IBM/data-prep-kit
Jan 2025 – Nov 2025
3 Months active
Languages Used
Jupyter NotebookPythonMarkdown
Technical Skills
AI Agent DevelopmentCode CommentingData EngineeringData PreparationDocumentationLLM Agents
Mohammad
PROFILE
Mohammad
Worked on the IBM/data-prep-kit repository to deliver four new features over three months, focusing on AI-assisted data preparation and scalable document processing. Developed LLM agent integration to automate data prep workflows, leveraging Python and Jupyter Notebooks for reproducible, agentic pipelines. Enhanced the project’s maintainability by refactoring code, improving documentation, and introducing Docker-based validation for robust testing. Expanded LLM provider support and streamlined onboarding through repository cleanup and clearer configuration. Added Spark-based document processing, enabling document quality assessment and Parquet conversion for analytics-ready outputs. The work emphasized workflow automation, data engineering, and integration of modern AI and data processing technologies.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
8Total
Bugs
0
Commits
8
Features
4
Lines of code
45,496
Activity Months3
Your Network
1051 peopleSame Organization
@ibm.com988
Arun VMember
Aayush-PanchalMember
Aayush KumarMember
Abhijit DeokarMember
Abhina SreeMember
Abhishek KumarMember
Abhishek Kr SrivastavMember
Abraham Lara GranadosMember
Adapa ChathuryaMember
Shared Repositories
63
Work History
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for IBM/data-prep-kit, focusing on delivering Spark-based document processing enhancements to broaden analytics-ready data pipelines. The sprint introduced Spark support for document processing, including document quality assessment and conversion of documents to Parquet format, enabling scalable, analytics-ready outputs and improved interoperability with Spark-centric workflows.
1 Commits • 1 Features
Nov 1, 2025November 2025 monthly summary for IBM/data-prep-kit, focusing on delivering Spark-based document processing enhancements to broaden analytics-ready data pipelines. The sprint introduced Spark support for document processing, including document quality assessment and conversion of documents to Parquet format, enabling scalable, analytics-ready outputs and improved interoperability with Spark-centric workflows.
November 2025
February 2025
5 Commits • 2 Features
Feb 1, 2025February 2025 focused on strengthening IBM/data-prep-kit with enhanced AI-assisted development and improved maintainability. Delivered Replicate-based interpreter integration to expand the agentic workflow, improved prompts for code generation, and introduced a Docker-based code validator for robust checks. Completed documentation and repository cleanup for Agentic to standardize structure, clarify LLM provider support (Replicate, Watsonx, Ollama), and clean up examples. These changes reduce onboarding time, increase reliability of AI-driven code, and set the stage for broader adoption across teams.
February 2025
5 Commits • 2 Features
Feb 1, 2025February 2025 focused on strengthening IBM/data-prep-kit with enhanced AI-assisted development and improved maintainability. Delivered Replicate-based interpreter integration to expand the agentic workflow, improved prompts for code generation, and introduced a Docker-based code validator for robust checks. Completed documentation and repository cleanup for Agentic to standardize structure, clarify LLM provider support (Replicate, Watsonx, Ollama), and clean up examples. These changes reduce onboarding time, increase reliability of AI-driven code, and set the stage for broader adoption across teams.
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 — IBM/data-prep-kit: Delivered Data Prep Kit (DPK) LLM Agent Integration enabling agentic planning, tool integration, and execution of DPK transforms. Shipped new example notebooks and Python scripts illustrating agentic data-prep workflows. Documented notebooks with added comments to improve readability. No major bugs fixed this month; focus was on delivering automation-ready capabilities and establishing a solid foundation for AI-assisted data preparation. Impact: accelerates data prep tasks, improves reproducibility and integration with AI agents. Technologies/skills demonstrated include LLM agents, Python, Jupyter notebooks, DPK transforms, and tool integration.
2 Commits • 1 Features
Jan 1, 2025January 2025 — IBM/data-prep-kit: Delivered Data Prep Kit (DPK) LLM Agent Integration enabling agentic planning, tool integration, and execution of DPK transforms. Shipped new example notebooks and Python scripts illustrating agentic data-prep workflows. Documented notebooks with added comments to improve readability. No major bugs fixed this month; focus was on delivering automation-ready capabilities and establishing a solid foundation for AI-assisted data preparation. Impact: accelerates data prep tasks, improves reproducibility and integration with AI agents. Technologies/skills demonstrated include LLM agents, Python, Jupyter notebooks, DPK transforms, and tool integration.
January 2025
Activity
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Quality Metrics
Correctness83.8%
Maintainability82.6%
Architecture76.2%
Performance81.2%
AI Usage52.6%
Skills & Technologies
Programming Languages
Jupyter NotebookMarkdownPython
Technical Skills
AIAI Agent DevelopmentAPI IntegrationCode CommentingCode RefactoringConfigurationData EngineeringData PreparationDockerDocumentationJupyter NotebookLLMLLM AgentsLLM IntegrationLangChain
Repositories Contributed To
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