str | None : Date segment for the report row

AdGroupAdLabelsSearchData(**data: Any) : Search result data for ad_group_ad_labels entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

ad_group_ad_ad_id: int | None : Ad ID

ad_group_ad_label_resource_name: str | None : Resource name of the ad group ad label

label_id: int | None : Label ID

label_name: str | None : Label name

label_resource_name: str | None : Resource name of the label

model_config : The type of the None singleton.

AdGroupAdsSearchData(**data: Any) : Search result data for ad_group_ads entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

ad_group_ad_ad_display_url: str | None : Display URL of the ad

ad_group_ad_ad_final_mobile_urls: list[typing.Any] | None : Final mobile URLs for the ad

ad_group_ad_ad_final_url_suffix: str | None : Final URL suffix

ad_group_ad_ad_final_urls: list[typing.Any] | None : Final URLs for the ad

ad_group_ad_ad_group: str | None : Ad group resource name

ad_group_ad_ad_id: int | None : Ad ID

ad_group_ad_ad_name: str | None : Ad name

ad_group_ad_ad_resource_name: str | None : Resource name of the ad

ad_group_ad_ad_strength: str | None : Ad strength rating

ad_group_ad_ad_tracking_url_template: str | None : Tracking URL template

ad_group_ad_ad_type: str | None : Ad type

ad_group_ad_labels: list[typing.Any] | None : Labels applied to the ad group ad

ad_group_ad_policy_summary_approval_status: str | None : Policy approval status

ad_group_ad_policy_summary_review_status: str | None : Policy review status

ad_group_ad_resource_name: str | None : Resource name of the ad group ad

ad_group_ad_status: str | None : Ad group ad status (ENABLED, PAUSED, REMOVED)

ad_group_id: int | None : Parent ad group ID

model_config : The type of the None singleton.

segments_date: str | None : Date segment for the report row

AdGroupLabelsSearchData(**data: Any) : Search result data for ad_group_labels entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

ad_group_id: int | None : Ad group ID

ad_group_label_resource_name: str | None : Resource name of the ad group label

label_id: int | None : Label ID

label_name: str | None : Label name

label_resource_name: str | None : Resource name of the label

model_config : The type of the None singleton.

AdGroupsSearchData(**data: Any) : Search result data for ad_groups entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

ad_group_ad_rotation_mode: str | None : Ad rotation mode

ad_group_base_ad_group: str | None : Base ad group resource name

ad_group_campaign: str | None : Parent campaign resource name

ad_group_cpc_bid_micros: int | None : CPC bid in micros

ad_group_cpm_bid_micros: int | None : CPM bid in micros

ad_group_cpv_bid_micros: int | None : CPV bid in micros

ad_group_effective_target_cpa_micros: int | None : Effective target CPA in micros

ad_group_effective_target_cpa_source: str | None : Source of the effective target CPA

ad_group_effective_target_roas: float | None : Effective target ROAS

ad_group_effective_target_roas_source: str | None : Source of the effective target ROAS

ad_group_id: int | None : Ad group ID

ad_group_labels: list[typing.Any] | None : Labels applied to the ad group

ad_group_name: str | None : Ad group name

ad_group_resource_name: str | None : Resource name of the ad group

ad_group_status: str | None : Ad group status (ENABLED, PAUSED, REMOVED)

ad_group_target_cpa_micros: int | None : Target CPA in micros

ad_group_target_roas: float | None : Target ROAS

ad_group_tracking_url_template: str | None : Tracking URL template

ad_group_type: str | None : Ad group type

campaign_id: int | None : Parent campaign ID

metrics_cost_micros: int | None : Cost in micros

model_config : The type of the None singleton.

segments_date: str | None : Date segment for the report row

AirbyteAuthConfig(**data: Any) : Authentication configuration for Airbyte hosted mode execution.

Pass this to the connector's auth_config parameter to use hosted mode, where API credentials are stored securely in Airbyte Cloud.

