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amithathreya / inference_layer
Custom inference gateway implementation for llama.cpp model deployments with standard openAI API spec
Languages
- python91.7%
- markdown8.3%
Explore amithathreya/inference_layer
Code health
Full report- Code health90
- Dead code92
- Hotspot density83
- Bus factor0
How amithathreya/inference_layer works
Custom inference gateway implementation for llama.cpp model deployments with standard openAI API spec This page is an auto-generated, always-fresh map of the amithathreya/inference_layer repository, written primarily in Python. Repowise indexes the source, parses every symbol, computes a dependency graph, scores per-file code health from complexity, duplication, test coverage and churn, mines git history for hotspots and ownership, and lifts the resulting architectural decisions into a wiki you can read or query through MCP.
The codebase has 12 source files, 51 symbols, and 2 languages. Git churn analysis flags 1 high-frequency files as hotspots — places where bugs, rewrites, and code review tend to concentrate. The dependency graph clusters into 4 tightly-coupled module communities.
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