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Python SDK for Admiral — combinatorial optimization platform. 11 problem types, 33 solvers, solver racing, AI advisor, NL builder.

Project description

Admiral Solver

Python SDK for the Admiral Combinatorial Optimization Platform.

Solve QUBO, Ising, MILP, MAX-SAT, and 7 more problem types through a single API. 33 proprietary algorithms. Solver racing. AI-powered analysis.

Install

pip install admiral-solver

Quick Start

from admiral import Solver

solver = Solver(api_key="adm_sk_...")

# Solve a QUBO problem
result = solver.solve_qubo(
    Q=[[-5, 2, 4], [0, -3, 1], [0, 0, -8]],
    timeout=10,
    race=True
)
print(result.energy)     # -13.0
print(result.solution)   # [1, 0, 1]

Features

  • 11 problem types: QUBO, Ising, HUBO, DQM, CQM, MILP, MIQP, MAX-SAT, PBO, WCSP, Potts
  • 33 proprietary algorithms: Auto-selected or raced in parallel
  • Solver Racing: Race up to 8 solvers — first to converge wins
  • AI Advisor: Analyze problem structure, get solver recommendations
  • NL Builder: Describe problems in plain English, get formulations
  • Auto-Detect: Submit JSON data, Admiral identifies the problem type

New in v2.0

# AI Advisor — analyze before solving
analysis = solver.analyze("qubo", {"Q": Q})
print(analysis["recommendations"])

# NL Builder — natural language to formulation
formulation = solver.formulate("Minimize travel between 5 cities")
print(formulation["problem_type"])  # "qubo"

# Solver Racing — race all algorithms
result = solver.solve_qubo(Q, race=True)

# Auto-Detect problem type
detected = solver.detect({"Q": Q})
print(detected["detected_type"])  # "qubo"

All Problem Types

Method Type Variables
solve_qubo(Q) QUBO Binary {0,1}
solve_ising(h, J) Ising Spin {-1,+1}
solve_hubo(terms, n) HUBO Binary, higher-order
solve_dqm(domains) DQM Discrete multi-valued
solve_cqm(c, Q, A, b) CQM Mixed with constraints
solve_milp(c, A, b) MILP Mixed integer linear
solve_miqp(c, Q, A, b) MIQP Mixed integer quadratic
solve_maxsat(clauses) MAX-SAT Boolean
solve_pbo(obj, cons, n) PBO Pseudo-boolean
solve_wcsp(n, domains, fns) WCSP Discrete constraint
solve_potts(nodes, states, edges) Potts Multi-state lattice

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