feat(litellm): 3 profils Qwen3.6 (reason/fast/default) via toggle enable_thinking
Contrainte VRAM: RX 7800 XT 16Go ne peut pas co-heberger Qwen3.6-27B (14.6 Go) + llama3.1-8b (5 Go). Ollama commente, on expose 3 profils du meme modele Qwen3.6 via le toggle chat_template_kwargs.enable_thinking: - qwen3.6-reason / qwen3.6-27b : raisonnement ON (taches complexes) - qwen3.6-fast / qwen3.6 : raisonnement OFF (chat rapide ~400ms TTFT) drop_params=false pour passer chat_template_kwargs a Jean. Teste en prod: qwen3.6-fast repond BONJOUR en 400ms, MTP 3/3 acceptes.
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# ═══════════════════════════════════════════════════════════
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# LiteLLM Proxy — Routing multi-backends pour Effi
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# Expose un endpoint OpenAI-compatible sur :4000
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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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# Backends :
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# 1. Jean (llama.cpp/ROCm sur PC gaming .11:8080) → modele "qwen3.6-27b"
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# 2. Ollama (PC gaming .11:11434 via wol-proxy :3011) → modele "llama3.1-8b" (+ autres)
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# Backend unique : Jean (llama.cpp/ROCm sur PC gaming .11:8080)
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# via jean-proxy :3012 + WOL auto si PC eteint.
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#
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# Les deux backends sont sur le meme PC gaming (192.168.1.11)
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# qui s eteint la nuit. Les proxies (wol-proxy + jean-proxy) declenchent
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# le WOL si besoin avec la meme adresse MAC cible.
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# CONTRAINTE VRAM : la RX 7800 XT a 16 Go. Le modele Qwen3.6-27B IQ4_XS
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# occupe ~15.3 Go. Ollama ne peut PAS cohabiter (llama3.1-8b = ~5 Go
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# supplémentaires -> OOM). On abandonne Ollama et on expose 3 profils
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# du meme modele Qwen3.6, avec ou sans raisonnement (toggle natif
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# chat_template_kwargs.enable_thinking):
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# - qwen3.6-reason : raisonnement ON (tâches complexes, code, analyse)
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# - qwen3.6-fast : raisonnement OFF (chat rapide, mail, extraction simple)
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# - qwen3.6-27b : alias (= reason, défaut)
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#
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# Latence observee (campagne de tests 2026-06-27) :
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# reason : TTFT 11-38s, 60-75 tok/s (le modele reflechit avant de repondre)
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# fast : TTFT 0.4-1s, 60-75 tok/s (reponse quasi immediate)
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# ═══════════════════════════════════════════════════════════
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model_list:
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# ═════════════════════════════════════════════════════════
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# Backend 1 — Jean (llama.cpp/v1 OpenAI-compatible)
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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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# Alias court pour open-webui (sans version)
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- model_name: qwen3.6
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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/qwen3.6-27b
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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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# Backend 2 — Ollama (via wol-proxy :3011 + WOL auto)
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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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- model_name: llama3.1
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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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# ═════════════════════════════════════════════════════════
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# Ollama "fallback" auto : tout modele ollama/* est route vers wol-proxy
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# (laisse open-webui lister les autres modeles ollama si besoin)
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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: true
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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
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master_key: sk-effi-litellm-master
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