Vertex AI API . projects . locations . evaluationSets

Instance Methods

operations()

Returns the operations Resource.

close()

Close httplib2 connections.

create(parent, body=None, x__xgafv=None)

Creates an Evaluation Set.

delete(name, x__xgafv=None)

Deletes an Evaluation Set.

get(name, x__xgafv=None)

Gets an Evaluation Set.

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

Lists Evaluation Sets.

list_next()

Retrieves the next page of results.

patch(name, body=None, updateMask=None, x__xgafv=None)

Updates an Evaluation Set.

Method Details

close() 
Close httplib2 connections.
create(parent, body=None, x__xgafv=None) 
Creates an Evaluation Set.

Args:
  parent: string, Required. The resource name of the Location to create the Evaluation Set in. Format: `projects/{project}/locations/{location}` (required)
  body: object, The request body.
    The object takes the form of:

{ # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
  "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
    "a_key": { # Represents configuration for an Agent.
      "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
      "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
      "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
      "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
      "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
        "A String",
      ],
      "tools": [ # Optional. The list of tools available to this agent.
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
          },
          "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
            "environment": "A String", # Required. The environment being operated.
            "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
              "A String",
            ],
          },
          "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
              "A String",
            ],
          },
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
              "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
              "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
            },
          ],
          "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
            "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
          },
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
              "A String",
            ],
            "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
              "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
              },
              "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
              },
            },
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
            "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
            "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
              "a_key": "", # Properties of the object.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
              "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                "apiKeyConfig": { # The API secret. # The API secret.
                  "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                  "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                },
              },
              "apiSpec": "A String", # The API spec that the external API implements.
              "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                  "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                  "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                  "httpElementLocation": "A String", # Optional. The location of the API key.
                  "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                },
                "authType": "A String", # Type of auth scheme.
                "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                  "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                },
                "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                  "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                },
                "oauthConfig": { # Config for user oauth. # Config for user oauth.
                  "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                },
                "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                  "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                },
              },
              "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                "index": "A String", # The ElasticSearch index to use.
                "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                "searchTemplate": "A String", # The ElasticSearch search template to use.
              },
              "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
              "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
              },
            },
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                  "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                },
              ],
              "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
              "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
              "filter": "A String", # Optional. Filter strings to be passed to the search API.
              "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                "A String",
              ],
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                  "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                },
                "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                  "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                    "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                  },
                  "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                    "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                  },
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
          "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
          },
        },
      ],
    },
  },
  "createTime": "A String", # Output only. Timestamp when this item was created.
  "displayName": "A String", # Required. The display name of the EvaluationSet.
  "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
    "A String",
  ],
  "metadata": "", # Optional. Metadata for the EvaluationSet.
  "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
  "updateTime": "A String", # Output only. Timestamp when this item was last updated.
}

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

Returns:
  An object of the form:

    { # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
  "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
    "a_key": { # Represents configuration for an Agent.
      "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
      "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
      "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
      "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
      "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
        "A String",
      ],
      "tools": [ # Optional. The list of tools available to this agent.
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
          },
          "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
            "environment": "A String", # Required. The environment being operated.
            "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
              "A String",
            ],
          },
          "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
              "A String",
            ],
          },
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
              "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
              "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
            },
          ],
          "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
            "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
          },
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
              "A String",
            ],
            "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
              "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
              },
              "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
              },
            },
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
            "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
            "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
              "a_key": "", # Properties of the object.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
              "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                "apiKeyConfig": { # The API secret. # The API secret.
                  "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                  "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                },
              },
              "apiSpec": "A String", # The API spec that the external API implements.
              "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                  "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                  "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                  "httpElementLocation": "A String", # Optional. The location of the API key.
                  "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                },
                "authType": "A String", # Type of auth scheme.
                "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                  "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                },
                "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                  "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                },
                "oauthConfig": { # Config for user oauth. # Config for user oauth.
                  "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                },
                "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                  "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                },
              },
              "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                "index": "A String", # The ElasticSearch index to use.
                "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                "searchTemplate": "A String", # The ElasticSearch search template to use.
              },
              "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
              "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
              },
            },
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                  "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                },
              ],
              "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
              "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
              "filter": "A String", # Optional. Filter strings to be passed to the search API.
              "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                "A String",
              ],
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                  "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                },
                "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                  "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                    "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                  },
                  "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                    "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                  },
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
          "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
          },
        },
      ],
    },
  },
  "createTime": "A String", # Output only. Timestamp when this item was created.
  "displayName": "A String", # Required. The display name of the EvaluationSet.
  "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
    "A String",
  ],
  "metadata": "", # Optional. Metadata for the EvaluationSet.
  "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
  "updateTime": "A String", # Output only. Timestamp when this item was last updated.
}
delete(name, x__xgafv=None) 
Deletes an Evaluation Set.

