Support Tools
The Sovereign AI Stack includes essential support tools for scripting, quality analysis, and system tracing. These tools integrate with Batuta’s orchestration workflow.
Tool Overview
| Tool | Purpose | Integration Point |
|---|---|---|
| Ruchy | Rust scripting language | Embedded scripting, automation |
| PMAT | Quality analysis (TDG scoring) | Phase 1: Analysis, CI/CD gates |
| APR-QA | APR model validation | Model quality assurance |
| Renacer | Syscall tracing | Phase 4: Validation |
Ruchy: Rust Scripting
Ruchy provides a scripting language that compiles to Rust, enabling:
- Automation scripts: Build, deployment, data processing
- Embedded scripting: In Presentar apps (Section 8)
- REPL development: Interactive exploration
// Ruchy script for data processing
let data = load_dataset("transactions")
let filtered = data.filter(|row| row.amount > 100)
let aggregated = filtered.group_by("category").sum("amount")
save_dataset(aggregated, "output.ald")
Security (in Presentar):
- Max 1M instructions per script
- Max 16MB memory allocation
- 10ms time slices (cooperative yielding)
PMAT: Quality Analysis
PMAT computes Technical Debt Grade (TDG) scores for projects:
- 0-100 scale: F, D, C-, C, C+, B-, B, B+, A-, A, A+
- Multi-language: Rust, Python, C/C++, Shell
- Metrics: Complexity, coverage, duplication, dependencies
# Analyze a project
pmat analyze ./myproject --output report.json
# CI gate (fail if below B+)
pmat gate ./myproject --min-grade B+
Integration with Batuta:
- Phase 1 (Analysis): Initial TDG assessment
- Phase 4 (Validation): Post-transpilation quality check
- CI/CD: Gate enforcement
Renacer: Syscall Tracing
Renacer captures system call traces for validation:
- Deterministic replay: Ensures transpiled code matches original behavior
- Golden trace comparison: Baseline vs current
- Cross-platform: Linux, macOS, Windows
# Capture baseline trace
renacer capture ./original_binary -- args > baseline.trace
# Compare against transpiled
renacer compare baseline.trace ./transpiled_binary -- args
Integration with Batuta:
- Phase 4 (Validation): Behavioral equivalence testing
APR-QA: Model Quality Assurance
APR-QA provides a comprehensive QA playbook for APR models:
- Test Generation: Automatic QA test generation for APR models
- Model Validation: Verify model correctness and integrity
- Benchmark Runner: Performance benchmarks on APR models
- Coverage Reports: Model coverage analysis and reporting
# Generate QA tests for an APR model
apr-qa gen model.apr --output tests/
# Run QA suite
apr-qa run tests/ --report report.html
# Quick validation
apr-qa validate model.apr
Integration with Batuta:
- Stack quality gates for APR model artifacts
- Integration with certeza for CI/CD pipelines
- Works with aprender (training) and realizar (inference)
Additional Support Tools
Trueno-RAG (v0.1.0)
Retrieval-Augmented Generation pipeline built on Trueno:
- Vector similarity search
- Document chunking
- Embedding generation
Trueno-Graph
Graph data structures and algorithms:
- Property graphs
- Traversal operations
- Connected component analysis
Trueno-DB
Embedded database with Trueno compute:
- Column-store backend
- SQL-like query interface
- ACID transactions
Tool Ecosystem Map
┌─────────────────────────────────────────────────────────────────┐
│ Batuta (Orchestration) │
├─────────────────────────────────────────────────────────────────┤
│ Transpilers │ Support Tools │ Data/ML │
│ ├── Depyler │ ├── Ruchy │ ├── Alimentar │
│ ├── Decy │ ├── PMAT │ ├── Aprender │
│ └── Bashrs │ ├── APR-QA │ └── Realizar │
│ │ └── Renacer │ │
├─────────────────────────────────────────────────────────────────┤
│ Visualization │ Extensions │ Registry │
│ ├── Trueno-Viz │ ├── Trueno-RAG │ └── Pacha │
│ └── Presentar │ ├── Trueno-Graph │ │
│ │ └── Trueno-DB │ │
└─────────────────────────────────────────────────────────────────┘
Further Reading
Navigate: Table of Contents | Foundation Libraries