Sail inference with voyage

Sail Inference With Voyage

Use this pattern when a Voyage-instrumented process calls Sail inference through Responses, Chat Completions, or Anthropic Messages. Calls routed through the SDK's sail.inference.* helpers automatically attach Voyage/span/agent headers. Raw Anthropic clients attach the same headers per request. Both paths make model-call rows appear in the dashboard's Native Model Calls panel, scoped to the right agent.

When to use

• Any call to sail.inference.responses.create() / sail.inference.chat.completions.create() from inside a sail.voyage.run(...) (or create(...)) context.
• Wrapping a raw OpenAI client when you can't switch to the SDK helper but still want Voyage attribution.
• Calling client.messages.create(...) through an Anthropic client pointed at Sail while preserving Voyage attribution.

If your Voyage doesn't make inference calls, you don't need this skill.

The contract

Every inference call inside an active Voyage gets these headers attached:

Header	Purpose
X-Sail-Voyage-Id	Required. Identifies which Voyage owns the call.
X-Sail-Voyage-Span-Id	Optional. Scopes the call to a specific span.
X-Sail-Voyage-Agent-Id	Optional. Scopes the call to a specific named agent.

Sail records the model-call association with the call's response_id as the key.

response_id is immutable, first-association-wins. If you retry an inference with the same response_id, the existing association stays attached to whichever Voyage was active at first successful association — even if the retry happens in a different Voyage.

Copy-paste-ready example (SDK helper, automatic attribution)

import sail


@sail.agent("Reviewer")
@sail.span("draft-response")
def draft():
    # Headers attached automatically because a Voyage is active; the call
    # auto-attributes to this agent/span.
    response = sail.inference.responses.create(
        model="zai-org/GLM-5.1-FP8",
        input="Summarize this diff in one paragraph: ...",
        background=False,
        timeout=120,
    )
    sail.voyage.event("response.drafted", payload={"response_id": response["id"]})


with sail.voyage.run(name="agent-with-inference", version=1):
    draft()

Nothing special needed. The Voyage/agent/span context propagates through sail.voyage.headers() → request headers → backend attribution.

No active span? The wrapper synthesizes one automatically (an "auto-span", marked _auto and chipped in the cockpit), named after your calling function — so wrapper calls never land as Missing span. Explicit spans always win; SAIL_VOYAGE_AUTO_SPANS=0 disables synthesis. Raw clients don't get synthesis (headers are request-time only) — wrap those calls in a span yourself when scoping matters.

For a recurring production workflow, use the current series/version shape:

with sail.voyage.run(
    name="deep-research",
    version=3,
    metadata={"topic": "Voyages public launch"},
):
    ...

Background mode

sail.inference.responses.create(background=True) returns the response before the model finishes. Useful for long-running calls when you want to poll or for parallel fan-out. Caveats:

• The call may complete after the Voyage completes. The dashboard's Native Model Calls panel will still attribute the call correctly (the row was reserved at request time), but the terminal status of the model call may lag the Voyage's terminal status. This is the documented behavior, not a bug.
• For deterministic smokes, prefer background=False; a background call's terminal state can lag the Voyage's, which the dashboard reconciles after the fact.

Wrapping a raw OpenAI client

If you can't switch to sail.inference.* (e.g., a third-party library uses the OpenAI client directly), wrap the client once with sail.voyage.wrap_openai() — every call then computes the attribution headers at call time and un-spanned calls get the same synthesized auto-spans as sail.inference.*:

from openai import OpenAI
import sail

cfg = sail.Config.from_env()
client = sail.voyage.wrap_openai(
    OpenAI(api_key=cfg.api_key, base_url=f"{cfg.api_url.rstrip('/')}/v1")
)

with sail.voyage.run(name="raw-client", version=1) as voyage:
    with voyage.agent("Reviewer"):
        with voyage.span("call"):
            response = client.responses.create(model="zai-org/GLM-5.1-FP8", input="...")

wrap_openai wraps responses.create, responses.retrieve, and chat.completions.create in place — every holder of that client object sees attributed calls, so wrap a dedicated client if some callers must stay unattributed. It is idempotent, supports AsyncOpenAI (the auto-span covers the awaited request), and follows the current Voyage per call (pass voyage= to pin one).

Attributing Anthropic Messages

The Anthropic client does not use wrap_openai. Point it at Sail and attach the current Voyage headers to each request:

from anthropic import Anthropic
import sail

cfg = sail.Config.from_env()
client = Anthropic(api_key=cfg.api_key, base_url=cfg.api_url.rstrip("/"))

with sail.voyage.run(name="messages-client", version=1) as voyage:
    with voyage.agent("Reviewer"):
        with voyage.span("call"):
            message = client.messages.create(
                model="zai-org/GLM-5.1-FP8",
                max_tokens=256,
                messages=[{"role": "user", "content": "Review this change."}],
                extra_headers=sail.voyage.headers(),
            )

Compute sail.voyage.headers() inside the request call. Raw Anthropic clients do not synthesize auto-spans, so use an explicit span when span attribution matters.

For any non-OpenAI-style HTTP client, attach sail.voyage.headers() yourself — it carries the full attribution context (voyage id plus the span and agent active at the moment you call it). Compute it per call, never once at client construction: OpenAI(default_headers=sail.voyage.headers()) freezes whatever context was active at construction onto every later call — constructed inside a span, that pins the wrong span to your whole run. (wrap_openai makes this mistake unrepresentable; prefer it whenever the client is OpenAI-style.)

Common pitfalls

• Calling sail.inference.responses.create() outside a Voyage. It still works, but it does not create any Voyage dashboard model-call association. If you intended Voyage attribution, you forgot to open a Voyage (sail.voyage.run(...)).
• Baking sail.voyage.headers() into default_headers at client construction. That snapshots one span/agent context onto every later call. Pass extra_headers=sail.voyage.headers() per call instead, including for Anthropic Messages.
• Reusing a response_id across Voyages. The first attribution wins forever; subsequent calls are effectively orphaned from a Voyage perspective. Don't try to "fix" an attribution mistake by re-calling with the same id — create a new response.
• Assuming non-Sail-routed inference calls show up in Voyages. Calls routed through other providers (Anthropic, OpenAI direct) don't pass through Sail's backend and won't appear. Voyages only track Sail inference.
• Parsing structured (JSON) replies without a fallback. Models occasionally return prose, fenced code blocks, or a differently-shaped object. Validate the shape and degrade gracefully — defaults plus a level="warn" event — instead of letting one malformed reply crash the run, and only report a successful parse when real values were found.
• Putting model output that contains secrets into Voyage payloads. Dashboard redaction is a backstop, not a design pattern. Summarize, hash, or omit sensitive values before storing them in Voyage events or metadata.

Verify it worked

Dashboard checklist:

• Overview → Native Model Calls panel: Scoped > 0, Unscoped = 0, Missing span = 0.
• Execution Trace and Waterfall: model rows reach terminal status (responses · completed or messages · completed, not in_progress). If they're stuck in_progress, see sail-voyage-debugging section 4.
• Waterfall model rows render solid, not striped.
• Each model call row shows the expected agent/span. If a row is unscoped, move the inference call inside @sail.agent(...) and @sail.span(...), or use the SDK helper / wrap_openai() path so headers are computed at request time.

Reference

• Entrypoint skill: sail-voyage
• Debugging stuck/unscoped model calls: sail-voyage-debugging