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<html><body>
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<h1><a href="aiplatform_v1.html">Vertex AI API</a> . <a href="aiplatform_v1.projects.html">projects</a> . <a href="aiplatform_v1.projects.locations.html">locations</a> . <a href="aiplatform_v1.projects.locations.evaluationItems.html">evaluationItems</a></h1>
<h2>Instance Methods</h2>
<p class="toc_element">
<code><a href="#close">close()</a></code></p>
<p class="firstline">Close httplib2 connections.</p>
<p class="toc_element">
<code><a href="#create">create(parent, body=None, x__xgafv=None)</a></code></p>
<p class="firstline">Creates an Evaluation Item.</p>
<p class="toc_element">
<code><a href="#delete">delete(name, x__xgafv=None)</a></code></p>
<p class="firstline">Deletes an Evaluation Item.</p>
<p class="toc_element">
<code><a href="#get">get(name, x__xgafv=None)</a></code></p>
<p class="firstline">Gets an Evaluation Item.</p>
<p class="toc_element">
<code><a href="#list">list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)</a></code></p>
<p class="firstline">Lists Evaluation Items.</p>
<p class="toc_element">
<code><a href="#list_next">list_next()</a></code></p>
<p class="firstline">Retrieves the next page of results.</p>
<h3>Method Details</h3>
<div class="method">
<code class="details" id="close">close()</code>
<pre>Close httplib2 connections.</pre>
</div>
<div class="method">
<code class="details" id="create">create(parent, body=None, x__xgafv=None)</code>
<pre>Creates an Evaluation Item.
Args:
parent: string, Required. The resource name of the Location to create the Evaluation Item in. Format: `projects/{project}/locations/{location}` (required)
body: object, The request body.
The object takes the form of:
{ # EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.
"createTime": "A String", # Output only. Timestamp when this item was created.
"displayName": "A String", # Required. The display name of the EvaluationItem.
"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). # Output only. Error for the evaluation item.
"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.
},
"evaluationItemType": "A String", # Required. The type of the EvaluationItem.
"evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
"evaluationResponse": { # Evaluation result. # Output only. The response from evaluation.
"candidateResults": [ # Optional. The results for the metric.
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
{ # Represents the verdict of an evaluation against a single rubric.
"evaluatedRubric": { # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics. # Required. The full rubric definition that was evaluated. Storing this ensures the verdict is self-contained and understandable, especially if the original rubric definition changes or was dynamically generated.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
"reasoning": "A String", # Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.
"verdict": True or False, # Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail".
},
],
"score": 3.14, # Optional. The score for the metric.
},
],
"evaluationRequest": "A String", # Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}
"evaluationRun": "A String", # Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}
"metadata": "", # Optional. Metadata about the evaluation result.
"metric": "A String", # Required. The metric that was evaluated.
"request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
},
"gcsUri": "A String", # The Cloud Storage object where the request or response is stored.
"labels": { # Optional. Labels for the EvaluationItem.
"a_key": "A String",
},
"metadata": "", # Optional. Metadata for the EvaluationItem.
"name": "A String", # Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`
}
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.
"createTime": "A String", # Output only. Timestamp when this item was created.
"displayName": "A String", # Required. The display name of the EvaluationItem.
"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). # Output only. Error for the evaluation item.
"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.
},
"evaluationItemType": "A String", # Required. The type of the EvaluationItem.
"evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
"evaluationResponse": { # Evaluation result. # Output only. The response from evaluation.
"candidateResults": [ # Optional. The results for the metric.
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
{ # Represents the verdict of an evaluation against a single rubric.
"evaluatedRubric": { # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics. # Required. The full rubric definition that was evaluated. Storing this ensures the verdict is self-contained and understandable, especially if the original rubric definition changes or was dynamically generated.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
"reasoning": "A String", # Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.
"verdict": True or False, # Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail".
},
],
"score": 3.14, # Optional. The score for the metric.
},
],
"evaluationRequest": "A String", # Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}
"evaluationRun": "A String", # Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}
"metadata": "", # Optional. Metadata about the evaluation result.
"metric": "A String", # Required. The metric that was evaluated.
