ai-orchestrator-client 0.1.0

Python client for the AI Orchestrator (https://github.com/ernesto01louis/ai-orchestrator).

ai-orchestrator-client

Python SDK for the AI Orchestrator.

This is the primary consumer contract for the orchestrator platform. Research projects (aerodynamics optimization, RF DF, music generation, anything) install this library, call OrchestratorClient.run(...) or OrchestratorClient.start_campaign(...), and stream results back without having to know the HTTP surface.

Status: alpha. First PyPI release: 0.1.0a0. See CHANGELOG.md for shipping work.

Install

pip install ai-orchestrator-client

Python 3.11+. Wraps the orchestrator's HTTP API + /ws log stream; async-first under the hood with a sync façade for scripts.

Quick start

Submit a single run (sync)

from ai_orchestrator_client import OrchestrateRequest, OrchestratorClient

req = OrchestrateRequest(
    project_name="hello-world",
    prompt="Write a Python script that prints fizzbuzz to 30.",
    planner_model="qwen2.5-coder:14b",
    generator_models=["qwen2.5-coder:14b"],
    judge_model="qwen2.5-coder:14b",
    deploy_target="local",
)

with OrchestratorClient(base_url="http://localhost:8000") as client:
    ack = client.run(req)
    final = client.wait_for_completion(ack.run_id, timeout=600)
    print(final.score, final.result)

Submit a campaign (parameter sweep) and stream results (async)

import asyncio
from ai_orchestrator_client import (
    AsyncOrchestratorClient, CampaignCreate, CampaignTemplate,
)

async def main() -> None:
    req = CampaignCreate(
        name="seed-sweep",
        hypothesis="output is invariant across seeds 1..4",
        template=CampaignTemplate(
            project_name="hello-{seed}",
            prompt="Print fizzbuzz with seed {seed}.",
            planner_model="qwen2.5-coder:14b",
            generator_models=["qwen2.5-coder:14b"],
            judge_model="qwen2.5-coder:14b",
            deploy_target="local",
        ),
        params={"seed": [1, 2, 3, 4]},
    )

    async with AsyncOrchestratorClient(base_url="http://localhost:8000") as client:
        ack = await client.start_campaign(req)
        campaign = await client.get_campaign(ack.campaign_id)
        async for run in campaign.iter_runs(client):
            print("new run:", run.run_id, run.params)
        verify = await client.verify_campaign_merkle(ack.campaign_id)
        print("merkle ok?", verify.valid)

asyncio.run(main())

Stream live log lines via WebSocket

import asyncio
from ai_orchestrator_client import AsyncOrchestratorClient

async def tail() -> None:
    async with AsyncOrchestratorClient(base_url="http://localhost:8000") as client:
        async for event in client.iter_logs("run-uuid-here", include_status=True):
            # LogEvent or StatusEvent — terminates on completed=True
            print(event)

asyncio.run(tail())

Forward-compatible auth

The orchestrator's HTTP surface has no auth in 1.6 — Phase 1.7 adds bearer tokens. Wire your token now and it'll start being honored once the server ships:

from ai_orchestrator_client import BearerTokenAuth, OrchestratorClient
client = OrchestratorClient(base_url=..., auth=BearerTokenAuth(token))

What's here

Surface	Sync	Async
Run lifecycle (run, get_status, wait_for_completion, get_result, verify_run, tail_log)	✓	✓
Control (pause, resume, restart, idempotent against the server's toggle endpoint)	✓	✓
Campaigns (start_campaign, get_campaign, get_campaign_tree, pause/resume/abort, verify_campaign_merkle)	✓	✓
Evidence (get_evidence, download_evidence_crate, refresh_evidence)	✓	✓
Campaign.iter_runs(client) streaming with empty-runs[] race guard	✓	✓
Live log streaming via /ws (iter_logs)	—	✓
Consumer registry (register_consumer, list_consumers, get_consumer, deregister_consumer, consumer_heartbeat)	✓	✓
Capability dispatch (invoke_capability)	✓	✓
Consumer data-plane push (write_memory, write_vault_note, send_notification, push_evidence)	✓	✓
Consumer base + @capability + dispatch() (framework-free)	✓	✓
Hindsight / Vault / Ntfy thin push clients	✓	—
Bearer-token auth hooks (no-op until orchestrator Phase 1.7 ships token auth)	✓	✓
Typed Pydantic models for every endpoint	✓	✓
OpenAPI drift fixture protecting wire-format mirrors	n/a	n/a

Registering as a consumer (Phase 3.6)

An external project registers with the orchestrator, declares capabilities, and exposes handlers the orchestrator can dispatch work to:

from ai_orchestrator_client import Consumer, capability, OrchestratorClient

class RfdfConsumer(Consumer):
    name = "rfdf"

    @capability("rf.doa.run")
    async def run_doa(self, payload: dict) -> dict:
        ...  # delegate to your platform

with OrchestratorClient(base_url="http://orchestrator.lan:8000") as client:
    consumer = RfdfConsumer()
    consumer.register(client, base_url="http://rfdf.lan:8000",
                      callback_token="…",
                      extra_capabilities=["memory.write"])

# In your own POST /capabilities/{cap} handler:
result = await consumer.dispatch(cap, payload)

Consumer imports no web framework — wire dispatch() into whatever HTTP server the consumer project already runs.

Errors

Catch OrchestratorError for the whole family. Specific subclasses for common failure modes:

• NotFound — server returned 404 (unknown run/campaign id)
• ValidationError — server returned 422; structured FastAPI detail preserved on .errors
• ServiceUnavailable — server returned 503 (typically: orchestrator paused via /control/pause)
• RunFailed — wait_for_completion saw completed=True with a non-empty error field
• WaitTimeout — wait_for_completion exceeded its timeout
• WaitInterrupted — caller-supplied stop_event fired during a poll

Notes

• download_evidence_crate(campaign_id) materializes the whole RO-Crate ZIP in memory — fine for typical bundles, but for multi-GB crates a streaming-to-path variant will land in a follow-up.
• iter_logs filters frames client-side because the orchestrator's /ws broadcasts globally; high-traffic deployments should prefer get_status() polling + tail_log().

Examples

Runnable scripts in examples/:

• examples/sync_run.py — single run end-to-end with the sync client
• examples/async_campaign.py — campaign + streaming runs + Merkle verify
• examples/stream_logs.py — live log tail via WS

Each script reads ORCHESTRATOR_URL (default http://localhost:8000) and an optional ORCHESTRATOR_TOKEN.

License

Apache 2.0 — see LICENSE.