Folzo
1f55f12331
- All models now route through single jean-proxy:3012 → orchestrator:8080 - Removed jean-proxy-moe (no longer needed with auto-switch orchestrator) - Added qwen3.6-moe and qwen3.6-moe-reason model routes - Updated architecture comments
112 lines
5.0 KiB
YAML
112 lines
5.0 KiB
YAML
# ═══════════════════════════════════════════════════════════
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# LiteLLM Proxy — Routing pour Effi
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# Endpoint OpenAI-compatible sur :4000 (host network)
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#
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# Backend unique : JeanOrchestrator (port 8080 sur PC gaming .11)
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# via jean-proxy :3012 + WOL auto si PC eteint.
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#
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# L'orchestrateur gere automatiquement le switch entre :
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# - Qwen3.6-35B MoE I-Nano (defaut, 11.7 Go, 100k ctx, ~70 tok/s)
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# - Qwen3.6-27B IQ4_XS (code/analyse, 14.6 Go, 55k ctx, ~60 tok/s)
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#
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# Tous les modeles passent par le meme proxy :3012.
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# L'orchestrateur detecte le modele demande et charge le bon LLM.
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# Retour automatique au MoE apres 15 min sans 27B.
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# ═══════════════════════════════════════════════════════════
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model_list:
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# ═════════════════════════════════════════════════════════
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# Profil 1 — Raisonnement ON (défaut, pour tâches complexes)
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# Le modele reflechit (jusqu'a 2048 tokens de reasoning_content)
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# avant de produire sa reponse. Bon pour code, analyse, RAG, rapports.
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# ═════════════════════════════════════════════════════════
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- model_name: qwen3.6-reason
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litellm_params:
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model: openai/qwen3.6-reason
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: true
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- model_name: qwen3.6-27b
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litellm_params:
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model: openai/qwen3.6-27b
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: true
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# ═════════════════════════════════════════════════════════
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# Profil 2 — Raisonnement OFF (chat rapide, ~5x moins de latence)
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# Reponse immediate (TTFT <1s) sans phase de reflexion.
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# Ideal pour : chat interactif, redaction de mail, extraction
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# structuree simple, Q/R directes.
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# ═════════════════════════════════════════════════════════
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- model_name: qwen3.6-fast
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litellm_params:
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model: openai/qwen3.6-fast
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: false
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# Alias court "qwen3.6" = fast par defaut (usage chat le plus courant)
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- model_name: qwen3.6
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litellm_params:
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model: openai/qwen3.6
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: false
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# ═════════════════════════════════════════════════════════
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# Profil 3 — Qwen3.6-35B MoE APEX I-Nano (chat Hermes, usage quotidien)
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# Modele MoE : 35B total / 3B actifs, 11.7 Go, cache KV 5x plus petit
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# que le 27B -> contexte 100k possible. Cohabite avec ComfyUI.
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# Route via le meme proxy :3012 que le 27B (orchestrateur fait le switch).
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# ═════════════════════════════════════════════════════════
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- model_name: qwen3.6-moe
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litellm_params:
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model: openai/qwen3.6-moe
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: false
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- model_name: qwen3.6-moe-reason
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litellm_params:
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model: openai/qwen3.6-moe-reason
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api_base: http://localhost:3012/v1
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api_key: "null"
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timeout: 600
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extra_body:
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chat_template_kwargs:
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enable_thinking: true
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# ═════════════════════════════════════════════════════════
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# Backend Ollama — COMMENTE (contention VRAM, voir entete)
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# Pour reactiver si dispo (autre machine / GPU dedie), decommenter
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# et s'assurer que le GPU peut charger les deux modeles.
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# ═════════════════════════════════════════════════════════
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# - model_name: llama3.1-8b
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# litellm_params:
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# model: ollama/llama3.1:8b
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# api_base: http://localhost:3011
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# timeout: 600
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litellm_settings:
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drop_params: false # ne pas dropper: on veut passer chat_template_kwargs a Jean
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telemetry: false
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general_settings:
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master_key: sk-effi-litellm-master |