rosetta-aaaj

name

rosetta-aaaj

description

Attach Agent-as-a-Judge (AaaJ / harness) evaluators to any Arize AX Wonder Toys project and trigger a one-time backfill. Reads scoring instructions from evals/aaaj/*.md and creates evaluators + tasks via GraphQL (REST and the ax CLI cannot create harness evals). Use when the user asks to add AaaJ, agent-as-a-judge, harness evals, or to score AX traces without the UI. AX-only; not part of rosetta-test e2e. Default PROJECT_DIR is ax/langchain-py; any ax/<framework> with .env.local works.

Rosetta — Agent-as-a-Judge

Create (or reuse) three space-level harness evaluators, attach one project task per evaluator on this AX project's modelId, and trigger a backfill. Do not use ax evaluators create or ax tasks create — those only support TEMPLATE / CODE. Do not POST to /api/graphql/v1 (cookie / session UI schema).

There is no committed runner script. Follow this file exactly.

Inputs

• PROJECT_DIR — default: repo ax/langchain-py. Any ax/<framework> with .env.local works (ARIZE_SPACE_ID, ARIZE_API_KEY, ARIZE_PROJECT_NAME). Phoenix and no-observability are out of scope.
• From $PROJECT_DIR/.env.local (never print values): ARIZE_SPACE_ID, ARIZE_API_KEY, ARIZE_PROJECT_NAME (required — each tier's env.example has its own default, e.g. wonder-toys-langchain-py for langchain-py). Do not hardcode a project name.
• Optional: ARIZE_GRAPHQL_URL (default https://app.arize.com/graphql)

Phoenix is out of scope. If the user is on phoenix/<framework> (or no-observability/), stop and say AaaJ is AX-only.

Traces must already exist in that project's ARIZE_PROJECT_NAME. Typically npm run synthetic-requests in $PROJECT_DIR (most AX apps already have this script). If they do not, run synthetic requests first (and keep EVAL_SECRET in .env.local so Next.js tags eval-user-001).

Stable names

Source of truth for scoring text is the markdown files — cat them into harnessEvaluator.template. Do not rewrite the rubrics.

Evaluators are space-level (one set of three, reused across frameworks). Tasks are per AX project (modelId).

Evaluator display name	Column (harnessEvaluator.name)	Rubric file	Labels (score)
rosetta-aaaj-trajectory-completion	aaaj_trajectory_completion	evals/aaaj/trajectory-task-completion.md	pass 1, fail 0
rosetta-aaaj-tool-grounding	aaaj_tool_grounding	evals/aaaj/tool-result-grounding.md	grounded 1, ungrounded 0, not_applicable 0.5
rosetta-aaaj-purchase-cancel	aaaj_purchase_cancel	evals/aaaj/purchase-cancel-protocol.md	safe 1, unsafe 0, not_applicable 0.5

Matching task names (one evaluator per task):

• rosetta-aaaj-trajectory-completion
• rosetta-aaaj-tool-grounding
• rosetta-aaaj-purchase-cancel

Idempotency: reuse an evaluator if the space already has that display name or the older ad-hoc names aaaj_trajectory_completion / aaaj_tool_grounding / aaaj_purchase_cancel. Reuse a task if one with the stable name already exists on this project/model. Same display names across projects are OK — tasks are per modelId. Still trigger runOnlineTask unless the user asked create-only.

If looping multiple ax/<framework> dirs: reuse the three evaluators; create or reuse the three tasks on each project's modelId; trigger runOnlineTask per task.

strictChoices: true, direction: maximize on every evaluator.

Endpoint

POST https://app.arize.com/graphql
Content-Type: application/json
x-api-key: $ARIZE_API_KEY
Origin: https://app.arize.com

Never print ARIZE_API_KEY. Use curl + env vars. $ARIZE_SPACE_ID is already a Space Relay GID (U3BhY2U6…).

Helper:

REPO_ROOT="$(git rev-parse --show-toplevel)"
PROJECT_DIR="${PROJECT_DIR:-$REPO_ROOT/ax/langchain-py}"
set -a
# shellcheck disable=SC1091
source "$PROJECT_DIR/.env.local"
set +a
: "${ARIZE_SPACE_ID:?}" "${ARIZE_API_KEY:?}" "${ARIZE_PROJECT_NAME:?set ARIZE_PROJECT_NAME in $PROJECT_DIR/.env.local}"
GQL="${ARIZE_GRAPHQL_URL:-https://app.arize.com/graphql}"

gql() {
  curl -sS "$GQL" \
    -H "Content-Type: application/json" \
    -H "x-api-key: $ARIZE_API_KEY" \
    -H "Origin: https://app.arize.com" \
    --data-binary @-
}

If a mutation returns GraphQL Mutation access is only available for enterprise accounts, or a permissions error, stop. Point the user at the UI fallback in evals/aaaj/README.md.