"request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
},
"gcsUri": "A String", # The Cloud Storage object where the request or response is stored.
"labels": { # Optional. Labels for the EvaluationItem.
"a_key": "A String",
},
"metadata": "", # Optional. Metadata for the EvaluationItem.
"name": "A String", # Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`
}</pre>
</div>
<div class="method">
<code class="details" id="delete">delete(name, x__xgafv=None)</code>
<pre>Deletes an Evaluation Item.
Args:
name: string, Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (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.
},
}</pre>
</div>
<div class="method">
<code class="details" id="get">get(name, x__xgafv=None)</code>
<pre>Gets an Evaluation Item.
Args:
name: string, Required. The name of the EvaluationItem resource. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (required)
x__xgafv: string, V1 error format.
Allowed values
1 - v1 error format
2 - v2 error format
Returns:
An object of the form:
{ # EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.
"createTime": "A String", # Output only. Timestamp when this item was created.
"displayName": "A String", # Required. The display name of the EvaluationItem.
"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). # Output only. Error for the evaluation item.
"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.
},
"evaluationItemType": "A String", # Required. The type of the EvaluationItem.
"evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
"evaluationResponse": { # Evaluation result. # Output only. The response from evaluation.
"candidateResults": [ # Optional. The results for the metric.
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
{ # Represents the verdict of an evaluation against a single rubric.
"evaluatedRubric": { # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics. # Required. The full rubric definition that was evaluated. Storing this ensures the verdict is self-contained and understandable, especially if the original rubric definition changes or was dynamically generated.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
"reasoning": "A String", # Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.
"verdict": True or False, # Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail".
},
],
"score": 3.14, # Optional. The score for the metric.
},
],
"evaluationRequest": "A String", # Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}
"evaluationRun": "A String", # Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}
"metadata": "", # Optional. Metadata about the evaluation result.
"metric": "A String", # Required. The metric that was evaluated.
"request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
"parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
{ # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
"codeExecutionResult": { # Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. # Optional. The result of executing the ExecutableCode.
"outcome": "A String", # Required. Outcome of the code execution.
"output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
},
"executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. # Optional. Code generated by the model that is intended to be executed.
"code": "A String", # Required. The code to be executed.
"language": "A String", # Required. Programming language of the `code`.
},
"fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
"displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"functionCall": { # A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
"args": { # Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details.
"a_key": "", # Properties of the object.
},
"name": "A String", # Optional. The name of the function to call. Matches [FunctionDeclaration.name].
"partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
{ # Partial argument value of the function call.
"boolValue": True or False, # Optional. Represents a boolean value.
"jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
"nullValue": "A String", # Optional. Represents a null value.
"numberValue": 3.14, # Optional. Represents a double value.
"stringValue": "A String", # Optional. Represents a string value.
"willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
},
],
"willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
},
"functionResponse": { # The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
"name": "A String", # Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name].
"parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
{ # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
"fileData": { # URI based data for function response. # URI based data.
"displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"fileUri": "A String", # Required. URI.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
"data": "A String", # Required. Raw bytes.
"displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
},
],
"response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
"a_key": "", # Properties of the object.
},
},
"inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
"data": "A String", # Required. The raw bytes of the data.
"displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
"mimeType": "A String", # Required. The IANA standard MIME type of the source data.
},
"mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
"level": "A String", # The tokenization quality used for given media.
},
"text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
"thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
"thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
"videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
"endOffset": "A String", # Optional. The end offset of the video.
"fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
"startOffset": "A String", # Optional. The start offset of the video.
},
},
],
"role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
},
},
},
"text": "A String", # Text prompt.
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
"a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
"displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
"groupId": "A String", # Unique identifier for the group.
"rubrics": [ # Rubrics that are part of this group.
{ # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
"content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
},
"importance": "A String", # Optional. The relative importance of this rubric.
"rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
"type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
},
],
},
},
},
},
"gcsUri": "A String", # The Cloud Storage object where the request or response is stored.
"labels": { # Optional. Labels for the EvaluationItem.
"a_key": "A String",
},
"metadata": "", # Optional. Metadata for the EvaluationItem.
"name": "A String", # Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`
}</pre>