Args:
  name: string, Required. The name of the EvaluationSet resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}` (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 an Evaluation Set.

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

Returns:
  An object of the form:

    { # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
  "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
    "a_key": { # Represents configuration for an Agent.
      "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
      "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
      "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
      "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
      "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
        "A String",
      ],
      "tools": [ # Optional. The list of tools available to this agent.
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
          },
          "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
            "environment": "A String", # Required. The environment being operated.
            "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
              "A String",
            ],
          },
          "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
              "A String",
            ],
          },
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
              "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
              "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
            },
          ],
          "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
            "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
          },
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
              "A String",
            ],
            "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
              "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
              },
              "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
              },
            },
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
            "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
            "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
              "a_key": "", # Properties of the object.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
              "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                "apiKeyConfig": { # The API secret. # The API secret.
                  "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                  "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                },
              },
              "apiSpec": "A String", # The API spec that the external API implements.
              "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                  "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                  "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                  "httpElementLocation": "A String", # Optional. The location of the API key.
                  "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                },
                "authType": "A String", # Type of auth scheme.
                "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                  "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                },
                "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                  "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                },
                "oauthConfig": { # Config for user oauth. # Config for user oauth.
                  "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                },
                "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                  "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                },
              },
              "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                "index": "A String", # The ElasticSearch index to use.
                "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                "searchTemplate": "A String", # The ElasticSearch search template to use.
              },
              "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
              "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
              },
            },
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                  "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                },
              ],
              "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
              "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
              "filter": "A String", # Optional. Filter strings to be passed to the search API.
              "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                "A String",
              ],
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                  "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                },
                "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                  "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                    "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                  },
                  "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                    "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                  },
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
          "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
          },
        },
      ],
    },
  },
  "createTime": "A String", # Output only. Timestamp when this item was created.
  "displayName": "A String", # Required. The display name of the EvaluationSet.
  "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
    "A String",
  ],
  "metadata": "", # Optional. Metadata for the EvaluationSet.
  "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
  "updateTime": "A String", # Output only. Timestamp when this item was last updated.
}
list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None) 
Lists Evaluation Sets.

