564f377d1b
2 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
rabbitblood
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37bca9176e |
feat(workspace): add idle-loop reflection pattern (Hermes/Letta shape)
Today's multi-framework research (Hermes, Letta, Trigger.dev, Inngest, AG2,
Rivet, n8n, Composio, SWE-agent — see docs/ecosystem-watch.md) confirmed
that nobody runs while(true) per agent. The working patterns are:
(a) event-driven + hibernation (Hermes, Letta, Trigger.dev, Inngest)
(b) cron/user-triggered ephemeral runs (AG2, Rivet, n8n, SWE-agent)
Molecule AI is currently 100% in category (b). Observed team utilization:
~0.5% — agents idle 99.5% of the time because cron fires and CEO-typed
A2A are the only initiating signals. CEO's north-star is 24/7 iteration,
current cadence falls short.
This PR closes the gap by adding an in-workspace idle loop that wakes the
agent periodically ONLY when it has no active task. The shape is the
Hermes reflection-on-completion pattern combined with the Letta backlog-pull
pattern, collapsed into a ~60 LOC change in the workspace-template. Zero
new Go code. Zero new DB tables. Zero new API endpoints.
## How it works
1. `config.py` gets two new fields on WorkspaceConfig:
- `idle_prompt: str = ""` — the prompt to self-send when idle
- `idle_interval_seconds: int = 600` — how often to check (default 10 min)
Both support inline or file ref (matching the initial_prompt pattern).
2. `main.py` spawns an `_run_idle_loop()` asyncio task alongside the
existing initial_prompt task (same lifecycle hooks — cancelled in the
`finally:` of the server.serve() block).
3. The loop body:
a. Sleep interval
b. Check `heartbeat.active_tasks == 0` LOCALLY (no LLM call, no HTTP)
c. If idle → self-POST the idle_prompt via the existing /workspaces/{id}/a2a proxy
d. Loop
The agent's own concurrency control rejects the post if it becomes busy
between the check and the POST — that's the safety valve.
4. Gated on `config.idle_prompt` being non-empty. Default = "" = no loop.
Existing workspaces upgrade silently as no-ops until someone explicitly
opts in by setting idle_prompt in org.yaml (either defaults: or
per-workspace:).
## Cost analysis (from the research report)
- while(true) pattern: ~$93/day/org (12 agents × 12 thinks/hour × $0.027). Unshippable.
- Hermes reflection-on-completion: ~$0.45/day/org. Cost ∝ useful work.
- This PR's idle loop at 10-min cadence: upper bound 12 × 6/hour × 24h
× ~3k tokens × Sonnet rate ≈ $5/day/org PER ROLE, only if they're
genuinely idle every check. In practice far less because busy periods
skip the LLM call entirely (the active_tasks check is local).
## Rollout plan
Research report recommended rolling to ONE workspace first (Technical
Researcher) and measuring 24h of activity_logs before enabling for
all 12. This PR enables the mechanism; it does NOT add any default
idle_prompt to org-templates/molecule-dev/org.yaml. That's a follow-up
PR after this one lands and one workspace has been manually opted in
for measurement.
## Not touched in this PR
- No Go code (no new platform endpoint, no new DB columns)
- No org.yaml changes (zero-impact until someone opts in)
- No scheduler changes (the idle loop is a workspace concern, not a
scheduler concern — matches the research report's layering)
## Test plan
- [x] Python syntax check (ast.parse) on main.py + config.py
- [ ] Unit test: WorkspaceConfig parses idle_prompt / idle_interval_seconds from yaml
- [ ] Integration test: set idle_prompt on Technical Researcher, measure that
an A2A message is received every ~10 min while idle, and NOT received
while busy with a delegation
- [ ] Dogfood: enable on Technical Researcher for 24h, count activity_logs
delta vs baseline, confirm cost stays within model
## Related
- Today's research report (conversation output, summarized in commit trailer)
- docs/ecosystem-watch.md → `### Hermes Agent` (the canonical reflection-on-completion example)
- #159 orchestrator/worker split — complementary: leaders pulse for dispatch,
workers idle-loop for pull. Together: leaders push work, workers pull work,
no role ever sits idle with a cold queue.
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||
|
Hongming Wang
|
24fec62d7f |
initial commit — Molecule AI platform
Forked clean from public hackathon repo (Starfire-AgentTeam, BSL 1.1) with full rebrand to Molecule AI under github.com/Molecule-AI/molecule-monorepo. Brand: Starfire → Molecule AI. Slug: starfire / agent-molecule → molecule. Env vars: STARFIRE_* → MOLECULE_*. Go module: github.com/agent-molecule/platform → github.com/Molecule-AI/molecule-monorepo/platform. Python packages: starfire_plugin → molecule_plugin, starfire_agent → molecule_agent. DB: agentmolecule → molecule. History truncated; see public repo for prior commits and contributor attribution. Verified green: go test -race ./... (platform), pytest (workspace-template 1129 + sdk 132), vitest (canvas 352), build (mcp). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |