nxtgauge-gitops/docs/PROJECT_STATUS_SUMMARY.md

# Project Status Summary - Nxtgauge Infrastructure

## Last Updated
2026-06-15

---

## What Has Been Completed

### 1. LiteLLM AI Gateway Deployment ✅
- **Status**: Fully deployed and working
- **Namespace**: `nxtgauge-ai`
- **Service**: `litellm.nxtgauge-ai.svc.cluster.local:4000`
- **Ingress**: `https://llm.nxtgauge.com` (TLS via cert-manager)
- **Models configured**:
  - `askash-fast` → `qwen3:4b` (fast, 2.5GB)
  - `askash-main` → `qwen3:8b` (powerful, 5.2GB)
  - Plus 10 specialized model aliases for different use cases
- **Security**: API key required via `LITELLM_MASTER_KEY`
- **Ollama**: Remains internal-only, NOT exposed publicly
- **Files created**:
  - `apps/litellm/base/configmap.yaml`
  - `apps/litellm/base/deployment.yaml`
  - `apps/litellm/base/service.yaml`
  - `apps/litellm/base/ingress.yaml`
  - `apps/litellm/base/secret.yaml`
  - `apps/litellm/base/ratelimit.yaml`
  - `apps/litellm/base/kustomization.yaml`
  - `apps/litellm/README.md`
  - `apps/litellm/OPENCODE_CONNECT.md`

### 2. Kubernetes Cluster Expansion ✅
- Added 4th worker node: **nxtgauge-4 / Ramaris** (89.167.0.148)
- All nodes labeled with character names:
  - `nxtgauge-1` → **Rimuru** (control plane)
  - `nxtgauge-2` → **Veldora** (worker)
  - `nxtgauge-3` → **Diablo** (worker)
  - `nxtgauge-4` → **Ramaris** (worker)
- All nodes Ready and schedulable

### 3. GHCR Registry Authentication ✅
- Created `ghcr-regcred` secret in `nxtgauge` and `nxtgauge-ai` namespaces
- Updated `registries.yaml` on all K3s nodes to authenticate with GHCR
- Restarted K3s services on all nodes
- All deployments now pulling images successfully from GitHub Container Registry

### 4. Latest Code Deployed via GitHub Actions + Flux ✅
All four repositories are live with their latest commits:

| Repository | Branch | Commit | Status |
|------------|--------|--------|--------|
| nxtgauge-frontend-solid | high-performance | `3b8f75d` feat: add AI usage widget to user dashboard | ✅ Deployed |
| nxtgauge-admin-solid | high-performance | `f511a3c` feat: add AI management page to admin panel | ✅ Deployed |
| nxtgauge-ai-assistant | main | `4505d89` feat: add Ask Ash AI assistant implementation | ✅ Deployed |
| nxtgauge-backend-rust | high-performance | `ba63736` feat: add AI management endpoints and LiteLLM support | ✅ Deployed |

- Flux synced to latest gitops commit `c5b32538`
- 22/22 deployments ready

### 5. Ollama Models Downloaded ✅
- `gemma3:270m` (291 MB) - original model
- `qwen3:4b` (2.5 GB) - fast/general use
- `qwen3:8b` (5.2 GB) - powerful/long-form generation

### 6. OpenCode Configuration ✅
- Updated OpenCode binary from `1.14.20` → `1.17.7`
- Reverted config back to use **Ollama Cloud** with **Kimi K2.7**
- Config file: `~/.config/opencode/opencode.jsonc`

### 7. AI Plans Implementation Plan ✅
- Created detailed implementation plan:
  - `docs/AI_PLANS_IMPLEMENTATION_PLAN.md`
  - `docs/AI_PLANS_FINAL_PLAN.md`
- Plan covers:
  - Database schema
  - Plan tiers (Free/Pro/Business/Enterprise)
  - API key generation
  - Usage tracking
  - Rate limiting
  - Model access control
  - Backend services architecture
  - API endpoints
  - Frontend integration
  - Deployment steps

---

## What We Are Stuck At / Blocked On

### 1. PostgreSQL for LiteLLM (Optional Advanced Tracking)
- **Status**: Attempted but not critical
- **Issue**: Tried to deploy PostgreSQL in `nxtgauge-ai` namespace for LiteLLM's built-in virtual key tracking, but it failed to schedule on the new node due to Longhorn CSI driver not being available on `nxtgauge-4`
- **Impact**: LOW - This is not required. We are building our own API key/usage tracking system instead.
- **Decision**: Skip LiteLLM-native virtual keys. Use custom backend implementation.

