# 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.