redhat-developer/rhdh-plugins
Mar 2026 – Mar 2026
1 Month active
Languages Used
JavaScriptTypeScriptYAML
Technical Skills
AI integrationGitNode.jsReactYarnbackend development
Raghuram Banda
PROFILE
Raghuram Banda
Rohit Banda developed a scalable augment plugin platform for the redhat-developer/rhdh-plugins repository, focusing on robust governance and enterprise-grade AI-assisted workflows. He established a new augment workspace skeleton with CODEOWNERS to enable self-managed plugin reviews and continuous integration compatibility. Leveraging JavaScript, TypeScript, and React, Rohit introduced a chat-based augment AI assistant powered by Llama Stack, multi-agent orchestration, and retrieval-augmented generation. His work included implementing human-in-the-loop approval, vector store management, and configurable safety guardrails. Comprehensive test coverage, documentation updates, and CI improvements demonstrated a thorough engineering approach, resulting in a reliable, maintainable foundation for future AI plugin development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
163,274
Activity Months1
Your Network
2726 peopleWork History
March 2026
3 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for redhat-developer/rhdh-plugins focused on delivering a scalable augment plugin platform, robust governance, and enterprise-grade AI-assisted workflows. The work established a new augment workspace skeleton with CODEOWNERS, enabling self-managed code reviews for augment AI plugins, and introduced a dedicated augment AI assistant workspace under workspaces/augment. The platform is powered by a chat interface backed by Llama Stack, multi-agent orchestration, RAG, MCP tool calling, and configurable safety guardrails, with documentation and tests updated to ensure reliability.
3 Commits • 1 Features
Mar 1, 2026March 2026 monthly summary for redhat-developer/rhdh-plugins focused on delivering a scalable augment plugin platform, robust governance, and enterprise-grade AI-assisted workflows. The work established a new augment workspace skeleton with CODEOWNERS, enabling self-managed code reviews for augment AI plugins, and introduced a dedicated augment AI assistant workspace under workspaces/augment. The platform is powered by a chat interface backed by Llama Stack, multi-agent orchestration, RAG, MCP tool calling, and configurable safety guardrails, with documentation and tests updated to ensure reliability.
March 2026
Activity
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Quality Metrics
Correctness86.6%
Maintainability86.6%
Architecture86.6%
Performance86.6%
AI Usage53.4%
Skills & Technologies
Programming Languages
JavaScriptTypeScriptYAML
Technical Skills
AI integrationGitNode.jsReactYarnbackend developmentfrontend developmentfull stack development
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline