Agent-based dashboard: how a deepfake spreads through a school network, and where a limited education budget actually helps. Illustrative, not validated.
Justin Visser
7c16e6ea4f
Two-terminal dev loop (go run + vite proxy), the full check matrix, and the regenerate-types rule: web/src/types/ is generated from the Go structs and must never be edited by hand. |
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|---|---|---|
| cmd/spreadlab | ||
| internal | ||
| web | ||
| .gitignore | ||
| generate.go | ||
| go.mod | ||
| go.sum | ||
| LICENSE | ||
| README.md | ||
| tygo.yaml | ||
spreadlab
Self-hosted dashboard that runs an agent-based deepfake-spread model live: change the levers, watch the spread, and (later) search for the best intervention under a budget. Output is illustrative, not validated.
Status: milestone 2, thin API + parity page done.
Layout
internal/engine/- the pure simulation engine (no web dependencies)internal/api/- thin JSON API over the enginecmd/spreadlab/- the server binary (-tableprints a CLI comparison)web/- Vue 3 + TypeScript frontend (Vite)web/src/types/- TypeScript types GENERATED from the Go structs; never edit by hand, regenerate withgo generate ./...
Development
Two terminals:
go run ./cmd/spreadlab # API on localhost:8080
cd web && npm run dev # Vite dev server, proxies /api to :8080
Checks:
go test ./... # engine + API tests
golangci-lint run ./... # Go linter
go test -bench=. -benchmem ./internal/engine/ # benchmark baseline
cd web && npm run test:unit && npm run lint && npm run type-check
After changing Config, Result, or the API response types, run
go generate ./... and commit the regenerated files in web/src/types/.
MIT licensed.