ratel-ai-telemetry (Python)

The ratel.* telemetry vocabulary for Python: the constants that codify the Tier 2 overlay of CONVENTIONS.md (attribute keys, span/EventRecord names, the Origin/SearchTarget/AuthOutcome value enums, the pinned semconv version). Importing the constants pulls no OpenTelemetry SDK — the vocabulary stays weight-free for the SDK (emit side), the cloud (read side), and edge/serverless emitters (ADR-0007). init() — turnkey OTLP exporter sugar over the standard OTel Python SDK — lives in the ratel_ai_telemetry.otlp submodule behind the optional [otlp] extra.

Usage

from opentelemetry import trace
from ratel_ai_telemetry import EXECUTE_TOOL, GEN_AI_OPERATION_NAME, GEN_AI_TOOL_NAME, RATEL_ORIGIN, Origin

# Emit a standard gen_ai `execute_tool` span enriched with the ratel.* overlay,
# on your own OTel provider — the constants alone, no extra needed.
span = trace.get_tracer("my-agent").start_span(
    EXECUTE_TOOL,
    attributes={
        GEN_AI_OPERATION_NAME: EXECUTE_TOOL,
        GEN_AI_TOOL_NAME: "send_email",
        RATEL_ORIGIN: Origin.AGENT.value,
    },
)
span.end()

Want turnkey OTLP export to Ratel? Install ratel-ai-telemetry[otlp] and call init():

from ratel_ai_telemetry.otlp import init  # also importable as `from ratel_ai_telemetry import init`

handle = init()  # reads RATEL_OTLP_ENDPOINT + RATEL_API_KEY (or pass endpoint=, api_key=, headers=)
# ... emit spans and EventRecords through the global OTel APIs ...
handle.shutdown()  # flush the exporter on exit

init() returns a shutdown handle (handle.shutdown() / handle.force_flush()), not a provider — emit through the global OTel API. Explicit arguments beat the environment: an explicit api_key= sets the Bearer header, and the RATEL_API_KEY fallback never overrides an Authorization header you pass yourself. The endpoint resolves from RATEL_OTLP_ENDPOINT; the superseded RATEL_URL is still read as a fallback and warns, since it also names the SDK's catalog source (ADR-0003). endpoint is the full traces URL; logs_endpoint overrides the Logs URL that otherwise derives from sibling /v1/logs. On first setup, pass enabled=False to get an OTel-free no-op shutdown handle without endpoint configuration or the [otlp] extra, span_filter= to narrow spans, or log_filter= to narrow EventRecords (both default to accepting everything). Repeated init() calls return the exact handle from the first successful Ratel-owned initialization—even if a later caller is disabled—so hot reload and multiple callers do not fight over the global provider; the first call's configuration remains authoritative, and shutting that shared handle down stops export for every caller. Shutdown is terminal: OTel's global provider is set once per process, so after handle.shutdown() a later init() raises rather than return a dead handle. A foreign provider still produces the actionable processor-composition error, including when it wins a registration race.

A complete, offline-runnable version (console exporter + a ratel.search → execute_tool trace) is in examples/telemetry-python.

Coexisting with other providers (Langfuse, the Vercel AI SDK, ...)

OpenTelemetry allows one global provider per signal, with many processors on each. When a partner already owns the providers, add the Ratel processors instead of calling init(). Their defaults forward only named gen_ai.* / ratel.* signal spans and EventRecords:

from opentelemetry import _logs
from opentelemetry.sdk._logs import LoggerProvider
from opentelemetry.sdk.trace import TracerProvider
from ratel_ai_telemetry.otlp import ratel_log_record_processor, ratel_span_processor

tracer_provider = TracerProvider()
tracer_provider.add_span_processor(existing_langfuse_processor)  # keeps every span
tracer_provider.add_span_processor(ratel_span_processor())  # Ratel takes gen_ai.*/ratel.* only

logger_provider = LoggerProvider()
logger_provider.add_log_record_processor(ratel_log_record_processor())
_logs.set_logger_provider(logger_provider)

Pass span_filter=lambda _s: True or log_filter=lambda _r: True (or your own predicates) to override the defaults. ratel_span_exporter() and ratel_log_exporter() are the bare OTLP exporters if you want to wire your own processors. Note that per-span filtering can orphan the AI SDK's ai.* wrapper from its gen_ai.* child; send everything (or tail-sample) when you need full-trace fidelity rather than just the gen_ai/ratel metrics. enabled=False returns an OTel-free no-op processor without resolving configuration.

Package shape

• Distribution name: ratel-ai-telemetry; import name: ratel_ai_telemetry
• Pure Python (hatchling build, no Rust extension); OTel-free constants, init() behind the [otlp] extra. That extra installs the complete exporter/SDK stack; callers do not install individual OpenTelemetry packages.
• Targets Python >=3.9 (the [otlp] OTel deps are pinned below 1.42, the last line supporting 3.9)
• Released under the telemetry-py-v* tag prefix (ADR-0008)
• MIT (ADR-0009)

Build & test

From this directory (needs uv):

uv venv --python 3.11 .venv
uv pip install --python .venv -e '.[dev]'
.venv/bin/ruff check . && .venv/bin/mypy ratel_ai_telemetry && .venv/bin/pytest

Unlike the Python SDK there is no maturin develop step — the package is pure Python, installed editable ([dev] pulls the [otlp] extra so the tests exercise the real SDK). The tests cover the vocabulary (each constant asserted against the pin), disabled/filtered/ idempotent/foreign-provider init() behavior for both signal providers, endpoint/auth resolution and the content-capture gate, the default predicates and processor no-op/filtering behavior, a purity guard that importing the package pulls no OTel, and the shared contract-against-the-pin conformance in conformance/ (spans and EventRecords built from these constants through the real SDK must emit the exact pinned keys).