Hue Python SDK

For frozen datasets, local experiments, custom scorers, durable retries and historical rescoring, see Local evaluations.

Python helpers around the official OpenTelemetry trace and log SDKs and OTLP HTTP/protobuf exporters. opentelemetry-api, opentelemetry-sdk and opentelemetry-exporter-otlp-proto-http are accepted as >=1.40,<2; 1.44.0 is the certified lockfile combination and 1.40.0 is tested as the floor in CI. Provider requests run in your application. This package does not proxy model calls or configure global OTel providers.

The distribution is named hue-run (import hue_sdk). Python 3.10+ is supported by the package contract; recorded validation below identifies the tested runtime.

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Install

pip install hue-run
# Or, in a uv project:
uv add hue-run

Send a trace

In the consuming application, use only public imports:

import os
from hue_sdk import Hue

with Hue(
    api_key=os.environ["HUE_API_KEY"],
    capture_content=False,  # Required: choose explicitly.
) as hue:
    project = hue.validate_project()
    with hue.context(session_id="conversation-42", user_id="observed-user-7"):
        with hue.span("agent.run") as run:
            run.set_input({"question": "What is 2 + 2?"})
            with hue.tool("add") as tool:
                tool.set_input({"a": 2, "b": 2})
                tool.set_output(4)
            run.set_output({"answer": 4})
    if not hue.force_flush():
        raise RuntimeError("Telemetry export failed; inspect Hue export_status.")

The SDK uses https://app.hue.run by default. Set base_url only for a different Hue deployment or a local receiver, using an origin without an API suffix. Existing Hue(base_url, api_key, ...) calls remain supported; a bare key passed as the first positional argument raises TypeError pointing at api_key=. The project service key determines the project. The SDK validates the project at GET /api/v1/projects/current when explicitly requested; construction itself does not perform a request. HTTP is permitted only for localhost and loopback IPs. Userinfo, query strings, fragments, paths and redirects are rejected. The key is sent only as Authorization: Bearer …; repr(hue), SDK errors and status counters omit it.

Content and semantic fields

capture_content has no default. False makes set_input and set_output omit content before it reaches an OTel queue and makes log_inference emit no record. Explicit JSON null, empty strings and absent content stay distinct when capture is enabled. Exception recording includes the exception type and ERROR status; exception messages and stacks are always excluded by these helpers.

When capture is disabled Hue also strips recognized GenAI, OpenInference, OpenLLMetry and Vercel AI SDK content attributes (including OpenInference retrieval documents, embeddings, reranker documents, prompt-template variables and images), legacy gen_ai.* message events, log bodies and status descriptions from every record it exports, including spans produced by third-party instrumentors on the same provider. COMPATIBILITY.md lists the exact keys. This setting is still not a blanket PII filter: custom attribute names, span names, session/user identifiers and resource attributes cannot be classified automatically and remain under your control, and other exporters keep their own policy. The server stores received content; there is no automatic telemetry expiry. Delete scoped data explicitly when required by your retention policy.

Hosted tools carry credentials in their definitions, such as the authorization and headers of an OpenAI hosted MCP tool. When content is captured, Hue's export path replaces credential-like fields including authorization, authorization_token, headers, api_key, access_token, x-api-key, and keys ending in token, secret, password, apikey or credential (case-insensitively, ignoring - and _) with "[redacted]" in recorded tool definitions (gen_ai.tool.definitions, ai.prompt.tools, llm.tools.*.tool.json_schema) and in the tools and mcp_servers entries of a raw provider request or response recorded as input.value, output.value or llm.invocation_parameters, as OpenInference does. Parameters named in a JSON Schema properties object keep their schemas, so a tool that takes a headers argument is still described. A definition nested more than 256 levels deep drops its record. Sensitive defaults, constants, examples and enum values under credential-named schema parameters are redacted too.