For hosted mode execution, provide client credentials with either:

  • connector_id: Direct connector/source ID (skips lookup)
  • workspace_name: Workspace name for connector lookup

Attributes: workspace_name: Workspace name for hosted mode connector lookup organization_id: Optional Airbyte organization ID for multi-org selection airbyte_client_id: Airbyte OAuth client ID (required for hosted mode) airbyte_client_secret: Airbyte OAuth client secret (required for hosted mode) connector_id: Specific connector/source ID (skips lookup if provided)

Examples:

Hosted mode with connector_id (no lookup needed)

connector = GongConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with workspace_name (lookup by workspace)

connector = GongConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

airbyte_client_id: str | None : The type of the None singleton.

airbyte_client_secret: str | None : The type of the None singleton.

connector_id: str | None : The type of the None singleton.

model_config : The type of the None singleton.

organization_id: str | None : The type of the None singleton.

workspace_name: str | None : The type of the None singleton.

AirbyteSearchMeta(**data: Any) : Pagination metadata for search responses.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

cursor: str | None : Cursor for fetching the next page of results.

has_more: bool : Whether more results are available.

model_config : The type of the None singleton.

took_ms: int | None : Time taken to execute the search in milliseconds.

AirbyteSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel
  • typing.Generic

Descendants​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[AccountsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[AdGroupAdLabelsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[AdGroupAdsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[AdGroupLabelsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[AdGroupsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[CampaignLabelsSearchData]
  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult[CampaignsSearchData]

Class variables​

data: list[~D] : List of matching records.

meta: airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchMeta : Pagination metadata.

model_config : The type of the None singleton.

AccountsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

AdGroupAdLabelsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

AdGroupAdsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

AdGroupLabelsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

AdGroupsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

CampaignLabelsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

CampaignsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • airbyte_agent_sdk.connectors.google_ads.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

CampaignLabelsSearchData(**data: Any) : Search result data for campaign_labels entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

campaign_id: int | None : Campaign ID

campaign_label_resource_name: str | None : Resource name of the campaign label

label_id: int | None : Label ID

label_name: str | None : Label name

label_resource_name: str | None : Resource name of the label

model_config : The type of the None singleton.

CampaignsSearchData(**data: Any) : Search result data for campaigns entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

campaign_advertising_channel_sub_type: str | None : Advertising channel sub-type

campaign_advertising_channel_type: str | None : Advertising channel type (SEARCH, DISPLAY, etc.)

campaign_bidding_strategy: str | None : Bidding strategy resource name

campaign_bidding_strategy_type: str | None : Bidding strategy type

campaign_budget_amount_micros: int | None : Campaign budget amount in micros

campaign_campaign_budget: str | None : Campaign budget resource name

campaign_end_date: str | None : Campaign end date

campaign_id: int | None : Campaign ID

campaign_labels: list[typing.Any] | None : Labels applied to the campaign

campaign_name: str | None : Campaign name

campaign_network_settings_target_content_network: bool | None : Whether targeting content network

campaign_network_settings_target_google_search: bool | None : Whether targeting Google Search

campaign_network_settings_target_partner_search_network: bool | None : Whether targeting partner search network

campaign_network_settings_target_search_network: bool | None : Whether targeting search network

campaign_resource_name: str | None : Resource name of the campaign

campaign_serving_status: str | None : Campaign serving status

campaign_start_date: str | None : Campaign start date

campaign_status: str | None : Campaign status (ENABLED, PAUSED, REMOVED)

metrics_average_cpc: float | None : Average cost per click

metrics_average_cpm: float | None : Average cost per thousand impressions

metrics_clicks: int | None : Number of clicks

metrics_conversions: float | None : Number of conversions

metrics_conversions_value: float | None : Total conversions value

metrics_cost_micros: int | None : Cost in micros

metrics_ctr: float | None : Click-through rate

metrics_impressions: int | None : Number of impressions

metrics_interactions: int | None : Number of interactions

model_config : The type of the None singleton.

segments_ad_network_type: str | None : Ad network type segment

segments_date: str | None : Date segment for the report row

segments_hour: int | None : Hour segment

GoogleAdsAuthConfig(**data: Any) : OAuth2 Authentication

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

client_id: str : OAuth2 client ID from Google Cloud Console

client_secret: str : OAuth2 client secret from Google Cloud Console

developer_token: str : Google Ads API developer token

model_config : The type of the None singleton.

refresh_token: str : OAuth2 refresh token

GoogleAdsConnector(auth_config: GoogleAdsAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Google-Ads API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new google-ads connector instance.

