Arize-ai/openinference
May 2026 – May 2026
1 Month active
Languages Used
Go
Technical Skills
API DevelopmentGoInstrumentationObservabilityOpenTelemetry
Gabe Barcelos
PROFILE
Gabe Barcelos
Contributed to the Arize-ai/openinference repository by developing OpenInference instrumentation for both the Anthropic and OpenAI Go SDKs, enhancing observability and traceability of large language model calls. Leveraging Go, API development, and OpenTelemetry, the work introduced features that support OpenInference spans and enable both automatic and manual tracing within LLM workflows. Each feature included practical examples to streamline onboarding and adoption for users integrating instrumentation into Go-based pipelines. The implementation focused on improving system visibility and reducing mean time to resolution for LLM-related issues, with all work co-authored and no major bugs reported during the development period.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
2
Lines of code
4,749
Activity Months1
Your Network
95 peopleWork History
May 2026
2 Commits • 2 Features
May 1, 2026May 2026 — Arize-ai/openinference: Delivered OpenInference instrumentation for Go SDKs, boosting observability and traceability of LLM calls across Anthropic and OpenAI workflows. Two features were implemented, each with examples to accelerate adoption, and crafted with collaboration (co-authored by Roger Hu): - OpenInference instrumentation for the Anthropic Go SDK with examples to support OpenInference spans. - OpenInference instrumentation for the OpenAI Go SDK with examples for auto and manual instrumentation. No major bugs are documented for this period. The work enhances system visibility, reduces MTTR for LLM-related issues, and provides a smoother onboarding path for users integrating instrumentation into Go-based LLM pipelines.
2 Commits • 2 Features
May 1, 2026May 2026 — Arize-ai/openinference: Delivered OpenInference instrumentation for Go SDKs, boosting observability and traceability of LLM calls across Anthropic and OpenAI workflows. Two features were implemented, each with examples to accelerate adoption, and crafted with collaboration (co-authored by Roger Hu): - OpenInference instrumentation for the Anthropic Go SDK with examples to support OpenInference spans. - OpenInference instrumentation for the OpenAI Go SDK with examples for auto and manual instrumentation. No major bugs are documented for this period. The work enhances system visibility, reduces MTTR for LLM-related issues, and provides a smoother onboarding path for users integrating instrumentation into Go-based LLM pipelines.
May 2026
Activity
Loading activity data...
Quality Metrics
Correctness100.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Go
Technical Skills
API DevelopmentGoInstrumentationObservabilityOpenTelemetry
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline