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Deployment

This guide covers practical deployment shapes for Orchestro beyond “run it once in a shell.”

Table Of Contents

  1. Supported Deployment Mindset
  2. Local Persistent Service
  3. Data Placement
  4. Backend Dependencies
  5. Recommended Validation After Deploy

Supported Deployment Mindset

The codebase is currently best suited to:

  • local personal deployment
  • a private workstation or homelab box
  • an operator who can inspect logs, files, and SQLite state directly

It is not yet documented or hardened as an internet-facing production SaaS deployment.

Local Persistent Service

The simplest long-running deployment is:

export ORCHESTRO_HOME=/path/to/orchestro-home
orchestro serve --host 127.0.0.1 --port 8765

Concrete examples now live under:

Data Placement

Persist:

  • the Orchestro home directory
  • the project repo if you rely on project-local instructions or constitutions

Important files under ORCHESTRO_HOME may include:

  • orchestro.db
  • global.md
  • constitutions/
  • mcp_servers.json
  • lsp_servers.json
  • tool_approvals.json
  • trust.json
  • plugins/

Backend Dependencies

A deployment is only as useful as its configured backends.

Common dependency classes:

  • local OpenAI-compatible server
  • agent CLIs present on PATH
  • Anthropic/OpenAI/OpenRouter API credentials
  • MCP server subprocess dependencies
  • language server binaries

Use these to inspect the deployed environment:

orchestro backends
orchestro plugins
orchestro mcp-status
orchestro lsp-status

Recommended Validation After Deploy

Minimum checks:

PYTHONPATH=src pytest -q
PYTHONPATH=src python scripts/orchestro_canary.py --backend mock --json
curl http://127.0.0.1:8765/health
curl http://127.0.0.1:8765/backends

If you rely on live backends:

ORCHESTRO_RUN_LIVE_BACKEND_TESTS=1 PYTHONPATH=src pytest -q tests/test_live_backends.py

Related docs: