Skip to main content

Python SDK for Admiral combinatorial optimization cloud

Project description

Admiral

Admiral

Combinatorial optimization cloud platform
Solve QUBO, Ising, CQM, MILP, Max-SAT and 6 more problem types
with specialized algorithms via cloud API, Python SDK, or CLI.

Docs · Pricing · Discord · Self-Host


Quick Start

pip install admiral-solver
from admiral import Solver
import numpy as np

solver = Solver(api_key="adm_sk_...")
Q = np.array([[-5, 2, 4], [0, -3, 1], [0, 0, -8]])
result = solver.solve_qubo(Q, timeout=30)
print(result.energy)     # -13.0
print(result.solution)   # [1, 0, 1]

Local mode (no server):

from admiral import LocalSolver
result = LocalSolver().solve_qubo(Q, solver="tabu", seed=42)

11 Problem Types

Type Formulation Variables Solvers
QUBO min x^TQx binary SB, PT, Tabu, Roof duality
Ising min Σhᵢsᵢ + ΣJᵢⱼsᵢsⱼ spin SB, PT, Tabu
HUBO min Σcₛ∏xᵢ binary Native SA, Quadratize→QUBO
DQM min Σaᵢ(xᵢ)+Σbᵢⱼ discrete Discrete SA/Tabu, Bucket elim
CQM min x^TQx+c^Tx s.t. Ax≤b mixed ADMM, Feasibility pump, B&C
MILP min c^Tx s.t. Ax≤b int+real Branch & cut, RINS
MIQP min x^TQx+c^Tx Ax≤b mixed QP B&C, ADMM
Max-SAT max Σwⱼ·sat(Cⱼ) boolean WalkSAT, Core-guided RC2
PBO min Σcⱼ∏lᵢ s.t. ≥b binary SAT cutting planes
WCSP min Σf(x) discrete VAC+B&B, LNS, BP
Potts min −ΣJδ(sᵢ,sⱼ) discrete Swendsen-Wang, Discrete PT

Architecture

Clients (SDK / REST / CLI)
        │
        ▼
   API Server (FastAPI)  ──▶  PostgreSQL
        │
        ▼
      Redis (job queue + rate limits)
        │
   ┌────┴────┐
   ▼         ▼
CPU Workers  GPU Workers
Tabu, B&C    SB, PT
ADMM, RC2

Self-Hosting

git clone https://github.com/admiral-dev/admiral-solver.git
cd admiral-solver
cp .env.example .env   # edit secrets
docker-compose up -d   # starts everything

Scale: docker-compose up -d --scale worker-cpu=8 --scale worker-gpu=4

K8s: kubectl apply -f deploy/k8s-api.yaml -f deploy/k8s-workers.yaml

CLI

admiral solve --type qubo --input problem.json --local
admiral convert --from qubo --to ising --input q.json
admiral bench --sizes 10,100,1000 --solver sb
admiral server start --port 8000
admiral worker start --redis redis://localhost:6379

API

curl -X POST https://api.admiral.dev/v1/solve \
  -H "Authorization: Bearer adm_sk_..." \
  -d '{"problem_type":"qubo","data":{"Q":[[-5,2,4],[0,-3,1],[0,0,-8]]}}'
Method Endpoint Description
POST /v1/solve Submit problem
GET /v1/jobs/{id} Status + result
GET /v1/jobs/{id}/pool Solution pool
POST /v1/analyze Complexity analysis
POST /v1/convert Format conversion
DELETE /v1/jobs/{id} Cancel
GET /v1/solvers List engines
GET /v1/health Health check

Development

pip install -e ".[dev]"
pytest tests/ -v
ruff check admiral/

License

Apache 2.0 — see LICENSE


Built by Admiral Technologies

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

admiral_solver-1.1.1-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file admiral_solver-1.1.1-py3-none-any.whl.

File metadata

  • Download URL: admiral_solver-1.1.1-py3-none-any.whl
  • Upload date:
  • Size: 15.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.7

File hashes

Hashes for admiral_solver-1.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 f6f92ea57fe0afafa28b31972adf8d01c55a1c85618791c880b64c6c662cb335
MD5 5f8476d7fcab226395b0220912d95cb5
BLAKE2b-256 f8e3096ad9648fe78c71bc6c34605eb3a6ca90bb7121e3478712c5ac63cae10d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page