Openinference Semantic Conventions
Semantic conventions for tracing LLM applications with OpenInference.
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Verified · Jul 12, 2026Overview
What is Openinference Semantic Conventions?
This package provides semantic conventions for tracing Large Language Model (LLM) applications, enabling better observability and monitoring of AI systems. It is part of the broader Arize ecosystem aimed at improving model performance and reliability.
Key differentiator
“This package stands out by providing standardized tracing conventions specifically for LLM applications, enhancing observability without imposing significant performance penalties.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official SDKs only available for Python and community-maintained TypeScript, lacking support for other languages like Java or Go
Tightly integrated with other Arize tools, making it difficult to switch to alternative observability solutions without significant refactoring
Fit analysis
Who is it for?
✓ Best for
Developers building LLM applications who need standardized tracing conventions
Teams integrating multiple AI models and require consistent monitoring practices
Organizations that prioritize transparency and traceability in their AI systems
✕ Not a fit for
Projects requiring real-time streaming capabilities (this tool focuses on batch processing)
Applications where the overhead of semantic conventions would be prohibitive
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with Openinference Semantic Conventions
Step-by-step setup guide with code examples and common gotchas.