SciMesh/mkdocs/index.md

SciMesh

SciMesh is a local-first platform for scientific computation on molecular datasets. It turns a scientific run into independent tasks, dispatches them to Python workers, and deterministically combines the partial results into a checksum-protected final artifact.

The two halves of the project:

• The Workload SDK (scimesh.sdk) — a strict Python framework for authoring scientific workloads. Workloads are ordinary user scripts built on the SDK; they run locally, in the conformance harness, and on claimed coordinator tasks without touching any other part of the program.
• The coordinator and worker — a Go/PostgreSQL coordinator with an operator UI and Python worker agents that execute SDK-built workloads over an HTTP contract.

What is implemented

• SDK-built workloads: similarity-search (exact top-k Tanimoto search), similarity-graph (exact sparse similarity graph with pair-coverage), descriptor-batch (pinned RDKit 2D descriptors), and molwt-filter (molecular-weight filter — the minimal authoring example).
• MapReduceWorkload: the primary authoring scaffold. A subclass declares identity, parameters, ports, and scientific hooks; the SDK assembles the manifest, map/reduce stages, the digest-pinned planner/runner/reducer, and the exact-artifact verifier.
• A local conformance runtime (LocalCoreBatchExecutor): a trusted, in-process harness that validates scientific parity, sealed outputs, provenance, and limits.
• A distributed worker that executes the same SDK workload handlers on tasks claimed from the coordinator, with digest-pinned TaskSpecs, resource reservation, and allowlist-driven workload discovery.
• An operator UI served by the coordinator: the control room, a workload library page, a workload-agnostic "new computation" form whose controls come from each workload's own UIElement declarations, and this documentation site at /ui/docs/.

Quick start

python -m venv .venv
source .venv/bin/activate
pip install -e '.[dev]'

List the installed SDK workloads and run one locally:

scimesh workload list
scimesh workload run molwt-filter \
  --input molecules.tsv \
  --params '{"min_molwt": 40.0}' \
  -o filtered.csv

Run the local scientific CLI workloads:

scimesh help

Start the full demo (PostgreSQL, coordinator, UI, two workers):

make demo-ui
# open http://localhost:18080/ui  (root@scimesh.local / rootpassword)

Prebuilt binaries

Every v* tag pushes a GitHub Release with static binaries for coordinator and worker-agent on linux/darwin/windows × amd64/arm64 (plus SHA-256 checksums) and the coordinator image on GHCR. Download and run:

curl -L -o coordinator https://github.com/emil28092005/SciMesh/releases/latest/download/coordinator-linux-amd64
chmod +x coordinator

• worker-agent runs anywhere with Python: it spawns python -m scimesh.worker.task, so the machine needs the scimesh package in a venv (pip install scimesh) and the usual environment: COORDINATOR_URL, WORKER_AUTH_TOKEN, WORK_DIR.
• coordinator needs PostgreSQL running (DATABASE_URL, COORDINATOR_STORAGE_DIR, JWT_SECRET); the binary applies its embedded schema migrations itself on startup (AUTO_MIGRATE=false opts out), so no separate migration step is needed. The interactive wizard provisions the rest: it checks the database, creates it when missing, generates a JWT_SECRET, and writes a .env file (coordinator setup --help, or make setup; --yes for non-interactive runs). The UI login additionally requires USERSERVICE_URL. coordinator --version / worker-agent --version print the build tag.

Build and serve this documentation site:

make docs
make docs-serve      # http://localhost:8000

Where to go next

• SDK overview — what the SDK is and is not.
• Authoring workloads — write your first workload with MapReduceWorkload.
• Workload CLI — list, run, and export workloads from the command line.
• Worker integration — how the distributed worker executes SDK workloads.
• API reference — the complete scimesh.sdk API, generated from docstrings.
• Documentation approach — the rules this site is written by.