Supports both local and hosted execution modes:

  • Local mode: Provide connector-specific auth config (e.g., GoogleAdsAuthConfig)
  • Hosted mode: Provide AirbyteAuthConfig with client credentials and either connector_id or workspace_name

Args: auth_config: Either connector-specific auth config for local mode, or AirbyteAuthConfig for hosted mode on_token_refresh: Optional callback for OAuth2 token refresh persistence. Called with new_tokens dict when tokens are refreshed. Can be sync or async. Example: lambda tokens: save_to_database(tokens) Examples:

Local mode (direct API calls)

connector = GoogleAdsConnector(auth_config=GoogleAdsAuthConfig(client_id="...", client_secret="...", refresh_token="...", developer_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = GoogleAdsConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with lookup by workspace_name

connector = GoogleAdsConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Class variables​

connector_name : The type of the None singleton.

connector_version : The type of the None singleton.

sdk_version : The type of the None singleton.

Static methods​

create(*, airbyte_config: AirbyteAuthConfig, auth_config: "'GoogleAdsAuthConfig' | None" = None, server_side_oauth_secret_id: str | None = None, name: str | None = None, replication_config: "'GoogleAdsReplicationConfig' | None" = None, source_template_id: str | None = None) : Create a new hosted connector on Airbyte Cloud.

This factory method:

  1. Creates a source on Airbyte Cloud with the provided credentials
  2. Returns a connector configured with the new connector_id

Supports two authentication modes:

  1. Direct credentials: Provide auth_config with typed credentials
  2. Server-side OAuth: Provide server_side_oauth_secret_id from OAuth flow

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. auth_config: Typed auth config. Required unless using server_side_oauth_secret_id. server_side_oauth_secret_id: OAuth secret ID from get_consent_url redirect. When provided, auth_config is not required. name: Optional source name (defaults to connector name + workspace_name) replication_config: Typed replication settings. Required for connectors with x-airbyte-replication-config (REPLICATION mode sources). source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: A GoogleAdsConnector instance configured in hosted mode

Raises: ValueError: If neither or both auth_config and server_side_oauth_secret_id provided

Example:

Create a new hosted connector with API key auth

connector = await GoogleAdsConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), auth_config=GoogleAdsAuthConfig(client_id="...", client_secret="...", refresh_token="...", developer_token="..."), )

With replication config (required for this connector):

connector = await GoogleAdsConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), auth_config=GoogleAdsAuthConfig(client_id="...", client_secret="...", refresh_token="...", developer_token="..."), replication_config=GoogleAdsReplicationConfig(customer_id="...", start_date="...", conversion_window_days="..."), )

With server-side OAuth:

connector = await GoogleAdsConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), server_side_oauth_secret_id="airbyte_oauth_...secret...", replication_config=GoogleAdsReplicationConfig(customer_id="...", start_date="...", conversion_window_days="..."), )

Use the connector

result = await connector.execute("entity", "list", {})

get_consent_url(*, airbyte_config: AirbyteAuthConfig, redirect_url: str, name: str | None = None, replication_config: "'GoogleAdsReplicationConfig' | None" = None, source_template_id: str | None = None) : Initiate server-side OAuth flow with auto-source creation.

Returns a consent URL where the end user should be redirected to grant access. After completing consent, the source is automatically created and the user is redirected to your redirect_url with a connector_id query parameter.

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. redirect_url: URL where users will be redirected after OAuth consent. After consent, user arrives at: redirect_url?connector_id=... name: Optional name for the source. Defaults to connector name + workspace_name. replication_config: Typed replication settings. Merged with OAuth credentials. source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: The OAuth consent URL

Example: consent_url = await GoogleAdsConnector.get_consent_url( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), redirect_url="https://myapp.com/oauth/callback", name="My Google-Ads Source", replication_config=GoogleAdsReplicationConfig(customer_id="...", start_date="...", conversion_window_days="..."), )

Redirect user to: consent_url

After consent, user arrives at: https://myapp.com/oauth/callback?connector_id=...

tool_utils(func: _F | None = None, *, update_docstring: bool = True, max_output_chars: int | None = 100000, framework: FrameworkName | None = None, internal_retries: int = 0, should_internal_retry: Callable[[Exception, tuple[Any, ...], dict[str, Any]], bool] | None = None, exhausted_runtime_failure_message: Callable[[Exception, tuple[Any, ...], dict[str, Any]], str | None] | None = None) ‑> ~_F | Callable[[~_F], ~_F] : Decorator that adds tool utilities like docstring augmentation and output limits.

