## Filter Evaluations

**post** `/v5/evaluations/filter`

Filter evaluations by metadata, status, and tags.

Accepts up to 10 filters combined with AND logic, each comparing a key against a value with an
operator (`==`, `!=`, `>=`, `<=`, `IN`, `NOT_IN`). Filter on metadata keys returned by the
metadata-keys endpoint, plus the built-in `status` and `tag` keys. Archived evaluations are
excluded unless `include_archived` is set, and the `tasks` view includes task configurations in
each result. Use this for metadata or status filtering; for simple name or tag lookups the list
endpoint is sufficient.

### Query Parameters

- `ending_before: optional string`

- `include_archived: optional boolean`

- `limit: optional number`

- `sort_by: optional string`

- `sort_order: optional SortOrder`

  - `"asc"`

  - `"desc"`

- `starting_after: optional string`

- `views: optional array of EvaluationViews`

  - `"tasks"`

### Body Parameters

- `filters: array of object { key, operator, value, object }`

  List of metadata filters to apply (maximum 10)

  - `key: string`

    The metadata key to filter on

  - `operator: "==" or "!=" or ">=" or 3 more`

    The comparison operator to use

    - `"=="`

    - `"!="`

    - `">="`

    - `"<="`

    - `"IN"`

    - `"NOT_IN"`

  - `value: string`

    The value to compare against (string for all types)

  - `object: optional "metadata_filter"`

    - `"metadata_filter"`

### Returns

- `PaginatedListEvaluation object { has_more, items, total, 2 more }`

  - `has_more: boolean`

    Whether there are more items left to be fetched.

  - `items: array of Evaluation`

    - `id: string`

      The unique identifier of the entity.

    - `created_at: string`

      The date and time when the entity was created in ISO format.

    - `created_by: Identity`

      The identity that created the entity.

      - `id: string`

      - `type: "user" or "service_account"`

        - `"user"`

        - `"service_account"`

      - `object: optional "identity"`

        - `"identity"`

    - `datasets: array of Dataset`

      - `id: string`

        The unique identifier of the entity.

      - `created_at: string`

        The date and time when the entity was created in ISO format.

      - `created_by: Identity`

        The identity that created the entity.

      - `current_version_num: number`

      - `name: string`

      - `tags: array of string`

        The tags associated with the entity

      - `archived_at: optional string`

        The date and time when the entity was archived in ISO format.

      - `description: optional string`

      - `object: optional "dataset"`

        - `"dataset"`

    - `name: string`

    - `status: "failed" or "completed" or "running"`

      - `"failed"`

      - `"completed"`

      - `"running"`

    - `tags: array of string`

      The tags associated with the entity

    - `archived_at: optional string`

      The date and time when the entity was archived in ISO format.

    - `description: optional string`

    - `error_count: optional number`

      Number of task errors across all items in this evaluation.

    - `metadata: optional map[unknown]`

      Metadata key-value pairs for the evaluation

    - `object: optional "evaluation"`

      - `"evaluation"`

    - `progress: optional EvaluationTasksProgressSchema`

      Progress of the evaluation's underlying async job

      - `items: optional object { failed, pending, successful, 2 more }`

        - `failed: number`

        - `pending: number`

        - `successful: number`

        - `total: number`

        - `failed_items: optional array of object { item_id, error, error_type }`

          - `item_id: string`

          - `error: optional string`

          - `error_type: optional string`

      - `workflows: optional object { completed, failed, pending, total }`

        - `completed: number`

        - `failed: number`

        - `pending: number`

        - `total: number`

    - `status_reason: optional string`

      Reason for evaluation status

    - `tasks: optional array of EvaluationTask`

      Tasks executed during evaluation. Populated with optional `task` view.

