Files
prose-contracts/litellm-health.prose.md
root 1c44bf1259 contract updates: ornith decommissioned, 256K→128K context, Mumuni Discord disabled
Change 1: Strix Halo — ornith decommissioned
- gpu-fleet: Genesis Hermes V3 APEX → qwen3.6-35B-udq4 throughout
- inference-optimization: ornith→strix-moe/qwen3.6-35B-udq4
- gpu-monitor: ornith status → Strix Halo status
- infrastructure-control: Strix Halo — ornith → qwen3.6-35B-udq4
- infrastructure-update: ornith→strix-moe via router
- proxmox-monitor: Strix Halo LLM (ornith) → (qwen3.6-35B-udq4, strix-moe)

Change 2: GPU context 256K→128K fleet-wide
- hermes-agent-baseline: frontmatter description updated
- litellm-health: GPU Fleet Topology table 256K→128K
- litellm-self-heal: GPU Fleet Topology, engine flags, VRAM alert
- inference-optimization: compress threshold 256K→128K compact at 85K
- gpu-fleet: instability note updated

Change 3: Mumuni Discord platform disabled
- gpu-fleet: Mumuni platforms: removed discord
2026-07-23 09:00:42 +00:00

142 lines
6.1 KiB
Markdown

---
kind: function
name: litellm-health
status: deprecated
deprecated_on: 2026-07-09
replaced_by: litellm-self-heal.prose.md
note: >
Consolidated into litellm-self-heal.prose.md to eliminate duplication
of architecture diagrams, GPU topology, timeout tables, and container
lists. Health check is now § Health Check within litellm-self-heal.
This file is retained for reference only — use litellm-self-heal instead.
description: >
Verifies the LiteLLM inference stack health. Current architecture (2026-07-09):
nginx:80 → LiteLLM:4000 → GPU(llama-server) via direct proxy.
Router (harness-router :9000) is DEPRECATED — container still runs but
is not in the request path. GPU monitoring via Prometheus/Grafana and
fleet dashboard (gpu-monitor :9100).
Designed as a reusable contract for any Syslog agent.
Source of truth: gpu-fleet.prose.md
---
## Architecture (v4.0.0 — Direct: nginx → LiteLLM → GPU)
```
Request → nginx:80 → LiteLLM:4000 → GPU(llama-server, parallel 2)
Key validation
Fallback chains
Budget tracking
Prometheus ← metrics
Grafana :3001
harness-router :9000 — DEPRECATED, container still runs but
NOT in request path. nginx routes /v1 → LiteLLM directly.
Router slot booking + circuit breakers replaced by
LiteLLM native fallbacks + timeouts.
```
**What changed (v3.2.0 → v4.0.0 — 2026-07-08)**:
- Router REMOVED from request path — LiteLLM proxies directly to GPU
- All GPUs at parallel 2 (was parallel 1)
- NVIDIA context reduced 256K→128K to free VRAM — now the stable ceiling across all GPUs (2026-07-17)
- LiteLLM timeouts tuned: gemma 25→120s, qwen 40→90s (SUPERSEDED 2026-07-16: qwen 300s, gemma 120s, strix 300s — see litellm-self-heal)
- nginx proxy_read_timeout: 600s, LiteLLM request_timeout: 300s
## Parameters
- public_url: string — The public LiteLLM URL (default: "https://litellm.sysloggh.net")
- backend_host: string — Internal CT host for container checks (default: "192.168.68.116")
- auth_host: string — Authentik server for OIDC (default: "192.168.68.11")
- gpu_hosts: array — GPU inference hosts (default: ["192.168.68.8", "192.168.68.110", "192.168.68.15"])
- gpu_dashboard_url: string — Fleet dashboard (default: "http://192.168.68.24:9100")
- grafana_url: string — Grafana dashboards (default: "http://192.168.68.116:3001")
## Returns
- overall_status: "healthy" | "degraded" | "down"
- checks: array of { name: string, status: string, detail: string }
