BioSight/AGENTS.md
allaun 41fcbc3daa feat(init): initial BioSight commit — equation-to-DNA Φ encoding
BioSight encodes mathematical equations as 30-base hachimoji DNA
sequences for Adleman/Lipton-style DNA computing.

4-layer Φ mapping:
  Layer 1: F(E) — byte-class histogram on Δ₇
  Layer 3: τ(E) + δ(E) — parse tree structure
  Layer 4: 6 consistency rules → allele-specific PCR pass/fail

Independent phi/ modules:
  charclass, ast_parse, consistency, embed, output

Build: python3 -m py_compile — all modules clean
2026-06-23 18:27:35 -05:00

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# BioSight — Equation-to-DNA Φ Encoding Pipeline
**Status:** Active, v0.1.0
BioSight encodes mathematical equations as hachimoji DNA sequences
for Adleman/Lipton-style DNA computing. The Φ mapping has 4 layers:
1. **F(E)** — byte-class histogram over Δ₇ (8 character classes)
2. *Phase alphabet — implicit in the mapping from Δ₇ to bases*
3. **τ(E) + δ(E)** — parse tree structure (node types + child ordering)
4. **Consistency** — 6 rules → allele-specific PCR G/T pass/fail
## Ground Rules
- **Decision logic is in Lean** — BioSight shims are Python I/O only.
If any logic here starts making admissibility or routing decisions,
port it to SilverSight's `Semantics.RRC.*` modules.
- **No floats in compute paths** — `phi.charclass` and `phi.embed`
use integer arithmetic for all core encoding. Only `phi.output`
uses math.acos (for Fisher distance in Adleman graph building).
- **Pure functions** — every phi module is a pure function of
its equation string input. No state, no I/O, no side effects.
- **Reproducibility** — two invocations on the same equation must
produce identical DNA sequences (deterministic byte-class and
AST order).
## Core Modules
| Module | Layer | Responsibility |
|--------|-------|----------------|
| `phi.charclass` | 1 | 8-class byte histogram → F(E) ∈ Δ₇ |
| `phi.ast_parse` | 3 | Python AST → τ(E) + δ(E) distributions |
| `phi.consistency` | 4 | 6 rules → ADMIT/QUARANTINE |
| `phi.embed` | Core | (F, τ, δ) → 30-base hachimoji DNA |
| `phi.output` | Formats | FASTQ, Adleman graph, PCR protocol |
## DNA Layout (30 bases)
```
bases 0-7: F(E) — byte-class frequencies on Δ₇
bases 8-15: τ(E) — parse tree node-type frequencies
bases 16-23: δ(E) — child-ordering frequencies
bases 24-29: Layer 4 consistency (G=pass, T=fail)
```
## External Integration
- **BioComputing** (`https://github.com/Abesuden/BioComputing`, MIT):
Our `phi.output.to_adleman_graph()` builds vertices+edges that
feed directly into `hampath.connectNodes()` and `sattv.createNodes()`.
Clone it alongside BioSight for wet-lab DNA sequence generation.
## Key References
- Adleman (1994) *Science* 266:10211024 — 7-vertex Hamiltonian path
- Lipton (1995) *Science* 268:542545 — SAT generalization
- Hoshika et al. (2019) *Science* 363:884887 — 8-base hachimoji alphabet
- Newton et al. (1989) *Nucleic Acids Res* 17:2503 — allele-specific PCR
## Build & Test
```bash
cd python
python3 -m py_compile phi/*.py equation_dna_encoder.py
python3 -c "import phi; print(phi.encode_phi('x + 1 = 2'))"
```
## SilverSight Relationship
BioSight is the DNA-computing branch of the Research Stack ecosystem.
SilverSight (`/home/allaun/SilverSight`) owns all formal Lean logic.
If BioSight needs a new theorem or receipt, it requests it from SilverSight.