      - `ChatCompletion object { configuration, alias, task_type }`

        - `configuration: object { messages, model, audio, 24 more }`

          - `messages: array of map[unknown] or ItemLocator`

            openai standard message format

            - `array of map[unknown]`

            - `ItemLocator = string`

          - `model: string`

            model specified as `model_vendor/model`, for example `openai/gpt-4o`

          - `audio: optional map[unknown] or ItemLocator`

            Parameters for audio output. Required when audio output is requested with modalities: ['audio'].

            - `map[unknown]`

            - `ItemLocator = string`

          - `frequency_penalty: optional number or ItemLocator`

            Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far.

            - `number`

            - `ItemLocator = string`

          - `function_call: optional map[unknown] or ItemLocator`

            Deprecated in favor of tool_choice. Controls which function is called by the model.

            - `map[unknown]`

            - `ItemLocator = string`

          - `functions: optional array of map[unknown] or ItemLocator`

            Deprecated in favor of tools. A list of functions the model may generate JSON inputs for.

            - `array of map[unknown]`

            - `ItemLocator = string`

          - `logit_bias: optional map[number] or ItemLocator`

            Modify the likelihood of specified tokens appearing in the completion. Maps tokens to bias values from -100 to 100.

            - `map[number]`

            - `ItemLocator = string`

          - `logprobs: optional boolean or ItemLocator`

            Whether to return log probabilities of the output tokens or not.

            - `boolean`

            - `ItemLocator = string`

          - `max_completion_tokens: optional number or ItemLocator`

            An upper bound for the number of tokens that can be generated, including visible output tokens and reasoning tokens.

            - `number`

            - `ItemLocator = string`

          - `max_tokens: optional number or ItemLocator`

            Deprecated in favor of max_completion_tokens. The maximum number of tokens to generate.

            - `number`

            - `ItemLocator = string`

          - `metadata: optional map[string] or ItemLocator`

            Developer-defined tags and values used for filtering completions in the dashboard.

            - `map[string]`

            - `ItemLocator = string`

          - `modalities: optional array of string or ItemLocator`

            Output types that you would like the model to generate for this request.

            - `array of string`

            - `ItemLocator = string`

          - `n: optional number or ItemLocator`

            How many chat completion choices to generate for each input message.

            - `number`

            - `ItemLocator = string`

          - `parallel_tool_calls: optional boolean or ItemLocator`

            Whether to enable parallel function calling during tool use.

            - `boolean`

            - `ItemLocator = string`

          - `prediction: optional map[unknown] or ItemLocator`

            Static predicted output content, such as the content of a text file being regenerated.

            - `map[unknown]`

            - `ItemLocator = string`

          - `presence_penalty: optional number or ItemLocator`

            Number between -2.0 and 2.0. Positive values penalize tokens based on whether they appear in the text so far.

            - `number`

            - `ItemLocator = string`

          - `reasoning_effort: optional string`

            For o1 models only. Constrains effort on reasoning. Values: low, medium, high.

          - `response_format: optional map[unknown] or ItemLocator`

            An object specifying the format that the model must output.

            - `map[unknown]`

            - `ItemLocator = string`

          - `seed: optional number or ItemLocator`

            If specified, system will attempt to sample deterministically for repeated requests with same seed.

            - `number`

            - `ItemLocator = string`

          - `stop: optional string or array of string`

            Up to 4 sequences where the API will stop generating further tokens.

            - `string`

            - `array of string`

          - `store: optional boolean or ItemLocator`

            Whether to store the output for use in model distillation or evals products.

            - `boolean`

            - `ItemLocator = string`

          - `temperature: optional number or ItemLocator`

            What sampling temperature to use. Higher values make output more random, lower more focused.

            - `number`

            - `ItemLocator = string`

          - `tool_choice: optional string or map[unknown]`

            Controls which tool is called by the model. Values: none, auto, required, or specific tool.

            - `string`

            - `map[unknown]`

          - `tools: optional array of map[unknown] or ItemLocator`

            A list of tools the model may call. Currently, only functions are supported. Max 128 functions.

