Adaptive Retrieval Engine

The Adaptive Retrieval Engine is responsible for gathering only the code and historical context required to fix a specific issue.
Instead of loading entire repositories, Chronos-1 performs precise, multi-hop traversal across the codebase to find the true root cause.

This system ensures that Chronos-1 always works with the right information, no more, no less, enabling efficient and accurate debugging at scale.

What This Engine Does

The retrieval engine identifies:

• the exact files involved in a failure
• relevant functions and modules
• surrounding code context
• historical changes linked to the issue
• prior bug patterns and regressions

It accomplishes this using a specialized graph-based approach.

How the Adaptive Graph Guided Retrieval Works

Chronos-1 uses the Adaptive Graph Guided Retrieval (AGR) system to navigate large codebases with high precision.

Key capabilities include:

• Dynamic k-hop neighbor expansion
  Expands through the code graph based on query complexity.

• AST-aware embeddings
  Preserves structural relationships across the code so the model understands semantics, not just tokens.

• Dependency graph indexing
  Detects cross-file interactions and impact zones across modules.

• Call hierarchy mapping
  Tracks execution flow to uncover where issues originate.

• Temporal indexing
  Uses commit history and evolution patterns to identify potential regressions.

• Confidence-based termination
  Stops traversal once enough relevant context is assembled, avoiding unnecessary computation.

Why This Matters

Many debugging failures come from retrieving too little or too much information.

The Adaptive Retrieval Engine solves this by:

• gathering only the context required for the fix
• uncovering cross-file relationships often invisible to traditional tools
• understanding how code changed over time
• isolating root-cause regions across large repositories

This ensures Chronos-1 can reliably diagnose and fix issues even in multi-file, large-scale environments.