forked from molecule-ai/molecule-core
cb74f0d6ae
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>
80 lines
3.3 KiB
Markdown
80 lines
3.3 KiB
Markdown
# Workspace Runtime PyPI Package
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## Overview
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The shared workspace runtime infrastructure lives in two places:
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1. **Source of truth (monorepo):** `workspace-template/` — this is where all development happens
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2. **Published package:** [`molecule-ai-workspace-runtime`](https://pypi.org/project/molecule-ai-workspace-runtime/) on PyPI
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## What's in the package
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Everything in `workspace-template/` except adapter-specific code:
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- `molecule_runtime/` — all shared `.py` files (main.py, config.py, heartbeat.py, etc.)
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- `molecule_runtime/adapters/` — `BaseAdapter`, `AdapterConfig`, `SetupResult`, `shared_runtime`
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- `molecule_runtime/builtin_tools/` — delegation, memory, approvals, sandbox, telemetry
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- `molecule_runtime/skill_loader/` — skill loading + hot-reload
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- `molecule_runtime/plugins_registry/` — plugin discovery and install pipeline
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- `molecule_runtime/policies/` — namespace routing policies
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- Console script: `molecule-runtime` → `molecule_runtime.main:main_sync`
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## Adapter repos
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Each of the 8 adapter repos now contains:
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- `adapter.py` — runtime-specific `Adapter` class
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- `requirements.txt` — `molecule-ai-workspace-runtime>=0.1.0` + adapter deps
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- `Dockerfile` — standalone image (no longer extends workspace-template:base)
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| Adapter | Repo |
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|---------|------|
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| claude-code | https://github.com/Molecule-AI/molecule-ai-workspace-template-claude-code |
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| langgraph | https://github.com/Molecule-AI/molecule-ai-workspace-template-langgraph |
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| crewai | https://github.com/Molecule-AI/molecule-ai-workspace-template-crewai |
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| autogen | https://github.com/Molecule-AI/molecule-ai-workspace-template-autogen |
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| deepagents | https://github.com/Molecule-AI/molecule-ai-workspace-template-deepagents |
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| hermes | https://github.com/Molecule-AI/molecule-ai-workspace-template-hermes |
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| gemini-cli | https://github.com/Molecule-AI/molecule-ai-workspace-template-gemini-cli |
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| openclaw | https://github.com/Molecule-AI/molecule-ai-workspace-template-openclaw |
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## Adapter discovery (ADAPTER_MODULE)
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Standalone adapter repos set `ENV ADAPTER_MODULE=adapter` in their Dockerfile.
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The runtime's `get_adapter()` checks this env var first:
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```python
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# In molecule_runtime/adapters/__init__.py
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def get_adapter(runtime: str) -> type[BaseAdapter]:
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adapter_module = os.environ.get("ADAPTER_MODULE")
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if adapter_module:
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mod = importlib.import_module(adapter_module)
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return getattr(mod, "Adapter")
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# Fall back to built-in subdirectory scan (monorepo local dev)
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...
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```
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## Publishing a new version
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```bash
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cd workspace-template
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# 1. Bump version in pyproject.toml
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# 2. Sync to molecule-ai-workspace-runtime repo
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# 3. Tag and push — CI publishes to PyPI via PYPI_TOKEN secret
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```
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Or manually:
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```bash
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cd workspace-template
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python -m build
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python -m twine upload dist/*
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```
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## Writing a new adapter
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1. Create a new standalone repo `molecule-ai-workspace-template-<runtime>`
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2. Copy `adapter.py` pattern from any existing adapter repo
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3. Change imports: `from molecule_runtime.adapters.base import BaseAdapter, AdapterConfig`
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4. Create `requirements.txt` with `molecule-ai-workspace-runtime>=0.1.0` + your deps
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5. Create `Dockerfile` with `ENV ADAPTER_MODULE=adapter` and `ENTRYPOINT ["molecule-runtime"]`
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6. Register the runtime name in the platform's known runtimes list
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