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
In July 2025, Danil Tatarinov developed a Python code generation recipe for the ibm-granite-community/granite-code-cookbook repository, focusing on AI-assisted code creation from natural language prompts. Leveraging IBM Granite models, he implemented one-shot and few-shot prompting workflows, system prompts to guide code quality, and comprehensive setup instructions. The solution, built using Python and Jupyter Notebook, included detailed documentation and a user guide to streamline onboarding and adoption. Danil’s work established end-to-end tooling for rapid prototyping, enabling developers to generate consistent Python code efficiently and reuse prompt engineering strategies, thereby accelerating productivity and improving the integration of large language models.
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 people
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
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