            - `array of map[unknown]`

            - `ItemLocator = string`

          - `top_k: optional number or ItemLocator`

            Only sample from the top K options for each subsequent token

            - `number`

            - `ItemLocator = string`

          - `top_logprobs: optional number or ItemLocator`

            Number of most likely tokens to return at each position, with associated log probability.

            - `number`

            - `ItemLocator = string`

          - `top_p: optional number or ItemLocator`

            Alternative to temperature. Only tokens comprising top_p probability mass are considered.

            - `number`

            - `ItemLocator = string`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `chat_completion`

        - `task_type: optional "chat_completion"`

          - `"chat_completion"`

      - `Inference object { configuration, alias, task_type }`

        - `configuration: object { model, args, inference_configuration }`

          - `model: string`

            model specified as `vendor/name` (ex. openai/gpt-5)

          - `args: optional map[unknown] or ItemLocator`

            Arguments passed into model

            - `map[unknown]`

            - `ItemLocator = string`

          - `inference_configuration: optional LaunchInferenceConfiguration or ItemLocator`

            Vendor specific configuration

            - `LaunchInferenceConfiguration object { num_retries, timeout_seconds }`

              - `num_retries: optional number`

              - `timeout_seconds: optional number`

            - `ItemLocator = string`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `inference`

        - `task_type: optional "inference"`

          - `"inference"`

      - `ApplicationVariant object { configuration, alias, task_type }`

        - `configuration: object { application_variant_id, inputs, history, 2 more }`

          - `application_variant_id: string`

          - `inputs: map[unknown] or ItemLocator`

            Input data for the application. For agents service variants, you must provide inputs as a mapping from `{input_name: input_value}`. For V0 variants, you must specify the node your input should be passed to, structuring your input as `{node_id: {input_name: input_value}}`.

            - `map[unknown]`

            - `ItemLocator = string`

          - `history: optional array of object { request, response, session_data }  or ItemLocator`

            History of the application

            - `ApplicationRequestResponsePairArray = array of object { request, response, session_data }`

              - `request: string`

                Request inputs

              - `response: string`

                Response outputs

              - `session_data: optional map[unknown]`

                Session data corresponding to the request response pair

            - `ItemLocator = string`

          - `operation_metadata: optional map[unknown] or ItemLocator`

            Arbitrary user-defined metadata that can be attached to the process operations and will be registered in the interaction.

            - `map[unknown]`

            - `ItemLocator = string`

          - `overrides: optional object { concurrent, initial_state, partial_trace, 2 more }  or map[object { artifact_ids_filter, artifact_name_regex, type } ] or ItemLocator`

            Optional overrides for the application

            - `AgenticApplicationOverrides object { concurrent, initial_state, partial_trace, 2 more }`

              Execution override options for agentic applications

              - `concurrent: optional boolean`

              - `initial_state: optional object { current_node, state }`

                - `current_node: string`

                - `state: map[unknown]`

              - `partial_trace: optional array of object { duration_ms, node_id, operation_input, 5 more }`

                - `duration_ms: number`

                - `node_id: string`

                - `operation_input: string`

                - `operation_output: string`

                - `operation_type: string`

                - `start_timestamp: string`

                - `workflow_id: string`

                - `operation_metadata: optional map[unknown]`

              - `return_span: optional boolean`

              - `use_channels: optional boolean`

            - `map[object { artifact_ids_filter, artifact_name_regex, type } ]`

              - `artifact_ids_filter: optional array of string`

              - `artifact_name_regex: optional array of string`

              - `type: optional "knowledge_base_schema"`

                - `"knowledge_base_schema"`

            - `ItemLocator = string`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `application_variant`

        - `task_type: optional "application_variant"`

          - `"application_variant"`

      - `AgentexOutput object { configuration, alias, task_type }`

        - `configuration: object { agentex_agent_id, input_column, agent_task_params, 6 more }`

          - `agentex_agent_id: string`

            The ID of the Agentex agent to use

          - `input_column: string or map[unknown] or array of unknown`

            The dataset column to use as input for the agent

            - `string`

            - `map[unknown]`

            - `array of unknown`

          - `agent_task_params: optional map[unknown] or ItemLocator`

            Extra params merged into the Agentex `task/create` call's `params` object and forwarded verbatim to the agent. Required by agents that demand configuration at task creation -- the golden agent, for example, rejects any task whose params omit `config_id`. SGP always pins `is_eval: true`; a caller-supplied `description` overrides the SGP default. Nested `item.`-prefixed strings and `{{item.x}}` templates are resolved per evaluation item, so a per-row `config_id` can come from a dataset column.

