close()

Close httplib2 connections.

delete(name, x__xgafv=None)

Deletes a reasoning engine revision.

Args:
name: string, Required. The name of the ReasoningEngineRuntimeRevision resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtime_revision}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # This resource represents a long-running operation that is the result of a network API call.
"done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
"details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
{
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
"message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
},
"metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
"name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
"response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
}

get(name, x__xgafv=None)

Gets a reasoning engine runtime revision.

Args:
name: string, Required. The name of the ReasoningEngineRuntimeRevision resource. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtimeRevision}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # ReasoningEngineRuntimeRevision is a specific version of the runtime related part of ReasoningEngine. Contains only the fields that are revision specific.
"createTime": "A String", # Output only. Timestamp when this ReasoningEngineRuntimeRevision was created.
"name": "A String", # Identifier. The resource name of the ReasoningEngineRuntimeRevision. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtime_revision}`
"spec": { # ReasoningEngine configurations # Immutable. Configurations of the ReasoningEngineRuntimeRevision. Contains only revision specific fields.
"agentCard": { # Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the-agent-card.
"a_key": "", # Properties of the object.
},
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
},
],
"containerSpec": { # Specification for deploying from a container image. # Deploy from a container image with a defined entrypoint and commands.
"imageUri": "A String", # Required. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.
},
"deploymentSpec": { # The specification of a Reasoning Engine deployment. # Optional. The specification of a Reasoning Engine deployment.
"agentGatewayConfig": { # Agent Gateway configuration for a Reasoning Engine deployment. # Optional. Agent Gateway configuration for the Reasoning Engine deployment.
"agentToAnywhereConfig": { # Configuration for traffic originating from a Reasoning Engine. # Optional. Configuration for traffic originating from the Reasoning Engine. When unset, outgoing traffic is not routed through an Agent Gateway.
"agentGateway": "A String", # Required. The resource name of the Agent Gateway for outbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `AGENT_TO_ANYWHERE`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`
},
"clientToAgentConfig": { # Configuration for traffic targeting a Reasoning Engine. # Optional. Configuration for traffic targeting the Reasoning Engine. When unset, incoming traffic is not routed through an Agent Gateway.
"agentGateway": "A String", # Required. The resource name of the Agent Gateway to use for inbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `CLIENT_TO_AGENT`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`
},
},
"agentServerMode": "A String", # The agent server mode.
"containerConcurrency": 42, # Optional. Concurrency for each container and agent server. Recommended value: 2 * cpu + 1. Defaults to 9.
"env": [ # Optional. Environment variables to be set with the Reasoning Engine deployment. The environment variables can be updated through the UpdateReasoningEngine API.
{ # Represents an environment variable present in a Container or Python Module.
"name": "A String", # Required. Name of the environment variable. Must be a valid C identifier.
"value": "A String", # Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
},
],
"keepAliveProbe": { # Represents the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings. # Optional. Specifies the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings.
"httpGet": { # Specifies the HTTP GET configuration for the probe. # Optional. Specifies the HTTP GET configuration for the probe.
"path": "A String", # Required. Specifies the path of the HTTP GET request (e.g., `"/is_busy"`).
"port": 42, # Optional. Specifies the port number on the container to which the request is sent.
},
"maxSeconds": 42, # Optional. Specifies the maximum duration (in seconds) to keep the instance alive via this probe. Can be a maximum of 3600 seconds (1 hour).
},
"maxInstances": 42, # Optional. The maximum number of application instances that can be launched to handle increased traffic. Defaults to 100. Range: [1, 1000]. If VPC-SC or PSC-I is enabled, the acceptable range is [1, 100].
"minInstances": 42, # Optional. The minimum number of application instances that will be kept running at all times. Defaults to 1. Range: [0, 75].
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I.
"dnsPeeringConfigs": [ # Optional. DNS peering configurations. When specified, Vertex AI will attempt to configure DNS peering zones in the tenant project VPC to resolve the specified domains using the target network's Cloud DNS. The user must grant the dns.peer role to the Vertex AI Service Agent on the target project.
{ # DNS peering configuration. These configurations are used to create DNS peering zones in the Vertex tenant project VPC, enabling resolution of records within the specified domain hosted in the target network's Cloud DNS.
"domain": "A String", # Required. The DNS name suffix of the zone being peered to, e.g., "my-internal-domain.corp.". Must end with a dot.
"targetNetwork": "A String", # Required. The VPC network name in the target_project where the DNS zone specified by 'domain' is visible.
"targetProject": "A String", # Required. The project ID hosting the Cloud DNS managed zone that contains the 'domain'. The Vertex AI Service Agent requires the dns.peer role on this project.
},
],
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"resourceLimits": { # Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {"cpu": "4", "memory": "4Gi"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits
"a_key": "A String",
},