With capture_content=False, export removes tool definitions but keeps a summary of them on the same record: hue.tool.names lists each definition's name (Chat Completions function.name, or the type of an unnamed built-in tool such as mcp) in order, and hue.tool.definitions.sha256 is the lowercase hex SHA-256 of the RFC 8785 canonical JSON of the credential-scrubbed definition list, identical to the TypeScript SDK's and unchanged when a credential rotates. Only definitions an instrumentor recorded can be summarized, for example OpenInference without hide_inputs. Recorded messages can inline files: GenAI blob parts in gen_ai.input.messages / gen_ai.output.messages and AI SDK 6 file parts in ai.prompt.messages. Before a record is admitted, Hue replaces the content/data of any such part longer than 64 KiB with the file's sha256 (of the decoded bytes for base64 and data: URLs, of the UTF-8 text otherwise) and size, keeping the part's other fields, so a span that inlines a large file exports the file's identity instead of being dropped for its size. This runs on the thread that ends the span and is bounded: a message attribute longer than 8 MiB is left unchanged and dropped by the snapshot budget as before.

Use redactor=lambda field, value: ... to transform content in supported helpers. It runs synchronously before serialization and export. Return a redacted JSON value; failures omit the field and increment export_status.instrumentation_failures without changing application behavior. It does not inspect arbitrary OTel attributes or logs:

def redact(field, value):
    if isinstance(value, dict):
        return {key: "[redacted]" if key == "email" else item for key, item in value.items()}
    return value

The callback should cover your actual nested input format; this small example is only a top-level dictionary transformation.

Before redaction, helpers copy supported content into detached built-in containers; in-place changes by a redactor cannot change application inputs or results. The input and the redactor's returned value each have a 1 MiB conservative value budget, 64 maximum nesting depth and 65,536 visited values/keys. Integers and integer keys are limited to 14,000 bits before decimal conversion. Final serialized content still has the 256 KiB UTF-8 JSON limit. Cyclic, nonfinite, unsupported or over-budget content is omitted and counted as an instrumentation failure. See the Python safety boundary for supported types and callback limits.

Tool/model metadata accepts plain strings; invalid values use stable fallback labels and increment instrumentation failures without invoking custom conversion hooks. Disabled tracing skips metadata validation.

For model helpers, pass the message representation produced by your integration. Prefer current GenAI message conventions when authoring your own messages. Use either span content or correlated logs for a given input/output, avoiding duplicate copies. log_inference sends a structured body (an explicit None field keeps its key with an empty value, distinct from an absent field) and copies gen_ai.operation.name, gen_ai.provider.name and gen_ai.request.model from the enclosing model() block, or from its operation=, provider= and model= keywords, plus gen_ai.conversation.id from context(), onto the record's attributes. A blank or over-long keyword is omitted and counted as an instrumentation failure.

Existing instrumentation

Pass an existing opentelemetry.sdk.trace.TracerProvider through tracer_provider=provider to add Hue's exporter, and an existing opentelemetry.sdk._logs.LoggerProvider through logger_provider= when the application already owns one. A provider Hue creates for the other signal reuses the borrowed provider's resource, so spans and correlated logs report the same service.name; service_name applies only when Hue creates both providers. Hue's processor then exports every span that ends on that provider, the same default as other OpenTelemetry exporters, plus placeholders for its running Hue and AI spans; wrap the processor if only part of the provider's spans should reach Hue, and forward on_start only for spans whose on_end the wrapper forwards unchanged. Session/user identifiers from hue.context() are stamped on Hue helper spans only. Hue does not call set_tracer_provider. It exposes hue.tracer_provider, hue.tracer and hue.logger_provider for explicit integration. shutdown() closes Hue's processors; borrowed providers and their other processors stay usable. Finish traced work before shutting Hue down: spans ending or external records emitted afterward increment Hue's dropped-record counters, including emissions through a borrowed provider. New Hue helpers after shutdown are no-ops. Do not repeatedly attach Hue clients to one long-lived provider: OTel has no public processor-removal API. Create one client per provider lifecycle.