            - `map[unknown]`

            - `ItemLocator = string`

          - `completion_mode: optional "first_message" or "turn_quiescence"`

            How the agent's first turn is judged finished. `first_message` (the default) grades the first non-empty agent text message after the input, which is cheap but grades a streaming harness on whatever text block streamed first. `turn_quiescence` keeps listening while the agent is still producing messages and grades once at least one agent text message exists and nothing new has arrived for `quiescence_seconds` -- the right choice for tool-using agents. Neither mode requires the agent to mark the task complete; a terminal task status always ends the wait, and `timeout_seconds` always bounds it.

            - `"first_message"`

            - `"turn_quiescence"`

          - `deployment_id: optional string`

            Optional Agentex deployment ID to pin the eval to a specific deployment. When set, RPC traffic routes through /agents/{agent_id}/deployments/{deployment_id}/rpc. When unset, traffic uses the agent's default RPC endpoint, which resolves through the agent's current routing rules on the Agentex side.

          - `include_traces: optional boolean or ItemLocator`

            Whether to include trace data in the evaluation results. Traces are read from SGP's own span store for the agent's trace, not from Agentex.

            - `boolean`

            - `ItemLocator = string`

          - `input_mode: optional "text" or "data"`

            How the resolved `input_column` is delivered to the agent. `text` (the default) sends a TextContent message with the value stringified. `data` sends a DataContent message whose `data` is the value as a JSON object; the resolved value must be an object, or a string that parses to one. Most agents accept text only and reject `data`.

            - `"text"`

            - `"data"`

          - `quiescence_seconds: optional number or ItemLocator`

            Seconds of no new messages before `completion_mode: turn_quiescence` considers the turn finished. Ignored in `first_message` mode. Should exceed the agent's longest expected gap between messages (a slow tool call), or the turn is graded early.

            - `number`

            - `ItemLocator = string`

          - `timeout_seconds: optional number or ItemLocator`

            Maximum seconds to wait for the agent's first-turn response per item. If not set, the server-side default of 600s applies. Capped at 1500s to stay within the evaluation item activity's 1800s start-to-close budget.

            - `number`

            - `ItemLocator = string`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `agentex_output`

        - `task_type: optional "agentex_output"`

          - `"agentex_output"`

      - `Metric object { configuration, alias, task_type }`

        - `configuration: object { candidate, reference, type }  or object { candidate, reference, type }  or object { candidate, reference, type }  or 4 more`

          - `Bleu object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "bleu"`

              - `"bleu"`

          - `Meteor object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "meteor"`

              - `"meteor"`

          - `CosineSimilarity object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "cosine_similarity"`

              - `"cosine_similarity"`

          - `F1 object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "f1"`

              - `"f1"`

          - `Rouge1 object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "rouge1"`

              - `"rouge1"`

          - `Rouge2 object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "rouge2"`

              - `"rouge2"`

          - `RougeL object { candidate, reference, type }`

            - `candidate: string`

            - `reference: string`

            - `type: "rougeL"`

              - `"rougeL"`

        - `alias: optional string`

          Alias to title the results column. Defaults to the metric type specified in the configuration

