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Ports the "code self-heals via Fibonacci alignment" pattern from the
ONN system (skill: onn-self-healing-code, ref:
omninet_package/register_singularity_integration.py).
Four new built-ins, available in both tree-walk and VM:
value_danger(x) = exp(-|x|)
Proximity gradient. Returns 1.0 when x ≈ 0 (high danger), decays
exponentially as |x| grows. The early-warning signal for
approaching singularities, BEFORE the operation that would
trigger them.
fold_escape(x)
If value_danger(x) > 0.5, snap to nearest Fibonacci attractor
(preserving sign). Special case: fold_escape(0) → 1, never
landing back on the singularity. Else passthrough.
harmony_value(x)
Fibonacci-proximity score in [0, 1]. 1.0 iff x is a Fibonacci
number. The general "is this value living on the φ-geodesic?"
reading.
safe_divide(a, b)
Divide with predictive self-healing: pre-applies fold_escape to
the divisor. Zero divisors heal to 1 transparently; the operation
always returns a number (never a Singularity).
Together these realize the canonical ONN pattern: when an input
isn't Fibonacci-aligned, fix the input. It's the predictive version
of HSingularity recovery — fold to a safe attractor BEFORE the
operation rather than catching the portal AFTER.
## Demo
examples/self_healing_demo.omc exercises both scenarios:
- Scenario 1: pipeline of divisions where some divisors are 0.
The unhealthy divisors silently heal to 1 before each division.
Output is bit-identical between tree-walk and VM.
- Scenario 2: pre-emptive Fibonacci alignment on a list of inputs.
Values already on the φ-geodesic (89, 233, 144) pass through.
Off-geodesic values get snapped, with harmony rising as a result.
## Tests
+9 conformance tests pinning the math:
- value_danger(0) = 1
- value_danger(1) = e^(-1)
- value_danger(89) < 1e-30
- fold_escape(0) → 1 (zero-trap escape)
- fold_escape(100) passthrough
- safe_divide(89, 0) = 89, NEVER a Singularity
- safe_divide(89, 2) = 44 (normal path unchanged)
- harmony_value(89) = 1.0
- harmony_value(100) < harmony_value(89)
134 total tests passing across the workspace (was 125).
## Why this matters
The Rust OMC now embodies the same self-repair mechanism the Python
omnicc has — but applied as runtime primitives rather than as a
compiler pass. Programs can write `safe_divide(a, b)` and `fold_escape(x)`
and let the language keep them on the φ-geodesic, with no try/catch
and no explicit singularity branching.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Ports the "code/compiler self-heals via Fibonacci alignment" pattern from the ONN system at `/home/thearchitect/.hermes/skills/onn-self-healing-code/` and `Sovereign_Lattice/omninet_package/register_singularity_integration.py`. Four new built-ins, available in both tree-walk and VM:
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-**`value_danger(x) = exp(-|x|)`** — proximity gradient. Returns 1.0 when `x ≈ 0` (high danger), decays exponentially. The early-warning signal for approaching singularities, *before* the operation that would trigger them.
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-**`fold_escape(x)`** — if `value_danger(x) > 0.5`, snap to the nearest Fibonacci attractor (preserving sign, with a special case: `fold_escape(0) → 1`, never landing back on the singularity). Else passthrough.
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-**`harmony_value(x)`** — Fibonacci-proximity score in `[0, 1]`. 1.0 iff x is a Fibonacci number. The general "is this value living on the φ-geodesic?" reading.
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-**`safe_divide(a, b)`** — divides, but pre-applies `fold_escape` to the divisor. Zero divisors heal to 1 transparently; the operation always returns a number (never a Singularity).
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Together, these realize the pattern the user described: *"when an error comes to the compiler it checks to see if it's Fibonacci-aligned, then it fixes itself."* It's the *predictive* version of HSingularity recovery — fold inputs to a safe attractor before the operation, rather than catching the portal after.
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Demo: `examples/self_healing_demo.omc` exercises both scenarios — a pipeline of unsafe divisions that silently heal, and pre-emptive Fibonacci alignment on a list of incoming values. Tree-walk and VM produce identical output.
`examples/phi_field_llm_demo.omc` — a working "language model" written in pure OMNIcode that demonstrates the harmonic computing thesis end-to-end. No transformer. No matrix multiply. No learned weights. Decisions are made by walking phi-space geodesics, with each step scored by OmniWeight `w = φ^(-|e|)` — the canonical formula from `omninet_phi/resonance.py`.
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