Optimize codebase indexing

[yetone]

Description

The current RAG service implementation handles codebase indexing, but there's room for optimization to improve performance and efficiency.

Potential improvements

1. Optimize indexing algorithms for large codebases
2. Implement intelligent chunking strategies for code files
3. Add incremental indexing to avoid re-indexing unchanged files
4. Improve parallel processing of files during indexing
5. Add progress reporting for long-running indexing operations
6. Optimize vector storage and retrieval mechanisms
7. Reduce memory usage during indexing operations

Benefits

• Faster response times when using RAG features
• Reduced system resource usage
• Better handling of large projects
• Improved user experience with indexing status visibility

[yetone]

‌‌This issue was automatically created in avante.nvim by the GitHub MCP server. 😁

[github-actions[bot]]

This issue is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 5 days.

[1Jo1]

@yetone could you explain how cursor handles codebase indexing? It clearly builds some kind of index for navigation, but does it store these indexes purely in memory, or are they persisted to disk somewhere? If saved locally, where exactly are these index files kept?

[github-actions[bot]]

This issue is stale because it has been open 30 days with no activity. Remove stale label or comment or this will be closed in 5 days.

[github-actions[bot]]

This issue was closed because it has been stalled for 5 days with no activity.