        - `task_type: optional "metric"`

          - `"metric"`

      - `AutoEvaluationQuestion object { configuration, alias, task_type }`

        - `configuration: object { model, prompt, question_id }`

          - `model: string`

            model specified as `model_vendor/model_name`

          - `prompt: string`

          - `question_id: string`

            question to be evaluated

        - `alias: optional string`

          Alias to title the results column. Defaults to the `auto_evaluation_question`

        - `task_type: optional "auto_evaluation.question"`

          - `"auto_evaluation.question"`

      - `AutoEvaluationGuidedDecoding object { configuration, alias, task_type }`

        - `configuration: object { model, prompt, response_format, 3 more }  or object { choices, model, prompt, 3 more }  or AutoEvaluationAgentTaskRequestWithItemLocator`

          - `AutoEvaluationStructuredOutputTaskRequestWithItemLocator object { model, prompt, response_format, 3 more }`

            - `model: string`

              model specified as `model_vendor/model_name`

            - `prompt: string`

            - `response_format: map[unknown]`

              JSON schema used for structuring the model response

            - `inference_args: optional map[unknown]`

              Additional arguments to pass to the inference request

            - `run_condition: optional object { op, value }  or object { path, op }  or EqEvaluationRunCondition or 12 more`

              - `Const object { op, value }`

                - `op: optional "const"`

                  - `"const"`

                - `value: optional string or number or boolean`

                  - `string`

                  - `number`

                  - `boolean`

              - `Var object { path, op }`

                - `path: string`

                - `op: optional "var"`

                  - `"var"`

              - `EqEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "eq"`

                  - `"eq"`

              - `NeEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "ne"`

                  - `"ne"`

              - `LtEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "lt"`

                  - `"lt"`

              - `LteEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "lte"`

                  - `"lte"`

              - `GtEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "gt"`

                  - `"gt"`

              - `GteEvaluationRunCondition object { left, right, op }`

                - `left: unknown`

                - `right: unknown`

                - `op: optional "gte"`

                  - `"gte"`

              - `AndEvaluationRunCondition object { operands, op }`

                - `operands: array of unknown`

                - `op: optional "and"`

                  - `"and"`

              - `OrEvaluationRunCondition object { operands, op }`

                - `operands: array of unknown`

                - `op: optional "or"`

                  - `"or"`

              - `InEvaluationRunCondition object { left, operands, op }`

                - `left: unknown`

                - `operands: array of unknown`

                - `op: optional "in"`

                  - `"in"`

              - `NotInEvaluationRunCondition object { left, operands, op }`

                - `left: unknown`

                - `operands: array of unknown`

                - `op: optional "not_in"`

                  - `"not_in"`

              - `NotEvaluationRunCondition object { operands, op }`

                - `operands: array of unknown`

                - `op: optional "not"`

                  - `"not"`

              - `IsNullEvaluationRunCondition object { operands, op }`

                - `operands: array of unknown`

                - `op: optional "is_null"`

                  - `"is_null"`

              - `IsNotNullEvaluationRunCondition object { operands, op }`

                - `operands: array of unknown`

                - `op: optional "is_not_null"`

                  - `"is_not_null"`

            - `system_prompt: optional string`

          - `AutoEvaluationGuidedDecodingTaskRequestWithItemLocator object { choices, model, prompt, 3 more }`

            - `choices: array of string`

              Choices array cannot be empty

            - `model: string`

              model specified as `model_vendor/model_name`

            - `prompt: string`

            - `inference_args: optional map[unknown]`

              Additional arguments to pass to the inference request

            - `run_condition: optional object { op, value }  or object { path, op }  or EqEvaluationRunCondition or 12 more`

