Ship annotation and tracking workflows faster.
Annolid combines a desktop GUI, a composable CLI, and agent-assisted tools for real-world behavior analysis projects.
Start with a stable local setup, then move into repeatable workflows, memory-backed context, and deployment-ready operations.
Choose Your Path¶
Installation | One-Line Installer
annolid-run, MCP integrations, and automation-friendly CLI flows.
Workflows | Agent CLI | MCP | Reference
Deployment | Migration Plan
Core Areas¶
Setup
Pick the right environment path for your platform and development mode.
Open installation guideWorkflow Execution
Run GUI and CLI tasks with explicit, reproducible command patterns.
Open workflowsZone Analysis
Draw chamber layouts, reuse zone files, and export phase-aware summaries.
Open zone analysis referenceAgent CLI
Use the typed annolid_run tool for safe agent-driven CLI operations.
Tutorials
Jump into focused guides for tracking, segmentation, and model operations.
Open tutorialsMemory System
Store reusable context, use scoped retrieval, and migrate legacy memory data.
Open memory docsAgents and Security
Configure agents, isolate secrets, and validate local security posture.
Open security docsOperations
Deploy docs/site assets and keep release and migration flows in sync.
Open deployment guideProduct Snapshot¶
- Python package metadata supports
>=3.10; CI/docs currently target Python 3.10-3.13. - Primary entry points are
annolid(GUI) andannolid-run(CLI/plugins). - Memory subsystem includes GUI CRUD manager, structured settings profiles, and legacy-source migration tooling.
- Annolid Bot supports multimodal chat and optional provider integrations in the GUI.
- Docs are built with MkDocs Material in strict mode and published through GitHub Actions.