> ## Documentation Index
> Fetch the complete documentation index at: https://docs.omnia-voice.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Get an eval run

> Status and, once `status` is `DONE`, the report: per-candidate win rate, W/T/L, average latency, cost, and savings versus the baseline on the same prompts. Poll this after queueing a run.



## OpenAPI

````yaml /openapi.json get /v1/evals/{id}
openapi: 3.1.0
info:
  title: Omnia Management API
  description: >-
    The management API behind the improvement loop: capture and setup, request
    logs and datasets, grades (labels), judges (criteria), evals and deploy
    gates, fine-tuning and reinforcement learning, dedicated GPU endpoints, and
    model aliases and versions. Authenticated with a workspace API key
    (sk_sovereign_...). The inference API (chat, embeddings, rerank, responses)
    is OpenAI-compatible and documented separately.


    Responses are snake_case, list endpoints on the loop products use the
    {"object": "list", "data": [...]} envelope, and refusals use the same nested
    error shape the gateway emits: {"error": {"message", "type", "code"}}.
    Request bodies on the loop products (logs, labels, criteria, evals,
    datasets, aliases) are snake_case; the training and infrastructure products
    (fine-tuning, GRPO, environment tools, dedicated, model-version adoption)
    validate camelCase bodies, and each schema below says which it is. Endpoints
    that spend money require a key minted by a workspace owner or admin and
    return 403 otherwise.
  version: 1.0.0
servers:
  - url: https://gateway.omnia-voice.com
    description: Production
  - url: https://platform.omnia-voice.com/api
    description: Production (legacy alias — same API, older base URL)
security:
  - bearerAuth: []
paths:
  /v1/evals/{id}:
    get:
      tags:
        - Evals
      summary: Get an eval run
      description: >-
        Status and, once `status` is `DONE`, the report: per-candidate win rate,
        W/T/L, average latency, cost, and savings versus the baseline on the
        same prompts. Poll this after queueing a run.
      operationId: getEvalRun
      parameters:
        - name: id
          in: path
          required: true
          schema:
            type: string
      responses:
        '200':
          description: The run.
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/EvalRun'
        '401':
          $ref: '#/components/responses/Unauthorized'
        '404':
          $ref: '#/components/responses/NotFound'
components:
  schemas:
    EvalRun:
      type: object
      properties:
        id:
          type: string
        name:
          type: string
        rubric:
          type: string
          description: What "good" means, in plain English. The judge scores against this.
        rubric_type:
          type: string
          enum:
            - direct
            - adherence
        eval_kind:
          type: string
          description: >-
            comparison: pairwise judging against the baseline. criterion: a
            saved judge grades each model pass/fail.
          enum:
            - comparison
            - criterion
        criterion_snapshot:
          type:
            - object
            - 'null'
          description: >-
            Criterion runs only: the judge frozen at creation (name, prompt, and
            its TPR/TNR/kappa at that moment), so the run's corrected rates stay
            reproducible after the judge changes.
        baseline_model:
          type: string
        candidate_models:
          type: array
          items:
            type: string
        judge_model:
          type: string
        sample_count:
          type: integer
        gen_max_output_tokens:
          type: integer
          description: >-
            Per-answer generation cap the run was created with (see
            max_output_tokens on create).
        sample_filters:
          type: object
          description: >-
            Where the prompts came from: tag, model, segment, dataset_id,
            trace_replay, and screening (set on screening runs). Echoes what the
            run was created with.
        status:
          type: string
          enum:
            - PENDING
            - RUNNING
            - DONE
            - ERROR
            - CANCELLED
        error:
          type:
            - string
            - 'null'
        assertions:
          type:
            - array
            - 'null'
          description: >-
            The deterministic assertion configs the run was created with, when
            any.
        progress_ratio:
          type: number
          description: 0–1. Completed inference calls over total.
        results:
          type:
            - object
            - 'null'
          description: >-
            Present when status is DONE. Comparison runs: sample_count,
            clipped_samples, baseline {model, stored_answers, truncated,
            avg_latency_ms, eval_cost_micros}, per_candidate [{model, win_rate,
            wins, ties, losses, ci95, failed, attempted, unreportable,
            truncated, avg_latency_ms, eval_cost_micros, savings_pct, replay?}],
            judge_cost_micros, and screening (screening runs only: incumbent,
            token_shape, per_candidate similarity + estimated cost placement,
            recommendation). Criterion runs: per_model [{model,
            observed_pass_rate, observed_ci, corrected_pass_rate, corrected_ci,
            ...}] using the frozen judge's measured error rates. Assertion runs
            add assertion_results.
        created_at:
          type: string
          format: date-time
    Error:
      type: object
      properties:
        error:
          type: object
          properties:
            message:
              type: string
            type:
              type: string
              description: >-
                invalid_request_error, insufficient_quota, rate_limit_error, or
                api_error.
            code:
              type: string
              description: >-
                Machine-stable cause, e.g. invalid_api_key, not_found,
                insufficient_permissions, precondition_failed.
          required:
            - message
            - type
            - code
      description: >-
        Every refusal — gateway and management API alike — uses this one
        envelope.
  responses:
    Unauthorized:
      description: Missing, malformed, or revoked API key.
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
          example:
            error:
              message: Invalid API key
              type: invalid_request_error
              code: invalid_api_key
    NotFound:
      description: The resource does not exist in your workspace.
      content:
        application/json:
          schema:
            $ref: '#/components/schemas/Error'
  securitySchemes:
    bearerAuth:
      type: http
      scheme: bearer
      description: >-
        Your workspace API key, e.g. `sk_sovereign_...`, sent as `Authorization:
        Bearer <key>`.

````