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Migrates the two Go modules under molecule-core off the dead
github.com/Molecule-AI/molecule-monorepo/... identity onto the vanity
host go.moleculesai.app. Also fixes the historical naming
inconsistency where the Gitea repo is molecule-core but the Go module
path said molecule-monorepo.
Module changes:
- workspace-server/go.mod:
github.com/Molecule-AI/molecule-monorepo/platform
-> go.moleculesai.app/core/platform
- tests/harness/cp-stub/go.mod:
github.com/Molecule-AI/molecule-monorepo/tests/harness/cp-stub
-> go.moleculesai.app/core/tests/harness/cp-stub
Surfaces touched
- 174 *.go files (374 import lines) — every import under
workspace-server/ + tests/harness/cp-stub/
- 2 Dockerfiles (workspace-server/Dockerfile + Dockerfile.tenant) —
-ldflags strings updated in lockstep with the module rename so
buildinfo.GitSHA injection still resolves correctly
- README + docs + scripts + comment URLs to git.moleculesai.app form
- NEW workspace-server/internal/lint/import_path_lint_test.go —
structural lint gate rejecting future github.com/Molecule-AI/ or
Molecule-AI/molecule-monorepo references. Identical template to the
other migration PRs (plugin-gh-identity#3, molecule-cli#2,
molecule-controlplane#32).
Cross-repo dep allowlist (documented in lint gate)
workspace-server requires molecule-ai-plugin-gh-identity, whose own
vanity migration is PR molecule-ai-plugin-gh-identity#3. Until that PR
merges + a tag is cut at go.moleculesai.app/plugin/gh-identity, the
two locations referencing the legacy github.com path
(workspace-server/go.mod require, cmd/server/main.go import) remain
allowlisted. Follow-up PR drops the allowlist + updates both refs in
one shot once gh-identity is fully migrated.
Test plan
- go build ./... clean for both modules
- go test ./... green except two pre-existing failures
(TestStartSweeper_RecordsMetricsOnSuccess flaky-on-suite,
TestLocalResolver_BubblesUpCopyFailure relies on read-only fs perms
but runs as root on operator host) — both reproduce identically on
baseline main pre-migration; NOT regressions of this PR
- Mutation-tested: lint gate fails on canaries in .go + .md;
allowlist correctly suppresses cross-repo dep references in go.mod
while still flagging unrelated additions
Open dependency
- go.moleculesai.app responder must be deployed before fresh-clone
external builds resolve the vanity path. Existing CI / Docker builds
ride pinned go.sum + self-referential module path + responder is
not on critical path for those.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2.8 KiB
2.8 KiB
Running a Gemini CLI Workspace on Molecule AI
Molecule AI now ships a gemini-cli runtime adapter alongside the existing claude-code adapter. This tutorial walks you from zero to a running Gemini agent workspace in under five minutes.
What you'll need
- A Molecule AI account with at least one provisioned tenant
- A Google
GEMINI_API_KEY(get one at aistudio.google.com) - The Molecule AI CLI (
pip install molecule-ai)
Setup (10 steps)
# 1. Install / upgrade the CLI
pip install --upgrade molecule-ai
# 2. Authenticate
molecule auth login
# 3. Store your Gemini API key as a global secret
molecule secrets set GEMINI_API_KEY="YOUR_KEY_HERE" --global
# 4. Create a gemini-cli workspace
molecule workspace create my-gemini-agent --runtime gemini-cli
# 5. Confirm it's running (status → "ready" within ~30 s)
molecule workspace status my-gemini-agent
# 6. Send your first task
molecule workspace run my-gemini-agent "Summarise the last 5 git commits in this repo"
# 7. View the streamed response
molecule workspace logs my-gemini-agent --follow
# 8. Check the agent's memory file (GEMINI.md)
molecule workspace exec my-gemini-agent cat GEMINI.md
# 9. Delegate a cross-workspace task to your new Gemini peer
molecule workspace run orchestrator "delegate_task my-gemini-agent 'Draft release notes for v1.4'"
# 10. Tear down when done
molecule workspace delete my-gemini-agent
Expected output
After step 5 you should see:
my-gemini-agent gemini-cli ready ord 2026-04-16T06:30:00Z
After step 6, Gemini CLI streams its reasoning and final answer directly to stdout. The agent uses GEMINI.md (seeded from your workspace's system-prompt.md) as persistent context — equivalent to CLAUDE.md for Claude Code workspaces.
How it works
Molecule AI's gemini-cli adapter mirrors the battle-tested claude-code pattern: a Docker image installs @google/gemini-cli globally, and CLIAgentExecutor drives the subprocess. Because Gemini CLI reads MCP config from ~/.gemini/settings.json rather than accepting a --mcp-config flag, the adapter's setup() method merges the A2A MCP server definition into that file at boot — preserving any user-defined tools.
Multi-provider teams
The real power surfaces when you mix runtimes on the same Molecule AI tenant. Your orchestrator workspace can delegate tasks to both claude-code and gemini-cli workers simultaneously using delegate_task_async, then synthesize results — all through the same A2A protocol. This is provider diversity at the infrastructure layer, not at the application layer.