"secretEnv": [ # Optional. Environment variables where the value is a secret in Cloud Secret Manager. To use this feature, add 'Secret Manager Secret Accessor' role (roles/secretmanager.secretAccessor) to AI Platform Reasoning Engine Service Agent.
{ # Represents an environment variable where the value is a secret in Cloud Secret Manager.
"name": "A String", # Required. Name of the secret environment variable.
"secretRef": { # Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable. # Required. Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable.
"secret": "A String", # Required. The name of the secret in Cloud Secret Manager. Format: {secret_name}.
"version": "A String", # The Cloud Secret Manager secret version. Can be 'latest' for the latest version, an integer for a specific version, or a version alias.
},
},
],
},
"effectiveIdentity": "A String", # Output only. The identity to use for the Reasoning Engine. It can contain one of the following values: * service-{project}@gcp-sa-aiplatform-re.googleapis.com (for SERVICE_AGENT identity type) * {name}@{project}.gserviceaccount.com (for SERVICE_ACCOUNT identity type) * agents.global.{org}.system.id.goog/resources/aiplatform/projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} (for AGENT_IDENTITY identity type)
"identityType": "A String", # Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used.
"packageSpec": { # User-provided package specification, containing pickled object and package requirements. # Optional. User provided package spec of the ReasoningEngine. Ignored when users directly specify a deployment image through `deployment_spec.first_party_image_override`, but keeping the field_behavior to avoid introducing breaking changes. The `deployment_source` field should not be set if `package_spec` is specified.
"dependencyFilesGcsUri": "A String", # Optional. The Cloud Storage URI of the dependency files in tar.gz format.
"pickleObjectGcsUri": "A String", # Optional. The Cloud Storage URI of the pickled python object.
"pythonVersion": "A String", # Optional. The Python version. Supported values are 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, the default value is 3.10.
"requirementsGcsUri": "A String", # Optional. The Cloud Storage URI of the `requirements.txt` file
},
"serviceAccount": "A String", # Optional. The service account that the Reasoning Engine artifact runs as. It should have "roles/storage.objectViewer" for reading the user project's Cloud Storage and "roles/aiplatform.user" for using Vertex extensions. If not specified, the Vertex AI Reasoning Engine Service Agent in the project will be used.
"sourceCodeSpec": { # Specification for deploying from source code. # Deploy from source code files with a defined entrypoint.
"agentConfigSource": { # Specification for the deploying from agent config. # Source code is generated from the agent config.
"adkConfig": { # Configuration for the Agent Development Kit (ADK). # Required. The ADK configuration.
"jsonConfig": { # Required. The value of the ADK config in JSON format.
"a_key": "", # Properties of the object.
},
},
"inlineSource": { # Specifies source code provided as a byte stream. # Optional. Any additional files needed to interpret the config. If a `requirements.txt` file is present in the `inline_source`, the corresponding packages will be installed. If no `requirements.txt` file is present in `inline_source`, then the latest version of `google-adk` will be installed for interpreting the ADK config.
"sourceArchive": "A String", # Required. Input only. The application source code archive. It must be a compressed tarball (.tar.gz) file.
},
},
"developerConnectSource": { # Specifies source code to be fetched from a Git repository managed through the Developer Connect service. # Source code is in a Git repository managed by Developer Connect.
"config": { # Specifies the configuration for fetching source code from a Git repository that is managed by Developer Connect. This includes the repository, revision, and directory to use. # Required. The Developer Connect configuration that defines the specific repository, revision, and directory to use as the source code root.
"dir": "A String", # Required. Directory, relative to the source root, in which to run the build.
"gitRepositoryLink": "A String", # Required. The Developer Connect Git repository link, formatted as `projects/*/locations/*/connections/*/gitRepositoryLink/*`.
"revision": "A String", # Required. The revision to fetch from the Git repository such as a branch, a tag, a commit SHA, or any Git ref.
},
},
"imageSpec": { # The image spec for building an image (within a single build step), based on the config file (i.e. Dockerfile) in the source directory. # Optional. Configuration for building an image with custom config file.
"buildArgs": { # Optional. Build arguments to be used. They will be passed through --build-arg flags.
"a_key": "A String",
},
},
"inlineSource": { # Specifies source code provided as a byte stream. # Source code is provided directly in the request.
"sourceArchive": "A String", # Required. Input only. The application source code archive. It must be a compressed tarball (.tar.gz) file.
},
"pythonSpec": { # Specification for running a Python application from source. # Configuration for a Python application.
"entrypointModule": "A String", # Optional. The Python module to load as the entrypoint, specified as a fully qualified module name. For example: path.to.agent. If not specified, defaults to "agent". The project root will be added to Python sys.path, allowing imports to be specified relative to the root. This field should not be set if the source is `agent_config_source`.
"entrypointObject": "A String", # Optional. The name of the callable object within the `entrypoint_module` to use as the application If not specified, defaults to "root_agent". This field should not be set if the source is `agent_config_source`.
"requirementsFile": "A String", # Optional. The path to the requirements file, relative to the source root. If not specified, defaults to "requirements.txt".
"version": "A String", # Optional. The version of Python to use. Support version includes 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, default value is 3.10.
},
},
},
"state": "A String", # Output only. The state of the revision.
}