Args:
  parent: string, Required. The resource name of the Location from which to list the Evaluation Sets. Format: `projects/{project}/locations/{location}` (required)
  filter: string, Optional. Filter expression that matches a subset of the EvaluationSets to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).
  orderBy: string, Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.
  pageSize: integer, Optional. The maximum number of Evaluation Sets to return.
  pageToken: string, Optional. A page token, received from a previous `ListEvaluationSets` call. Provide this to retrieve the subsequent page.
  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 EvaluationManagementService.ListEvaluationSets.
  "evaluationSets": [ # List of EvaluationSets in the requested page.
    { # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
      "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
        "a_key": { # Represents configuration for an Agent.
          "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
          "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
          "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
          "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
          "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
            "A String",
          ],
          "tools": [ # Optional. The list of tools available to this agent.
            { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
              "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
              },
              "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
                "environment": "A String", # Required. The environment being operated.
                "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
                  "A String",
                ],
              },
              "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
                "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
                "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
                  "A String",
                ],
              },
              "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
                { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
                  "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
                  "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
                  "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                    "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                    "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                      # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    ],
                    "default": "", # Optional. Default value to use if the field is not specified.
                    "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                      "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    },
                    "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                    "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                      "A String",
                    ],
                    "example": "", # Optional. Example of an instance of this schema.
                    "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                    "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                    "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                    "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                    "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                    "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                    "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                    "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                    "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                    "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                    "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                    "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                    "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                      "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    },
                    "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                      "A String",
                    ],
                    "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                    "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                      "A String",
                    ],
                    "title": "A String", # Optional. Title for the schema.
                    "type": "A String", # Optional. Data type of the schema field.
                  },
                  "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
                  "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                    "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                    "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                      # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    ],
                    "default": "", # Optional. Default value to use if the field is not specified.
                    "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                      "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    },
                    "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                    "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                      "A String",
                    ],
                    "example": "", # Optional. Example of an instance of this schema.
                    "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                    "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                    "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                    "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                    "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                    "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                    "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                    "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                    "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                    "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                    "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                    "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                    "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                      "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                    },
                    "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                      "A String",
                    ],
                    "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                    "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                      "A String",
                    ],
                    "title": "A String", # Optional. Title for the schema.
                    "type": "A String", # Optional. Data type of the schema field.
                  },
                  "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
                },
              ],
              "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
                "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
              },
              "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
                "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
                "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
                  "A String",
                ],
                "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
                  "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
                  },
                  "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
                  },
                },
              },
              "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
                "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
                  "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
                  "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
                },
              },
              "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
                "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
                "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
                  "a_key": "", # Properties of the object.
                },
              },
              "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
                "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
                "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
                  "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                    "apiKeyConfig": { # The API secret. # The API secret.
                      "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                      "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                    },
                  },
                  "apiSpec": "A String", # The API spec that the external API implements.
                  "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                    "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                      "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                      "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                      "httpElementLocation": "A String", # Optional. The location of the API key.
                      "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                    },
                    "authType": "A String", # Type of auth scheme.
                    "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                      "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                    },
                    "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                      "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                    },
                    "oauthConfig": { # Config for user oauth. # Config for user oauth.
                      "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                      "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                    },
                    "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                      "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                      "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                    },
                  },
                  "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                    "index": "A String", # The ElasticSearch index to use.
                    "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                    "searchTemplate": "A String", # The ElasticSearch search template to use.
                  },
                  "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
                  "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
                  },
                },
                "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
                  "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                    { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                      "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                      "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                    },
                  ],
                  "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
                  "filter": "A String", # Optional. Filter strings to be passed to the search API.
                  "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
                },
                "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
                  "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                    "A String",
                  ],
                  "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                    { # The definition of the Rag resource.
                      "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                      "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                        "A String",
                      ],
                    },
                  ],
                  "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                    "filter": { # Config for filters. # Optional. Config for filters.
                      "metadataFilter": "A String", # Optional. String for metadata filtering.
                      "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                      "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                    },
                    "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                      "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                    },
                    "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                      "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                        "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                      },
                      "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                        "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                      },
                    },
                    "topK": 42, # Optional. The number of contexts to retrieve.
                  },
                  "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
                  "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
                  "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
                },
              },
              "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
              },
            },
          ],
        },
      },
      "createTime": "A String", # Output only. Timestamp when this item was created.
      "displayName": "A String", # Required. The display name of the EvaluationSet.
      "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
        "A String",
      ],
      "metadata": "", # Optional. Metadata for the EvaluationSet.
      "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
      "updateTime": "A String", # Output only. Timestamp when this item was last updated.
    },
  ],
  "nextPageToken": "A String", # A token to retrieve the next page of results.
}
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.
patch(name, body=None, updateMask=None, x__xgafv=None) 
Updates an Evaluation Set.

Args:
  name: string, Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}` (required)
  body: object, The request body.
    The object takes the form of:

{ # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
  "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
    "a_key": { # Represents configuration for an Agent.
      "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
      "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
      "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
      "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
      "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
        "A String",
      ],
      "tools": [ # Optional. The list of tools available to this agent.
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
          },
          "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
            "environment": "A String", # Required. The environment being operated.
            "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
              "A String",
            ],
          },
          "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
              "A String",
            ],
          },
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
              "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
              "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
            },
          ],
          "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
            "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
          },
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
              "A String",
            ],
            "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
              "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
              },
              "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
              },
            },
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
            "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
            "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
              "a_key": "", # Properties of the object.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
              "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                "apiKeyConfig": { # The API secret. # The API secret.
                  "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                  "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                },
              },
              "apiSpec": "A String", # The API spec that the external API implements.
              "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                  "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                  "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                  "httpElementLocation": "A String", # Optional. The location of the API key.
                  "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                },
                "authType": "A String", # Type of auth scheme.
                "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                  "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                },
                "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                  "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                },
                "oauthConfig": { # Config for user oauth. # Config for user oauth.
                  "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                },
                "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                  "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                },
              },
              "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                "index": "A String", # The ElasticSearch index to use.
                "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                "searchTemplate": "A String", # The ElasticSearch search template to use.
              },
              "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
              "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
              },
            },
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                  "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                },
              ],
              "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
              "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
              "filter": "A String", # Optional. Filter strings to be passed to the search API.
              "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                "A String",
              ],
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                  "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                },
                "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                  "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                    "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                  },
                  "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                    "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                  },
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
          "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
          },
        },
      ],
    },
  },
  "createTime": "A String", # Output only. Timestamp when this item was created.
  "displayName": "A String", # Required. The display name of the EvaluationSet.
  "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
    "A String",
  ],
  "metadata": "", # Optional. Metadata for the EvaluationSet.
  "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
  "updateTime": "A String", # Output only. Timestamp when this item was last updated.
}

  updateMask: string, Optional. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask.
  x__xgafv: string, V1 error format.
    Allowed values
      1 - v1 error format
      2 - v2 error format

