huggingface/cookbook
Oct 2024 – Nov 2024
2 Months active
Languages Used
Jupyter NotebookMarkdownPythonJSON
Technical Skills
CrewAIDockerDocumentationHugging Face SpacesLLM Application TracingObservability
Andrew Reed
PROFILE
Andrew Reed
Andrew Reed developed end-to-end observability solutions for Phoenix deployments within the Hugging Face ecosystem, focusing on reproducibility and onboarding. Working in the huggingface/cookbook repository, he authored a comprehensive cookbook entry that guides users through deploying Phoenix, configuring OpenTelemetry-based application tracing, and visualizing LLM call traces in multi-agent CrewAI workflows. He enhanced documentation with actionable guidance, improved UI/UX in the Phoenix observability notebook using Python and Jupyter Notebook, and clarified persistent disk usage for new users. Andrew’s work addressed onboarding friction and improved demo reliability, demonstrating depth in both technical implementation and user-focused documentation for complex LLM application tracing.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
3
Lines of code
647
Activity Months2
Your Network
27 people
Work History
November 2024
4 Commits • 2 Features
Nov 1, 2024November 2024: Delivered targeted UI and guidance enhancements for the Hugging Face Cookbook Phoenix observability notebook to boost onboarding, readability, and user experience. The work focused on introducing a clearer UI with visuals and a reorganized feature display, and improving guidance with actionable callouts and setup tips.
4 Commits • 2 Features
Nov 1, 2024November 2024: Delivered targeted UI and guidance enhancements for the Hugging Face Cookbook Phoenix observability notebook to boost onboarding, readability, and user experience. The work focused on introducing a clearer UI with visuals and a reorganized feature display, and improving guidance with actionable callouts and setup tips.
November 2024
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 was focused on delivering a practical, end-to-end observability solution for Phoenix deployments in the HuggingFace ecosystem, with emphasis on reproducibility and developer onboarding. The work culminated in a dedicated cookbook entry that demonstrates setting up a Phoenix observability dashboard on Hugging Face Spaces, configuring application tracing with OpenTelemetry, and visualizing LLM call traces. It also improves demo-space usability and resource guidance for persistent disk usage.
October 2024
2 Commits • 1 Features
Oct 1, 2024October 2024 was focused on delivering a practical, end-to-end observability solution for Phoenix deployments in the HuggingFace ecosystem, with emphasis on reproducibility and developer onboarding. The work culminated in a dedicated cookbook entry that demonstrates setting up a Phoenix observability dashboard on Hugging Face Spaces, configuring application tracing with OpenTelemetry, and visualizing LLM call traces. It also improves demo-space usability and resource guidance for persistent disk usage.
Activity
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Quality Metrics
Correctness96.6%
Maintainability96.6%
Architecture96.6%
Performance96.6%
AI Usage30.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
CrewAIDockerDocumentationHugging Face SpacesLLM Application TracingObservabilityOpenTelemetryPhoenixPython DevelopmentUI/UX
Repositories Contributed To
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