### 2. AI Plans Implementation ✅
- **Status**: Core backend implementation complete
- **Completed**: Database migration, models, repositories, core services, LiteLLM integration, endpoint wiring, admin endpoints, cron jobs, AI credit packages, auto-apply/auto-request log endpoints
- **Remaining**: Kubernetes env-var wiring (`AI_CREDIT_ADMIN_TOKEN`), real payment gateway integration, automated integration tests
- **Next step**: Apply migrations in target environment and configure Kubernetes secrets

---

## Current System Health

| Component | Status |
|-----------|--------|
| Kubernetes cluster | ✅ 4 nodes Ready |
| Flux GitOps | ✅ Synced |
| All 22 deployments | ✅ Running |
| LiteLLM gateway | ✅ Running |
| Ollama | ✅ Running |
| AI Assistant | ✅ Running |
| Frontend | ✅ Running |
| Admin panel | ✅ Running |
| 19 backend rust services | ✅ Running |

---

## Decisions Made

1. ✅ Using **GitHub Container Registry (GHCR)** instead of `registry.nxtgauge.com`
2. ✅ Using **GitHub Actions + Flux** instead of Forgejo/Gitea
3. ✅ Using **custom API key/usage tracking** instead of LiteLLM Enterprise
4. ✅ Using **qwen3:4b** as main fast model and **qwen3:8b** for long-form/power tasks
5. ✅ Keeping **Ollama internal-only**, exposing only LiteLLM
6. ✅ OpenCode using **Ollama Cloud Kimi K2.7**

---

## Next Recommended Actions

1. **Run database migrations** for AI plans and credit packages (`cargo run -p db-migrate` or `sqlx migrate run`)
2. **Configure `AI_CREDIT_ADMIN_TOKEN`** secret for payments service to credit AI credits via users admin endpoint
3. **Add `LITELLM_BASE_URL` env var** for users service (default already points to cluster local service)
4. **Credit purchase flow** — integrate real payment gateway with `/api/admin/ai/users/{id}/credits`
5. **Add monitoring/alerting** for AI usage and credit thresholds

---

## Key Files and Commands

### Useful Commands
```bash
# Check cluster nodes
kubectl get nodes -o custom-columns='NAME:.metadata.name,CHARACTER:.metadata.labels.node-name,ROLE:.metadata.labels.node-role\.kubernetes\.io/worker,STATUS:.status.conditions[-1].type,IP:.status.addresses[0].address'

# Check deployments
kubectl get deployments -n nxtgauge

# Check AI namespace
kubectl get pods -n nxtgauge-ai

# Check LiteLLM models
curl http://litellm.nxtgauge-ai.svc.cluster.local:4000/v1/models \
  -H "Authorization: Bearer sk-litellm-prod-1c66d63e701c32cd85922a62fd2e087469486a9b7a34d950423a8726d0aceec9"

# Check Flux status
flux get kustomizations --all-namespaces

# Get LiteLLM master key
kubectl get secret litellm-secrets -n nxtgauge-ai -o jsonpath='{.data.LITELLM_MASTER_KEY}' | base64 -d
```

### Important Paths
- GitOps repo: `/home/ashwin/nxtgauge-gitops`
- Frontend repo: `/home/ashwin/nxtgauge-projects/nxtgauge-frontend-solid`
- Backend repo: `/home/ashwin/nxtgauge-projects/nxtgauge-backend-rust`
- Admin repo: `/home/ashwin/nxtgauge-projects/nxtgauge-admin-solid`
- AI Assistant repo: `/home/ashwin/nxtgauge-projects/nxtgauge-ai-assistant`
- AI plans plan: `/home/ashwin/nxtgauge-gitops/docs/AI_PLANS_FINAL_IMPLEMENTATION.md`

---

## Blockers Requiring User Input

None currently. Core AI plans implementation is complete on the backend.

---

## Notes

- The PostgreSQL deployment attempt left a `postgres-pvc` in `nxtgauge-ai` namespace. It can be cleaned up safely since we are not using it.
- No git commits have been made during recent infrastructure changes unless explicitly requested.
- All changes were applied directly to Kubernetes and config files.
- Local `.opencode` plugin was updated, but OpenCode binary upgrade was done via built-in `opencode upgrade` command.