An instrumentor that accepts tracer_provider can receive hue.tracer_provider; follow that instrumentor's own capture/redaction configuration. OpenInference and other OTel instrumentors are optional dependencies, not implicitly enabled. Hue's export path strips their recognized content attributes when capture_content is False, but configure their own capture controls as well: unrecognized custom keys pass through, and the instrumentor may still send content to other exporters. The optional compatibility group pins OpenAI 3.14.0, OpenInference OpenAI 0.1.60 and its resolved OpenInference instrumentation 0.1.63. A synthetic HTTP streaming response verifies parentage, canonical model/usage attributes and enabled/disabled message capture with TraceConfig(enable_genai_semconv=True, hide_inputs=..., hide_outputs=..., hide_input_messages=..., hide_output_messages=...). This is a tested adapter combination, not a claim about all OpenAI APIs or live-provider compatibility. See the instrumentor's official source. See the Python integration guide for application setup.

Local development without a Hue account

Hue speaks standard OTLP, so any local collector works. Point base_url at a loopback receiver that accepts /api/v1/otlp/v1/traces and /api/v1/otlp/v1/logs (for example an OpenTelemetry Collector otlp receiver with http.traces_url_path and logs_url_path set to those paths, forwarding to Jaeger or the debug exporter) and pass any placeholder api_key; HTTP is allowed for loopback origins. validate_project() and verify_trace() are Hue-only diagnostics and are not available against a generic collector.

Export behavior and limits

• Traces go to /api/v1/otlp/v1/traces; correlated logs go to /api/v1/otlp/v1/logs. Both use the official OTLP HTTP/protobuf exporter with gzip-compressed request bodies and a hue-sdk-python/<version> User-Agent ahead of the exporter's own token. The official exporter handles retryable network/service failures; Hue additionally honors 429 and Retry-After within its transport budget. There is no proprietary provider transport.
• Exporter work and its HTTP worker run with OpenTelemetry instrumentation suppressed. Hue ignores records emitted within that suppressed scope, preventing HTTP instrumentation and exporter diagnostics from feeding back into its own queues. Application instrumentation resumes outside that scope. If an OpenTelemetry release ever stops exposing its suppression key, Hue warns once at import and keeps exporting: its own queues still ignore its export work, but OTel HTTP instrumentors could then record Hue's export requests on other exporters.
• Batches initially contain at most 64 records and are split by encoded protobuf size to fit 1 MiB, both on wire and after decoding. A single oversized record fails visibly through export status. Helper content exceeding 256 KiB UTF-8 JSON is omitted before enqueue and increments instrumentation failures; it is never silently truncated by Hue. Third-party record validation remains the receiver's responsibility. OTel's own attribute/count/environment limits can still affect externally configured providers.
• Hue accepts at most 2,000 distinct spans per trace. This is enforced by the receiver across distributed producers; the client cannot guarantee a global count.
• HTTP errors, malformed/non-200 success responses and OTLP partial_success rejected counts cause a failed export status. Partial rejection is not retried wholesale. Receiver error text is not echoed. A warning-only partial-success response with zero rejected records remains successful. A request carrying only live-span placeholders never fails the status.
• force_flush(timeout_millis=30000) drains both processors and returns False for a timeout, failed export, dropped record or instrumentation omission since this client was created. Hue's processors honor the shared deadline and serialize drains in a bounded background worker. Pending exports continue after timeout. export_status exposes cumulative failure counters. shutdown() stops new helpers, drains and closes owned exporters within the caller's wait budget; repeated calls wait for the same shutdown. After a timeout, keep the process alive and call shutdown again to confirm completion. Context-manager exit calls shutdown_safe(timeout_millis=1000); check flush explicitly when an exit code must reflect delivery failure.
• Hue processors use the public OTel interfaces and bound each signal to 2,048 records and 8 MiB of encoded telemetry by default, including in-flight records (max_queue_size, max_queue_bytes). Dropped records and instrumentation omissions make cumulative export_status.ok false. Queue overflow, process termination and sampling can lose telemetry. Flush success reports observed exporter outcomes, not durable local delivery or proof that every application operation was instrumented. The exporter timeout controls individual export/retry operations. A caller timeout does not cancel an HTTP request already in flight; background workers continue until the operation completes.
• A timed-out HTTP worker can retain one encoded request of up to 1 MiB per signal outside the queue counters. Later records remain queued within the configured limits until that worker finishes; shutdown counts any queued records it must discard. Queue bytes are not total process memory.
• A flush timeout releases drain coordination so later flushes can make progress. Both signals share the caller's remaining wait budget, including time spent waiting for another flush. Shutdown's exporter cleanup can continue after the caller returns without holding that coordination lock. Repeated shutdown calls report current failures and drops as well as cleanup completion.

Live spans

OpenTelemetry exports a span only when it ends, so a long agent turn or model call would otherwise stay invisible until it finishes. When a Hue helper span or an AI span is still open at the export worker's next 0.5 s tick, Hue queues a placeholder: a standard OTLP span whose parent is the running span, with its name, kind, start time and current attributes, an end time of 0, hue.span_type = "pending_span" and hue.pending_parent_id (the running span's own parent, omitted for a root). Hue shows the span as running and replaces the placeholder when the finished span arrives. Input set right after entering, such as set_input, is included.

The placeholder then waits for the worker's next export like any queued span: up to 0.5 s until the next tick, then the 1 s export delay when nothing else is queued, so it usually reaches Hue within about 1.5 s of its span starting. It goes out sooner when an export is already scheduled, for example because another span has just ended, and at once for 64 queued records or force_flush(). It goes out later while an earlier export is still in flight, because the worker runs the next tick and starts the next 1 s delay only after that export returns. A placeholder whose span ends before it is exported is not sent, so a short span may send none and appear in Hue only when it finishes.

• Only spans from hue.tracer (every helper) and spans with a gen_ai., ai., llm. or traceloop. attribute at start, or a name starting with ai., are announced. HTTP, database and other framework spans are not.
• Placeholders follow the same capture_content policy as finished spans, so recognized content attributes are stripped from them too when it is False. Tool definitions, system instructions and any value over 64 KiB are left out; the finished span still carries them. The markers are written last, and these reserved keys are removed from finished spans.
• Apart from that policy (capture_content=False strips recognized content keys) and those omissions, a placeholder carries the running span's attributes as they stand when it is queued. redactor= rewrites the value passed to set_input or set_output before it is set on the span, so placeholders carry the redacted value. Any other sensitive attribute, such as custom metadata or a value recorded by an instrumentor, must be scrubbed where it is recorded: the finished span carries it too, so live_spans=False does not keep it from Hue. That option only prevents the placeholder's earlier copy, for example of a value the span overwrites before it ends.
• Placeholders are advisory. At most 1,024 open spans wait to be announced, and each is announced once. A placeholder is queued only while the queue is under a quarter of its record and byte budgets and is skipped silently otherwise, so placeholders use at most a quarter of the queue. While queued they count in queued_trace_records and queued_trace_bytes, but never as dropped or failed telemetry.
• This needs a Hue deployment that accepts placeholders. It marks every trace acknowledgement with Hue-Pending-Spans: 1, and its rejections fail the export status as before. An acknowledgement without the header comes from a generic collector or an older Hue, which rejects placeholders by their zero end time: the SDK credits up to one rejection per placeholder to the placeholders, sets export_status.live_spans_rejected (a warning that does not affect ok) and stops announcing spans for the rest of that client's life. Further rejections in that response still fail the export status.
• Pass live_spans=False to send none. Setup keys (hue_setup_…) never announce spans.
• A processor wrapper that forwards on_start to Hue should also forward on_end for the same spans. Hue builds each placeholder from the running span itself, so code in the wrapper's on_end never runs on it: if the wrapper scrubs attributes, renames the span or drops it there, a placeholder exported while the span is still open is sent anyway, with the span's original name and its attributes after capture_content. A dropped span is then forgotten and its unsent placeholder discarded, but one already sent can leave the span shown as running. Do not forward on_start for spans you scrub, rename or drop, or pass live_spans=False.

