Commit Graph
10 Commits
Author SHA1 Message Date
mumuni-bot 82464d2158 README table: gpu-vision slots/ctx aligned to roster (parallel 1, 131K) 2026-09-20 15:33:31 +00:00
mumuni-bot 973335d35b security+alignment pass from PR review: env-var keys (strip dead literals), Rule-7 unmapped-GPU warning, README slots vs live roster args 2026-09-20 15:27:57 +00:00
mumuni-bot 80811511e7 fix(harness): align repo with verified live state; retire model-version names from the client surface
litellm_config.yaml
- client-visible model_list reduced to capability names: syslog-auto, gpu-dense, strix-moe, gpu-vision
- retired qwen3.6-27B-code, qwen3.8-27B-uncensored, qwen3.6-35B-udq4 (and the already-dead gemma-4-12b)
- fallbacks and model_cost re-keyed to the surviving names
- upstream litellm_params.model set to the capability names; the backends ignore the model field
  (verified HTTP 200 on all three hosts), so this needs no llama.cpp relaunch and loses no KV warmth
- verified live: /v1/models advertises exactly the four names, each returns 200 through nginx

gpu_roster.yaml
- launch args replaced with the VERIFIED live command lines, read from the running processes via the
  PVE guest agent (acerpve VM 101 = .8, ocupve VM 103 = .110) and on amdpve (.15)
- .8: model_path corrected to Qwen3.8-27B-Uncensored-Q4_K_M.gguf, max_concurrent 2 -> 1,
  context 262144 -> 131072, full arg list recorded (incl. --parallel 1 and the new
  --slot-save-path / --metrics added 2026-09-12)
- .15: model_path corrected to Carnice-Qwen3.6-MoE-35B-A3B-Q4_K_M.gguf, full arg list recorded
- keys renamed to the capability names; hosts.current_model aligned

README.md / dashboard
- README dense entry corrected (1 slot, 131K ctx, actual model file)
- dashboard picker now uses capability names; fixed the "Gemma 4 12B" / "12B VLM" labels (the RTX 5070
  serves a 9B Qwen3.5) and the gpu-vision -> gpu-light id mapping

scripts/
- added the three operational monitors as tracked files (they were untracked): gpu-monitor.py,
  gpu-self-heal.py, litellm-health-check.sh
- cleared their references to retired model names, which were causing failed calls every benchmark
  cycle (150 failed gemma-4-12b calls in the last 7 days); gpu-monitor.py's .110 entry also wrongly
  listed .8's model

Intentionally NOT changed
- LITELLM-MIGRATION-PLAN.md: historical planning document (June 14), not a live-state claim
- backups/, graphify-out/, litellm_config.yaml.backup: historical artifacts
- unrelated untracked files (router.py, docker-compose.yml.pre-1991-20260911, nginx/default.conf,
  dashboard/gpu-monitor.html, scripts/gitea-logger.sh): out of scope for this change
2026-09-12 21:03:48 +00:00
agent-zero 93e7605aa2 chore(ct116): capture production state (LiteLLM 1.99.1, nginx /ui //docs, router decommission, trove agent) 2026-09-11 19:34:30 +00:00
Abiba Bot 1e24bc3b9b docs: update model table with context windows, capabilities, GPU labels 2026-06-05 23:49:03 +00:00
Abiba Bot dace488f93 VLM migration: qwen3.5-9b-vlm → gemma-4-12b across entire harness
- router/router.py: model ID, context window (131K→262K), VRAM comment
- litellm_config.yaml: model name updated
- gpu-router.conf, gpu-router-docker.conf: pool names, comments
- dashboard/dashboard.py: MODELS array refactor for single-point config
- README.md: architecture diagram, model table
2026-06-05 21:37:18 +00:00
Abiba b67021ac69 docs: complete design documentation — auth, routing tiers, queue, models, maintenance 2026-05-19 19:17:52 +00:00
Abiba 76ade81fda docs: add Koonimo to agent API keys table 2026-05-19 15:48:39 +00:00
Abiba 9c31b5d622 May 19, 2026: Full harness update
- Model migration: gemma-4-E4B → qwen3.5-9b-vlm
- Dashboard reorder: Usage Over Time + GPU Metrics to top
- Router counter leak fix (gpu_decr in except handler)
- VLM slot upgrade 1→2
- Redis stale key cleanup
- Automated maintenance cron job
- LiteLLM config update
- GPU router config update
- README update
2026-05-19 15:03:34 +00:00
Abiba (pi) 7b6c6aabe1 Initial commit: CT 116 inference harness — nginx, LiteLLM, router, dashboard, Redis
- Complexity-based routing (MoE default, Dense heavy, Gemma light)
- Per-agent API keys with metrics tracking
- Time-series usage graphs (24h/7d/30d)
- Streaming support (SSE passthrough)
- Unicode cleanup (ASCII-only output)
- Vision support (gemma-4-E4B)
- Tier enforcement (starter/professional/enterprise)
- GPU health monitoring via sidecar polling
- Unified dashboard with line graph
2026-05-16 18:51:50 +00:00