Hongming Wang cb74f0d6ae chore: extract workspace runtime to PyPI + move adapter Dockerfiles to template repos

Published `molecule-ai-workspace-runtime==0.1.0` to PyPI:
  https://pypi.org/project/molecule-ai-workspace-runtime/0.1.0/

Source repo: https://github.com/Molecule-AI/molecule-ai-workspace-runtime

Each adapter's Dockerfile and requirements.txt have moved to the corresponding
standalone template repo (molecule-ai-workspace-template-<runtime>). The adapter
Python code (.py files) stays in the monorepo for local dev and testing.

Changes:
- workspace-template/pyproject.toml — new, packages the shared runtime as a PyPI package
- workspace-template/adapters/*/Dockerfile — removed (now in template repos)
- workspace-template/adapters/*/requirements.txt — removed (now in template repos)
- workspace-template/Dockerfile — drop COPY adapters/ (still copies .py files via *.py glob)
- workspace-template/build-all.sh — simplified to base-image-only build
- workspace-template/entrypoint.sh — remove adapter requirements.txt install step
- workspace-template/tests/test_hermes_adapter.py — skip Dockerfile/requirements.txt checks
- CLAUDE.md — update architecture description + workspace image table
- docs/workspace-runtime-package.md — new, explains the package + adapter repo layout

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-04-16 04:33:10 -07:00

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Workspace Runtime PyPI Package

Overview

The shared workspace runtime infrastructure lives in two places:

Source of truth (monorepo): workspace-template/ — this is where all development happens
Published package: molecule-ai-workspace-runtime on PyPI

What's in the package

Everything in workspace-template/ except adapter-specific code:

molecule_runtime/ — all shared .py files (main.py, config.py, heartbeat.py, etc.)
molecule_runtime/adapters/ — BaseAdapter, AdapterConfig, SetupResult, shared_runtime
molecule_runtime/builtin_tools/ — delegation, memory, approvals, sandbox, telemetry
molecule_runtime/skill_loader/ — skill loading + hot-reload
molecule_runtime/plugins_registry/ — plugin discovery and install pipeline
molecule_runtime/policies/ — namespace routing policies
Console script: molecule-runtime → molecule_runtime.main:main_sync

Adapter repos

Each of the 8 adapter repos now contains:

adapter.py — runtime-specific Adapter class
requirements.txt — molecule-ai-workspace-runtime>=0.1.0 + adapter deps
Dockerfile — standalone image (no longer extends workspace-template:base)

Adapter	Repo
claude-code	https://github.com/Molecule-AI/molecule-ai-workspace-template-claude-code
langgraph	https://github.com/Molecule-AI/molecule-ai-workspace-template-langgraph
crewai	https://github.com/Molecule-AI/molecule-ai-workspace-template-crewai
autogen	https://github.com/Molecule-AI/molecule-ai-workspace-template-autogen
deepagents	https://github.com/Molecule-AI/molecule-ai-workspace-template-deepagents
hermes	https://github.com/Molecule-AI/molecule-ai-workspace-template-hermes
gemini-cli	https://github.com/Molecule-AI/molecule-ai-workspace-template-gemini-cli
openclaw	https://github.com/Molecule-AI/molecule-ai-workspace-template-openclaw

Adapter discovery (ADAPTER_MODULE)

Standalone adapter repos set ENV ADAPTER_MODULE=adapter in their Dockerfile. The runtime's get_adapter() checks this env var first:

# In molecule_runtime/adapters/__init__.py
def get_adapter(runtime: str) -> type[BaseAdapter]:
    adapter_module = os.environ.get("ADAPTER_MODULE")
    if adapter_module:
        mod = importlib.import_module(adapter_module)
        return getattr(mod, "Adapter")
    # Fall back to built-in subdirectory scan (monorepo local dev)
    ...

Publishing a new version

cd workspace-template
# 1. Bump version in pyproject.toml
# 2. Sync to molecule-ai-workspace-runtime repo
# 3. Tag and push — CI publishes to PyPI via PYPI_TOKEN secret

Or manually:

cd workspace-template
python -m build
python -m twine upload dist/*

Writing a new adapter

Create a new standalone repo molecule-ai-workspace-template-<runtime>
Copy adapter.py pattern from any existing adapter repo
Change imports: from molecule_runtime.adapters.base import BaseAdapter, AdapterConfig
Create requirements.txt with molecule-ai-workspace-runtime>=0.1.0 + your deps
Create Dockerfile with ENV ADAPTER_MODULE=adapter and ENTRYPOINT ["molecule-runtime"]
Register the runtime name in the platform's known runtimes list

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