openinference-instrumentation
OpenInference instrumentation utilities
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and provides a well-designed abstraction for a common need in LLM observability. Use it if you are already using OpenTelemetry and need to attach structured annotations or evaluation data to spans in a standardized way.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later (supports up to 3.14).
- Low friction installation with a pure-Python wheel.
- Actively maintained with a release 7 days ago and 1147 repository stars.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
last release 2026-08-07 (7 days) · last repo commit 2026-08-14 · 1,147 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 8,310,434 downloads/mo, #1,636 on PyPI
Alternatives
Verify before relying
pip install openinference-instrumentation
from openinference.instrumentation import (
Annotation,
get_annotation_attributes,
)
span_annotations = get_annotation_attributes(
annotations=[Annotation(name="hallucination", label="factual")]
)
span.set_attributes(span_annotations)- Whether the package works with OpenTelemetry versions older than those in the current SDK release.
- Performance impact of context manager overhead in high-throughput tracing scenarios.
What it is and what it does
OpenInference Instrumentation is a utility library that bridges typed annotation and evaluation objects into OpenTelemetry span attributes following the OpenInference specification. It provides helper functions to flatten Annotation objects (with fields like name, score, label, explanation, annotator_kind, and metadata) into span attributes at different scopes (span, trace, or session), and context managers to attach session IDs, user IDs, custom metadata, tags, and prompt template information to spans during execution.
The package is designed for teams instrumenting LLM applications and AI systems that need to attach structured evaluation results, annotations, and operational context to their traces. It depends on opentelemetry-api, opentelemetry-sdk, and openinference-semantic-conventions to ensure compatibility with standard observability tooling. The library handles JSON serialization of metadata and manages scope-specific prefixes automatically, reducing boilerplate in tracing code.
Use it for
- Attach LLM evaluation scores and hallucination labels to spans for post-hoc analysis of model outputs.
- Track multi-turn conversations by wrapping code blocks with session and user context managers.
- Log prompt templates with versions and variable bindings to spans for prompt management and debugging.
- Add custom metadata and tags to traces for filtering and grouping related requests in observability platforms.
- Standardize annotation attributes across multiple instrumentation points using the Annotation model.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has low install friction, carries a permissive Apache-2.0 license, and provides a well-designed abstraction for a common need in LLM observability. Use it if you are already using OpenTelemetry and need to attach structured annotations or evaluation data to spans in a standardized way.
Install
openinference-instrumentation on PyPI
Before you install
Low friction installation with a pure-Python wheel. Actively maintained with a release 7 days ago and 1147 repository stars. Depends on opentelemetry-api, opentelemetry-sdk, and openinference-semantic-conventions, all standard observability packages.
Requires Python 3.10 or later (supports up to 3.14).
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; suitable for most projects.
Quickstart
pip install openinference-instrumentation
from openinference.instrumentation import (
Annotation,
get_annotation_attributes,
)
span_annotations = get_annotation_attributes(
annotations=[Annotation(name="hallucination", label="factual")]
)
span.set_attributes(span_annotations)Verify before relying
- Whether the package works with OpenTelemetry versions older than those in the current SDK release.
- Performance impact of context manager overhead in high-throughput tracing scenarios.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesopeninference-semantic-conventionsopentelemetry-apiopentelemetry-sdkwrapt |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 8,310,434 / month, #1,636 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersLicense :: OSI Approved :: Apache Software LicenseProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: openinference_instrumentation-0.1.57-py3-none-any.whl
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See also openinference-instrumentation-openai · openinference-instrumentation-mcp · openinference-instrumentation-langchain · openinference-instrumentation-claude-agent-sdk · openinference-instrumentation-portkey · openinference-instrumentation-openai-agents · openinference-instrumentation-haystack · openinference-instrumentation-dspy · openinference-instrumentation-anthropic · openinference-instrumentation-google-adk