OrbitGuide AI
Inspiration
As students and developers, we often face a common challenge when working on a new project: understanding the codebase. Whether it's an open-source repository or a project developed by another team, it can take hours or even days to understand the architecture, folder structure, dependencies, and workflow before making meaningful contributions.
We realized that while AI tools can answer programming questions, they usually don't understand the specific context of a repository. This inspired us to build OrbitGuide AI, a repository-aware assistant powered by GitLab Orbit that helps developers understand unfamiliar codebases quickly and efficiently.
What it does
OrbitGuide AI transforms a repository into an interactive knowledge assistant.
Using GitLab Orbit, the system analyzes the structure and relationships within a codebase and provides contextual guidance to developers. Users can ask questions about the repository, understand how different modules are connected, locate important files, and explore project architecture without manually searching through hundreds of files.
OrbitGuide AI helps developers:
- Understand project architecture faster
- Discover key files and modules
- Trace dependencies between components
- Get repository-specific answers
- Follow personalized onboarding paths
- Become productive in less time
How we built it
We built OrbitGuide AI by combining GitLab Orbit's repository intelligence with AI-powered analysis.
The workflow starts with GitLab Orbit, which provides structured information about the repository. This contextual information is then processed through an AI layer that understands user questions and retrieves relevant repository insights.
The system analyzes project structure, file relationships, dependencies, and metadata to generate accurate explanations tailored to the repository being explored.
Challenges we ran into
One of the biggest challenges was ensuring that the assistant provides accurate repository-specific answers rather than generic AI responses.
Another challenge was presenting technical information in a way that is easy to understand for both beginners and experienced developers. Large repositories often contain complex relationships, so designing a clear and intuitive explanation system required careful planning.
We also explored how to efficiently use repository context without overwhelming users with excessive technical details.
Accomplishments that we're proud of
- Created a practical solution for developer onboarding.
- Leveraged GitLab Orbit to provide repository-aware intelligence.
- Reduced the effort required to understand complex codebases.
- Built an assistant that focuses on real developer productivity challenges.
What we learned
Throughout this project, we learned a lot about:
- Repository intelligence systems
- AI-assisted software development
- Context-aware retrieval techniques
- Developer onboarding workflows
- GitLab Orbit and its capabilities
Most importantly, we learned that providing the right context significantly improves the usefulness of AI-generated responses.
What's next for OrbitGuide AI
In the future, we plan to enhance OrbitGuide AI with:
- Interactive architecture diagrams
- Visual dependency mapping
- Pull request impact analysis
- Team onboarding recommendations
- Multi-repository support
- Integration with CI/CD pipelines
Our vision is to make understanding any software project as simple as having a conversation with an experienced team member.
Built With
- agent
- api
- database
- docker
- duo
- fastapi
- git
- gitlab
- langchain
- openai
- orbit
- platform
- postgresql
- python
- rest
- vector
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