Dependencies

The tracing core depends on the official OpenTelemetry packages and requests only. JSON Schema scoring (builtin_scorers.json_schema) runs jsonschema in an isolated process and needs the optional extra; without it builtin_scorers.json_schema raises ImportError and stored schema scorers report SchemaValidatorUnavailable:

pip install 'hue-run[evals]'

Import the bundle as from hue_sdk.evals import builtin_scorers. The builtins name remains as an alias for parity with TypeScript, but it shadows the standard-library module of the same name inside any file that imports it.

See THIRD_PARTY_NOTICES.md for licenses.

Confirm a trace reached Hue

Hue.verify_trace() checks a server receipt for a known trace from a real application request. It does not send a synthetic trace, invoke a model, or flush an exporter. Finish the request, then flush the provider that produced it. If you borrow a provider, call its force_flush() first, then check Hue's force_flush() result before verifying:

# Retain these IDs while your application's instrumented request runs.
# After the request finishes and the relevant providers have flushed:
confirmation = hue.verify_trace(
    request_trace_id,
    expected_span_ids=[request_span_id, model_span_id],
    required_fields=["input", "output", "model", "usage", "session"],
    timeout_millis=10_000,
)
if confirmation.verified:
    print(confirmation.receipt.trace_url)
else:
    # The latest partial receipt, or None if this trace has not appeared yet.
    print(confirmation.receipt)

Only require fields your instrumentation emits and your capture policy permits. For metadata-only capture, omit input and output. The receipt contains presence booleans and counts, not captured content. verified=True confirms the requested trace, every supplied expected span, and every required field; it does not prove that unlisted application operations were instrumented. Missing spans or fields continue polling until the deadline, then return verified=False with the latest receipt. Trace IDs must be nonzero and contain 32 lowercase hexadecimal characters; expected span IDs must be nonzero, contain 16, be unique, and number at most 100. The timeout must be positive and at most 60,000 ms.

Only trace-not-found responses, HTTP 429 and HTTP 503 are retried. Authentication, unsupported receipt endpoints, malformed responses and connection failures raise TraceVerificationError with a safe code and optional status_code; response bodies and keys are omitted. Redirects are rejected. The deadline covers connection, polling and response-body reads. An in-flight network read may finish in the background after the caller times out. This helper requires a Hue deployment that implements /api/v1/traces/{traceId}/receipt.

Supported runtimes and verification

Python 3.10+ is supported. CI tests Python 3.10 and 3.14, source imports and an independently installed wheel. Tests use synthetic loopback HTTP receivers and decode official OTLP protobuf messages to verify trace/log correlation, metadata-only capture, redaction, propagation, existing-provider ownership, authentication failures, redirects, partial rejection, retries, encoded request limits and live-span placeholders, including their downgrade against a receiver without the Hue-Pending-Spans header. Compatibility tests also exercise local evaluations and the optional OpenInference adapter. No live model provider is required for these checks.

See the documentation for integration guidance and troubleshooting for export failures.

