Ask HN: Open-source alternatives to enterprise-grade code indexing/RAG systems?
I've been exploring various AI coding assistants (Cursor, GitHub Copilot, Devin, etc.) and noticed they all share a common foundation: sophisticated retrieval-augmented generation (RAG) systems that enable deep understanding of codebases. These systems excel at:
- Rapidly indexing entire codebases
- Semantic search across code snippets
- Contextual ranking of relevant code sections
- Integration with LLMs for enhanced code understanding
While proprietary solutions are abundant, I'm looking for open-source alternatives that could provide similar functionality. Specifically:
- Tools for building and maintaining code indexes
- Systems that can integrate with existing LLMs
- Solutions for semantic code search and retrieval
- Frameworks for contextual code understanding
Has anyone built or worked with open-source tools that could serve as building blocks for such a system? I'm particularly interested in hearing about:
- Real-world implementations
- Performance comparisons with commercial solutions
- Scalability considerations
- Integration challenges
The goal is to understand what's possible with current open-source technology in this space, and potentially contribute to building more accessible alternatives to proprietary systems. You can try: https://github.com/swirlai/swirl-search - doesn't indexes data
- has connectors to various apps
- metasearch under the hood
- re-ranking of search results before RAG You could take a look at sourcegraph Cody