Improving AST Self-Healing Loops for Multi-File Python Patches

What We Built Today

Today, we focused on improving LuxurAI Coder’s AST self-healing loop for multi-file Python patches. The goal is to make AI-generated code more reliable and production-ready.

The Problem We Solved

AI-generated code often breaks in production due to syntax errors or failed tests. Our self-healing loop ensures that patches are validated and repaired automatically.

How The Architecture Works

1. Multi-Stage Pipeline: We use AST parsing to map dependencies and plan changes across files.
2. Self-Healing Validator: If tests fail, the agent automatically feeds runtime errors back into the loop for repair.
3. Ensemble Voter: Parallel model outputs are evaluated to select the cleanest implementation.

Transparent Economics

LuxurAI operates on a pay-as-you-go model at ₹0.25 per credit. No subscriptions, no hidden fees.

How We Can Make This Better

We’re in the experimental beta phase and would love feedback from Python devs. How can we improve test-healing reliability?

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LuxurAI Coder