ibm-granite-community/granite-code-cookbook
Jul 2025 – Jul 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
AICode GenerationLarge Language ModelsPrompt EngineeringPython Development
idkwhttsay
PROFILE
Idkwhttsay
Developed a Python code generation recipe for the ibm-granite-community/granite-code-cookbook repository, enabling AI-assisted code creation from natural language prompts using IBM Granite models. The solution incorporated prompt engineering techniques, including both one-shot and few-shot workflows, and provided system prompts to guide code quality. Delivered comprehensive setup instructions and a detailed user guide to support rapid adoption and onboarding. Leveraging Python and Jupyter Notebook, the work established end-to-end tooling for developers to prototype efficiently and reuse prompt templates. This feature addressed the need for consistent, high-quality code generation and streamlined the integration of large language models into Python development workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
460
Activity Months1
Your Network
7 peopleShared Repositories
7
Work History
July 2025
1 Commits • 1 Features
Jul 1, 2025In July 2025, delivered a new Python code generation recipe leveraging IBM Granite models, enabling AI-assisted Python code creation from natural language prompts. The feature includes setup instructions, one-shot and few-shot prompting workflows, and system prompts to steer code quality, accompanied by a comprehensive user guide. This work establishes end-to-end tooling for rapid prototyping and accelerates developer productivity through reusable prompts and guidance.
1 Commits • 1 Features
Jul 1, 2025In July 2025, delivered a new Python code generation recipe leveraging IBM Granite models, enabling AI-assisted Python code creation from natural language prompts. The feature includes setup instructions, one-shot and few-shot prompting workflows, and system prompts to steer code quality, accompanied by a comprehensive user guide. This work establishes end-to-end tooling for rapid prototyping and accelerates developer productivity through reusable prompts and guidance.
July 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage100.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
AICode GenerationLarge Language ModelsPrompt EngineeringPython Development
Repositories Contributed To
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