Step 1 — Resolve integration + project

query ($spaceId: ID!, $projectName: String!) {
  node(id: $spaceId) {
    ... on Space {
      llmIntegrations { id name provider hasApiKey }
      models(first: 20, search: $projectName, useExactSearchMatch: true) {
        edges { node { id name } }
      }
    }
  }
}

Variables: { "spaceId": "<ARIZE_SPACE_ID>", "projectName": "<ARIZE_PROJECT_NAME>" }.

Pick the first Anthropic integration with hasApiKey (provider case-insensitive anthropic). Abort if none.

Take the model whose name equals ARIZE_PROJECT_NAME. Abort if missing — traces may not have created the project yet.

enableManagedAgents is not required to create evaluators. It is required to create harness tasks; if createEvalTask fails with a managed-agents / feature-flag error, stop and use the UI fallback.

Step 2 — List existing evaluators

Use whatever list query works on this schema (for example Space evaluators connection, or ax evaluators list --space "$ARIZE_SPACE_ID" -o json for names/ids only). Build {displayName → evaluatorId}.

Treat these as already created for the three slots:

• rosetta-aaaj-trajectory-completion or aaaj_trajectory_completion
• rosetta-aaaj-tool-grounding or aaaj_tool_grounding
• rosetta-aaaj-purchase-cancel or aaaj_purchase_cancel

Step 3 — Create missing evaluators

mutation CreateAaaJ($input: CreateEvaluatorMutationInput!) {
  createEvaluator(input: $input) {
    evaluator { id name taskType }
  }
}

{
  "input": {
    "spaceId": "<ARIZE_SPACE_ID>",
    "name": "rosetta-aaaj-trajectory-completion",
    "description": "Wonder Toys AaaJ trajectory task completion",
    "commitMessage": "Initial version",
    "harnessEvaluator": {
      "llmIntegrationId": "<Anthropic LlmIntegration GID>",
      "name": "aaaj_trajectory_completion",
      "template": "<full contents of evals/aaaj/trajectory-task-completion.md>",
      "classificationChoices": { "pass": 1, "fail": 0 },
      "strictChoices": true,
      "direction": "maximize"
    
  

Repeat for grounding and purchase-cancel with the table above. JSON-escape the template (newlines as \n). Top-level name is the hub display name; harnessEvaluator.name is the eval column (trace_eval.<column>.*).

Step 4 — Create missing tasks

One evaluator per task. queryFilter must be JSON null (not span_kind = 'LLM').

mutation CreateAaaJTask($input: CreateEvalTaskMutationInput!) {
  createEvalTask(input: $input) {
    evalTask { id name }
  }
}

{
  "input": {
    "name": "rosetta-aaaj-trajectory-completion",
    "modelId": "<Model Relay GID>",
    "samplingRate": 1,
    "runContinuously": false,
    "queryFilter": null,
    "evaluators": [
      { "evaluatorId": "<Evaluator Relay GID>", "position": 0 }
    ]
  }
}

If a task with that name already exists on this project, reuse its id.

Step 5 — Trigger runs

Window: UTC midnight yesterday through now, span ≤ 30 days. Example: dataStartTime 2026-08-19T00:00:00.000Z, dataEndTime now with Z. maxSpans: 200. overrideEvaluations: false.

mutation RunAaaJ($input: RunOnlineTaskMutationInput!) {
  runOnlineTask(input: $input) {
    result { __typename }
  }
}

{
  "input": {
    "onlineTaskId": "<OnlineTask Relay GID>",
    "dataStartTime": "<ISO8601 Z>",
    "dataEndTime": "<ISO8601 Z>",
    "maxSpans": 200,
    "overrideEvaluations": false
  }
}

Call once per task. Do not wait for sandbox completion unless the user asks. Print display names + Relay ids for evaluators, tasks, and runs.

Tell the user scores appear as trace_eval.aaaj_trajectory_completion.label (and the other two columns) on root spans when the harness runs finish.

Output

AaaJ: <ARIZE_PROJECT_NAME>
  Evaluators: created|reused × 3
  Tasks:      created|reused × 3
  Runs:       triggered × 3
  Scores:     trace_eval.aaaj_*.{label,score,explanation} on root spans

UI fallback

If GraphQL is blocked, the user pastes the same three .md files in AX:

1. Evaluators → Agent-as-a-Judge → Create From Blank
2. Scoring instructions = file contents; lock the labels from the table; maximize
3. New Eval Task → Agent-as-a-Judge → this project, one evaluator, empty query filter, one-time backfill

Full click-path: evals/aaaj/README.md.

What not to do

• Do not call this from rosetta-test / rosetta-test-evals (sandbox time + enableManagedAgents)
• Do not mix TEMPLATE evaluators onto a harness task
• Do not print API keys, integration secrets, or .env.local
• Do not clone evaluators per framework — they stay space-level