Simulated worlds

hue_sdk.environment.EnvironmentClient drives Hue's World API: create a world after the case's execution starts, hand the agent the provider mirror URLs and the world token (never the project key), finish and wait_for_seal before the execution completes, and read the sealed world's evaluator-only evidence.

import os
import subprocess

from hue_sdk.environment import EnvironmentClient, agent_environment, mcp_config_file, world_handoff

client = EnvironmentClient(api_key=os.environ["HUE_API_KEY"])
run = client.create_run(
    idempotency_key=f"execution:{execution_id}",
    environment_version_id=version_id,
    execution_id=execution_id,
    ttl_seconds=600,
    traceparent=f"00-{span.trace_id}-{span.span_id}-01",
    agent_revision="my-agent@1.4.2",
)
world = None
try:
    world = world_handoff(run)
    if world is None:  # the deployment's gateway is off: this run has Hue-native actions instead
        client.finish_run(
            run["id"], idempotency_key=f"execution:{execution_id}:abandoned", status="abandoned"
        )
        raise RuntimeError("this deployment does not serve simulation worlds")
    child = agent_environment(world)  # os.environ minus Hue control-plane credentials, plus the carriers
    with mcp_config_file(world) as path:  # owner-only mcp.json, removed after the block
        subprocess.run(agent_command, env={**child, "MCP_CONFIG": path}, check=True)
finally:
    if world is not None:
        finished = client.finish_run(
            run["id"], idempotency_key=f"execution:{execution_id}:completed", status="completed"
        )
        client.wait_for_seal(run["id"], completing_until=finished.get("completingUntil"))
evidence = client.get_evidence(run["id"], section="ledger")

agent_environment removes HUE_API_KEY, HUE_MCP_KEY and any hue_sk_, hue_mcp_ or hue_attempt_ value unless include_hue_credentials=True, and for one compatibility release also sets HUE_MCP_URL, HUE_MCP_TOKEN and HUE_MCP_EXPIRES_AT from the first MCP mirror. Nothing here logs the token. The client waits Hue's Retry-After on 429 and 503 before retrying. Refusal errors expose a validated HueEnvironmentError.diagnostic from X-Hue-Diagnostic when the server sends one; the code distinguishes refusals with the same status without exposing response bodies.

Managed targets

Start a frozen dataset run in Hue while your existing agent stays in your application:

import os
from hue_sdk.managed import ManagedTargetHandler, ManagedTargetResult

def target(invocation):
    # Your function consumes unchanged inputs and verified attachment bytes.
    result = run_agent_for_evaluation(invocation)
    return ManagedTargetResult(output=result)

handler = ManagedTargetHandler(
    machine_credential=os.environ["HUE_MANAGED_TARGET_SECRET"],
    target=target,
    tracer=hue.tracer,  # Required with a Hue-owned client: Hue never sets a global tracer.
    flush_telemetry=hue.force_flush,  # Existing client; False keeps telemetry pending.
)

Without tracer, the handler falls back to the global OpenTelemetry tracer, its span is not recorded and every invocation returns uncertain.

Your POST route calls handler.handle(raw_body_bytes, request_headers) and returns its JSON body, status code and headers. Limit request bodies to 1 MiB; use asyncio.to_thread from an async route. The target must honor cancelled and deadline_monotonic. Use a 120-second host limit for the default 90-second callback and 30-second finalization budget.

For generated files, return ManagedOutputFile entries containing actual bytes, filename, content type and an optional primary flag. The helper claims the invocation, verifies files and saves the outcome without automatically rerunning the agent. See the managed-run guide and full adapter contract for registration, existing-provider flush callbacks and recovery. Local/CI runners remain available.

Serving safely

Use create_hue_safe for best-effort startup and enabled=False for a local kill switch. The safe constructor returns a disabled client and records an instrumentation failure if initialization fails. Disabled helpers execute application work without exporting. Initialize after fork, once per serving process. force_flush_safe(timeout_millis=1000) and shutdown_safe(timeout_millis=1000) return booleans without raising; monitor those results and export_status. Keep strict project validation and receipt/delivery checks out of customer request paths. Never rerun application work to recover telemetry.

Queue bytes bound retained telemetry rather than total RSS. Network waits have a wall-clock caller bound and at most one retained HTTP worker per signal; a stuck OS call can outlive that wait. Arbitrary user hooks and third-party instrumentation retain their own behavior. See production safety for lifecycle examples, failure tests and limitations.