- timestamp: string — ISO timestamp of the check run
- duration_ms: number — How long the check took
## Requires
- SSH key access to backend_host for container checks
- Network access to public_url, auth_host, and gpu_dashboard_url
- LiteLLM master key for key management endpoints
## GPU Fleet Topology
| Host | IP | Hardware | Models Served | Engine | Context | Parallel |
|------|-----|----------|---------------|--------|---------|----------|
| llm-gpu | 192.168.68.8 | NVIDIA RTX 3090 (24 GB) | qwen3.6-27B-code | llama-server systemd | **128K** | 2 |
| ocu-llm | 192.168.68.110 | NVIDIA RTX 5070 (12 GB) | gemma-4-12b | llama-server systemd | **128K** | 2 |
| amdpve | 192.168.68.15 | AMD Strix Halo 64GB UMA | qwen3.6-35B-udq4 (LiteLLM alias: strix-moe) | llama-server systemd (Vulkan) | 128K | 2 |
## Model Fallback Chains (LiteLLM)
| Primary | Timeout | Fallback | Timeout |
|---------|---------|----------|---------|
| qwen3.6-27B-code | 300s | gemma-4-12b | 120s |
| gemma-4-12b | 120s | qwen3.6-27B-code | 300s |
| qwen3.6-35B-udq4 / strix-moe | 300s | qwen → gemma | — |
| syslog-auto (balanced) | 300s | qwen → gemma | — |
> Global: request_timeout=300s, nginx proxy_read_timeout=600s
## Containers on CT 116
| Container | Image | Port | Health Check |
|-----------|-------|------|-------------|
| harness-litellm | berriai/litellm:1.90.0-rc.1 | :4000→:4001 | /health/liveliness |
| harness-router | inference-harness-router | :9000 (127.0.0.1) | /health (DEPRECATED — not in path) |
| harness-nginx | nginx:alpine | :80 | HTTP 200 on /health |
| harness-postgres | postgres:16-alpine | :5432 | pg_isready |
| harness-redis | redis:7-alpine | :6379 | PING |
| harness-dashboard | inference-harness-dashboard | :3000 | /health |
| harness-grafana | grafana/grafana | :3000→:3001 | /api/health |
| harness-prometheus | prom/prometheus | :9090 | /-/healthy |
## Execution
1. **Read parameters** — Use provided values or defaults
2. **Check public endpoints**:
- GET {{public_url}}/ui/ → expect 200 ("LiteLLM Dashboard")
- GET {{public_url}}/docs → expect 200 ("LiteLLM API - Swagger UI")
3. **Check LiteLLM health (no-auth)**:
- GET http://{{backend_host}}/litellm/health/liveliness → expect 200
4. **Check backend container health**:
- SSH to {{backend_host}} → `docker ps` → verify 8 containers healthy
- Critical: harness-litellm, harness-router, harness-nginx, harness-postgres
- Monitoring: harness-redis, harness-dashboard, harness-grafana, harness-prometheus
5. **Check router roster loaded**:
- GET http://{{backend_host}}:9000/health → expect 200
- GET http://{{backend_host}}:9000/health/unified → expect 3 models
- If router returns "all GPUs saturated" but GPUs idle: roster not loaded → reload
6. **Check GPU fleet health** (via fleet dashboard):
- GET {{gpu_dashboard_url}}/gpu-data → expect 200 with GPU metrics JSON
- Verify GPUs reporting status "healthy"
- Check alerts array for active warnings/critical
7. **Check model inference via LiteLLM** — Test each model:
- POST /v1/chat/completions model=gemma-4-12b → expect 200
- POST /v1/chat/completions model=qwen3.6-27B-code → expect 200
- POST /v1/chat/completions model=strix-moe → expect 200
- Use master key for auth
8. **Check agent keys**:
- GET /key/list with master key → verify all 6 agents have keys
9. **Check Grafana**:
- GET {{grafana_url}}/api/health → expect 200
10. **Compile and report** — Determine overall_status from individual check results