list(parent, filter=None, pageSize=None, pageToken=None, x__xgafv=None)

Lists runtime revisions in a reasoning engine.

Args:
parent: string, Required. The resource name of the ReasoningEngine to list the ReasoningEngineRuntimeRevisions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` (required)
filter: string, Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160).
pageSize: integer, Optional. The maximum number of ReasoningEngineRuntimeRevisions to return. The service may return fewer than this value. If unspecified, at most 50 revisions will be returned. The maximum value is 100; values above 100 will be coerced to 100.
pageToken: string, Optional. The standard list page token.
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format

Returns:
An object of the form:

{ # Response message for ReasoningEngineRuntimeRevisionService.ListReasoningEngineRuntimeRevisions
"nextPageToken": "A String", # A token to retrieve the next page of results. Pass to ListReasoningEngineRuntimeRevisionsRequest.page_token to obtain that page.
"reasoningEngineRuntimeRevisions": [ # List of ReasoningEngineRuntimeRevisions in the requested page.
{ # ReasoningEngineRuntimeRevision is a specific version of the runtime related part of ReasoningEngine. Contains only the fields that are revision specific.
"createTime": "A String", # Output only. Timestamp when this ReasoningEngineRuntimeRevision was created.
"name": "A String", # Identifier. The resource name of the ReasoningEngineRuntimeRevision. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/runtimeRevisions/{runtime_revision}`
"spec": { # ReasoningEngine configurations # Immutable. Configurations of the ReasoningEngineRuntimeRevision. Contains only revision specific fields.
"agentCard": { # Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the-agent-card.
"a_key": "", # Properties of the object.
},
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
},
],
"containerSpec": { # Specification for deploying from a container image. # Deploy from a container image with a defined entrypoint and commands.
"imageUri": "A String", # Required. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.
},
"deploymentSpec": { # The specification of a Reasoning Engine deployment. # Optional. The specification of a Reasoning Engine deployment.
"agentGatewayConfig": { # Agent Gateway configuration for a Reasoning Engine deployment. # Optional. Agent Gateway configuration for the Reasoning Engine deployment.
"agentToAnywhereConfig": { # Configuration for traffic originating from a Reasoning Engine. # Optional. Configuration for traffic originating from the Reasoning Engine. When unset, outgoing traffic is not routed through an Agent Gateway.
"agentGateway": "A String", # Required. The resource name of the Agent Gateway for outbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `AGENT_TO_ANYWHERE`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`
},
"clientToAgentConfig": { # Configuration for traffic targeting a Reasoning Engine. # Optional. Configuration for traffic targeting the Reasoning Engine. When unset, incoming traffic is not routed through an Agent Gateway.
"agentGateway": "A String", # Required. The resource name of the Agent Gateway to use for inbound traffic. It must be set to a Google-managed gateway whose `governed_access_path` is `CLIENT_TO_AGENT`. Format: `projects/{project}/locations/{location}/agentGateways/{agent_gateway}`
},
},
"agentServerMode": "A String", # The agent server mode.
"containerConcurrency": 42, # Optional. Concurrency for each container and agent server. Recommended value: 2 * cpu + 1. Defaults to 9.
"env": [ # Optional. Environment variables to be set with the Reasoning Engine deployment. The environment variables can be updated through the UpdateReasoningEngine API.
{ # Represents an environment variable present in a Container or Python Module.
"name": "A String", # Required. Name of the environment variable. Must be a valid C identifier.
"value": "A String", # Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not.
},
],
"keepAliveProbe": { # Represents the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings. # Optional. Specifies the configuration for keep-alive probe. Contains configuration on a specified endpoint that a deployment host should use to keep the container alive based on the probe settings.
"httpGet": { # Specifies the HTTP GET configuration for the probe. # Optional. Specifies the HTTP GET configuration for the probe.
"path": "A String", # Required. Specifies the path of the HTTP GET request (e.g., `"/is_busy"`).
"port": 42, # Optional. Specifies the port number on the container to which the request is sent.
},
"maxSeconds": 42, # Optional. Specifies the maximum duration (in seconds) to keep the instance alive via this probe. Can be a maximum of 3600 seconds (1 hour).
},
"maxInstances": 42, # Optional. The maximum number of application instances that can be launched to handle increased traffic. Defaults to 100. Range: [1, 1000]. If VPC-SC or PSC-I is enabled, the acceptable range is [1, 100].
"minInstances": 42, # Optional. The minimum number of application instances that will be kept running at all times. Defaults to 1. Range: [0, 75].
"pscInterfaceConfig": { # Configuration for PSC-I. # Optional. Configuration for PSC-I.
"dnsPeeringConfigs": [ # Optional. DNS peering configurations. When specified, Vertex AI will attempt to configure DNS peering zones in the tenant project VPC to resolve the specified domains using the target network's Cloud DNS. The user must grant the dns.peer role to the Vertex AI Service Agent on the target project.
{ # DNS peering configuration. These configurations are used to create DNS peering zones in the Vertex tenant project VPC, enabling resolution of records within the specified domain hosted in the target network's Cloud DNS.
"domain": "A String", # Required. The DNS name suffix of the zone being peered to, e.g., "my-internal-domain.corp.". Must end with a dot.
"targetNetwork": "A String", # Required. The VPC network name in the target_project where the DNS zone specified by 'domain' is visible.
"targetProject": "A String", # Required. The project ID hosting the Cloud DNS managed zone that contains the 'domain'. The Vertex AI Service Agent requires the dns.peer role on this project.
},
],
"networkAttachment": "A String", # Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network-attachments#create-network-attachments). This field is only used for resources using PSC-I.
},
