--- title: "Get evaluator" method: GET path: "/v2/evaluators/{evaluator_id}" tags: ["Evaluators"] --- # Get evaluator `GET /v2/evaluators/{evaluator_id}` Returns an evaluator and a resolved version. By default, the latest version is included. Use the version_id query parameter to resolve a specific version. This endpoint is in beta, read more [here](https://arize.com/docs/ax/rest-reference#api-version-stages). ## Path parameters - `evaluator_id` string, required — A universally unique identifier (base64-encoded opaque string). ## Query parameters - `version_id` string — A universally unique identifier (base64-encoded opaque string). ## Response `200` Returns an evaluator with a resolved version - EvaluatorWithVersion — An evaluator defines reusable evaluation logic that can be attached to evaluation tasks. The type field determines the kind of evaluation: TEMPLATE (LLM-based template evaluation) or CODE (custom code evaluation). - `id` string, required — The unique identifier for the evaluator - `name` string, required — The name of the evaluator - `description` string, nullable — The description of the evaluator - `type` 'TEMPLATE' | 'CODE' | 'HARNESS' | 'REMOTE', required — The evaluator type: - `TEMPLATE` — LLM-based evaluator. - `CODE` — managed built-in evaluators or custom Python code (both are subtypes of `CODE`, discriminated by the nested `CodeConfig.type` = `MANAGED` | `CUSTOM`). - `HARNESS` — test harness evaluator. - `REMOTE` — remote evaluator. Applies to both the parent `Evaluator.type` field and every version's `type` discriminator — a version's `type` must always match its parent evaluator's `type`. - `space_id` string, required — The unique identifier for the space the evaluator belongs to - `created_at` string, date-time, required — When the evaluator was created - `updated_at` string, date-time, required — When the evaluator was last updated - `created_by_user_id` string, nullable, required — The unique identifier for the user who created the evaluator - `version` union, required — A versioned snapshot of an evaluator's configuration. The `type` field discriminates the branch and matches the parent evaluator's `type`. - EvaluatorVersionTemplate — Evaluator version carrying a template (LLM) configuration. - `id` string, required — The unique identifier for this version - `evaluator_id` string, required — The parent evaluator ID - `commit_hash` string, required — A unique hash identifying this version - `commit_message` string, nullable, required — A message describing the changes in this version - `created_at` string, date-time, required — When this version was created - `created_by_user_id` string, nullable, required — The unique identifier for the user who created this version - `type` 'TEMPLATE', required — Discriminator identifying this as a template evaluator version. Always `TEMPLATE` for this variant. - `template_config` TemplateConfig, required - `name` string, required — Eval column name. Must match ^[a-zA-Z0-9_\s\-&()]+$ - `template` string, required — The prompt template with variable placeholders - `include_explanations` boolean, required — Whether to include explanations in the evaluation output - `use_function_calling_if_available` boolean, required — Whether to use function calling if the model supports it - `use_structured_output` boolean — Whether to use structured output if the model supports it - `classification_choices` object, nullable — Map of choice label to numeric score (e.g. {"relevant": 1, "irrelevant": 0}). Null for legacy freeform evaluators that predate required choices. - `direction` 'MAXIMIZE' | 'MINIMIZE' | 'NONE' — The direction for optimization. Defaults to `NONE` when omitted. - MAXIMIZE: higher scores are better - MINIMIZE: lower scores are better - NONE: higher or lower scores are neither better nor worse - `data_granularity` 'SPAN' | 'TRACE' | 'SESSION' — Data granularity level for evaluation. - SPAN - Evaluate at the individual span level. - TRACE - Evaluate at the full trace level. - SESSION - Evaluate at the session level. - `llm_config` EvaluatorLlmConfig, required - `ai_integration_id` string, required — AI integration identifier (base64) - `model_name` string, required — Model name (e.g. gpt-4o) - `invocation_parameters` InvocationParams, required — Parameters for the LLM invocation - `temperature` number — Sampling temperature (higher = more random) - `max_tokens` integer — Maximum number of tokens to generate - `max_completion_tokens` integer — Maximum number of completion tokens to generate - `top_p` number — Nucleus sampling parameter - `frequency_penalty` number — Frequency penalty (-2.0 to 2.0) - `presence_penalty` number — Presence penalty (-2.0 to 2.0) - `stop` string[] — Stop sequences - `response_format` ResponseFormat — Response format configuration - … - `tool_config` ToolConfig — Tool configuration for the LLM invocation - … - `top_k` integer — Top-K sampling parameter. A top-K of 1 means the next selected token is the most probable (greedy decoding). - `thinking_level` string — Controls how much reasoning the model performs before responding. Supported by Gemini 3.x models. Accepted values: 'low', 'high'. - `thinking_budget` integer — Maximum tokens the model may use for internal reasoning. Supported by Gemini 2.5 models. Range: 0-24576 (Flash/Flash-Lite) or 128-32768 (Pro). Set 0 to disable thinking on Flash models. - `reasoning_effort` string — Controls how much reasoning the model performs before responding. Supported by OpenAI o-series and GPT-5 models. o-series: 'low' | 'medium' | 'high'. GPT-5: 'none' | 'low' | 'medium' | 'high' | 'xhigh'. - `verbosity` string — Controls the verbosity of model output. Supported by OpenAI GPT-5 series. Accepted values: 'low' | 'medium' | 'high'. - `provider_parameters` ProviderParams, required — Provider-specific parameters - `azure_params` AzureParams — Azure OpenAI specific parameters - … - `anthropic_headers` AnthropicHeaders — Anthropic-specific headers - … - `anthropic_version` string — Anthropic API version - `bedrock_options` BedrockOptions — AWS Bedrock options - … - `region` string — Region for the model deployment - EvaluatorVersionCode — Evaluator version carrying a code configuration. - `id` string, required — The unique identifier for this version - `evaluator_id` string, required — The parent evaluator ID - `commit_hash` string, required — A unique hash identifying this version - `commit_message` string, nullable, required — A message describing the changes in this version - `created_at` string, date-time, required — When this version was created - `created_by_user_id` string, nullable, required — The unique identifier for the user who created this version - `type` 'CODE', required — Discriminator identifying this as a code evaluator version. Always `CODE` for this variant. - `code_config` union, required — Discriminated union representing either a managed (built-in) or custom (user-supplied Python) code evaluator configuration, resolved by the nested `type` field (`MANAGED` -> `ManagedCodeConfig`, `CUSTOM` -> `CustomCodeConfig`). This inner `type` is independent of the parent evaluator version's `type` (which is always `CODE` here). - ManagedCodeConfig - `data_granularity` 'SPAN' | 'TRACE' | 'SESSION' — Data granularity level for evaluation. - SPAN - Evaluate at the individual span level. - TRACE - Evaluate at the full trace level. - SESSION - Evaluate at the session level. - `query_filter` string, nullable — Optional filter query over the chosen data granularity. When omitted or null, no filter is applied. - `type` 'MANAGED', required — Discriminator identifying this as a managed (built-in) code evaluator - `name` string, required — Eval column name. Must match ^[a-zA-Z0-9_\s\-&()]+$ - `managed_evaluator` 'MATCHES_REGEX' | 'JSON_PARSEABLE' | 'CONTAINS_ANY_KEYWORD' | 'CONTAINS_ALL_KEYWORDS' | 'EXACT_MATCH', required — Built-in managed code evaluator name - `variables` string[], required — Dataset columns or span attributes passed into the evaluator (order and count must match the managed evaluator's requirements). - `static_params` StaticParam[] — Static parameters for the managed evaluator (see registry `args`). When omitted, the registry's required arguments must be satisfied by defaults on the evaluator class; otherwise validation fails with 400. If the registry has no args, omitting this field is equivalent to an empty list. - `name` string, required — Parameter name (matches the managed evaluator's argument name) - `type` 'STRING' | 'STRING_ARRAY' | 'REGEX', required — Argument type for static evaluator parameters. - STRING - A single string value. - STRING_ARRAY - An array of string values. - REGEX - A regular expression string. - `default_value` union, required — Default value. Must be a string when `type` is STRING or REGEX, and a string array when `type` is STRING_ARRAY. Mismatches are rejected with 400 by the server. - … - CustomCodeConfig - `data_granularity` 'SPAN' | 'TRACE' | 'SESSION' — Data granularity level for evaluation. - SPAN - Evaluate at the individual span level. - TRACE - Evaluate at the full trace level. - SESSION - Evaluate at the session level. - `query_filter` string, nullable — Optional filter query over the chosen data granularity. When omitted or null, no filter is applied. - `type` 'CUSTOM', required — Discriminator identifying this as a custom (user-supplied Python) code evaluator - `name` string, required — Eval column name. Must match ^[a-zA-Z0-9_\s\-&()]+$ - `code` string, required — Python source defining the evaluator class - `imports` string, nullable — Optional package import block prepended when running the evaluator - `variables` string[], required — Dataset columns or span attributes mapped to evaluate() arguments - `static_params` StaticParam[] — Optional typed defaults accessible on the evaluator instance. Omit or pass an empty array when the custom class does not read any static parameters. - `name` string, required — Parameter name (matches the managed evaluator's argument name) - `type` 'STRING' | 'STRING_ARRAY' | 'REGEX', required — Argument type for static evaluator parameters. - STRING - A single string value. - STRING_ARRAY - An array of string values. - REGEX - A regular expression string. - `default_value` union, required — Default value. Must be a string when `type` is STRING or REGEX, and a string array when `type` is STRING_ARRAY. Mismatches are rejected with 400 by the server. - … - EvaluatorVersionHarness — Evaluator version backed by a harness evaluation config. Only common version metadata (id, commit info, timestamps) is returned — the harness configuration is not yet accessible and will be a future addition. - `id` string, required — The unique identifier for this version - `evaluator_id` string, required — The parent evaluator ID - `commit_hash` string, required — A unique hash identifying this version - `commit_message` string, nullable, required — A message describing the changes in this version - `created_at` string, date-time, required — When this version was created - `created_by_user_id` string, nullable, required — The unique identifier for the user who created this version - `type` 'HARNESS', required — Discriminator identifying this as a harness evaluator version. - EvaluatorVersionRemote — Evaluator version backed by a remote evaluation config. Only common version metadata (id, commit info, timestamps) is returned — the remote configuration is not yet accessible and will be a future addition. - `id` string, required — The unique identifier for this version - `evaluator_id` string, required — The parent evaluator ID - `commit_hash` string, required — A unique hash identifying this version - `commit_message` string, nullable, required — A message describing the changes in this version - `created_at` string, date-time, required — When this version was created - `created_by_user_id` string, nullable, required — The unique identifier for the user who created this version - `type` 'REMOTE', required — Discriminator identifying this as a remote evaluator version. ## Other responses - `400` — Invalid request - `401` — Authentication is required - `404` — Not found - `429` — Rate limit exceeded --- [API](https://skmtc.net/arize-ai/apis/arize-rest-api.md) · [All operations](https://skmtc.net/arize-ai/apis/arize-rest-api/llms.txt) · [OpenAPI document](https://skmtc-service-staging.skmtc.workers.dev/v1/apis/arize-ai/arize-rest-api/versions/1e87d8a4cf69/schema)