modaic-api

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Reference for the Modaic REST API — every public endpoint with a working curl + Python example. Use this skill when the user is calling Modaic over HTTP directly (not via the Python SDK), debugging an API request, or wiring Modaic into a non-Python service.

modaic-ai By modaic-ai schedule Updated 6/4/2026
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name: modaic-api description: Reference for the Modaic REST API — every public endpoint with a working curl + Python example. Use this skill when the user is calling Modaic over HTTP directly (not via the Python SDK), debugging an API request, or wiring Modaic into a non-Python service.

Modaic REST API

Base URL: https://api.modaic.dev

All endpoints require a bearer token in the Authorization header. Get a token at https://modaic.dev/settings/tokens and set it as MODAIC_TOKEN.

export MODAIC_TOKEN=mk_...

The Python examples below use the httpx client and assume the env var is set. They are written so you can paste them straight into a script.

The arbiter run endpoints require the provider's API key (e.g. TOGETHER_API_KEY) to be set as an Environment Variable on Modaic Hub at https://modaic.dev/settings/env-vars. Without it, POST /api/v1/arbiters/predictions will fail server-side regardless of how you're calling it.

Arbiters

Initialize an arbiter

POST /api/v1/arbiters — creates a new arbiter repository from a JSON-schema-style field spec. Use this when you don't have a Python environment available; otherwise prefer the Signature + modaic.Predict flow from the SDK.

curl -X POST https://api.modaic.dev/api/v1/arbiters \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "repo": "your-org/support-triage",
    "inputs": [
      {"name": "ticket", "type": "string", "description": "Support ticket text"}
    ],
    "outputs": [
      {
        "name": "queue",
        "type": "string",
        "options": ["billing", "technical", "account"],
        "description": "Which queue the ticket belongs to"
      },
      {
        "name": "severity",
        "type": "number",
        "range": [1, 5],
        "description": "Urgency from 1 (low) to 5 (high)"
      }
    ],
    "instructions": "Route the ticket to the correct queue.",
    "model": "gpt-oss-120b"
  }'

import os, httpx

httpx.post(
    "https://api.modaic.dev/api/v1/arbiters",
    headers={"Authorization": f"Bearer {os.environ['MODAIC_TOKEN']}"},
    json={
        "repo": "your-org/support-triage",
        "inputs": [{"name": "ticket", "type": "string"}],
        "outputs": [
            {
                "name": "queue",
                "type": "string",
                "options": ["billing", "technical", "account"],
            },
            {"name": "severity", "type": "number", "range": [1, 5]},
        ],
        "instructions": "Route the ticket to the correct queue.",
        "model": "gpt-oss-120b",
    },
).raise_for_status()

Each field in inputs / outputs accepts:

  • options — restrict the field to a fixed set of allowed values. (The former name allowed_values is still accepted.)
  • range — a two-element [lo, hi] inclusive integer scale (e.g. [1, 5]), valid only when type is number. Mutually exclusive with options.

Get arbiter metadata

GET /api/v1/arbiters/?repo=... — returns the arbiter's metadata.

curl "https://api.modaic.dev/api/v1/arbiters/?repo=your-org/support-triage" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Get arbiter schema

GET /api/v1/arbiters/schema?repo=... — returns the arbiter's input/output schema.

curl "https://api.modaic.dev/api/v1/arbiters/schema?repo=your-org/support-triage" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Update arbiter metadata

PATCH /api/v1/arbiters/metadata — patch arbiter metadata (e.g. confidence threshold, slack notifications).

curl -X PATCH https://api.modaic.dev/api/v1/arbiters/metadata \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "repo": "your-org/support-triage",
    "metadata": {"confidence_threshold": 0.8}
  }'

Run a prediction

POST /api/v1/arbiters/predictions — run one or more arbiters on a single input. This is what the Python Arbiter.__call__ calls under the hood, and what Braintrust scorers + LangSmith integrations end up hitting.

curl -X POST https://api.modaic.dev/api/v1/arbiters/predictions \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {"ticket": "My payment failed twice in a row."},
    "arbiters": [
      {"arbiter_repo": "your-org/support-triage", "arbiter_revision": "main"}
    ]
  }'

import os, httpx

r = httpx.post(
    "https://api.modaic.dev/api/v1/arbiters/predictions",
    headers={"Authorization": f"Bearer {os.environ['MODAIC_TOKEN']}"},
    json={
        "input": {"ticket": "My payment failed twice in a row."},
        "arbiters": [{"arbiter_repo": "your-org/support-triage"}],
    },
    timeout=60,
)
r.raise_for_status()
print(r.json()["predictions"][0]["output"])

To attach ground-truth at prediction time (e.g. when running labeled data through an arbiter for evaluation), include ground_truth and ground_reasoning per arbiter:

{
  "input": {"ticket": "..."},
  "arbiters": [{
    "arbiter_repo": "your-org/support-triage",
    "ground_truth": "billing",
    "ground_reasoning": "Refund request"
  }]
}

Dispatch predictions across arbiters

POST /api/v1/arbiters/predictions/dispatch — fan one input out across multiple arbiters/groups. Use this when one record needs to be routed through several arbiters at once.

