README.md

---
title: Neuromorphic Molecular Constraint Solver
emoji: 🧬
colorFrom: blue
colorTo: green
sdk: streamlit
sdk_version: 1.27.2
app_file: app.py
pinned: false
---

## Neuromorphic Molecular Constraint Solver (Vibecoded by amateur, it is a mess)

This is a demonstration of a novel approach to *de novo* molecular generation. Instead of using a traditional generative model (like a VAE or GAN), this system translates chemical rules into a large Boolean Satisfiability (3-SAT) problem and solves it using a custom solver inspired by neuromorphic computing principles.

### How it Works

The process involves two main stages:

1.  **Encoding**: User-defined chemical properties (molecular weight, number of aromatic rings, forbidden functional groups, minimum atom count) are compiled into a massive 3-SAT problem. This includes complex chemical intelligence like valence rules (e.g., Carbon must have 4 bonds) and graph connectivity, which are encoded using cardinality constraints.

2.  **Solving**: A memory-efficient, sparse solver inspired by P-KAS (Phase-Keyed Associative Storage) and Kuramoto oscillators finds a satisfying assignment for the tens of thousands of variables and clauses. This method finds a solution by relaxing into a stable state rather than through algorithmic search.

The key advantage is **generation by construction**. The output is guaranteed to satisfy the hard constraints, leading to a very high validity rate.

### How to Use the Demo

1.  Use the sidebar on the left to set your desired molecular properties.
2.  **Crucially, set a "Minimum atom count" greater than 0** to avoid trivial solutions like H₂O. A value of 10-15 is a good starting point.
3.  Click the "Generate Molecules" button.
4.  Be patient. The encoding and solving process for such a large constraint problem can take 10-30 seconds per molecule.

### Limitations & Current Status

This is a proof of concept and has several important limitations:

* **Graph Generation, Not Full Chemistry**: The solver's primary output is a **structural graph** of atoms and their connections. It does not yet solve for bond orders (single, double, triple).
* **Visualization**: The RDKit visualizer assumes all bonds are `SINGLE` for drawing purposes. This means that even if the solver finds a valid graph where an atom has the correct *number* of bonds, the drawing may appear chemically incorrect (e.g., a Carbon with four single bonds to two atoms). The atom labels (`ID:Element`) are provided to help you inspect the raw graph structure.
* **Approximate Solver**: The neuromorphic solver is a heuristic method that aims for very high satisfaction (99%+). It is not a formal, complete SAT solver and may not find a perfect 100% solution for extremely difficult or unsatisfiable problems.