"resourceLimits": { # Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {"cpu": "4", "memory": "4Gi"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits
"a_key": "A String",
},
"secretEnv": [ # Optional. Environment variables where the value is a secret in Cloud Secret Manager. To use this feature, add 'Secret Manager Secret Accessor' role (roles/secretmanager.secretAccessor) to AI Platform Reasoning Engine Service Agent.
{ # Represents an environment variable where the value is a secret in Cloud Secret Manager.
"name": "A String", # Required. Name of the secret environment variable.
"secretRef": { # Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable. # Required. Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable.
"secret": "A String", # Required. The name of the secret in Cloud Secret Manager. Format: {secret_name}.
"version": "A String", # The Cloud Secret Manager secret version. Can be 'latest' for the latest version, an integer for a specific version, or a version alias.
},
},
],
},
"effectiveIdentity": "A String", # Output only. The identity to use for the Reasoning Engine. It can contain one of the following values: * service-{project}@gcp-sa-aiplatform-re.googleapis.com (for SERVICE_AGENT identity type) * {name}@{project}.gserviceaccount.com (for SERVICE_ACCOUNT identity type) * agents.global.{org}.system.id.goog/resources/aiplatform/projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} (for AGENT_IDENTITY identity type)
"identityType": "A String", # Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used.
"packageSpec": { # User-provided package specification, containing pickled object and package requirements. # Optional. User provided package spec of the ReasoningEngine. Ignored when users directly specify a deployment image through `deployment_spec.first_party_image_override`, but keeping the field_behavior to avoid introducing breaking changes. The `deployment_source` field should not be set if `package_spec` is specified.
"dependencyFilesGcsUri": "A String", # Optional. The Cloud Storage URI of the dependency files in tar.gz format.
"pickleObjectGcsUri": "A String", # Optional. The Cloud Storage URI of the pickled python object.
"pythonVersion": "A String", # Optional. The Python version. Supported values are 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, the default value is 3.10.
"requirementsGcsUri": "A String", # Optional. The Cloud Storage URI of the `requirements.txt` file
},
"serviceAccount": "A String", # Optional. The service account that the Reasoning Engine artifact runs as. It should have "roles/storage.objectViewer" for reading the user project's Cloud Storage and "roles/aiplatform.user" for using Vertex extensions. If not specified, the Vertex AI Reasoning Engine Service Agent in the project will be used.
"sourceCodeSpec": { # Specification for deploying from source code. # Deploy from source code files with a defined entrypoint.
"agentConfigSource": { # Specification for the deploying from agent config. # Source code is generated from the agent config.
"adkConfig": { # Configuration for the Agent Development Kit (ADK). # Required. The ADK configuration.
"jsonConfig": { # Required. The value of the ADK config in JSON format.
"a_key": "", # Properties of the object.
},
},
"inlineSource": { # Specifies source code provided as a byte stream. # Optional. Any additional files needed to interpret the config. If a `requirements.txt` file is present in the `inline_source`, the corresponding packages will be installed. If no `requirements.txt` file is present in `inline_source`, then the latest version of `google-adk` will be installed for interpreting the ADK config.
"sourceArchive": "A String", # Required. Input only. The application source code archive. It must be a compressed tarball (.tar.gz) file.
},
},
"developerConnectSource": { # Specifies source code to be fetched from a Git repository managed through the Developer Connect service. # Source code is in a Git repository managed by Developer Connect.
"config": { # Specifies the configuration for fetching source code from a Git repository that is managed by Developer Connect. This includes the repository, revision, and directory to use. # Required. The Developer Connect configuration that defines the specific repository, revision, and directory to use as the source code root.
"dir": "A String", # Required. Directory, relative to the source root, in which to run the build.
"gitRepositoryLink": "A String", # Required. The Developer Connect Git repository link, formatted as `projects/*/locations/*/connections/*/gitRepositoryLink/*`.
"revision": "A String", # Required. The revision to fetch from the Git repository such as a branch, a tag, a commit SHA, or any Git ref.
},
},
"imageSpec": { # The image spec for building an image (within a single build step), based on the config file (i.e. Dockerfile) in the source directory. # Optional. Configuration for building an image with custom config file.
"buildArgs": { # Optional. Build arguments to be used. They will be passed through --build-arg flags.
"a_key": "A String",
},
},
"inlineSource": { # Specifies source code provided as a byte stream. # Source code is provided directly in the request.
"sourceArchive": "A String", # Required. Input only. The application source code archive. It must be a compressed tarball (.tar.gz) file.
},
"pythonSpec": { # Specification for running a Python application from source. # Configuration for a Python application.
"entrypointModule": "A String", # Optional. The Python module to load as the entrypoint, specified as a fully qualified module name. For example: path.to.agent. If not specified, defaults to "agent". The project root will be added to Python sys.path, allowing imports to be specified relative to the root. This field should not be set if the source is `agent_config_source`.
"entrypointObject": "A String", # Optional. The name of the callable object within the `entrypoint_module` to use as the application If not specified, defaults to "root_agent". This field should not be set if the source is `agent_config_source`.
"requirementsFile": "A String", # Optional. The path to the requirements file, relative to the source root. If not specified, defaults to "requirements.txt".
"version": "A String", # Optional. The version of Python to use. Support version includes 3.9, 3.10, 3.11, 3.12, 3.13, 3.14. If not specified, default value is 3.10.
},
},
},
"state": "A String", # Output only. The state of the revision.
},
],
}