              - `Const object { op, value }`

                - `op: optional "const"`

                  - `"const"`

                - `value: optional string or number or boolean`

                  - `string`

                  - `number`

                  - `boolean`

              - `Var object { path, op }`

                - `path: string`

                - `op: optional "var"`

                  - `"var"`

              - `EqEvaluationRunCondition object { left, right, op }`

              - `NeEvaluationRunCondition object { left, right, op }`

              - `LtEvaluationRunCondition object { left, right, op }`

              - `LteEvaluationRunCondition object { left, right, op }`

              - `GtEvaluationRunCondition object { left, right, op }`

              - `GteEvaluationRunCondition object { left, right, op }`

              - `AndEvaluationRunCondition object { operands, op }`

              - `OrEvaluationRunCondition object { operands, op }`

              - `InEvaluationRunCondition object { left, operands, op }`

              - `NotInEvaluationRunCondition object { left, operands, op }`

              - `NotEvaluationRunCondition object { operands, op }`

              - `IsNullEvaluationRunCondition object { operands, op }`

              - `IsNotNullEvaluationRunCondition object { operands, op }`

            - `system_prompt: optional string`

          - `AutoEvaluationAgentTaskRequestWithItemLocator object { definition, name, output_rules, 6 more }`

            - `definition: string`

            - `name: string`

            - `output_rules: array of string`

            - `data_fields: optional array of string`

            - `designated_to: optional object { config, agent_name }  or object { config, agent_name }  or object { config, agent_name }  or object { config, agent_name }`

              - `ApeAgent object { config, agent_name }`

                - `config: object { model, temperature }`

                  - `model: optional string`

                  - `temperature: optional number`

                - `agent_name: optional "APEAgent"`

                  - `"APEAgent"`

              - `IfAgent object { config, agent_name }`

                - `config: object { model }`

                  - `model: optional string`

                - `agent_name: optional "IFAgent"`

                  - `"IFAgent"`

              - `TruthfulnessAgent object { config, agent_name }`

                - `config: object { model }`

                  - `model: optional string`

                - `agent_name: optional "TruthfulnessAgent"`

                  - `"TruthfulnessAgent"`

              - `BaseAgent object { config, agent_name }`

                - `config: object { model }`

                  - `model: optional string`

                - `agent_name: optional "BaseAgent"`

                  - `"BaseAgent"`

            - `output_type: optional "text" or "integer" or "float" or "boolean"`

              - `"text"`

              - `"integer"`

              - `"float"`

              - `"boolean"`

            - `output_values: optional array of string or number or boolean`

              - `string`

              - `number`

              - `boolean`

            - `rubric_id: optional string`

            - `rubric_version: optional number`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `auto_evaluation_guided_decoding`

        - `task_type: optional "auto_evaluation.guided_decoding"`

          - `"auto_evaluation.guided_decoding"`

      - `AutoEvaluationAgent object { configuration, alias, task_type }`

        - `configuration: AutoEvaluationAgentTaskRequestWithItemLocator`

        - `alias: optional string`

          Alias to title the results column. Defaults to the `auto_evaluation_agent`

        - `task_type: optional "auto_evaluation.agent"`

          - `"auto_evaluation.agent"`

      - `ContributorEvaluationQuestion object { configuration, alias, task_type }`

        - `configuration: object { layout, question_id, prefill_from, 3 more }`

          - `layout: Container`

            - `children: array of Container or Component`

              The children to be displayed within the container

              - `Container object { children, direction }`

              - `Component object { data, label }`

                - `data: ItemLocator`

                  A pointer to the data in each evaluation item to be displayed within the component

                - `label: optional string`

            - `direction: optional "row" or "column"`

              The axis that children are placed in the container. Based on CSS `flex-direction` (see: https://developer.mozilla.org/en-US/docs/Web/CSS/flex-direction)

              - `"row"`

              - `"column"`

          - `question_id: string`

          - `prefill_from: optional string`

            Dataset column to prefill contributor question task result

          - `queue_id: optional string`

            The contributor annotation queue to include this task in. Defaults to `default`

          - `required: optional boolean`

            Whether the question is required to be answered

          - `rubric_id: optional string`

            ID of the rubric to use for scoring this evaluation question

        - `alias: optional string`

          Alias to title the results column. Defaults to the `contributor_evaluation_question`

        - `task_type: optional "contributor_evaluation.question"`

          - `"contributor_evaluation.question"`

      - `CustomFunction object { configuration, alias, task_type }`

        - `configuration: object { function_source, arg_mapping, config_args, outputs }`

          Configuration for a custom Python function evaluation task.

