openinference-semantic-conventions
OpenInference Semantic Conventions
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
Defines semantic conventions and standardized attributes for tracing AI applications, particularly LLM invocations, retrieval operations, and tool usage, for use with OpenTelemetry-compatible backends.
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
pip
pip install openinference-semantic-conventionsuv
uv add openinference-semantic-conventionspoetry
poetry add openinference-semantic-conventionsInstalling openinference-semantic-conventions
Before you install
Low friction; pure Python wheel with no runtime dependencies. Actively maintained with a release 7 days ago and 1147 repository stars.
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 instrumentation
Requires Python 3.10 or later (supports up to 3.14).
Verify 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) |
Evidence: openinference_semantic_conventions-0.1.32-py3-none-any.whl
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