Returns:
  An object of the form:

    { # EvaluationSet is a collection of related EvaluationItems that are evaluated together.
  "agentConfigs": { # Optional. Static configurations for each agent associated with the items in this set. Key: `agent_id` (matches the `author` field in `events`). Value: The static configuration of the agent.
    "a_key": { # Represents configuration for an Agent.
      "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
      "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
      "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
      "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
      "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
        "A String",
      ],
      "tools": [ # Optional. The list of tools available to this agent.
        { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
          "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
          },
          "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
            "environment": "A String", # Required. The environment being operated.
            "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
              "A String",
            ],
          },
          "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
              "A String",
            ],
          },
          "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
            { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
              "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
              "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
              "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
              "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
                "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
                "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
                  # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                ],
                "default": "", # Optional. Default value to use if the field is not specified.
                "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
                "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
                  "A String",
                ],
                "example": "", # Optional. Example of an instance of this schema.
                "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
                "items": # Object with schema name: GoogleCloudAiplatformV1beta1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
                "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
                "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
                "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
                "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
                "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
                "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
                "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
                "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
                "nullable": True or False, # Optional. Indicates if the value of this field can be null.
                "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
                "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
                  "a_key": # Object with schema name: GoogleCloudAiplatformV1beta1Schema
                },
                "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
                  "A String",
                ],
                "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
                "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
                  "A String",
                ],
                "title": "A String", # Optional. Title for the schema.
                "type": "A String", # Optional. Data type of the schema field.
              },
              "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
            },
          ],
          "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
            "enableWidget": True or False, # Optional. If true, include the widget context token in the response.
          },
          "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
            "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
            "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
              "A String",
            ],
            "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
              "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
              },
              "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
              },
            },
          },
          "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
            "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
              "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
              "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
            },
          },
          "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
            "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
            "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
              "a_key": "", # Properties of the object.
            },
          },
          "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
            "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
            "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
              "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
                "apiKeyConfig": { # The API secret. # The API secret.
                  "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
                  "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
                },
              },
              "apiSpec": "A String", # The API spec that the external API implements.
              "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
                "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
                  "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                  "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
                  "httpElementLocation": "A String", # Optional. The location of the API key.
                  "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
                },
                "authType": "A String", # Type of auth scheme.
                "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
                  "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
                },
                "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
                  "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
                },
                "oauthConfig": { # Config for user oauth. # Config for user oauth.
                  "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
                },
                "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
                  "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
                  "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
                },
              },
              "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
                "index": "A String", # The ElasticSearch index to use.
                "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
                "searchTemplate": "A String", # The ElasticSearch search template to use.
              },
              "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
              "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
              },
            },
            "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
              "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
                { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
                  "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
                  "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
                },
              ],
              "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
              "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
              "filter": "A String", # Optional. Filter strings to be passed to the search API.
              "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
            },
            "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
              "ragCorpora": [ # Optional. Deprecated. Please use rag_resources instead.
                "A String",
              ],
              "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
                { # The definition of the Rag resource.
                  "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
                  "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
                    "A String",
                  ],
                },
              ],
              "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
                "filter": { # Config for filters. # Optional. Config for filters.
                  "metadataFilter": "A String", # Optional. String for metadata filtering.
                  "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
                  "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
                },
                "hybridSearch": { # Config for Hybrid Search. # Optional. Config for Hybrid Search.
                  "alpha": 3.14, # Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally.
                },
                "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
                  "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
                    "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
                  },
                  "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
                    "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
                  },
                },
                "topK": 42, # Optional. The number of contexts to retrieve.
              },
              "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
              "storeContext": True or False, # Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions.
              "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
            },
          },
          "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
          },
        },
      ],
    },
  },
  "createTime": "A String", # Output only. Timestamp when this item was created.
  "displayName": "A String", # Required. The display name of the EvaluationSet.
  "evaluationItems": [ # Required. The EvaluationItems that are part of this dataset.
    "A String",
  ],
  "metadata": "", # Optional. Metadata for the EvaluationSet.
  "name": "A String", # Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
  "updateTime": "A String", # Output only. Timestamp when this item was last updated.
}