openinference-semantic-conventions
OpenInference Semantic Conventions
Decision gist · record as of 2026-08-14
Yes, if you are building or instrumenting AI applications and need a shared semantic vocabulary for tracing. It is lightweight, actively maintained, and essential infrastructure for any project using OpenInference instrumentation libraries or OpenTelemetry with AI workloads. No security vulnerabilities and permissive licensing. Install it as a dependency of instrumentation packages rather than directly unless you are defining custom tracing logic.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; pure Python wheel with no runtime dependencies.
- 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.
last release 2026-08-07 (7 days) · last repo commit 2026-08-14 · 1,147 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 8,531,636 downloads/mo, #1,610 on PyPI
Alternatives
Verify before relying
pip install openinference-semantic-conventions
from openinference_semantic_conventions import ...
# Import semantic convention constants for use in tracing instrumentation- Whether this package alone provides tracing without a separate instrumentation library or OpenTelemetry backend.
- What specific semantic convention constants or classes are exported and how they are typically used in practice.
What it is and what it does
OpenInference Semantic Conventions is a specification library that standardizes how AI application traces—particularly LLM calls, vector store retrievals, and external tool invocations—are represented and labeled. It works alongside OpenTelemetry to provide a common vocabulary for observability across AI systems, enabling consistent tracing whether you use Arize Phoenix, Arize AX, or any other OpenTelemetry-compatible backend.
The package itself is a pure Python module with no external runtime dependencies, making it lightweight to integrate into instrumentation libraries and AI frameworks. It defines the attribute names, semantic meanings, and conventions that other OpenInference instrumentation packages (for LangChain, LlamaIndex, OpenAI, and others) use when emitting trace data. If you are building or using an AI application that needs observability, this package provides the foundational schema that ensures your traces are interpreted consistently across tools.
Use it for
- Standardize trace attributes when instrumenting LLM applications with OpenTelemetry for observability.
- Ensure consistent semantic meaning of trace events across different AI frameworks and backends.
- Build custom instrumentation libraries that emit traces following OpenInference conventions.
- Integrate with Arize Phoenix or other OpenTelemetry backends using a common trace schema.
- Document and enforce tracing standards for retrieval-augmented generation (RAG) and agent workflows.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building or instrumenting AI applications and need a shared semantic vocabulary for tracing.
It is lightweight, actively maintained, and essential infrastructure for any project using OpenInference instrumentation libraries or OpenTelemetry with AI workloads. No security vulnerabilities and permissive licensing. Install it as a dependency of instrumentation packages rather than directly unless you are defining custom tracing logic.
Install
openinference-semantic-conventions on PyPI
Before you install
Low friction; pure Python wheel with no runtime dependencies. Actively maintained with a release 7 days ago and 1147 repository stars.
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.
Quickstart
pip install openinference-semantic-conventions
from openinference_semantic_conventions import ...
# Import semantic convention constants for use in tracing instrumentationVerify before relying
- Whether this package alone provides tracing without a separate instrumentation library or OpenTelemetry backend.
- What specific semantic convention constants or classes are exported and how they are typically used in practice.
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 | None |
| Maintenance | Actively maintained 7 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 8,531,636 / month, #1,610 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_semantic_conventions-0.1.32-py3-none-any.whl
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See also openinference-instrumentation-langchain · openinference-instrumentation-openai · aliyun-semantic-conventions · openinference-instrumentation-openai-agents · openinference-instrumentation-claude-agent-sdk · openinference-instrumentation-haystack · openinference-instrumentation-litellm · openinference-instrumentation-google-genai · openinference-instrumentation-agno · openinference-instrumentation-portkey