Architecture and data flow

Screph is a Windows-first PySide6 workbench. The canonical project is central: Capture supplies sources, Selector owns markup, CV produces reviewable results, and downstream components receive selected context.

Components

Desktop shell / Program ModeNavigation, settings, tray and workspace selection.
Capture → Canvas / SelectorSources move to a shared canvas; markup changes through undoable commands.
CV Registry / Pipeline / PresentationsMethods and graphs compute masks, overlays, candidates, evidence and diagnostics.
Canonical projectElements/features, annotations, relations, groups and artifact references.
Downstream adaptersAutomation runtime, AI Assistant, Screph Code/Pro Agent, IDE and voice.
Online boundariesDevice auth, support, diagnostics and working server speech start from a selected operation. A profile with a stored token, update metadata and the help cache refresh automatically; activating Speech settings may probe its provider. Model catalogues/archives and streams use separate endpoints.

Local and online execution

The canonical project, Selector and local CV, voice and LLM paths stay on the user's computer. User content is transferred by a selected function: support sends a message and attachments, diagnostics sends an explicitly confirmed ZIP, server speech sends WAV audio and a cloud LLM receives allowed context. The Logging page offers a manifest for review; the startup crash prompt does not show it. Separately, a desktop with a stored token refreshes the profile every 30 seconds; an installed build may fetch update metadata and six embedded-help pages. Activating OpenAI/LiteLLM Speech settings checks a catalogue or sends a synthetic silent probe. Model catalogues/archives and URL streams contact their hosts but do not upload the canonical project. A SCREPH_TELEMETRY configuration flag exists, but the current runtime initializes no automatic telemetry exporter.

Online service contracts →

Local processes and loopback

A separate process separates lifecycle and failures, but does not create a sandbox by itself. Unless stated otherwise below, a child component runs as the current Windows user and can use that user's files, network and devices.

ComponentBoundaryWhat matters to the user
Screph Code / Pro AgentSeparate processes, JSON-RPC over stdin/stdout and session/context filesSame OS-user permissions; review and diff are workflow controls, not an OS sandbox
Support helperscreph-support-chat.v1 over stdin/stdout; the helper performs HTTPSSecret-shaped environment variables are filtered, but the selected request's auth context is passed explicitly; no loopback port is opened
Monaco127.0.0.1, ephemeral portThe local static-asset server closes with the widget; it is not a cloud API
Codex bridge logPOST /codex-bridge-log on an ephemeral loopback portAn unauthenticated local endpoint accepts JSON up to 256 KiB and writes its fields to the Screph log
Automation Manager UI / workflowThe UI normally lives in the desktop process; the selected workflow runs as a Python child with stdout/EVT and a control fileThe child inherits the environment and user permissions; Stop controls the direct child, not necessarily its entire process tree
OAuth callback127.0.0.1:8443/8765A legacy mechanism disabled by default; the current device flow does not open this listener
Temporal workermultiprocessing pipe/shared memoryAn internal/prototype transport; normal CV execution must not be described as an isolated worker

Trust boundary

Automatic live-preview recalculation is not saved, and a candidate does not become canonical geometry or semantics without explicit review/apply. Manual Apply in the main CV panel may attach a visual result to an image series but does not accept the candidate as markup. Downstream boundaries differ: Automation Runtime requires a separate run action, while sending a request to the current Screph Code Builder grants agent-mode write access inside the selected workspace. This path has no universal per-file confirmation.

Mode readiness

  • General, GUI Automation: end-to-end workflows are ready.
  • Industrial, UAV: selectable foundation/domain workspaces; not a production control/export path.
  • Ground Robotics: an internal deferred scaffold.

Detailed engineering documents

State reports, the capability matrix, technical architecture and decisions live with the source code and are updated against implementation evidence.

Open engineering documentation on GitHub →