list_next()

Retrieves the next page of results.

        Args:
          previous_request: The request for the previous page. (required)
          previous_response: The response from the request for the previous page. (required)

        Returns:
          A request object that you can call 'execute()' on to request the next
          page. Returns None if there are no more items in the collection.

query(name, body=None, x__xgafv=None)

Queries using a reasoning engine.

Args:
  name: string, Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for ReasoningEngineExecutionService.Query.
  "classMethod": "A String", # Optional. Class method to be used for the query. It is optional and defaults to "query" if unspecified.
  "input": { # Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.
    "a_key": "", # Properties of the object.
  },
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Response message for ReasoningEngineExecutionService.Query
  "output": "", # Response provided by users in JSON object format.
}

streamQuery(name, body=None, x__xgafv=None)

Streams queries using a reasoning engine.

Args:
  name: string, Required. The name of the ReasoningEngine resource to use. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` (required)
  body: object, The request body.
    The object takes the form of:

{ # Request message for ReasoningEngineExecutionService.StreamQuery.
  "classMethod": "A String", # Optional. Class method to be used for the stream query. It is optional and defaults to "stream_query" if unspecified.
  "input": { # Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc.
    "a_key": "", # Properties of the object.
  },
}

  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top-level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged.
  "contentType": "A String", # The HTTP Content-Type header value specifying the content type of the body.
  "data": "A String", # The HTTP request/response body as raw binary.
  "extensions": [ # Application specific response metadata. Must be set in the first response for streaming APIs.
    {
      "a_key": "", # Properties of the object. Contains field @type with type URL.
    },
  ],
}

Vertex AI API . projects . locations . reasoningEngines . runtimeRevisions

Instance Methods

Method Details