openai/openai-cookbook
Apr 2025 – Mar 2026
3 Months active
Languages Used
JSONMarkdownPythonJupyter Notebook
Technical Skills
AI IntegrationAPI IntegrationData HandlingDebuggingDocumentationLLM Development
Tom Pakeman
PROFILE
Tom Pakeman
Tom Pakeman developed advanced function calling and real-time evaluation frameworks for the openai/openai-cookbook repository over a three-month period. He built example notebooks and documentation to demonstrate reasoning-powered function calls, integrating external data sources and web search, and provided guidance on sequential and parallel tool usage. Using Python, Jupyter Notebooks, and Streamlit, Tom implemented robust error handling, persistent result storage, and interactive data visualization for API evaluation metrics. His work included a Streamlit-based results viewer for real-time metric comparison, improving feedback cycles and reliability. The deliverables provided production-ready references that accelerated onboarding and enabled data-driven API tuning for developers.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
3
Lines of code
13,058
Activity Months3
Your Network
416 peopleSame Organization
@openai.com301
Shared Repositories
115
Work History
March 2026
2 Commits • 1 Features
Mar 1, 2026March 2026: Delivered a real-time evaluation framework for OpenAI API evaluations, including a Streamlit-based results viewer to compare metrics and inspect individual runs in real time. Implemented robust error handling, persistent result storage, and plotting capabilities for evaluation metrics. This work, supported by realtime evals types tooling and a dedicated results viewer (both co-authored), reduces feedback cycles, improves reliability, and enables data-driven API tuning. Key technologies include Python, Streamlit, data visualization, and collaborative tooling.
2 Commits • 1 Features
Mar 1, 2026March 2026: Delivered a real-time evaluation framework for OpenAI API evaluations, including a Streamlit-based results viewer to compare metrics and inspect individual runs in real time. Implemented robust error handling, persistent result storage, and plotting capabilities for evaluation metrics. This work, supported by realtime evals types tooling and a dedicated results viewer (both co-authored), reduces feedback cycles, improves reliability, and enables data-driven API tuning. Key technologies include Python, Streamlit, data visualization, and collaborative tooling.
March 2026
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary: Delivered a focused feature enhancement in the openai-cookbook that strengthens advanced function calling with reasoning models and external data sources. The work consolidates updates to the Reasoning Function Call cookbook and its example notebook, introduces a new web search example, and provides guidance on sequential and parallel tool calls, along with improvements to output correctness and demonstration notebook clarity. These deliverables enhance developer workflows, improve the accuracy of data-driven outputs, and reduce time-to-value when integrating external data sources.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary: Delivered a focused feature enhancement in the openai-cookbook that strengthens advanced function calling with reasoning models and external data sources. The work consolidates updates to the Reasoning Function Call cookbook and its example notebook, introduces a new web search example, and provides guidance on sequential and parallel tool calls, along with improvements to output correctness and demonstration notebook clarity. These deliverables enhance developer workflows, improve the accuracy of data-driven outputs, and reduce time-to-value when integrating external data sources.
April 2025
4 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for openai/openai-cookbook: Delivered hands-on capability for function calls with reasoning models through new example notebooks, improved documentation for reasoning models and function calling, and fixed a bug in the reasoning-function-call notebook related to error handling and logging. The work provides a clear, production-leaning reference for prototyping and validating reasoning-powered function calls, accelerating onboarding and adoption.
4 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for openai/openai-cookbook: Delivered hands-on capability for function calls with reasoning models through new example notebooks, improved documentation for reasoning models and function calling, and fixed a bug in the reasoning-function-call notebook related to error handling and logging. The work provides a clear, production-leaning reference for prototyping and validating reasoning-powered function calls, accelerating onboarding and adoption.
April 2025
Activity
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Quality Metrics
Correctness93.8%
Maintainability90.0%
Architecture90.0%
Performance82.6%
AI Usage62.6%
Skills & Technologies
Programming Languages
JSONJupyter NotebookMarkdownPython
Technical Skills
AI Function CallingAI IntegrationAPI IntegrationAPI integrationData HandlingData RefinementData analysisDebuggingDocumentationFunction CallingJupyter NotebooksLLM DevelopmentLLM UsageMachine learningNatural Language Processing
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline