Files
cluster-knaster/sites/knaster/registry.yaml
T

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# Registry für den Cluster "knaster" (SPEC-core §1).
# Clients sprechen nur Slot-Namen an; litellm_model ist der Alias in deploy/litellm/config.yaml.
# ops: Labels für den Healer (Portainer-Endpoint, Container, Proxmox-Node, VM-ID).
slots:
tier0-strong:
tier: 0
device: external
engine: openrouter
litellm_model: tier0-strong
base_model: openrouter-strong # konkretes Modell steht nur in der LiteLLM-Konfiguration
max_context: 200000
effective_context: 120000
tier1-general:
tier: 1
device: gpu
engine: vllm
node: gpu-main # RTX 4000 Ada #1
litellm_model: tier1-general
base_model: qwen3-14b-awq # Startkandidat, Entscheidung per Kalibrierungslauf
max_context: 32768
effective_context: 16384
supports_lora: true
fallbacks: [tier1-flex]
ops: {docker_host: gpu-main, container: vllm, pve_node: pve-ada, vmid: "201"} # VM-IDs/Hosts: ANNAHME bis Deployment
tier1-flex:
tier: 1
device: gpu
engine: vllm
node: gpu-flex # RTX 4000 Ada #2 (nachts Training → unavailable)
litellm_model: tier1-flex
base_model: qwen3-14b-awq
max_context: 32768
effective_context: 16384
supports_lora: true
ops: {docker_host: gpu-flex, container: vllm, pve_node: pve-ada, vmid: "202"} # VM-IDs/Hosts: ANNAHME bis Deployment
verifier-small:
tier: 1
device: gpu
engine: llamacpp
node: gpu-small # Quadro M4000 (Nutzen per Benchmark prüfen)
litellm_model: verifier-small
base_model: qwen3-4b-q4km
max_context: 8192
effective_context: 6144
ops: {docker_host: gpu-small, container: llamacpp-chat, pve_node: pve3, vmid: "231"} # VM-IDs/Hosts: ANNAHME bis Deployment
signature-extractor:
tier: 1
device: gpu
engine: llamacpp
node: gpu-small
litellm_model: signature-extractor
base_model: qwen3-4b-q4km
max_context: 8192
effective_context: 6144
ops: {docker_host: gpu-small, container: llamacpp-chat, pve_node: pve3, vmid: "231"} # VM-IDs/Hosts: ANNAHME bis Deployment
embed-default:
tier: 1
device: gpu
engine: llamacpp
node: gpu-embed # Quadro P2000
litellm_model: embed-default
base_model: qwen3-embedding-0.6b-q8
max_context: 8192
kind: embedding
ops: {docker_host: gpu-embed-1, container: llamacpp-embed, pve_node: pve3, vmid: "221"} # VM-IDs/Hosts: ANNAHME bis Deployment
rerank-default:
tier: 1
device: gpu
engine: llamacpp
node: gpu-embed
litellm_model: rerank-default
base_model: bge-reranker-v2-m3-q8
max_context: 8192
kind: rerank
ops: {docker_host: gpu-embed-1, container: llamacpp-rerank, pve_node: pve3, vmid: "221"} # VM-IDs/Hosts: ANNAHME bis Deployment
adapters: []