curl -X POST https://api.modaic.dev/api/v1/arbiters/predictions/dispatch \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "input": {"ticket": "My payment failed twice in a row."},
    "alt_id": "ticket-12345",
    "arbiters_map": {
      "triage": [{"arbiter_repo": "your-org/support-triage"}],
      "sentiment": [{"arbiter_repo": "your-org/sentiment"}]
    }
  }'

Chat completions (OpenAI-compatible)

POST /api/v1/arbiters/chat/completions — OpenAI-compatible chat completions surface. The model field is your Arbiter repo path. This is the endpoint LangSmith and other OpenAI-compatible tools point at.

curl -X POST https://api.modaic.dev/api/v1/arbiters/chat/completions \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "your-org/support-triage",
    "messages": [
      {"role": "user", "content": "<run><ticket>My payment failed</ticket></run>"}
    ]
  }'

The endpoint parses the user message for XML tags whose names match the arbiter's signature input fields, then runs the arbiter. See the langsmith.md reference in modaic-python-sdk for the templating contract.

Examples (predictions store)

Each arbiter run produces an example stored in Modaic's prediction store. These endpoints manage that store.

Create examples

POST /api/v1/examples — bulk-insert examples (NDJSON body).

curl -X POST https://api.modaic.dev/api/v1/examples \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: text/plain" \
  --data-binary $'{"input":{"ticket":"refund please"},"ground_truth":"billing"}\n{"input":{"ticket":"login broken"},"ground_truth":"technical"}'

List examples

GET /api/v1/examples — paginated, filterable list.

curl "https://api.modaic.dev/api/v1/examples?program=your-org/support-triage&page=1&page_size=50&max_confidence=0.6" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Useful filters: user, program, version, commit_hash, search, sort_by, sort_order, max_confidence (great for "show me the arbiter's least-certain predictions").

Get a single example

GET /api/v1/examples/{example_id} — fetch one prediction.

curl "https://api.modaic.dev/api/v1/examples/ex_01HZ9K2F8V" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Annotate an example

PATCH /api/v1/examples/{example_id}/annotation — attach ground_truth / ground_reasoning to an existing prediction. This is the supervision signal Modaic uses to align the arbiter and re-train the confidence probe.

curl -X PATCH https://api.modaic.dev/api/v1/examples/ex_01HZ9K2F8V/annotation \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "annotations": [{
      "arbiter_repo": "your-org/support-triage",
      "ground_truth": "escalate",
      "ground_reasoning": "Repeated failures suggest a payment-provider outage."
    }]
  }'

Delete examples

DELETE /api/v1/examples — bulk-delete by IDs scoped to one arbiter.

curl -X DELETE https://api.modaic.dev/api/v1/examples \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "arbiter_repo": "your-org/support-triage",
    "example_ids": ["ex_01HZ9K2F8V", "ex_01HZ9K2F8W"]
  }'

Check for uncalibrated examples

GET /api/v1/examples/has-uncalibrated — does the program still have examples awaiting confidence scoring?

curl "https://api.modaic.dev/api/v1/examples/has-uncalibrated?program=your-org/support-triage" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Jobs

Long-running background work. Both confidence scoring and prompt optimization (GEPA) follow the same start/poll/cancel pattern.

Confidence scoring

POST /api/v1/jobs/confidence-scores — kick off scoring for any unscored predictions in an arbiter's repo.

curl -X POST https://api.modaic.dev/api/v1/jobs/confidence-scores \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"arbiter_repo": "your-org/support-triage"}'

GET /api/v1/jobs/confidence-scores/{job_id} — poll status.

curl "https://api.modaic.dev/api/v1/jobs/confidence-scores/job_abc123" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

DELETE /api/v1/jobs/confidence-scores/{job_id} — cancel.

curl -X DELETE "https://api.modaic.dev/api/v1/jobs/confidence-scores/job_abc123" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

Prompt optimization (GEPA)

POST /api/v1/jobs/gepa — kick off prompt optimization on labeled examples and push the result back to the repo.

curl -X POST https://api.modaic.dev/api/v1/jobs/gepa \
  -H "Authorization: Bearer $MODAIC_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "arbiter_repo": "your-org/support-triage",
    "arbiter_revision": "main",
    "push_branch": "main",
    "push_tag": "optimized-v1",
    "gepa_kwargs": {
      "auto": "light",
      "candidate_selection_strategy": "pareto",
      "component_selector": "round_robin"
    }
  }'

GET /api/v1/jobs/gepa/{job_id} — poll status. Response includes status (in_progress | completed | failed), an optional message, and a results payload when finished.

curl "https://api.modaic.dev/api/v1/jobs/gepa/job_xyz" \
  -H "Authorization: Bearer $MODAIC_TOKEN"

DELETE /api/v1/jobs/gepa/{job_id} — cancel.

curl -X DELETE "https://api.modaic.dev/api/v1/jobs/gepa/job_xyz" \
  -H "Authorization: Bearer $MODAIC_TOKEN"
Install via CLI
npx skills add https://github.com/modaic-ai/modaic --skill modaic-api
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