          - `function_source: string`

            Python function source code

          - `arg_mapping: optional map[string]`

            Mapping of function parameter names to item locators (e.g. item.field). Auto-derived from function signature if not provided.

          - `config_args: optional map[unknown]`

            Literal argument values for function parameters, such as thresholds or RNG seeds. Serialized JSON must be at most 10000 characters.

          - `outputs: optional array of object { path, alias }`

            Optional output paths to materialize as separate result columns. If omitted, the function return value is stored only under the task alias/data key.

            - `path: string`

              Dot path in the custom function return value to materialize.

            - `alias: optional string`

              Result column alias. Defaults to path with dots replaced by underscores.

        - `alias: optional string`

          Alias to title the results column. Defaults to the function name.

        - `task_type: optional "custom_function"`

          - `"custom_function"`

  - `total: number`

    The total of items that match the query. This is greater than or equal to the number of items returned.

  - `limit: optional number`

    The maximum number of items to return.

  - `object: optional "list"`

    - `"list"`

### Example

```http
curl https://api.egp.scale.com/v5/evaluations/filter \
    -H 'Content-Type: application/json' \
    -H "x-api-key: $SGP_API_KEY" \
    -d '{
          "filters": [
            {
              "key": "key",
              "operator": "==",
              "value": "value"
            }
          ]
        }'
```

#### Response

```json
{
  "has_more": true,
  "items": [
    {
      "id": "id",
      "created_at": "2019-12-27T18:11:19.117Z",
      "created_by": {
        "id": "id",
        "type": "user",
        "object": "identity"
      },
      "datasets": [
        {
          "id": "id",
          "created_at": "2019-12-27T18:11:19.117Z",
          "created_by": {
            "id": "id",
            "type": "user",
            "object": "identity"
          },
          "current_version_num": 0,
          "name": "name",
          "tags": [
            "string"
          ],
          "archived_at": "2019-12-27T18:11:19.117Z",
          "description": "description",
          "object": "dataset"
        }
      ],
      "name": "name",
      "status": "failed",
      "tags": [
        "string"
      ],
      "archived_at": "2019-12-27T18:11:19.117Z",
      "description": "description",
      "error_count": 0,
      "metadata": {
        "foo": "bar"
      },
      "object": "evaluation",
      "progress": {
        "items": {
          "failed": 0,
          "pending": 0,
          "successful": 0,
          "total": 0,
          "failed_items": [
            {
              "item_id": "item_id",
              "error": "error",
              "error_type": "error_type"
            }
          ]
        },
        "workflows": {
          "completed": 0,
          "failed": 0,
          "pending": 0,
          "total": 0
        }
      },
      "status_reason": "status_reason",
      "tasks": [
        {
          "configuration": {
            "messages": [
              {
                "foo": "bar"
              }
            ],
            "model": "model",
            "audio": {
              "foo": "bar"
            },
            "frequency_penalty": -2,
            "function_call": {
              "foo": "bar"
            },
            "functions": [
              {
                "foo": "bar"
              }
            ],
            "logit_bias": {
              "foo": 0
            },
            "logprobs": true,
            "max_completion_tokens": 0,
            "max_tokens": 0,
            "metadata": {
              "foo": "string"
            },
            "modalities": [
              "string"
            ],
            "n": 0,
            "parallel_tool_calls": true,
            "prediction": {
              "foo": "bar"
            },
            "presence_penalty": -2,
            "reasoning_effort": "reasoning_effort",
            "response_format": {
              "foo": "bar"
            },
            "seed": 0,
            "stop": "string",
            "store": true,
            "temperature": 0,
            "tool_choice": "string",
            "tools": [
              {
                "foo": "bar"
              }
            ],
            "top_k": 0,
            "top_logprobs": 0,
            "top_p": 0
          },
          "alias": "alias",
          "task_type": "chat_completion"
        }
      ]
    }
  ],
  "total": 0,
  "limit": 0,
  "object": "list"
}
```