Composes :func:airbyte_agent_sdk.translation.translate_exceptions for runtime wrapping (sync/async branch + output-size check + framework signal translation + optional internal retry loop), and adds connector-specific docstring augmentation on top of it.

Usage: @mcp.tool() @GoogleAdsConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @GoogleAdsConnector.tool_utils(update_docstring=False, max_output_chars=None) async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @GoogleAdsConnector.tool_utils(framework="pydantic_ai", internal_retries=2) async def execute(entity: str, action: str, params: dict): ...

Args: update_docstring: When True, append connector capabilities to doc. max_output_chars: Max serialized output size before raising. Use None to disable. framework: One of "pydantic_ai" | "langchain" | "openai_agents" | "mcp". Defaults to None → auto-detect by attempting each framework's canonical import in order. Explicit always wins. internal_retries: How many transient runtime failures (429/5xx, network, timeout) to retry silently before surfacing. Default 0. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. should_internal_retry: Optional predicate (error, args, kwargs) -> bool further restricting which retryable errors are safe for this specific tool. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. exhausted_runtime_failure_message: Optional callback (error, args, kwargs) -> str | None. Invoked after internal retries are exhausted OR were skipped via should_internal_retry returning False. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions.

Instance variables​

connector_id: str | None : Get the connector/source ID (only available in hosted mode).

Returns: The connector ID if in hosted mode, None if in local mode.

Example: connector = await GoogleAdsConnector.create(...) print(f"Created connector: {connector.connector_id}")

Methods​

check(self) ‑> airbyte_agent_sdk.connectors.google_ads.models.GoogleAdsCheckResult : Perform a health check to verify connectivity and credentials.

Executes a lightweight list operation (limit=1) to validate that the connector can communicate with the API and credentials are valid.

Returns: GoogleAdsCheckResult with status ("healthy" or "unhealthy") and optional error message

Example: result = await connector.check() if result.status == "healthy": print("Connection verified!") else: print(f"Check failed: {result.error}")

close(self) : Close the connector and release resources.

entity_schema(self, entity: str) ‑> dict[str, typing.Any] | None : Get the JSON schema for an entity.

Args: entity: Entity name (e.g., "contacts", "companies")

Returns: JSON schema dict describing the entity structure, or None if not found.

Example: schema = connector.entity_schema("contacts") if schema: print(f"Contact properties: {list(schema.get('properties', {}).keys())}")

execute(self, entity: str, action: "Literal['list', 'update', 'create', 'context_store_search']", params: Mapping[str, Any] | None = None) ‑> Any : Execute an entity operation with full type safety.

This is the recommended interface for blessed connectors as it:

  • Uses the same signature as non-blessed connectors
  • Provides full IDE autocomplete for entity/action/params
  • Makes migration from generic to blessed connectors seamless

Args: entity: Entity name (e.g., "customers") action: Operation action (e.g., "create", "get", "list") params: Operation parameters (typed based on entity+action)

Returns: Typed response based on the operation

Example: customer = await connector.execute( entity="customers", action="get", params={"id": "cus_123"} )

list_entities(self) ‑> list[dict[str, typing.Any]] : Get structured data about available entities, actions, and parameters.

Returns a list of entity descriptions with:

  • entity_name: Name of the entity (e.g., "contacts", "deals")
  • description: Entity description from the first endpoint
  • available_actions: List of actions (e.g., ["list", "get", "create"])
  • parameters: Dict mapping action -> list of parameter dicts

Example: entities = connector.list_entities() for entity in entities: print(f"{entity['entity_name']}: {entity['available_actions']}")

GoogleAdsReplicationConfig(**data: Any) : Replication Configuration - Settings for data replication from Google Ads.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)​

  • pydantic.main.BaseModel

Class variables​

conversion_window_days: int | None : Number of days for the conversion attribution window. Default is 14.

customer_id: str : Comma-separated list of Google Ads customer IDs (10 digits each, no dashes).

model_config : The type of the None singleton.

start_date: str | None : UTC date in YYYY-MM-DD format from which to start replicating data. Defaults to 2 years ago if not specified.

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