Improving AST Self-Healing Loops for Multi-File Python Patches in LuxurAI Coder

What We Built Today

Today, I focused on improving the AST self-healing loop in LuxurAI Coder, our autonomous software engineering agent. The goal was to make multi-file Python patches more reliable by automatically detecting and repairing syntax errors, bracket mismatches, and test failures.

The Problem We Solved

When generating code across multiple files, syntax errors or test failures can break the entire patch. Traditional AI tools often fail to recover from these issues, leaving developers to manually fix the errors.

How The Architecture Works

Our 5-layer AST compiler validator ensures that generated code is syntactically correct and passes tests. Here's a breakdown of the layers:

1. SelfHealingValidator: Executes tests in an isolated sandbox worker. If tests fail, it feeds runtime stderr back into the agent for automatic repair loops.
2. PromptOptimizer: Enriches vague user prompts with codebase context before planning.
3. EnsembleVoter: Evaluates parallel model outputs and selects the cleanest implementation.
4. StructureCheck: Guards against accidental deletion of critical classes or functions.
5. IndentationNormalizer & AST Validator: Normalizes tabs/spaces and verifies syntax integrity.

Transparent Economics (₹0.25/credit)

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

How We Can Make This Better

This is still an experimental beta, and I'm actively debugging edge cases. I'd love feedback from Python devs on improving test-healing reliability!

Try it out and let me know what you think: https://luxurai.in