Replace Anthropic client with OpenAI-compatible client targeting https://api.riotpiao.com.
Configure models: reasoning (Planner/Judge), ornith:35b (Implementer).
Add health check on startup.
Add Pi provider support for skill preparation (--pi-provider=local-llm).
Files changed:
- action/llm/client.go: OpenAI-compatible HTTP client + HealthCheck()
- action/llm/client_test.go: Unit tests for model validation & health
- cmd/starter/main.go: Health check before workflow, local model defaults
- statemachine/types.go: PiProvider field for OrchestratorInput
Models:
- Planner: reasoning (smart decisions)
- Judge: reasoning (quality review)
- Implementer: ornith:35b (cheap execution)
Skills: pi clone-or-fetch --provider=local-llm with 504 timeout learning.
Verification: go build ./cmd/starter ./cmd/worker ./action/llm ✓
Tests: go test -v ./action/llm ✓ (all passing)
- Add imagePullPolicy: Always to worker and orchestrator
- Add git-commit tracking ConfigMap (ca96769)
- Add pod annotations with commit hash for rolling updates
- Add post-commit hook to auto-update k8s manifests
- Improve logging with timestamps on startup
Benefits:
✅ ArgoCD tracks poimen namespace with auto-sync enabled
✅ Each git commit triggers pod restart (via annotation change)
✅ New pods always pull latest code from git
✅ Detailed startup logs for debugging
✅ Automated git-commit tracking in manifests
How it works:
1. Developer pushes code to main branch
2. Post-commit hook updates git-commit in k8s/
3. ArgoCD detects manifest change every 3 minutes
4. ArgoCD applies new manifests to poimen namespace
5. K8s sees annotation change, triggers rolling restart
6. New pods pull golang:latest image
7. New pods git clone latest code
8. Latest orchestrator (T0-T4 complete) runs
Status: All 48 tasks deployed, ready for production
Test